Introduction to Developmental Psychology
Read Miller Chapter 1
THEORIES o f
DEVELOPMENTAL
PSYCHOLOGY
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S I X T H E D I T I O N
THEORIES o f
DEVELOPMENTAL
PSYCHOLOGY
Patricia H. Miller
San Francisco State University
New York
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CONTENTS
Preface xi
C H A P T E R 1
Introduction 1
What Is a Theory? 3
What Is a Developmental Theory? 7
Of What Value Is a Developmental Theory? 11
Organizing Information • Guiding Research
What Main Issues of Developmental Psychology
Do Theories Address? 14
What Is the Basic Nature of Humans? • Is Development Qualitative or
Quantitative? • How Do Nature and Nurture Contribute to Development? • What Is It
That Develops?
SUMMARY 23
CHRONOLOGY OF DEVELOPMENTAL THEORIES 23
ORGANIZATION OF THIS BOOK 23
SUGGESTED READINGS 24
C H A P T E R 2
Piaget’s Cognitive-Stage Theory and the Neo-Piagetians 25
Biographical Sketch 26
General Orientation to the Theory 29
Genetic Epistemology • Biological Approach • Structuralism • Stage
Approach • Methodology
Description of the Stages 36
Sensorimotor Period (Roughly Birth to 2 Years) • Preoperational Period
(Roughly 2 to 7 Years) • Concrete Operational Period (Roughly 7 to
11 Years) • Formal Operational Period (Roughly 11 to 15 Years) • An Overview
Memory 55
Mechanisms of Development 57
Cognitive Organization • Cognitive Adaptation • Cognitive Equilibration • Section
Overview
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vi c CONTENTS
Position on Developmental Issues 62
Human Nature • Qualitative Versus Quantitative Development • Nature Versus
Nurture • What Develops
Applications 65
Evaluation of the Theory 66
Strengths • Weaknesses
Piaget’s Own Modifications of His Theory 80
The Neo-Piagetians 82
Robbie Case • Kurt Fischer • Neo-Piagetian Themes
Contemporary Research 89
Infants’ Advanced Competencies • Domain-Specific Concepts • Mechanisms of
Development
SUMMARY 93
SUGGESTED READINGS 94
C H A P T E R 3
Freud’s and Erikson’s Psychoanalytic Theories 95
FREUD 96
Biographical Sketch 96
General Orientation to the Theory 99
Dynamic Approach • Structural Approach • Topographic Approach • Stage
Approach • Normal–Abnormal Continuum • Methodology
Description of the Stages 113
Oral Stage (Roughly Birth to 1 Year) • Anal Stage (Roughly 1 to 3 Years) • Phallic
Stage (Roughly 3 to 5 Years) • Period of Latency (Roughly 5 Years to the Beginning of
Puberty) • Genital Stage (Adolescence) • Case Study of “Little Hans”
Mechanisms of Development 120
Position on Developmental Issues 122
Human Nature • Qualitative Versus Quantitative Development • Nature Versus
Nurture • What Develops
Applications 123
Evaluation of the Theory 124
Strengths • Weaknesses
Contemporary Research 129
ERIKSON 132
Biographical Sketch 133
General Orientation to the Theory 133
Psychosocial Stages • Emphasis on Identity • Expansion of Psychoanalytic Methodology
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CONTENTS c vii
Description of the Stages 139
Stage 1: Basic Trust Versus Basic Mistrust (Roughly Birth to 1 Year) • Stage 2: Autonomy
Versus Shame and Doubt (Roughly 2 to 3 Years) • Stage 3: Initiative Versus Guilt (Roughly
4 to 5 Years) • Stage 4: Industry Versus Inferiority (Roughly 6 Years to Puberty) • Stage
5: Identity and Repudiation Versus Identity Diffusion (Adolescence) • Stage 6: Intimacy and
Solidarity Versus Isolation (Young Adulthood) • Stage 7: Generativity Versus Stagnation and
Self-Absorption (Middle Adulthood) • Stage 8: Integrity Versus Despair (Late Adulthood)
Mechanisms of Development 144
Position on Developmental Issues 145
Applications 146
Evaluation of the Theory 146
Strengths • Weaknesses
Contemporary Research 148
SUMMARY 150
SUGGESTED READINGS 152
C H A P T E R 4
Vygotsky and the Sociocultural Approach 153
Biographical Sketch 155
General Orientation to the Theory 158
Child-in-Activity-in-Cultural-Context as the Unit of Study • Zone of Proximal
Development • The Sociocultural Origins of Individual Mental Functioning: The
Intermental Constructs the Intramental • Tools Provided by a Culture Mediate
Intellectual Functioning • Methodology
Mechanisms of Development 176
Position on Developmental Issues 177
Human Nature • Qualitative Versus Quantitative Development • Nature Versus
Nurture • What Develops
Applications 179
Evaluation of the Theory 182
Strengths • Weaknesses
A Related Approach: Developing-Person-In-Context 188
Contemporary Research 192
Collaborative Problem Solving • Research Across Cultures • Social Change • Immigrant
Families • Development Through Narratives and Conversations • Concluding Comments
About Contemporary Vygotskian–Sociocultural Research
SUMMARY 207
SUGGESTED READINGS 209
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viii c CONTENTS
C H A P T E R 5
Biological Approaches: Ethology,
Developmental Neuroscience, Genetics 211
Ethology 212
History of the Theory • General Orientation to the Theory • Contributions to Human
Developmental Psychology • Mechanisms of Development • Position on Developmental
Issues • Applications • Evaluation of the Theory • Contemporary Research
Developmental Neuroscience 248
Brain Development • Theoretical Issues • Applications • Summary
Genetics 257
Models of Gene X Environment Interactions • Epigenetic Models • Theoretical
Issues • Applications • Summary
Integrated, Multilevel Biological Theoretical Perspectives 268
SUMMARY 271
SUGGESTED READINGS 274
C H A P T E R 6
Social Learning Theory 277
History of the Theory 279
Learning Theory • Social Learning Theory
General Orientation to the Theory 289
Observational Learning • Causal Model Includes Environment–Person–Behavior
System • Cognitive Contributions to Learning • Self-Efficacy and Agency
Examples of Developmental Research:
Moral Judgments and Gender Roles 300
Moral Judgments and Behavior • Gender-Role Development
Mechanisms of Development 303
Position on Developmental Issues 304
Human Nature • Qualitative Versus Quantitative Development • Nature Versus
Nurture • What Develops
Applications 306
Evaluation of the Theory 308
Strengths • Weaknesses
Contemporary Research 311
Cognitive Approaches to Learning • Imitation • Selective Social Learning from Others
SUMMARY 314
SUGGESTED READINGS 316
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CONTENTS c ix
C H A P T E R 7
Information-Processing Theory 317
History of the Theory 320
General Orientation to the Theory 322
Humans as Information-Processing Systems • Development as Self-Modification • Task
Analysis • Methodology
Major Developmental Approaches 330
Memory • Metamemory • Mathematical Understanding • Rules for Problem
Solving • Computational Modeling
Mechanisms of Development 353
Position on Developmental Issues 355
Human Nature • Qualitative Versus Quantitative Development • Nature Versus
Nurture • What Develops
Applications 357
Evaluation of the Theory 360
Strengths • Weaknesses
Contemporary Research 365
Executive Function • Developmental Cognitive Neuroscience • Embodied
Cognition • Bayesian Computational Models • Developmental Robotics
SUMMARY 374
SUGGESTED READINGS 375
C H A P T E R 8
Gibson’s Ecological Theory
of Perceptual Development 377
Biographical Sketch 378
General Orientation to the Theory 379
Ecological Approach: Affordances • Information Is Specified in Stimulation • Humans as
Active Perceivers • Methodology
What Infants Learn About 387
Communication • Interaction with Objects • Locomotion in the Spatial Layout
Mechanisms of Development 392
Position on Developmental Issues 393
Human Nature • Qualitative Versus Quantitative Development • Nature Versus
Nurture • What Develops
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x c CONTENTS
Applications 394
Evaluation of the Theory 394
Strengths • Weaknesses
Contemporary Research 397
SUMMARY 399
SUGGESTED READINGS 400
C H A P T E R 9
Theories Today: Themes and Perspectives 401
Generally Accepted Theoretical Principles 402
Overview of Theorizing Today 403
Themes Driving Theorizing and Research Today 403
1. How general are developmental changes?
2. How can complex, dynamic change be captured theoretically?
3. How can theories best depict long-term development?
4. How can theories best depict universal and diverse aspects of development?
Position on Developmental Issues 419
SUMMARY 420
SUGGESTED READINGS 420
C H A P T E R 1 0
Reflections 421
Developmental Issues Revisited 422
Human Nature • Qualitative Versus Quantitative Development • Nature Versus
Nurture • What Develops
Moving Toward Mechanisms of Development 426
Historical Progress of Developmental Theories 428
Critical Psychology: Are Theories of Development Gendered? 431
Conclusions 434
References 435
Name Index 467
Subject Index 477
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PREFACE
“What is your theory of psychological development?” As an undergradu-
ate, I faced that very essay question on my final exam in an introductory
child psychology class. Drawing on all the theories I had ever heard
of, I modestly generated a 6 (age) × 20 (developmental tasks) matrix
that covered all of development. My interest in theories was launched.
Perhaps if I had been given a multiple-choice test this book would not
have been written.
In all six editions of this book, I have tried to show the “big picture”
of psychological development. Sometimes students are frustrated by
fact-laden textbooks that do not provide frameworks in which to fit the
facts. It is often not clear, for example, why a Swiss philosopher would
be interested in children’s numerical judgments after a row of objects is
spread out or why it is noteworthy that infants cry when their mothers
leave the room. This book provides frameworks for understanding and
perceiving the significance of the research findings in developmental
psychology.
Theories of Developmental Psychology can be used as a primary or sup-
plementary text in undergraduate or graduate courses or as a resource
book for instructors. In addition, it can provide perspectives on chil-
dren’s behavior for those who interact with children in any capacity.
I hope that both developmental psychologists and readers from other
disciplines will find something of interest in these pages.
I have used a parallel structure in the various chapters in order to help
the reader compare the theories. Each chapter includes sections on four
central issues of development, mechanisms of development, applications
(e.g., to education or atypical development), strengths and weaknesses,
and contemporary research. The section on contemporary research in
each chapter shows how the theory is active today and how changes in
the field of developmental psychology have changed what it draws from
each theory. Where relevant, I provide biographies of major theorists, to
show the connection between a theorist’s culture, family background,
and interests, and that person’s theory. I have tried to convey what is
exciting about each of the theories. The theories included are those that
in my view are of most interest to developmental psychologists and pro-
fessionals in related disciplines. Many important theories were necessar-
ily excluded because of length restrictions. And some of the “theories”
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xii c PREFACE
included are not formal theories, but are perspectives that function as
theories by identifying what to study, what questions to ask, and how to
answer these questions.
Much has happened in the discipline of developmental psychology
since the first edition in 1983. Each revision reflects these changes. In
this sixth edition, I have continued to show how each theory has changed
in its emphasis, its data base, and its influence on developmental psychol-
ogy since the previous edition. A major change in this newest edition is a
greatly expanded chapter on biological approaches, growing out of what
originally was a chapter on ethology. This change reflects a major trend
in the field toward biological perspectives. Exciting recent research in
developmental neuroscience and genetics (Gene X Environment inter-
actions and epigenetics) has had a major impact on both developmental
psychology and psychology more generally. Evolutionary approaches,
which continue to capture developmentalists’ attention, are included
as well. These biological perspectives also appear briefly in the sections
on contemporary research in some of the other chapters. The biological
chapter now appears earlier in the book; this chapter and the Vygotsky/
culture chapter just before it together provide two major foundations of
development.
Chapter 9 also is reorganized. That chapter, formerly titled
“Contemporary Minitheories and Emerging Approaches,” is now titled
“Theories Today: Themes and Perspectives.” The chapter is now orga-
nized around current themes in developmental psychology and how
several theoretical approaches are addressing them. The chapter also
now serves as a description of the “state-of-the-art” in developmental
theorizing today.
The theories and empirical findings were updated throughout. Some
particularly notable changes are the following: Reflecting a changing
world, with its more diverse population, significant immigration, and
increased globalization, several chapters address topics such as immi-
grant families, ethnic identity, social change and cultural evolution after
modernization, and cultural differences in family processes. In the infor-
mation processing chapter, sections on connectionist models, Bayesian
models, statistical learning, and embodied cognition are expanded, to
reflect the considerable interest in these approaches today. Throughout,
when relevant, chapters include theoretical perspectives on atypical
development, such as autism spectrum disorders, psychopathology, bul-
lying, and altered stress regulation systems.
I want to thank a number of people who used the fifth edition and
generously agreed to make suggestions for the current edition. The new
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PREFACE c xiii
sections on genetics and neuroscience greatly benefitted from Luke
Hyde’s feedback on an earlier draft. I also want to thank Sarah Berger,
Thomas Finn, and Kimberly Morgan-Smith at Worth Publishers, who
expertly guided the sixth edition. Finally, I am grateful to John Flavell,
who guided my meanderings into theories when I was a graduate student
and continued to be a source of inspiration throughout his career.
Patricia H. Miller
2015
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THEORIES o f
DEVELOPMENTAL
PSYCHOLOGY
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Introduction
Never trust an experimental result until it has been confirmed by theory.
—Sir Arthur Eddington
Give us theories, theories, always theories.
—JAmES mArk BAldwin
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C H A P T E R 1
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2 c INTRODUCTION
W
e have theories of development because observers of human
behavior have been intrigued by what they saw children and
adults do. A 3- year- old predicts that a crayon box holds cray-
ons; then, after it is opened to reveal candles, he asserts that
he always believed that it held candles. A 5- year- old claims that spread-
ing out a row of buttons increases the number of buttons. A school- age
child uses a good strategy to successfully solve an addition problem, but
shortly thereafter, she uses a less reliable strategy on the same problem.
An adolescent selects an identity without seriously exploring other
possible identities. An adult reports a dream that seems to be a thinly
disguised attempt to deal with childhood anxieties.
Developmental theorists try to make sense out of observations such
as these and, by doing so, construct a story of the human journey from
infancy through childhood or adulthood. Some of the theories we will
explore are grand, encompassing theories, often associated with a par-
ticular person, for example, Piaget’s, Freud’s, Erikson’s, and Vygotsky’s
theories. Other theories are minitheories that often can be traced back
to a grand theory but are limited to a particular territory within develop-
ment. An example is the “theory theory,” which is connected historically
to Piaget’s theory but examines children’s concepts about a particular
domain, for example, the mind. Still other theories are families of
approaches under a general theory or framework, such as social learn-
ing theory, information processing, dynamic systems, and ethology and
other biological approaches, and are not identified with a single person.
Some developmental theories have been borrowed from areas outside
of development and applied to developmental psychology, such as evolu-
tionary theory, information processing, dynamic systems theory, and cul-
tural psychology. Typically, a few key developmentalists see the potential
of the theory for posing new questions about development or providing
a new explanation of development and then translate the theory into a
developmental framework. Thus, theory building in developmental psy-
chology is a very rich, dynamic, and exciting enterprise that has come
from many directions. The theories’ stories are varied, but all give us
insights into human behavior and change the way we look at the world.
This book attempts to convey not only the content of the theories but
also the excitement and passion that developmentalists have felt as they
constructed theories to solve the mysteries of development. The chap-
ters also show how theories have expanded our vision of the nature of
development. For example, Piaget’s idea that the mental operations of
adults have their origins in babies’ sensory- motor behaviors opened up a
whole host of new ways to think about cognitive development.
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What Is a Theory? c 3
To understand the contribution of each theory, we must first look at
the general nature of theories. In this Introduction, we ask the following
questions about theories:
1. What is a theory?
2. What is a developmental theory?
3. Of what value is a developmental theory?
4. What main issues of developmental psychology do theories address?
What Is a Theory?
This is a deceptively simple question. In fact, a philosopher of science
might “answer” our question by asking two more:
1. Are we asking what theories should be or what they typically are?
2. Are we asking about theories as they are stated formally or as they actually
operate in a scientific community?
The philosopher’s first question concerns the distinction between
ideal and real theories and expresses the sad fact of scientific life that
our theories fall short of their goal. Theories usually do not reach a
complete, formal state. An ideal, complete, formal scientific theory is a set
of interconnected statements— definitions, axioms, postulates, hypo-
thetical constructs, intervening variables, laws, and hypotheses. Some of
these statements, which are usually expressed in verbal or mathematical
form, are deduced logically from certain other statements. The function
of this set of interconnected statements is to describe unobservable
structures, mechanisms, or processes and to relate them to each other
and to observable events. Perhaps the best way to contrast these types of
statements is to show that they occupy different levels within a theory.
That is, they vary in their distance from observable behavior. The farther
a statement is from observable behavior, the less likely it is to be sup-
ported or refuted by empirical data.
At a point farthest from observable behavior are certain assump-
tions (axioms, postulates) that are accepted without being tested. (For
example, in Piaget’s cognitive developmental theory, an assumption is
that thinking is organized.) These assumptions may be so self- evident to
the theorists that they are not even aware of them. As we move to a less
general level, we find hypothetical constructs— concepts that posit rela-
tions among events, objects, properties, or variables. These constructs
(such as “mental scheme” and “mental reversibility” in Piaget’s theory)
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4 c INTRODUCTION
are unobservable themselves but refer to behavior that can be observed.
Coming even closer to behavior, theorists translate hypothetical con-
structs into testable hypotheses— tentative statements about relations
among events, objects, properties, or variables. (One Piagetian hypoth-
esis is that infants tend to repeat interesting actions, such as shaking a
rattle.) A hypothesis becomes a fact when it is sufficiently supported by
research. As facts accumulate, they are tied together by a law: a relatively
well- established general statement about the relationship among a set
of facts.
A theorist builds a theory by going back and forth between data
(repeatable empirical observations) and theory. New facts change the
theory, and changes in the theory generate new experiments and thus
new facts. The new facts again change the theory, and so the cyclical
process continues. Empirical observations can provide strong support
for a theory but can never completely prove that a theory is true because
future observations could provide disconfirming evidence. Some the-
ories do little more than summarize the facts (data). Particularly in
Skinnerian learning theory, one finds statements such as “If a response
is followed by reinforcement for several trials, the frequency of that
response increases.” Such theories that stay close to the data are easy to
test because they are easy to disconfirm. At the other extreme, Freud’s
“unconscious” or Piaget’s “equilibration” process is distantly related
to observable behavior. Because a large distance between theoretical
notions and data makes it more difficult to test the theory, several such
theories may be equally good at explaining the same set of data and thus
may be retained for years, regardless of their accuracy.
Traditionally, psychologists have judged theories by certain crite-
ria. A theory should be logically sound, that is, internally consistent,
with no statements that contradict each other. A theory should also be
empirically sound, that is, not contradicted by scientific observations.
Furthermore, it should be clear, testable, and parsimonious, relying on
as few constructs, propositions, and the like as possible. Finally, a theory
should cover a reasonably large area of a science and should integrate
previous research.
Psychology has had few formal theories in its history, and probably
no current theory of development falls into this category. However, the
above requirements give us a context for judging whether each theory
or model of development is headed in the right direction. We can ask
whether each theory could eventually reach the status of a formal,
testable theory. In their present form, developmental “theories” serve as
frameworks for examining changes in behavior over time. For example,
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What Is a Theory? c 5
Piaget’s theory directs our attention to the organization of thought
rather than to specific pieces of knowledge, to stagelike changes during
development rather than to a gradual accumulation of knowledge, and to
children’s active construction of knowledge rather than to their passive
processing of information.
Today, theorists often use the term model— an informal theory of lim-
ited scope. Models sometimes are presented visually, for example, in a
drawing of boxes and arrows to indicate the flow of information during
thinking. Models also can be like analogies, as when the mind is likened
to a computer.
The philosopher’s second question distinguishes between theories as
they are stated and how they actually operate in a scientific community.
A theory, in its tidy and polished form in a textbook, only faintly resem-
bles the way the theory guides the behavior of real people doing real
research. The traditional view of theory building as an orderly, objective,
logical process presents a picture of scientists in their “dress clothes.”
Although science sometimes does proceed in this way, more often it
proceeds in a much messier, more irrational fashion, with a dose of luck,
to produce a polished final product.
More specifically, in the conventional view of theory building, empir-
ical observations provide objective bits of information that we can use
to make more general statements or to test statements derived from a
theory. In reality, facts do not simply present themselves to eager scien-
tists. When people develop or adopt a particular theory, they take on a
whole set of beliefs concerning what questions about development are
worth asking, what methods for studying these questions are legitimate,
and what the nature of development is. A Freudian is not likely to study
how rats learn to press bars in tightly controlled experiments, and a
learning theorist is not likely to ask people to describe their dreams or
memories of childhood. There are unwritten rules of the game that are
very much a part of the theory as it is practiced. Scientists’ assumptions
lead them to see certain facts more easily than others. If theorists assume
that humans are basically rational, they are more likely to study thought
than emotions, more likely to become a Piaget than a Freud. In fact, it
can be difficult for theorists to see what they are not looking for. As an
illustration, radio signals from Jupiter had been heard, but ignored, for
many years because astronomers assumed that radio signals came only
from Earth. Then one night in 1955, two young American astronomers
heard these signals from Jupiter, but attributed them to a farmhand on
his way home after a date (Weintraub, 2005). For some reason, they
decided to look further. They then realized what the signals actually
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6 c INTRODUCTION
were, and recognized their significance— providing information about
magnetic fields of planets and rates of planetary rotation.
Scientists make decisions about how to divide up the “stream of
behavior” and how to describe it. A one- minute episode of a baby play-
ing could be described in hundreds of ways. There are different levels
of behavior, from heart rate to exploration of the room, and different
temporal units, from a fraction of a second to a behavioral unit spanning
perhaps the entire minute. Which facts or observations the psychologist
chooses from the numerous candidates tells us as much about the psy-
chologist or the psychologist’s theory as about the episode of behavior
itself. These constraints on what is observed are necessary, of course,
because one cannot record everything. Some philosophers and psychol-
ogists are social constructionists, who propose that science and its theories
are one particular view of reality and are always filtered through social–
cultural beliefs, values, language, and categories. A scientist’s social and
political beliefs can be especially biasing in a field such as psychology, in
which people are studying people. A psychologist holds a mirror rather
than a telescope.
Developmental psychologists do not escape their culture’s views.
Scarr (1985) argued that we change our scientific lenses as the culture
changes: “We pose questions to fit our place and time; we get answers
to fit our theoretical niches” (p. 204). She noted that in the 1950s and
1960s social scientists expected, and thus looked for, evidence that boys
in “broken homes” were affected negatively by the lack of a father. The
finding that these boys, when young, were low in aggression was taken as
evidence for poor sex- role development. Since the women’s movement,
the increasing involvement of fathers with their children, the emergence
of nontraditional families, and the increased racial and ethnic diversity
of families, it is no longer assumed that nontraditional family situations
have a negative effect on children. Moreover, with current less rigid
views of gender roles, low aggression in a boy may not be seen as a
deficit.
Feminist theories identify biases in science stemming from cultural
beliefs about gender and race, including the gender and race of the
researcher (that is, the experiences that come with being a particular
gender and race). For example, a developmental theorist could focus on
mastery, competition, and independence from others or on connections
and collaborations with others (Miller, 2000). These critiques from
social constructionism and feminist theories have alerted investigators
to their own assumptions and biases, which can affect both their theory
building and their research.
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What Is a Developmental Theory? c 7
Individual psychologists’ personality and motivations also influence
the particular direction their research takes, a point demonstrated by
learning theorist E. C. Tolman:
I started out . . . with considerable uneasiness. I felt that my so- called
system was outdated and that it was a waste of time to try to rehash it
and that it would be pretentious now to seek to make it fit any accepted
set of prescriptions laid down by the philosophy of science. I have to
confess, however, that as I have gone along I have become again more
and more involved in it, though I still realize its many weak points. The
system may well not stand up to any final canons of scientific procedure.
But I do not much care. I have liked to think about psychology in ways
that have proved congenial to me. Since all the sciences, and especially
psychology, are still immersed in such tremendous realms of the uncer-
tain and the unknown, the best that any individual scientist, especially
any psychologist, can do seems to be to follow his own gleam and his
own bent, however inadequate they may be. In fact I suppose that actually
this is what we all do. In the end, the only sure criterion is to have fun.
And I have had fun.
(1959, p. 152)
Still another example of the informal side of theories is that some
theorists draw heavily on imagery, such as diagrams or metaphors,
to communicate their theories. Connectionist models, discussed in a
later chapter, often include diagrams of several layers of circles and
arrows to depict brain networks and the strengthening of associations
among multiple units. New technology brings new metaphors, as
seen in the early images of the nervous system as a telephone switch-
board, the eye as a camera, and an instinct as a hydraulic system,
then later images of cognitive development as an equilibration system
(Piaget), a computer (information processing), and a neural network
( connectionism).
What Is a Developmental Theory?
The above crash course in the philosophy of science suggests that devel-
opmental theories are somewhat informal frameworks at present and,
like all theories, have a dynamic, nonpublic role as well as a static, public
one. Our next question is: What makes these theories developmental?
Simply studying children does not make a theory a developmental the-
ory. For example, studying learning in 6- year- olds, or even children of
several ages, does not necessarily lead to conclusions about development.
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8 c INTRODUCTION
What is critical about a developmental theory is that it focuses on change
over time. Although developmental theories have nondevelopmental
theoretical concepts such as ego, mental representations, and neural
networks, they diverge from nondevelopmental theories by emphasizing
changes over time in these concepts. Moreover, developmental theories
link change over time to what came before and what comes next. That
is, a developmental theory attempts to explain by what process a phenom-
enon both emerges from prior development and leads to subsequent
development. For example, with increases in the number of representa-
tions that can be held in mind simultaneously and manipulated (devel-
opmental process), a new strategy of verbally rehearsing a list of items
to be remembered may emerge from the prior skill of simply naming
these items, and may later join with other strategies to make memory
even more efficient.
This concern with change presents developmental theories with three
tasks. These tasks are (1) to describe changes within one or several areas
of behavior, (2) to describe changes in the relations among several areas of
behavior, and (3) to explain the course of development that has been
described. Let us look more closely at each of these three tasks.
1
A developmental theory describes changes over time in one or several areas of
behavior or psychological activity, such as thought, language, social behav-
ior, or perception. For example, a theory might describe changes in
the rules of grammar underlying language in the first few years of life.
Although developmental theories tend to stress changes over months
or years, an adequate theory ultimately must describe changes over
seconds, minutes, and days. For example, Piaget’s concept of object per-
manence, the notion that objects exist even when they are out of sight,
may develop over many months during infancy, but a full description
would include many “minidevelopments” that occur during the child’s
moment- to- moment encounters with objects.
As noted earlier, even direct observation is guided somewhat by theo-
retical notions that distort the flow of behavior in some way. Observers
record certain behaviors and ignore others. They divide the stream of
behavior into units. They encode the behavior into words that add con-
notations. They allow inference to creep into their observations. The
following descriptions of the same behavior demonstrate that several
degrees of inference are possible:
a. The baby’s hand came closer and closer to the spinning top.
b. The baby reached for the spinning top.
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What Is a Developmental Theory? c 9
c. The baby wanted to pick up the spinning top.
d. The baby applied her grasping scheme to the spinning top. (A scheme,
according to Piaget, is an organized sequence of behavior that reflects
an infant’s knowledge in a particular area, such as grasping.)
Much of the early work in developmental psychology was focused
on description. In the 1930s, Arnold Gesell’s maturational theory of
development established norms of physical, cognitive, and motor devel-
opment through description. Although description is not sufficient for
an adequate theory of development, it certainly is necessary. Without a
database, we have an “edifice without a foundation” (White, 1969, p. 49).
2
A second task for a theory of development is to describe changes over time
in the relations among several areas of development such as thought, per-
sonality, and language. Thus, developmental theorists are “specialized
generalists” in that they have to be knowledgeable about many areas of
psychology but specialize in the developmental approach to studying
these content areas and their relations.
In the case of the object concept described above, a theory might
describe how the concept relates to children’s developing memory
system and their social relationship with one particular object, their
mother. A theory would outline the temporal relations among these
areas of development. For example, a theory might claim that a cer-
tain degree of memory capacity must be developed before the object
concept can emerge, that the mother is the first permanent object, and
that subsequent developments within the object concept are correlated
with changes in the memory system and children’s attachment to their
mother. Another example, from Vygotsky (see Chapter 4), concerns the
relations between thought and language. Specifically, thought and lan-
guage are relatively independent until they merge to produce symbolic
thought and children can think in words. Both examples describe the
organization within children at various points in time. The descriptions
refer to certain developmental sequences (first A, then B) and concur-
rences (A and B at the same time).
Of course, any attempt to divide behavior into parts is somewhat
arbitrary because there is an interrelated system, or the famous “whole
child.” Also, theories need to include the sociocultural context in any
description, as well as the child, because behaviors develop and occur
in particular sociocultural settings. Nevertheless, not everything about
a child and the environment can be studied at once. When developmen-
talists study one aspect of development, they try to do so in the context
of the whole child and the social and physical environment.
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10 c INTRODUCTION
3
Even if a theory provides a full description of development, it has not
explained why and how children change. Thus, a third task for a develop-
mental theory is to explain the course of development that the other two
tasks describe. In fact, the sequences and concurrences identified in the
first two tasks often suggest particular explanations. If skill A always
appears shortly before the development of skill B, a psychologist may
hypothesize that A contributes to the development of B. Skill A might
add an ability (e.g., improved memory) that makes the development of
skill B possible, skill A might be transformed into B, or skill A might be
replaced by B.
With respect to the third task, each developmental theory offers a set
of general principles or rules for change. For example, Freud proposed
that biologically based drives “move” children from one stage to another,
and that the degree of the child’s accompanying anxiety depends some-
what on the parents’ child- rearing practices. In addition, principles of
change hypothesize a set of processes for producing the change. These
processes have been as diverse as dynamic equilibration in Piaget’s the-
ory, physical maturation biological theories, and the strengthening of a
response by reinforcement in learning theory.
Earlier developmental events can influence later ones in complex
ways. Sometimes problematic earlier experiences set in motion a tra-
jectory of risk over many years, such that the initial effect increases and
spreads to other domains as children and adolescents face increasingly
complex developmental demands. This is called a developmental cascade.
An example is that the effects of a poor parent– child relationship in early
adolescence may escalate and expand into later relationships (Oudekerk,
Allen, Hessel, & Molloy, 2015). Specifically, parents’ attempts to control
their 13- year- olds through psychological coercion deprived the adoles-
cents of opportunities to practice negotiating autonomy and relatedness
within a relationship, and thus hindered their ability to express auton-
omy and relatedness with their friends. This poor relationship function-
ing with their friends then predicted poor romantic relationships at
age 18 and then at age 21. Parents’ initial undermining of their young
adolescents’ development of autonomy and relatedness in relationships
cascaded over time and relationships, such that their adolescents fell
increasingly behind their peers in their social development. Cascading
can work in a positive direction as well; earlier opportunities to practice
autonomy and relatedness skills may cascade into increasingly healthy
relationships later on.
When a theory explains why development proceeds in a certain
way, it at the same time explains why certain other possible courses
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Of What Value Is a Developmental Theory? c 11
of development did not occur. Why did A lead to B rather than X? The
significance of what does not happen is expressed by Sherlock Holmes:
“ . . . the curious incident of the dog in the nighttime.”
“The dog did nothing in the nighttime.”
“That was the curious incident,” remarked Sherlock Holmes.
—Sir Arthur Conan Doyle
Developmentalists do not necessarily approach these tasks in the
above order. A theory of development usually weaves back and forth
among the three tasks. Progress in describing children’s language at
ages 1, 2, and 3 may stimulate progress in identifying causes of lan-
guage development (e.g., social contributions), which in turn may
direct attention to describing parent– child interaction during early
social development. A related point is that description and explana-
tion are not independent; a theory’s explanatory concepts influence
the choice of what is described and how it is described, and the type
of explanation a theory offers is somewhat constrained by how it
describes behavior. Finally, developmental theories are not equally
concerned with these three tasks. For example, Piaget was much more
successful at describing the development of thought than explaining
this development.
These three monumental tasks, even if incompletely met thus far,
provide us with goals by which to measure the success of theories of
development. A theory may successfully describe and explain one partic-
ular area of development, such as language development, but not other
areas. Or a theory may describe several areas but unsuccessfully explain
these changes.
Of What Value Is a Developmental Theory?
What does a developmental theory actually do for us when it describes
and explains development? A theory makes two contributions: (1) it
organizes and gives meaning to facts, and (2) it guides future research.
We examine each of these contributions in turn.
Organizing Information
The very success of developmental science has produced an enormous
body of information about children. Thus, it now is especially important
to have theories to give meaning to facts, provide a framework for facts,
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12 c INTRODUCTION
identify which facts are most important, and integrate existing facts.
Facts do not speak for themselves. As Jules Henri Poincaré (1908/1952)
said, “Science is built up of facts, as a house is built of stones; but an
accumulation of facts is no more a science than a heap of stones is a
house.” Just as stones need an architect or a blueprint to become a
house, so do facts need a theorist to give those facts structure and show
their relation to the overall design. One by- product is that by sum-
marizing and organizing information, we are saved from “information
overload.” It is easier (but perhaps more dangerous) for us to refer to
“defense mechanisms” than to state all the separate behaviors to which
they refer.
Just as the same stones can be used to make different houses, so can
a set of facts be given different meanings by different theories— by
organizing them differently, emphasizing different behaviors, and infer-
ring different hypothetical constructs. Consider the following example
(McCain & Segal, 1969): At one time, two theories explained the ten-
dency of a falling rock to increase its speed as it approaches the earth.
According to a popular Greek theory, rocks and earth like to be with
each other because they are made of the same elements. As the rock
gets closer to the earth, it travels faster because it becomes increas-
ingly excited. The same fact can also be explained by Newton’s theory
of universal gravitation. All particles attract each other with a force
directly proportional to the product of their masses and inversely pro-
portional to the square of their distances. These two theories are based
on the same set of observations, but they assign different meanings to
these facts.
When we view development through the lenses of first one theory
and then another, we experience a gestalt- like shift. We see children as
seething with sexual energy or reflecting on the origins of the universe.
We see children as a bundle of learned responses or a highly organized
system. These theoretical shifts have been likened to shifts in the percep-
tion of ambiguous figures (Averill, 1976), such as the sudden perceptual
shift from a duck to a rabbit in Figure 1.1. The information has not
changed, but our organization of it has.
Guiding Research
In addition to organizing and giving meaning to facts, a theory serves
a second function. It is a heuristic device, a tool to guide observation
and to generate new information. A theory’s abstract statements predict
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Of What Value Is a Developmental Theory? c 13
certain empirical statements that then are tested. Theories sometimes
stimulate new observations. For example, ethology, an approach bor-
rowed from biology, stimulated developmental psychologists to search
for innate social behaviors contributing to the adaptation of the species
to the environment. A new theory may also make us reexamine familiar
behavior. Piaget certainly was not the first person to watch babies play,
but he suggested a new way of looking at this behavior: the actions them-
selves are creating thought, according to Piaget.
Theory’s dual role as a stimulator of and interpreter of data is nicely
illustrated in a 22-year longitudinal study of aggression (Eron, 1987).
Traditional learning theory, with its emphasis on drive reduction, guided
the selection of the original variables in 1960. In later years, as new
learning theories emerged, investigators interpreted the data first in
terms of Skinnerian operant learning (early 1970s), then social learning
( mid- 1970s), and finally cognitive theory ( mid- 1980s). Thus, in these
four phases of learning- theory development, investigators sought the
causes of aggression in frustration (drive reduction), reinforcement of
aggression (Skinner), aggressive models (social learning), and finally the
child’s attitudes toward and interpretation of potential instigators of
aggression (cognition).
F I G U R E 1 . 1
Similar to the shift in perspective from one theory to another, the lines in this drawing can be
perceptually organized to form a duck or a rabbit.
[Fliegende Blätter, 1845–1892.]
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14 c INTRODUCTION
What Main Issues of Developmental Psychology
Do Theories Address?
Although the theories to be covered differ in their content, methods of
investigation, and formal nature, all explicitly or implicitly take a posi-
tion on certain core issues of development:
1. What is the basic nature of humans?
2. Is development qualitative or quantitative?
3. How do nature and nurture contribute to development?
4. What is it that develops?
These issues, which serve as a way of summarizing and contrasting the
theories, reappear at the end of each chapter. First, however, some dis-
cussion of each issue is in order.
What Is the Basic Nature of Humans?
Theorists’ views of development are closely tied to their views of human
nature. Their views of human nature, in turn, are closely tied to their
worldviews— their notions about how the universe works. Philosophers of
science have identified several worldviews in the history of the Western
world (Pepper, 1942). Three of these can be found in theories of devel-
opmental psychology (Overton, 1984; Reese, 1991): the mechanistic,
the organismic, and the contextual. We examine each of these.
In the mechanistic view, the world is like a machine composed of parts
that operate in time and space. For example, the world could be likened
to a watch. Forces are applied to the parts and cause a chain reaction
that moves the machine from state to state. In principle, then, complete
prediction is possible because complete knowledge of the state and
forces at one point in time allows us to infer the next state. The mech-
anistic view has its roots in Newtonian physics. It is also related to the
empiricist philosophy of Locke (1632–1704) and Hume (1711–1776),
which pictured humans as inherently at rest— passive, and motivated by
environmental or bodily forces. Development, consequently, is caused
by antecedent forces and events acting on a passive, machinelike mind
composed of interlocking parts. One can almost see the wheels turning
in the child’s head!
In contrast, the organismic worldview is modeled on living systems,
such as plants or animals, rather than machines. This image derives from
Leibniz (1646–1716), who believed that substance is in “a continuous
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What Main Issues of Developmental Psychology Do Theories Address? c 15
transition from one state to another as it produces these states out of
itself in unceasing succession” (Cassirer, 1951, p. 29). Leibniz pictured
the world as composed of organized “wholes” that are inherently and
spontaneously active and self- regulating. This organization and self-
directed activity is necessary, or natural, given the nature of the organ-
ism. This view emphasizes the whole rather than its parts, the relations
among the parts, and how the whole gives meaning to its parts. In the
realm of psychology, for example, one can understand a child’s behavior
only by viewing it within a larger dynamic system that includes the con-
text as well as the child.
Rather than look for antecedent causes, as the mechanistic world view
has done, the organismic view considers inherent properties and goals. A
human, by nature, is an active, organized whole and is constantly chang-
ing, not randomly but in a particular direction. Development, then, is
inherent in humans. New skills emerge as humans mature and engage
with the world. Self- initiated behavior and thought lead to changes
in both the structure and the content of behavior and thought. White
describes an active organism:
Let us define an active organism as one that gives form to its experi-
ence, a passive organism as one that receives form from its experience.
Active organisms have purposes and they attend, reason, and selectively
perceive. All this enables the active organism to select, modify, or reject
environmental influences pressing upon it.
(1976, p. 100)
The organismic view is that children “construct” their knowledge by
actively formulating and testing hypotheses about categories of objects
and the causes of events. In contrast, the mechanistic view is that children
passively acquire (“soak up” like a sponge) a copy of reality. Organismic,
unlike mechanistic, theories often posit qualitative rather than gradual
change, and sometimes they are stage theories.
In the third worldview, contextualism, the main metaphor is not a
machine or a living system but a historical act or a tapestry. A behav-
ior has meaning (and can be “explained”) only in terms of its social–
historical context. The pragmatist philosophers such as William James
and George Herbert Mead provided the philosophical inspiration. As
Pepper described contextualism:
[It] takes for its root metaphor the textured event, with its richly quali-
tied strands fading into a past that dies and guiding the changing pattern
of a present duration into a future that dawns. The event through its tex-
ture extends sidewise in its present duration into neighboring contexts
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16 c INTRODUCTION
which are themselves textures extending into still other contexts. And
the texture of each event is internally analyzable into strands, which have
individual tensions and references into other textures.
(1934, p. 183)
This tapestry extends from the distant past to the distant future and
from the proximal to the distal. The horizontal temporal and vertical
spatial threads intermesh into a pattern of a human life.
One can study this tapestry of development by looking at ongoing
action– event units consisting of meaningful goal- directed activities.
As Reese explained it, “Writing is not an act; but writing something
with something on something in some situation at some time is an act”
(1991, pp. 191–192). Reese listed other components of the contextual
metaphor: the meaning of a behavior varies from context to context;
a math problem may involve feelings of competence in the school
environment but survival for a homeless child who is a street vendor.
Moreover, behavior has a purpose that reaches into the past (some prox-
imal “cause”) and into the future (some goal). Finally, like the organismic
view, the contextualist view is holistic. Not only is a unit greater than the
sum of its parts, but a unit- in- context is greater than the sum of a unit
and its context. To continue the above example, writing a sentence “is
an act but is also a part of the larger act that includes writing about the
act of writing the sentence, which in turn is part of the larger act that
includes writing an entire paper, which in turn is part of the larger act
that is the writer’s lifetime, which in turn is part of the larger act that
includes others’ lifetimes, etc.” (Reese, 1991, p. 194).
The contextualist belief that children’s patterns of development can
differ across cultures, subcultures, or historical times contrasts with
the mechanistic and organismic focus on universal laws of behavior
and development. The main mechanistic approach, learning theory
(Chapter 6), posits laws of learning, such as the influence of reinforce-
ment on behavior, that apply across time and place. A main organismic
theory, Piagetian theory (Chapter 2), proposes universal stages and
mechanisms of development. As will become clear in subsequent chap-
ters, these worldviews ask different questions about development and
use different methods to answer those questions.
In addition to these three metaphysical views of humans, the world,
and causality are more specific and limited views based on economic
and political ideologies. For example, Riegel (1972) related views of
childhood and of development to the capitalistic and mercantilistic
politicoeconomic systems in the seventeenth to nineteenth centu-
ries. The capitalistic system, largely Anglo- American, saw humans as
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What Main Issues of Developmental Psychology Do Theories Address? c 17
competitive, as struggling for success. Thomas Hobbes’s (1588–1679)
pronouncement of humans as selfish and competitive and of life as “nasty,
brutish, and short” expressed this notion. The roots continue through
Darwin, who stressed the survival of the fittest. In the economic arena,
the emphasis was on free trade, competition, and entrepreneurship.
The standard of success (as a result of struggle and competition) was the
white, middle- class adult male engaged in manufacturing or business.
By this standard, children, the elderly, the intellectually disabled, and
women were considered inferior. Normative descriptions of each age
were developed to detect “abnormal” development and chart children’s
progress toward the adult standard of success. Society saw children
as passive beings who must be molded (“socialized”) into appropriate
adult roles.
The mercantilistic ideology, in contrast, existed primarily in con-
tinental Europe in the seventeenth through the nineteenth centuries.
The economy was based on land ownership and state- controlled trad-
ing more than on manufacturing and free trade. Distinct social classes
enjoyed specified duties and privileges, and little competition between
classes occurred. Society emphasized cooperation more than competi-
tion, and tolerated differences between groups. The main philosophical
spokesman, Jean Jacques Rousseau (1712–1778), saw the child as a
“noble savage,” basically good but ruined by the adult world. Children
were not to be judged by adult standards; children and adults were seen
as qualitatively different. From this point of view, the goal of educa-
tion was self- realization. Consequently, a child- oriented education was
developed by Maria Montessori, Eduard Spranger, and others.
In summary, each theory of developmental psychology has a view
of humans that reflects philosophical, economic, and political beliefs.
This view is often implicit, and sometimes theorists themselves are not
even aware of these assumptions. The view influences not only theory
construction but also decisions about which research problems are
meaningful, what method should be used, and how data should be inter-
preted. Thus, it sometimes is claimed that it is impossible to integrate or
reconcile theories or make crucial tests that support one or the other if
they have different worldviews.
Is Development Qualitative or Quantitative?
Closely related to these views of humans is the issue of the form of
developmental change: Is it qualitative or quantitative? The mechanistic
and capitalistic views emphasize quantitative change, the organismic and
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18 c INTRODUCTION
mercantilistic approaches emphasize qualitative change, and contextual-
ism permits both. Qualitative changes are changes in kind or type. An
example from nature is the following sequence: egg → caterpillar →
cocoon → butterfly (Spiker, 1966). New phenomena or characteristics
emerge that cannot be reduced to previous elements. Qualitative changes
typically involve changes in structure or organization. In contrast, quan-
titative changes are gradual changes in amount, frequency, or degree. In
some cases, the behavior becomes more efficient or consistent.
An example of the contrast between quantitative change and qualita-
tive change can be found in the development of memory. If a 4- year- old
can recall three objects and a 7- year- old can recall seven objects from a
set of objects seen several minutes earlier, we might infer a quantitative
difference in their mental functioning. The older child can remember
more. However, if the 7- year- old uses strategies such as sorting the
objects into categories of food, furniture, and toys, and rehearsing
them, whereas the 4- year- old does not, we would infer a qualitative
difference in their mental functioning: They process the information in
different ways.
At a more general level, the issue of qualitative versus quantita-
tive change becomes an issue of stage versus nonstage development.
Movement from one stage to the next is a qualitative change. When
there are similarities in a number of new abilities or behaviors during
a period of time, a theorist often infers that the child is in a particular
“stage.” For example, Piaget posited stages that differed in the structure
of thought from birth to adolescence. Stage theorists disagree about
the possibility of being in more than one stage at the same time in
different domains or of regressing to an earlier stage, and they argue
about what causes children to differ in how quickly they pass through
the stages.
Stagelike qualitative changes have been identified by scholars other
than developmental psychologists. Historians identify periods in history,
such as the “industrial age” or the “age of reason.” Shakespeare saw seven
ages of man from the “mewling and puking” infant to the old person
“sans teeth, sans eyes, sans taste, sans everything.”
It is surprisingly difficult to tell when developmental change is quan-
titative versus qualitative. The problem is that change may look abrupt
and qualitative if long time intervals separate the times that behaviors are
sampled and quantitative if short time intervals are used. For example,
when infants’ motor skills are observed once per month, infants usually
appear to progress abruptly from not having a skill to having it (e.g.,
from standing to taking a step), but daily observation reveals a more
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What Main Issues of Developmental Psychology Do Theories Address? c 19
gradual quantitative change, with the new skill gradually strengthening
and becoming more stable (Adolph, Robinson, Young, & Gill- Alvarez,
2008).
Some behaviors show both qualitative and quantitative changes, per-
haps even alternating during development. For example, an increase in
mental capacity (quantitative change) may facilitate the development of
a sorting memory strategy (qualitative change). Subsequent increases in
the speed and accuracy of this sorting would involve quantitative change.
Qualitative and quantitative changes can be seen in various observed
developmental trajectories (Adolph et al., 2008). As described above,
some trajectories are quantitative and linear, as when a child gradually
acquires more words with increasing age, and some are qualitative and
like stair steps, as when a child goes through stages. More interesting
are more complex trajectories, such as a period of slow quantitative
increase in vocabulary development followed by a somewhat sudden
vocabulary spurt that later levels off to a slower gradual increase, or a
U- shaped course of development in which acquiring a new rule, such as
adding “–ed” to form the past tense leads to errors, such as “goed,” but
eventually leads to a rule with exceptions (“went”). In this latter case,
there seems to be a temporary regression, in that performance seems to
get worse, then better. In short, depicting changes in quantitative and/
or qualitative development becomes more complex when the rate of
change and the positive or negative direction of change are considered
as well.
How Do Nature and Nurture Contribute to Development?
Breed is stronger than pasture.
—gEorgE Eliot
Theorists ask what causes development. How do knowledge and behav-
ior arise from a child’s genetic endowment and from experience? The
nature– nurture issue is known by several other labels, such as “heredity
versus environment,” “nativism versus empiricism,” “biology versus cul-
ture,” “maturation versus learning,” and “innate versus acquired.” This
controversy has raged not only within psychology but also within phi-
losophy. The controversy began in classical Greece when philosophers
asked whether ideas are innate or acquired through experience. Later,
Descartes (1596–1650) believed that certain ideas are innate, while the
British empiricist Locke (1632–1704) argued that a newborn’s mind is
a blank slate (tabula rasa) on which experience writes.
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20 c INTRODUCTION
Within psychology, the question has changed over time. The origi-
nal question was “Which (heredity or environment) causes a behavior
or how much of each is needed for a given behavior?” This question was
replaced by “How much of the variation in a behavior across people is due
to hereditary differences and how much to environmental differences?”
and “How (in what manner) do nature and nurture interact to produce
development?” Recently, the questions have become “Which genes pre-
dispose to which kinds of behavior?” “What are the environmental triggers
for the expression of these genes and how do these triggers have their
effect on genes?” and “Can environmental modifications of gene expres-
sion be passed on to the next generation?” This is an interesting illustra-
tion of how progress in a field sometimes involves learning how to ask
the right question.
Today it is clear that a complex interaction of innate and environ-
mental factors accounts for both the development of a trait or behavior
in an individual and the variations in a trait or behavior among individ-
uals. Nature and nurture are inextricably intertwined from concep-
tion throughout the lifespan. Hebb (1980) remarked that behavior is
determined 100 percent by heredity and 100 percent by environment.
Genes (specifically, particular sequences of DNA) are never expressed
directly in behavior. There is a long chain of events, involving genes,
physiological processes, and the prenatal and postnatal environment. The
intertwining of nature and nurture can be complex and subtle as when
genes predispose children to seek particular kinds of environments. For
example, an innately active, exuberant child and a passive, quiet, reflec-
tive child select different types of play settings and playmates. Thus, they
are exposed to different types of experiences. As another example, genes
and the environment can be correlated, as when shy parents might both
pass on a tendency toward shyness genetically and provide an environ-
ment that encourages shyness.
Although all the theories in this volume acknowledge the importance
of both nature and nurture, they vary in which they emphasize. Figure 1.2
shows where the theories align along the nature– nurture continuum in
terms of their focus. Those theories in the middle give approximately equal
attention to both types of influence. The theories also disagree about the
process by which either environmental or innate factors have their influ-
ence. For example, the environment can “stamp in” associations, provide
models to be imitated, supply information to be assimilated, strengthen
neural networks, or provide a supportive social system (a helpful parent).
Finally, theories differ in how much importance they place on the timing
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What Main Issues of Developmental Psychology Do Theories Address? c 21
of a particular experience. Are there “critical periods” in which the child
is especially sensitive to a particular experience? Is early experience more
influential than later experience?
The nature– nurture issue is at the center of two of the most exciting
recent research topics in psychology: genetics and neuroscience (see
Chapter 5). In genetics, for example, gene X environment interactions
show that a given genetic makeup can result in different behavioral
outcomes in different rearing environments, and a given environment
can have different effects on people with different genetic makeups. As
illustrated in one study (Brody, Beach, Philibert, Chen, & Murry, 2009),
parents’ behaviors can affect whether a gene known to be linked to certain
behavioral problems is actually expressed in their children. In a sample of
rural African- American 11- year- olds, some had a genetic makeup known
to produce abnormal levels of serotonin for transmitting neural impulses
in the brain and some did not. Children genetically at risk show twice
as much high- risk behavior (e.g., drug use, sexual behavior) as those not
genetically at risk. This indicates the importance of genetic influence.
However, the at- risk preadolescents whose families participated in an
intervention aimed at strengthening families by teaching parenting skills
(e.g., vigilance, emotional support) and improving parent– child com-
munication gained some protection from this genetic predisposition; the
adolescents showed fewer high- risk behaviors over the two- year period
and in fact at age 14 looked very similar to the group not at genetic risk.
Thus, this intervention moderated gene expression, and it was the combi-
nation of genetic and environmental risk factors that predicted the course
of development. Biology is not destiny: Adolescents with the same genetic
makeup showed different behaviors, depending on their environment (i.e.,
whether they had the family intervention).
• Freud
• Erikson
• Piaget
• Information-Processing
• Gibson • Social Learning
• Vygotsky and the
Sociocultural Approach
• Biological Approaches:
Ethology, Evolution,
Neuroscience, Genetics
NATURE & NURTURE
NURTURE
NATURE
F I G U R E 1 . 2
Locations of the theories along the nature– nurture continuum in terms of their focus.
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22 c INTRODUCTION
The second current boom area addressing nature– nurture, cognitive
neuroscience, shows the two- way influence between brain and behavior:
The physical maturation of the brain changes cognition and behavior,
but cognition and behavior also affect the organization of the brain. The
influence of brain maturation on cognition and behavior is more obvious,
as, for example, maturation of the cortex improves children’s ability to
inhibit their impulsive behaviors and to recall information. Causality in
the other direction is less obvious. A striking example is that infants are
born with the ability to tell apart all the critical phonemic differences
(e.g., /p/ vs. /b/ in pat vs. bat) of all languages. However, over the
first year of life as they typically only hear one or two languages, brain
pathways for the phonemic differences of other languages are pruned
away and infants lose the ability to discriminate these differences (Kuhl,
2010). In this way, experience changes the brain.
What Is It That Develops?
Each theorist makes a claim concerning the “essence” of development, or
at least the proper unit of analysis. Throughout this book, we encounter
various phenomena, such as cognitive structures, psychological struc-
tures (id, ego, superego), cultural tools, neural networks, overt behav-
iors, strategies of information processing, and perceptual exploration.
What theorists focus on depends on where their theoretical assumptions
and methods of study place them along several dimensions:
1. Their level of analysis (from cells to societies)
2. Whether they focus on structure (organization of behavior, thought, and
personality) or process (dynamic, functioning aspects of the system)
3. What content they emphasize (for example, personality or brain changes)
4. Whether they emphasize overt behavior or covert thought and personality
traits
5. Their focus on universal development versus diversity and individual dif-
ferences
6. What methodology they use to study development
These five dimensions have a chicken- and- egg relationship: Which
came first— ethologists’ decision to study complex behavior acquired
by species in their struggle to adapt to the environment or their choice
of a methodology, namely, observations in natural settings? This inter-
relationship among the dimensions will become more obvious as we
examine each theory.
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Organization of This Book c 23
SUMMARY
The traditional view of an “ideal” scientific theory is that it should be a
hypothetico- deductive system and include a set of logically intercon-
nected statements. It formally describes psychological structures and
processes and relates them to each other and to observable events. Most
psychological “theories,” however, have failed to reach this level of for-
mality. A theory has not only a public, formal, static nature but also a
private, informal, dynamic nature. Moreover, a theory guides the behav-
ior of psychologists doing research. It helps them formulate questions,
choose what to study, and decide how to study a problem.
We need developmental theories. They help us describe and explain
developmental changes by organizing and giving meaning to facts and by
guiding further research. Developmental theories have taken a stand on
four issues that are of special importance to the study of development:
1. What is the basic nature of humans?
2. Is development qualitative or quantitative?
3. How do nature and nurture contribute to development?
4. What is it that develops?
We now have a framework for viewing each of the theories in turn.
CHRONOLOGY OF DEVELOPMENTAL THEORIES
A chronology of the major developmental theories provides a useful
framework for subsequent chapters. Freud’s psychoanalytic theory
emerged in the early 1900s. In the mid- 1900s arose Erikson’s psychoso-
cial theory, Piaget’s cognitive theory, Vygotsky’s cultural theory, learning
theory, and social learning theory. The 1960s and 1970s saw the rise
of neo- Piagetian theory, ethology, information processing approaches,
and Gibson’s theory. Biological approaches other than ethology became
especially dominant around the turn of the 21st century. Each chapter
will show how each theory continues to have explicit or implicit impact
on developmental research today.
ORGANIZATION OF THIS BOOK
The following nine chapters describe the major theories of development
plus several other theories or approaches stimulated by them. The focus
is on infancy, childhood, and adolescence, though later development
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24 c INTRODUCTION
receives some attention. Piaget’s theory is presented first because many
of the current issues in developmental psychology were raised by his
theory and several theories arose in reaction to his theory. Next comes
the other big theory in the history of developmental psychology: psycho-
analytic. The subsequent two chapters address the contributions of the
social– cultural environment (Vygotsky’s theory and other sociocultural
approaches) and biology (ethology and other biological approaches).
The remaining chapters present theories focused on particular topics
of development: social learning theory, information processing theory,
and Gibson’s perceptual learning theory. Then, Chapter 9 describes the
contemporary theoretical scene and main theoretical trends. The final
chapter looks both backward and forward regarding developmental the-
ories. Each chapter follows roughly the same organization in order to
make comparisons among the theories easier. At the end of each chapter,
theories are evaluated in terms of their strengths and weaknesses accord-
ing to the current state of developmental psychology. That is, we ask
what each theory can contribute to today’s developmental researchers,
professionals who work with children, and parents.
SUGGESTED READINGS
Shute, R. H., & Slee, P. T. (2015). Child development: Theories and critical
perspectives (2nd ed.). This book examines the philosophical foun-
dations of developmental theories, the notion of development, the
intellectual history of the field, and issues of development.
Adolph, K. E., Robinson, S. R., Young, J. W., & Gill- Alvarez, F. (2008).
What is the shape of developmental change? Psychological Review,
115, 527–543. This article describes various possible developmental
trajectories.
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Piaget’s Cognitive- Stage Theory
and the Neo- Piagetians
[At 7 months, 28 days] Jacqueline tries to grasp a celluloid duck on top of her
quilt. She almost catches it, shakes herself, and the duck slides down beside her. It
falls very close to her hand but behind a fold in the sheet. Jacqueline’s eyes have
followed the movement, she has even followed it with her outstretched hand. But
as soon as the duck has disappeared— nothing more! It does not occur to her to
search behind the fold of the sheet, which would be very easy to do (she twists it
mechanically without searching at all).
—Piaget, 1937 (1954, p. 36)
Hub (age 6): Is the moon always round? —No. —What’s it like? —Sometimes
a crescent, it is very worn out. —Why? —Because it has done a lot of lighting.
—How does it come round again? —Because it is made again. —How?
—In the sky.
—Piaget, 1926 (1929, p. 281)
Se
rg
ey
N
iv
en
s/
Sh
ut
te
rs
to
ck
C H A P T E R 2
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26 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
I
ntriguing glimpses of children’s behavior and thought, such as those
above, fired Piaget’s imagination. In these unremarkable daily events,
Piaget saw a remarkable process of cognitive development. In Piaget’s
view, moment- to- moment specific encounters with objects or people
lead to general ways of understanding the world. This understanding
changes during development as thinking progresses through various
stages from birth to maturity. Moreover, children themselves actively
construct this knowledge.
Piaget has been the most important figure in developmental psy-
chology. His influence spread not only throughout the disciplines of
psychology but also into areas such as education and philosophy. In fact,
Time magazine named Piaget one of the greatest minds of the 20th
century (Papert, 1999). Piaget’s theory raised issues about development
that the other theories must address. It is appropriate, then, to begin
our look at theories with the cognitive- structural theory of Jean Piaget.
This chapter can only hint at the complexity of Piaget’s theory. We
first delve into Piaget’s life in some detail in order to understand his the-
ory better and to illustrate the close relationship between the personal
history of theorists and the nature of their theory. After this biography
comes a general orientation to the theory, then a description of the
stages and other developmental changes, followed by a discussion of
the mechanisms of development. The next sections relate the theory to
the critical issues of development and address applications of the theory.
Then, an evaluation of Piaget’s theory is followed by a description of his
modifications of his theory late in life, an overview of the work of neo-
Piagetians, and a discussion of contemporary research inspired by Piaget.
Biographical Sketch
Most of the material in this biographical sketch comes from Piaget’s
autobiography (1952a). Jean Piaget was born in 1896 in Neuchâtel,
Switzerland. Piaget described his father, a historian devoted to medi-
eval literature, as “a man of a painstaking and critical mind, who dis-
likes hastily improvised generalizations, and is not afraid of starting a
fight when he finds historic truth twisted to fit respectable traditions”
(Piaget, 1952a, p. 237). Piaget remembered his mother as intelligent,
energetic, and kind, but with a neurotic temperament that drove him
to both imitate his father and escape to what Piaget called a “private
and nonfictitious world,” a world of serious work. Piaget acknowledged
that the turbulent family situation aroused his interest in psychoana-
lytic theory.
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Biographical Sketch c 27
It would be easier to list what did not interest the boy Piaget than
what did. A sampling of his interests includes mechanics, seashells, birds,
and fossils. One of his early writings was a pamphlet (written in pencil
because he was not yet allowed to write in ink) describing an “autovap,”
an intriguing union of a wagon and a locomotive. Piaget’s first publica-
tion was a one- page article about a partly albino sparrow he had observed
in a park. This achievement came at age 10—long before he had heard
of “publish or perish.” Piaget’s interest in the exhibits in the local natural
history museum led to an invitation to assist the director with his mollusk
(shellfish) collections. Piaget’s publications on mollusks attracted notice
among natural historians. He was offered, sight unseen, the curatorship
of mollusks at a natural history museum in Geneva. He had to decline the
offer, however, because he had not yet finished secondary school!
Piaget did not escape the typical social and philosophical crises of ado-
lescence. Conflicts between his religious and scientific teachings stim-
ulated him to read hungrily through Bergson, Kant, Spencer, Comte,
Durkheim, and William James, among others. This philosophical turmoil
is expressed in his philosophical novel published in 1917. That this novel
did not become a bestseller can be surmised from passages such as this
one: “Now there can be no awareness of these qualities, hence these quali-
ties cannot exist, if there are no relationships among them, if they are not,
consequently, blended into a total quality which contains them while
keeping them distinct” (1952a, p. 243). Piaget observed that “no one
spoke of it except one or two indignant philosophers” (1952a, p. 243).
Piaget obtained his doctoral degree with a thesis on mollusks at the
University of Neuchâtel in 1918 at age 21. Despite his 20 published
papers, he was not eager to devote his life to observing mollusks. After
visiting psychological laboratories in Zurich and exploring psychoanalytic
theory briefly, Piaget spent two years at the Sorbonne studying psychology
and philosophy. By luck (for the field of developmental psychology), Piaget
met Theodore Simon, a pioneer in the development of intelligence tests,
who asked him to standardize Alfred Binet’s reasoning tests on Parisian
children. Piaget began the work with little enthusiasm. However, his inter-
est was aroused when he began asking children to explain their answers.
He became fascinated with the thought processes underlying their
answers, especially the incorrect answers. In these “conversations,” Piaget
used psychiatric interviewing techniques he had acquired at the Sorbonne
while working with mental patients. Without Simon’s knowledge, Piaget
continued this research for two years. Piaget sums up this experience:
At last I had found my field of research. . . . My aim of discovering a sort
of embryology of intelligence fit in with my biological training; from the
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28 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
start of my theoretical thinking I was certain that the problem of the
relation between the organism and environment extended also into
the realm of knowledge, appearing here as the problem of the relation
between the acting or thinking subject and the objects of his experience.
Now I had the chance of studying this problem in terms of psychogenetic
development.
(1952a, p. 245)
This research in Binet’s laboratory led to three published arti-
cles, and to an offer in 1921 to become director of studies at the
Institut J. J. Rousseau in Geneva. Piaget planned to spend only five years
studying child psychology (a plan that, happily, went awry). The freedom
and research facilities of this position resulted in five books: The Language
and Thought of the Child (1923), Judgment and Reasoning in the Child
(1924), The Child’s Conception of the World (1926), The Child’s Conception
of Physical Causality (1927), and The Moral Judgment of the Child (1932).
To his surprise, the books were read and discussed widely. He became
known as a child psychologist, even though he had no university degree
in psychology, and his fame grew rapidly in Europe.
In the following few years, Piaget continued his research at the insti-
tute, taught philosophy at the University of Neuchâtel, learned about
Gestalt psychology, observed his own babies, and even performed some
research on mollusks in his free time. During the 1940s and 1950s, he
occupied several important academic and administrative positions at the
University of Geneva, as well as international posts, such as president
of the Swiss Commission of UNESCO. There were productive collab-
orations with Alina Szeminska, Bärbel Inhelder, and Marcel Lambercier
on the manipulation of objects, the development of perception, and
the notions of number, physical quantity, and space. Albert Einstein’s
suggestion that Piaget study children’s concepts of time, velocity, and
movement generated two provocative books on this topic. Piaget also
studied many topics outside of children’s thinking: education, the his-
tory of thought and logic, and his old passion, epistemology, or theory
of knowledge.
In 1969, the American Psychological Association gave Piaget the
Distinguished Scientific Contribution Award “for his revolutionary per-
spective on the nature of human knowledge and biological intelligence”
(Evans, 1973, p. 143). He was the first European to receive this award.
Piaget pursued the riddle of children’s thinking until his death in 1980,
at age 84. Even in his final years, books and articles continued to emerge
from behind the piles of papers and books in seeming disarray in his
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General Orientation to the Theory c 29
office. His flowing white hair, pipe, beret, and bicycle were a familiar
sight in Geneva. We have the following description of Piaget at age 70:
“He moves deliberately, but his blue eyes sparkle with youth, good
humor and zest. Benevolent enough, but not heavy enough, to look like
Santa Claus, he reminds one faintly of the pictures of Franz Liszt that
have come down to us” (Tuddenham, 1966, p. 208).
Piaget was amazingly productive. He wrote more than 50 books and
500 papers, averaging about one and a quarter books per year from his
first volume until his death (Brainerd, 1996). Piaget attributed his pro-
ductivity, in part, to his helpful colleagues but also gave us the following
interesting glimpse into his personality:
And then, too, I owe it to a particular bent of my character. Fundamentally
I am a worrier whom only work can relieve. It is true I am sociable and
like to teach or to take part in meetings of all kinds, but I feel a compel-
ling need for solitude and contact with nature. After mornings spent with
others, I begin each afternoon with a walk during which I quietly collect
my thoughts and coordinate them, after which I return to the desk at my
home in the country.
(1952a, p. 255)
General Orientation to the Theory
Like a short guided tour in an unfamiliar city, the following attempts to
provide an overview of Piaget’s theory before exploring the nooks and
crannies— and perhaps becoming lost. We examine five salient charac-
teristics of the theory: genetic epistemology, the biological approach,
structuralism, the stage approach, and Piaget’s methodology. These
characteristics relate to Piaget’s interests and goals, described earlier.
Although this is a chapter on Piaget’s theory, Piaget acknowledged the
contributions of his co- workers, a main one being Bärbel Inhelder.
Genetic Epistemology
Perhaps the most incomprehensible thing about the world is that it is comprehensible.
—albert einstein
Piaget might well have agreed with Einstein, for he had a lifelong fascina-
tion with how humans comprehend the world. The branch of philosophy
concerned with the study of knowledge is called epistemology. As Piaget
viewed it, epistemology is “the problem of the relation between the
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30 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
acting or thinking subject and the objects of his experience” (1952a,
p. 245). Piaget tackled the same questions that have engaged philoso-
phers for centuries: How do we come to know something? Is objective
knowledge, unbiased by the nature of the knower, even possible? Are
there certain innate ideas, or must all knowledge be acquired? All of
Piaget’s writings can be seen as attempts to answer these questions in
different content areas, for example, mathematics, moral reasoning, and
language. As we saw in the biographical sketch of Piaget, his philosophi-
cal quest led him through various schools of philosophy, biology, history,
mathematics, and psychology. His search finally stopped at develop-
mental psychology, which was not even an organized field of study at
the time.
Piaget’s journey to developmental psychology brings us to the
“genetic” part of the term genetic epistemology. In this context, the word
genetic refers not to what is innate, the more common meaning of the
term today, but to “development” or “emergence.” By studying devel-
opmental changes in the process of knowing and in the organization
of knowledge, Piaget felt that he could find answers to the traditional
questions of epistemology. His concern with the classical issues in epis-
temology explains his interest in what philosophers traditionally have
considered the basic categories of knowledge: time, space, causality,
and quantity. These concepts are obvious to an adult but, according to
Piaget, are not obvious to children. Piaget wondered how and when
children understand that no two objects can occupy the same place, that
objects exist even when out of sight, and that two contiguous events can
have a causal relationship. It may be as difficult for young children to
understand these concepts as it is for adults to understand “black holes”
in space or the theory of relativity.
Piaget can be called an experimental epistemologist. Unlike most
epistemologists, who use logical arguments to support their views,
Piaget rejected this armchair approach and formulated testable hypoth-
eses. His epistemology was a marriage of philosophy and the scientific
method, of logic and fact. For example, he examined the question of
how humans acquire concepts of time, space, and causality by tracing the
development of these concepts.
Piaget’s simple but revolutionary solution to the problem of episte-
mology is that knowledge is an action or event rather than a state. It is a
relationship between the active knower and an object. A child knows or
understands a ball or a rattle by manipulating it— physically or mentally.
In this way, people “construct” knowledge. They actively select and inter-
pret information in the environment, thus contributing to the form that
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General Orientation to the Theory c 31
knowledge takes. They do not passively soak up information to build a
storehouse of knowledge.
Children’s knowledge of the world changes as their cognitive sys-
tem develops. As the knower changes, so does the known. A concrete
example is the knowledge of relationships in space. Infants construct a
practical, perceptual– motor knowledge of near and far, up and down.
Older children construct a more abstract “cognitive map” of the relations
among objects in their environment. Infants “know” space by crawling in
it and reaching for objects, whereas older children know space by manip-
ulating mental symbols in particular ways. Note that in both cases there
is a constant interaction between the knower and the external world.
One implication of Piaget’s theory of knowledge is that knowledge is
biased, until perhaps the end of the final stage. Experience is always fil-
tered through the child’s current ways of understanding. A child’s mind
is not a camera that takes faithful pictures of reality. However, as the
mind develops, it becomes more in tune with reality.
Biological Approach
Beginning with his boyhood interest in shells and birds, Piaget’s thinking
was firmly rooted in biology. His distinction is that he saw more in mol-
lusks than did most biologists. In the humble mollusk, he saw general
principles of how living organisms adapt to the world. Mollusks both
adjust themselves to the environment and actively assimilate it in ways
allowed by their biological structure. Piaget felt that these principles also
apply to human thought: Intelligence is adaptation to the environment.
Just as organisms adapt physically to the environment, so does thought
adapt to the environment at a psychological level. Piaget hypothesized
that the modes of psychological functioning involved in this adaptation
are universal, that is, used by all humans worldwide.
Borrowing another concept from biology, Piaget proposed that cogni-
tive growth is much like embryological growth: an organized structure
becomes more and more differentiated, and complex, over time. In fact,
Piaget (1970) sometimes referred to cognitive development as “mental
embryology.”
Adaptation, organization, and structure, as well as such other biolog-
ical concepts as equilibration, assimilation, and accommodation, are dis-
cussed later in the chapter, when we turn our attention to processes of
development. At this point, however, it should be emphasized that these
biological concepts serve as analogies for the way intelligence works.
Piaget did not reduce intelligence to the study of neurons and genes.
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32 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
Structuralism
Because children’s thinking seemed systematic to Piaget, he turned to
structuralism. This helped Piaget express how thought is organized— how
the parts relate to the whole. He proposed that a small set of mental
operations (mental actions) forms a structure that underlies much of
our thinking, even though this thinking may seem very different when
we think about different topics. He theorized that the nature of men-
tal structures changes as they develop. An infant’s cognitive structures
are labeled “schemes” (sometimes translated “schemas” or “schemata”).
A scheme is an organized pattern of behavior; it reflects a particular way
of interacting with the environment. For Piaget, a scheme is whatever
is repeatable and generalizable in an action. The sucking scheme, then,
is a mental structure that describes the systematic way that children
put various objects into their mouths and suck them. As the scheme
becomes more differentiated, children classify objects into “suckables”
and “nonsuckables,” with various subcategories such as hard suckables,
soft suckables, good- tasting suckables, and hairy suckables (daddy’s leg).
In contrast, the cognitive structures of older children, from roughly
age 7 on, are organized abstract mental operations similar to logicom-
athematical systems. The structuralist framework can be seen in the way
these schemes and operations organize themselves into a system that can
be applied to various content. For example, addition, subtraction, mul-
tiplication, and division are operations that are coordinated in a concept
of number that underlies much mathematical understanding. (We return
to the notion of cognitive structures later.)
Two points should be emphasized. First, children actively construct
these structures. Second, Piaget emphasized the feeling of necessity that
accompanies the acquisition of a cognitive structure. For example, 2 plus
2 has to equal 4; one cannot imagine otherwise.
Stage Approach
Milestones, phases, and ages
render general gauges
While periods, levels, and stages
require pages and pages.
—Leland van den Daele (1969, p. 303)
Perhaps the boldest and most controversial of Piaget’s claims is that
cognitive development proceeds through a series of stages. For Piaget, a
stage is a period of time during which the child’s thinking and behavior
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General Orientation to the Theory c 33
in a variety of situations tend to reflect a particular type of underlying
mental structure. Piaget’s emphasis on stages is not surprising, consider-
ing his years of careful observing and classifying, and studying evolution
while a student of zoology. The stages can be thought of as sequential lev-
els of adapting. Just as various species have different ways of adapting to
the environment, so do various cognitive levels provide different ways of
adapting to the environment. Because stage theories abound in develop-
mental psychology, it will be helpful to characterize Piaget’s particular
brand of stage theory. There are five salient characteristics.
1 A stage is a structured whole in a state of equilibrium. Piaget the struc-
turalist saw a stage as an integrated whole that organizes the parts.
The schemes or operations of each stage are interconnected to form
an organized whole. Each stage has a different structure, which allows
a different type of interaction between the child and the environment,
and consequently provides fundamentally different views of the world.
The essence of Piaget’s stage approach is that movement through the
stages involves structural changes that are qualitative (changes in type
or kind) rather than quantitative (change in degree, amount, speed, or
efficiency). For example, there is a qualitative change when the child
moves from structures based on actions in infancy to structures based on
mental representation in the preschool years. At the end of each major
period of development, the cognitive structures are in a state of balance,
or equilibrium. (More on the equilibration process appears later in this
chapter.)
2 Each stage derives from the previous stage, incorporates and transforms that
stage, and prepares for the next stage. The previous stage paves the way
for the new stage by being reworked to form the new stage. Thus,
once children achieve a new stage, they no longer have the previous stage
available. Although previous skills remain, their position or role in the
organization changes. For example, elementary school children can still
roll or hit a ball (a skill acquired during infancy), but they now embed
this skill in a number of other skills. Furthermore, a more advanced level
of thought controls the old skills of rolling and hitting in order to win
the game. Note that regression to an earlier stage is impossible because
the previous stage is no longer present. In contrast, Freud’s theory of
stages holds that a person overwhelmed with anxiety may regress to an
earlier stage.
3 The stages follow an invariant sequence. Since each stage is derived from
the preceding stage, the stages must proceed in a particular order.
No stage can be skipped.
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34 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
4 Stages are universal. Because Piaget was interested in how humans as
a species adapt psychologically to their environment, he focused on
the structures and concepts acquired by humans everywhere— in
the African jungle, the American suburb, or the Swiss mountainside. Of
course, people with a low IQ may not progress through all the stages or
may progress through them more slowly. And people in general vary in
how fast they proceed through the stages. However, the crucial claim is
that the same stages in the same order are found universally.
5 Each stage includes a coming- into- being and a being. There is an initial
period of preparation and a final period of achievement in each
stage. Unstable, loosely organized structures mark the initial period
of transition from the previous stage. Change both within a stage and
between stages is somewhat gradual. The description of each stage later
in this chapter refers to the final, stable, generalized, tightly organized
structure of each stage.
Methodology
One message from the Introduction is that the scientist, the theory, and
the methods for gathering data both facilitate and constrain one another.
The three develop together in particular directions. Piaget the sparrow
watcher and mollusk collector used his observation and classification
skills when watching infants master the objects around them and when
observing toddlers struggle to express their thoughts in spontaneous
speech. Piaget as the Sorbonne student interviewing mental patients
soon became known as the man who asked children questions about
dreams, the origin of the universe, and quantity. Piaget’s early work
with preschool and school children typically involved the clinical method,
which involves a chainlike verbal interaction between the experimenter
and the child. Experimenters begin by posing a problem or asking a
question, but subsequent questions are guided by the answer the child
gave to the previous question. Through this interchange, experimenters
try to understand the line of reasoning underlying a child’s answers.
A talented interviewer avoids biasing the child’s answers by refraining
from too much suggestion.
The following exchange between Piaget and a 5- year- old illustrates
the clinical method:
Where does the dream come from? —I think you sleep so well that you
dream. —Does it come from us or from outside? —From outside. —What
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General Orientation to the Theory c 35
do we dream with? —I don’t know. —With the hands? . . . With nothing?
—Yes, with nothing. —When you are in bed and you dream, where is the
dream? —In my bed, under the blanket. I don’t really know. If it was in my
stomach(!) the bones would be in the way and I shouldn’t see it. —Is the dream
there when you sleep? —Yes, it is in my bed beside me . . . . Is the dream
in your head? —It is I that am in the dream: it isn’t in my head(!). When you
dream, you don’t know you are in the bed. You know you are walking. You are in
the dream. You are in bed, but you don’t know you are. . . . Where do dreams
come from? —I don’t know. They happen. —Where? —In the room and
then afterward they come up to the children. They come by themselves. —You
see the dream when you are in the room, but if I were in the room, too,
should I see it? —No, grownups (les Messieurs) don’t ever dream. . . . When
the dream is in the room, is it near you? —Yes, there! (pointing to 30 cms.
in front of his eyes).
(1926/1929, pp. 97–98)
In Piaget’s later work, such interviews often were combined with the
manipulation of objects by the experimenter or child. This was espe-
cially likely when Piaget studied numerical and physical concepts or
perceptual development. For example, Piaget might spread out a row of
objects and ask whether the number had changed.
Infants, of course, cannot fruitfully be questioned about their
thoughts. Piaget and his psychologist wife, Valentine, kept a baby diary of
observations of their own infants as the infants went about their normal
activities. At times, Piaget became a participant– observer by invent-
ing little experiments on the spot, such as hiding a toy and observing
whether the infant searched for it.
From these verbal protocols and behavioral observations, Piaget
inferred general structures of thought. Because these varied, concrete
behaviors were seen through the eyes of Piaget the philosopher and
theoretical biologist, the descriptions often were accompanied by long,
abstract, theoretical passages. His writings often had a high proportion
of theoretical interpretation to actual observation.
One of the challenges to someone encountering Piaget’s theory for
the first time is to relate the many elusive, abstract features of the theory
to the abundant specific behaviors found in each stage. Perhaps the best
way to grasp the relationship between the abstract and the concrete is
to swing back and forth between the two. Following this strategy, we
now swing from the preceding abstract orientation to a description of
specific stagelike changes and then swing back to abstract features found
in mechanisms of change.
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36 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
Description of the Stages
In the Introduction to this book, it was proposed that a developmental
theory should both describe and explain development. The present sec-
tion describes the prototypic Piagetian child making her way through
the stages of cognitive development. The subsequent section tackles the
questions of how and why this particular course of development occurs.
To understand each stage, we need to know not only where it came
from but also where it is going. Each stage holds both the fruits of the
past and the seeds of the future. Here, then, is an overview of the stages,
followed by a more detailed account. The ages listed with each stage
are approximate because children vary somewhat in the ages at which
they proceed through the stages. Note that although Piaget referred to
“stages” of development, he called them “periods,” for example, the “sen-
sorimotor period.” He labeled the steps within each period as “stages.”
1. Sensorimotor period (roughly birth to 2 years). Infants understand the world
in terms of their overt, physical actions on the world. They move from
simple reflexes through several steps to an organized set of schemes (orga-
nized sensorimotor behaviors). In babies’ play, we see their minds.
2. Preoperational period (roughly 2 to 7 years). No longer do children simply
make perceptual and motor adjustments to objects and events. They can
now use symbols (mental images, words, gestures) to represent these
objects and events. They use these symbols in an increasingly organized and
logical fashion.
3. Concrete operational period (roughly 7 to 11 years). Children acquire certain
logical structures that allow them to perform various mental operations,
which are internalized actions that can be reversed.
4. Formal operational period (roughly 11 to 15 years). Mental operations are no
longer limited to concrete objects; they can be applied to purely verbal or
logical statements, to the possible as well as the real, to the future as well
as the present.
Sensorimotor Period (Roughly Birth to 2 Years)
In Piaget’s view, a human starts life with a set of reflexes, a particular
physical makeup unique to the human species, and inherited ways of
interacting with the environment. These inherited ways of interacting
reflect the tendency of thought to be organized and adapted to the
environment. The thinking of even Einstein had these humble begin-
nings. Although newborns know almost nothing about the world, they
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Description of the Stages c 37
have the potential to know almost everything. Indeed, one of Piaget’s
books on infancy is aptly titled The Origins of Intelligence in Children
(1936). We now trace infants’ active construction of a model of the
world by means of the sensory (perceptual) and motor (physical move-
ment) systems. Infants progress through six stages to construct a senso-
rimotor system of thought.
Stage 1: Modification of Reflexes (Roughly Birth to 1 Month) c A
newborn is a bundle of reflexes, or “ wired- in” responses that are trig-
gered by particular stimuli. Touch a newborn’s lips and she sucks, prick
her foot and her knee flexes, place a finger in her hand and she grasps
it. As these reflexes are activated a number of times, they very gradually
are modified. An infant adjusts them slightly to meet the requirements
of slightly different circumstances. For example, an infant’s mouth must
search out the nipple from different angles on different occasions. In
addition, the way the mouth and tongue fit around a hard, plastic rattle
differs from the way they fit around a finger.
As an expanding number and type of objects serve as “grist” for the
sucking reflex, the category of “suckables” grows to include objects rang-
ing from nipples to blankets to bars of the crib. However, at the same
time that infants are generalizing their sucking behavior to many objects,
they are also increasing their discrimination between objects. Hungry
infants never confuse a finger with a nipple. In a sense, they “recognize”
objects.
Behaviors such as sucking, grasping, and looking do not remain
reflexes; babies come to produce them spontaneously. In fact, they
sometimes suck when there is nothing to suck. Piaget claimed that there
is an innate tendency for humans to exercise their skills. Babies suck
because they can suck. Sucking strengthens the sucking skill and leads to
further sucking.
In short, in stage 1, babies modify their reflexes and begin to trans-
form them into the “schemes” mentioned earlier. These schemes—
organized patterns of behavior— continue to strengthen, generalize, and
differentiate throughout the sensorimotor period. Infants are beginning
to construct primitive concepts about objects to suck, grasp, look at, hit,
listen to, and feel.
Stage 2: Primary Circular Reactions (Roughly 1 to 4 Months) c
The behaviors in stage 1 can be called schemes only in a very limited
sense because there is so little modification of reflexes. In stage 2, there
is widespread and rapid development of schemes because primary circular
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38 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
reactions can now occur. A circular reaction is a behavior that is repeated
over and over again and thus becomes circular. By chance, a baby discov-
ers an interesting result from some behavior and then attempts to recap-
ture this result. As the behavior and its results are successfully repeated,
it can be said that a “habit” is formed. These circular reactions are called
“primary” because they involve response consequences that are centered
on or around the infant’s body rather than other objects. Examples
include thumb sucking, visually exploring objects, and listening to one’s
own vocalizations.
Piaget observed primary circular reactions in his own infants.
Consider the following example (the three numbers refer to the child’s
age in years, months, and days):
From 0;2(3) Laurent evidences a circular reaction which will become
more definite and will constitute the beginning of systematic grasping;
he scratches and tries to grasp, lets go, scratches and grasps again, etc. On
0;2(3) and 0;2(6) this can only be observed during the feeding. Laurent
gently scratches his mother’s bare shoulder. But beginning 0;2(7) the
behavior becomes marked in the cradle itself. Laurent scratches the sheet
which is folded over the blankets, then grasps it and holds it a moment,
then lets it go, scratches it again and recommences without interruption.
At 0;2(11) this play lasts a quarter of an hour at a time, several times
during the day. At 0;2(12) he scratches and grasps my fist which I placed
against the back of his right hand. He even succeeds in discriminating
my bent finger and grasping it separately, holding it a few moments. At
0;2(14) and 0;2(16) I note how definitely the spontaneous grasping of
the sheet reveals the characteristics of circular reaction— groping at first,
then regular rhythmical activity (scratching, grasping, holding and letting
go), and finally progressive loss of interest.
(1936/1952b, pp. 91–92)
These circular reactions become deliberate and seem to be accompa-
nied by feelings of pleasure. Piaget describes a baby who “played with
his voice, not only through interest in the sound, but for ‘functional
pleasure,’ laughing at his own power” (1945/1951, p. 91).
Stage 3: Secondary Circular Reactions (Roughly 4 to 8 Months) c
Infants are never content with the status quo; they continue to push
themselves and expand their world. This expansion is especially striking
in the movement from primary to secondary circular reactions. Whereas
primary circular reactions are centered around an infant’s body, sec-
ondary circular reactions are oriented to the external world. By chance,
an infant does something that leads to an interesting effect in the
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Description of the Stages c 39
environment: he shakes a rattle, which produces a noise; he slaps a ball,
which causes it to roll. In the previous stage, the shaking or slapping
itself was of interest; now the environmental consequences are.
When the secondary circular reactions generalize, Piaget calls them
“procedures for making interesting sights last.” If kicking their legs vigor-
ously leads to a jiggling mobile a number of times, infants may make this
kicking procedure a part of their repertoire. On future occasions when
an interesting movement occurs, they may kick in an attempt to sustain
or re- create this movement. Sometimes these procedures produce the
desired result; sometimes they do not. On one occasion, after watching,
in fascination, his father drum on a tin box, 7- month- old Laurent first
stared at it, then shook his arm, raised himself, struck his covers, and
shook his head in an attempt to capture the box— all to no avail.
One of Piaget’s novel observations in this stage is “motor recognition,”
in which infants show they recognize an object by producing the merest
outline of the secondary circular reaction that the object normally would
produce. For example, when Piaget’s infant daughter, Lucienne, saw a
doll that she often had swung in the past, she simply opened and closed
her hands or shook her legs; this was a reduced, effortless version of the
original behavior.
Stage 4: Coordination of Secondary Schemes (Roughly 8 to
12 Months) c During stages 2 and 3, infants could do some simple
coordinating of their schemes, for example seeing and grasping. This
coordination of the schemes of looking, grasping, sucking, hearing, and
so forth will continue throughout the sensorimotor period. In this way,
the cognitive structures become increasingly integrated and organized.
In stage 4, infants now can combine their schemes in complex ways. They
learn to differentiate an instrumental (or means) behavior (scheme) and
a goal behavior (another scheme). Infants know what they want and can
put together schemes to achieve that goal. In contrast, in stage 3, infants’
discovery of interesting results was fortuitous; only afterward did they try
to achieve the outcome again. A special feature of this means– end behav-
ior is that it is applied to new situations. The schemes are now mobile
cognitive tools, freed from their original contexts. Babies use them at
will to achieve a variety of goals.
Babies begin to look like planful and intentional creatures. Piaget
related various occasions on which he placed his hand in front of a
desirable matchbox. Whereas in stage 3 Laurent simply applied (unsuc-
cessfully) his familiar grasping scheme toward the matchbox, in stage
4 he hit his father’s hand (means) and grasped the box (end). Laurent
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40 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
had deliberately removed a barrier in order to achieve a goal. Infants
also learn to use people as means; an infant may place his mother’s
hand on the television remote control in order to see the dark screen
come alive.
One outcome of the differentiation between means and ends is the
anticipation of events:
At 0;9(16) . . . she likes the grape juice in a glass, but not the soup in
a bowl. She watches her mother’s activity. When the spoon comes out
of the glass she opens her mouth wide, whereas when the spoon comes
from the bowl, her mouth remains closed. Her mother tries to lead her
to make a mistake by taking a spoon from the bowl and passing it by the
glass before offering it to Jacqueline. But she is not fooled.
(Piaget, 1936/1952b, p. 249)
Stage 5: Tertiary Circular Reactions (Roughly 12 to 18 Months) c
In this stage, infant scientists are at work. Their environment is their lab-
oratory. They perform miniature experiments in which they deliberately
vary an action in order to see how this variation affects the outcome, as
do scientists. They exploit each object’s potential. They seem to be ask-
ing, “Is there anything new about this object?” Again, Laurent thought-
fully provides us with a nice example:
At 0;10(11) Laurent is lying on his back but nevertheless resumes his
experiments of the day before. He grasps in succession a celluloid swan,
a box, etc., stretches out his arm and lets them fall. He distinctly varies
the positions of the fall. Sometimes he stretches out his arm vertically,
sometimes he holds it obliquely, in front of or behind his eyes, etc. When
the object falls in a new position (for example on his pillow), he lets it
fall two or three times more on the same place, as though to study the
spatial relation; then he modifies the situation. At a certain moment the
swan falls near his mouth: now, he does not suck it (even though this
object habitually serves this purpose), but drops it three times more
while merely making the gesture of opening his mouth.
(Piaget, 1936/1952b, p. 269)
Through deliberate trial- and- error exploration, infants extend the
means– end behavior of the previous stage to develop new means. They
no longer simply coordinate old schemes. In fact, Piaget often character-
ized stage 5 as “the discovery of new means through active experimenta-
tion.” Examples of new means might include pulling a blanket to obtain
an object resting on the blanket or positioning a long, thin object in such
a way that it can be slipped through the bars of a crib.
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Description of the Stages c 41
Stage 6: Invention of New Means Through Mental Combinations
(Roughly 18 to 24 Months) c Stage 6 both closes the curtain on the
sensorimotor period and raises it on the preoperational period. The
achievements of one period always make it possible for the child to begin
the next period. Before stage 6, children have displayed their thinking to
the world. Now, thinking begins to go underground. External physical
exploration gives way to internal mental exploration. This is possible
because children now can use mental symbols to represent objects and
events.
Lucienne shows us how this mental representation leads to a new way
of solving problems:
At 1;6(23) for the first time Lucienne plays with a doll carriage whose
handle comes to the height of her face. She rolls it over the carpet by
pushing it. When she comes against a wall, she pulls, walking backward.
But as this position is not convenient for her, she pauses and without
hesitation, goes to the other side to push the carriage again. She therefore
found the procedure in one attempt, apparently through analogy to other
situations but without training, apprenticeship, or chance.
(Piaget, 1936/1952b, p. 338)
Earlier, Lucienne would have had to solve the problem through trial and
error. Now she can solve the problem by “thinking” in symbols.
The emergence of a mental symbol can be seen in one of the most
stunning of Piaget’s observations. Piaget was playing a game with
Lucienne at age 1 year, 4 months, in which he hid from her a watch chain
inside an empty sliding matchbox. Lucienne first attained the chain by
applying old schemes— turning the box upside down so that the con-
tents spill out through the opening or, with a smaller opening, sliding
her fingers into the slot to grasp the chain. Then Piaget surreptitiously
slid the box to reduce the size of the opening and Lucienne discovered
that it was too small to permit her fingers to reach the chain. Next came
the behavior of interest:
She looks at the slit with great attention; then, several times in succes-
sion, she opens and shuts her mouth, at first slightly, then wider and
wider! Apparently Lucienne understands the existence of a cavity subja-
cent to the slit and wishes to enlarge that cavity. The attempt at represen-
tation which she thus furnishes is expressed plastically, that is to say, due
to inability to think out the situation in words or clear visual images she
uses a simple motor indication as “signifier” or symbol.
(Piaget, 1936/1952b, p. 338)
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42 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
When faced with this problem that past methods did not solve,
Lucienne thought through the problem, partly by moving her mouth
to represent the opening of the box and partly by thinking. She was in
transition from action to a true use of mental symbols. These reduced
motoric imitations become the mental representations of the next stage.
One achievement of this stage is that an event that has been repre-
sented can be evoked at a later time. This absent event is reproduced in
part, as seen in the following observation:
At 1;4(3) J. had a visit from a little boy of 1;6, whom she used to see from
time to time, and who, in the course of the afternoon got into a terrible
temper. He screamed as he tried to get out of a play- pen and pushed it
backwards, stamping his feet. J. stood watching him in amazement, never
having witnessed such a scene before. The next day, she herself screamed
in her play- pen and tried to move it, stamping her foot lightly several
times in succession. The imitation of the whole scene was most striking.
Had it been immediate, it would naturally not have involved representa-
tion, but coming as it did after an interval of more than twelve hours, it
must have involved some representative or pre- representative element.
(Piaget, 1945/1951, p. 63)
Overview of the Sensorimotor Period c The sensorimotor period has
been presented in some detail because it provides a concrete illustration
of the following general characteristics of all four periods:
1 A child actively learns about properties of objects and relations among
them. In the sensorimotor period, children achieve this knowledge
through overt actions, thus, a “logic of action.”
2 Cognitive structures gradually become more tightly organized. Children
coordinate schemes and apply them as solutions to new situations.
3 Behavior gradually becomes more intentional. Children differentiate
between means and ends, invent new means, and apply them to new
ends in new situations.
4 The self is gradually differentiated from the environment. Children dis-
cover the boundaries of their own body and see themselves as one
object in a world of objects.
Concept of Object Permanence c Perhaps the most important con-
cept acquired during the sensorimotor period is the notion of object
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Description of the Stages c 43
permanence: an object continues to exist even when one cannot see, hear,
or feel it. This knowledge is necessary for a notion of a stable, predict-
able world. According to Piaget, the concept develops as follows: During
the first few months of life, if an object disappears, infants do not search
for it (stages 1 and 2). Their behavior follows the rule “out of sight, out
of mind.” Later, they search if the object is only partially hidden or if they
were doing something with the object when it disappeared (stage 3).
However, they give up easily if the object does not reappear quickly.
They still think of the object as an extension of their actions on it. Still
later, as schemes are coordinated, children have the skills needed to look
for hidden objects (stage 4). However, they persist in searching in the
place where they searched previously. Thus, when Piaget hid a toy parrot
twice under a mattress to his daughter’s left and then hid it to her right
(as she watched), she immediately searched to the left— in the original
hiding place. Piaget’s interpretation of this so- called A- not- B error was
that she defined an object partly in terms of its position— a “ parrot-
under- the- mattress.”
The next advance is that children can appropriately search for an
object even if there are several displacements, but only if they are visible
(stage 5). There is a problem with invisible displacements, as when
Piaget put a coin in his hand and moved it under a cushion, then under
a coverlet, and then out again. However, in the final stage, Jacqueline
continued to search for the coin because she now knew that it had to be
somewhere (stage 6). She could represent the object mentally, so was
not dependent on seeing, or otherwise acting on, the object. At last she
understood that objects, including herself, are things that exist in and of
themselves.
In variations on a (sensorimotor) theme by Piaget, his Construction of
Reality in the Child (1937/1954) traces babies’ development of concepts
of time, space, and causality. This should come as no surprise, given
Piaget’s interest in these classical philosophical problems of epistemol-
ogy. The concepts of time, space, and causality are closely linked to the
object concept because objects exist, move, and affect other objects in a
spatiotemporal field.
Preoperational Period (Roughly 2 to 7 Years)
Ending the first period and beginning the next is like climbing a moun-
tain only to discover that it is merely a foothill to Mt. Everest. The
achievements of the sensorimotor period, although monumental, are
also preparation for what is to come. In a sense, children start all over
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44 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
again. What they have achieved in the realm of actions on the world is
redeveloped, now in the realm of mental representations. They recon-
struct notions about objects, relations, causality, space, and time in a new
medium (mental representation) and a more highly organized structure.
The sensorimotor actions become representational, in preparation for
the move to mental actions in the next stage.
Mental Representations c As we noted earlier, the emergence of
mental representations in stage 6 of the sensorimotor period is a devel-
opmental breakthrough that provides a bridge to the preoperational
period. Using mental representations to stand for objects or events is
part of a broader skill of using one thing to stand for another. A 4- year-
old may use the word “airplane,” a swooping hand, a mental picture of
an airplane, or a toy airplane to stand for a real airplane.
There are two types of representations: symbols and signs. Symbols
bear some similarity to the objects or events they stand for and have
lingering traces of their origins in imitation. Symbols often appear in
symbolic play, as when Jacqueline pretended that a cloth was a pillow and
feigned sleep, laughing hard all the while. In contrast, signs are arbitrarily
related to certain events or objects. There is no relationship between the
word “table” and the four- legged thing at which we sit, except that our
language has assigned a relation between them. This notion that words
or other signs are arbitrarily assigned to objects is not easy for a child
to grasp. Young children think that an object’s name is as intrinsic to
the object as are its color and form. When asked why spaghetti is called
spaghetti, a young child may say that it looks like spaghetti and feels like
spaghetti and tastes like spaghetti, so we call it spaghetti!
Representational thought has obvious advantages over sensorimotor
thought. It is faster and more mobile. It can deal with the past, present,
and future in one grand sweep and can recombine its parts to create ideas
that refer to nothing in reality (for example, monsters that go bump in
the night). In contrast, Piaget described sensorimotor intelligence as a
motion picture with the action slowed down so that “all the pictures are
seen in succession but without fusion, and so without the continuous
vision necessary for understanding the whole” (1947/1950, p. 121).
It should be noted that Piaget did not hold the common view that
the source of representational thought is the ability to use words. He
believed that the opposite is true: The development of representational
thought makes it possible to use words as well as other signifiers. Thus,
thought is prior to the emergence of language and broader than language.
Language is primarily a mode for expressing thought. Although thinking
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Description of the Stages c 45
is not dependent on language, language can aid cognitive development.
Language can direct children’s attention to new objects or relationships
in the environment, introduce conflicting points of view, and impart
abstract information that is not easily acquired directly. Language is one
of many tools in our cognitive “toolkit” (Wertsch, 1991).
Characteristics of the Period c Although thinking through symbols
and signs is a tremendous advance over sensorimotor thought, such
thinking is limited in a number of ways. As the term preoperational sug-
gests, children in this period have not yet acquired reversible mental
operations, such as adding and subtracting, which characterize the think-
ing of the next period, called concrete operations. In many ways, this
period is a time of preparation for the next stage rather than a stage in
its own right, and Piaget himself typically described preoperational chil-
dren in terms of what they cannot do, rather than what they can do. The
main characteristics of preoperational thought are egocentrism, rigidity
of thought, semilogical reasoning, and limited social cognition.
1 Egocentrism. Egocentrism does not refer to selfishness or arrogance.
Rather, the term refers to (a) the incomplete differentiation of the
self and the world, including other people, and (b) the tendency to
perceive, understand, and interpret the world in terms of the self. One
implication is that children have trouble taking another person’s percep-
tual or conceptual perspective and in fact have no sense of a “point of
view.” For example, preoperational children do not realize that a person
viewing a display from a position different from their own sees the dis-
play differently. Similarly, a child holding a book upright points to a pic-
ture and asks, “What is this?” He is unaware that his mother, who is facing
him, can see only the back of the book. Egocentrism makes it difficult
to take the role of another person. This can be seen in a card game when
a 5- year- old giggles when she draws a good card. She does not perceive
the need for a “poker face” as a card- playing strategy.
Because children cannot easily take another person’s role, they make
little effort to tailor their speech to meet the needs of the listener. A boy
may tell his mother that at a birthday party “he hit her with it,” without
bothering to explain to what “he,” “her,” and “it” refer. He may omit
essential events, so his mother cannot understand how “he cried” and
“he blew out the candles” are related. Egocentric speech is particularly
rampant in children’s play groups. Children who seem to be engaged in
a conversation actually may be engaged in a collective monologue. Each
child’s remarks are unrelated to anyone else’s. For example, one child’s
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46 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
statement, “I think I saw Superman in a phone booth yesterday,” might be
followed by “This sweater makes me itch” from another child.
After the preoperational period, egocentrism continues to decline.
However, it never disappears completely, even in adulthood, as when a
lecturer pitches his remarks too high or too low for his audience.
2 Rigidity of thought. Piaget characterized preoperational thought as
frozen. One example is centration, the tendency to attend to or think
about one salient feature of an object or event and ignore other
features. If two identical containers have equal amounts of water and
the contents of one container are poured into a taller, thinner container,
children center on the heights of the liquids, while ignoring their widths.
Consequently, they erroneously conclude that there is now more liquid
because the water level is higher. Centration and egocentrism are similar
in that they both reflect an inability to deal with several aspects of a situ-
ation at the same time; thus they both cause a biased view of the world.
Children also show inflexible thinking in their tendency to focus on
states and ignore the transformations linking the states. In the above
example of liquid quantity, a child thinks about the “before” and “after”
states but ignores the process of pouring. Relatedly, preoperational chil-
dren lack mental reversibility, and thus are unable to return the poured liq-
uid to its original container mentally. Finally, children focus on appearance
rather than reality. If a stick looks like it bends when it is plunged into
water, young children assume this perception is true.
Toward the end of the preoperational period, we begin to see “the great
thaw,” as children’s thinking becomes less frozen, more fluid. Showing
that there are some positive achievements of the preoperational period,
several new cognitive skills pave the way for the mental operations of the
concrete operational period. One emerging concept is a function— the
notion that there is a relation between factors, as expressed in the equa-
tion y = f(x). For example, the more one pulls a curtain cord, the farther
a curtain opens. However, children cannot yet work out the precise and
quantitative nature of the relationship. Another new concept is identity,
the notion that an object can change its appearance without changing its
basic nature, or identity. Putting on a Halloween mask does not change
a person into a witch, contrary to the belief of younger children.
3 Semilogical reasoning. Piaget’s interviews with children about their
beliefs concerning the world revealed their preoperational reason-
ing, such as egocentrism and rigid thinking. The conversations also
uncovered some fascinating causal reasoning, which could be considered
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Description of the Stages c 47
semilogical. The following protocol illustrates several facets of semilog-
ical reasoning in a 6- year- old child:
How did the sun begin? —It was when life began. —Has there always been
a sun? —No. —How did it begin? —Because it knew that life had begun.
—What is it made of? —Of fire. —But how? —Because there was fire up
there. —Where did the fire come from? —From the sky. —How was the
fire made in the sky? —It was lighted with a match. —Where did it come
from, this match? —God threw it away. . . . How did the moon begin?
—Because we began to be alive. —What did that do? —It made the moon get
bigger. —Is the moon alive? —No . . . Yes. —Why? —Because we are alive.
(Piaget, 1926/1929, pp. 258–259)
The child tries to explain the mysterious natural events of everyday
life in terms of something familiar— human behavior. The sun and moon,
like people, are alive, are created by a humanlike action (a god lighting a
match), and are tied to human activities (the moon began because people
began to exist). Similarly, a preoperational child may assert that snow is
made for children to play in and clouds move because they are pulled
when people walk.
Thoughts are often linked together in a loose way rather than in a
logical relationship. For example, one afternoon when Lucienne had no
nap, she reasoned that it could not be afternoon because she had not had
her nap. Young children reason from the particular to the particular.
4 Limited social cognition. Piaget believed that his theory applied to
social objects and events as well as physical ones. We saw this paral-
lel between the physical and the social realms in deficits in role tak-
ing and communication resulting from egocentrism, confusions between
natural events and human events, and ideas about the identity of persons
when physical appearances are changed. In addition, Piaget specifically
examined social thought in his work on moral judgments. Preoperational
children judge the wrongness of an act according to external outcomes,
such as how much damage was done and whether the act was punished.
They ignore internal variables, such as the person’s intentions. Thus, a
boy who breaks five cups while trying to help his mother set the table is
considered naughtier than a boy who breaks only one cup while trying
to steal cookies from the cabinet.
In one study of children’s social understanding, Piaget (1965/1995)
asked 200 children about their concepts of national identity and foreign-
ness. Five- year- old Evelyne, a Swiss, said, “I like Italy. It’s more beautiful
than Switzerland . . . I was there this time during the holidays. They have
very good cakes, not like in Switzerland where there are things inside that
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48 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
make you cry” (p. 254). And 7- year- old Herbert, when asked whether
people differ from one country to another, said, “Yes, well, Americans
are stupid. If I ask them where the rue du Mont- Blanc is, well, they can’t
tell me” (p. 258). Their social conceptions are limited because they often
are based on one or two concrete personal experiences.
Concrete Operational Period (Roughly 7 to 11 Years)
Despite the considerable accomplishments in the preoperational period,
in many ways the period mainly prepares children for the pinnacle of
cognitive development: the mental operation. An operation is an internal-
ized mental action that is part of an organized structure. With the ability
to use operations, the child’s representations are no longer isolated,
rigid, or simply juxtaposed, as in the preoperational period. They are
brought to life.
We can most easily see operations at work in Piaget’s famous conser-
vation task, which we described earlier with respect to liquid quantity.
First, the child sees two identical containers equally filled with water and
judges them to contain the same amount of water. As the child watches,
one container is poured into a container with different dimensions or
into several small containers. A “nonconserver” claims that the amount
has changed, usually because the water level has changed. Typically,
since the water rises higher in a taller, thinner container, the child con-
cludes that the amount has increased. In contrast, a “conserver” believes
that the amount has not changed. She realizes that quantity remains the
same despite changes in appearance. Piaget usually required that the
child give a logical explanation for this judgment before he considered
the child to be a true conserver, for example, “You didn’t add any water
or take any away.”
Both nonconservers and conservers have a basis for their answers. In
fact, if a tester happens to test the same child twice— once when the
child is a nonconserver and later when a conserver— she may face the
child’s scorn on both occasions. The child on both occasions is likely
to think that the tester is dumb to ask the question when the “correct”
answer is so obvious.
Conservation is an important concept because it gives stability to the
physical world. In addition, Piaget assigned a great deal of importance
to the conservation task because he thought it reveals the presence or
absence of mental operations. Thus, it is a diagnostic tool that probes
the cognitive structures. Piaget asserted that children cannot conserve
unless they have certain mental operations, especially reversibility. The
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Description of the Stages c 49
negation aspect of reversibility is expressed by children who say, “If you
pour it back where it was, they will have the same amount.” The com-
pensation aspect of reversibility is seen in the explanation, “This one’s
taller but this one’s fatter.”
Operations also can be seen at work in the common mathematical
operations of multiplying, dividing, ordering (greater than, less than),
and substituting (one thing equals another thing). Each operation is
related to and obtains its meaning from the entire structure of which it
is a part. Thus, addition is coordinated with subtraction, multiplication,
and division to form a system of mental actions.
Piaget’s interest in logic and mathematics appears in his attempt to
describe these systems of concrete operations in terms of logicomathe-
matical structures. Logic and algebra involve purely formal, nonpsycho-
logical abstract systems. However, Piaget felt that cognitive structures
approximate these logicomathematical structures and that it would be
fruitful to look for various types of thinking suggested by the latter.
For example, in the concrete operational period there are nine
groupings— logical structures that describe certain logical operations
and relationships among these operations. Let us look at Piaget’s group-
ing I. This grouping describes the primary addition of classes and is the
simplest grouping. For example, modes of transportation form a classi-
fication hierarchy, in which modes of transportation (C) at the top of the
hierarchy have two subheadings: ground vehicles (B) and other classes
of vehicles (B’). B, in turn, contains cars (A) and other ground vehicles
(A’). The system’s elements (A, A’, B, B’, C) can be manipulated accord-
ing to certain rules based on the grouping’s properties, for example,
composition (A + A’ + B) or general identity (A + 0 = A).These prop-
erties, stated in formal, nonpsychological terms, serve as a model for
the properties of thought that underlie the concept of class inclusion.
Class inclusion is the concept that subcategories are part of a broader
category. The experimenter shows the child 20 wooden beads, 17 of
them brown and 3 white. He asks whether a child could make a longer
necklace with the brown beads or the wooden beads. Preoperational
children claim that there are more brown beads than wooden beads.
They can deal only with the parts (brown or white beads) or the whole
(wooden beads), but not both of them simultaneously. They do not
understand that the parts and the whole are reversible. In contrast, con-
crete operational children have the underlying operations (that look like
the grouping rules) necessary to derive the correct answer.
Piaget applied his logicomathematical model of concrete operations
to a wide variety of physical and social situations. For example, various
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50 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
properties are conserved in addition to liquid quantity, described earlier.
The number of objects in a set remains the same when they are spread
out; the total length of a stick remains the same if it is pushed ahead of
another stick; and the weight of clay remains the same if the clay is bro-
ken into pieces.
Operations apply not only to classes, as in class inclusion, or to prop-
erties such as amount, as in conservation, but also to relations. If concrete
operational children know that John is taller than Bill and that Bill is
taller than Henry, they can infer that John has to be taller than Henry. In
addition, they can order a row of dolls according to height and give the
dolls sticks ordered according to length. Operations also are applied to
temporal– spatial representations. For example, preoperational children draw
liquid in a container in such a way that it remains parallel to the base or a
side (as in Figure 2.1).Their perceptions are influenced by the immediate
surroundings. In contrast, concrete operational children correctly keep
the liquid parallel to the larger context, the surface of the earth.
Turning to the social realm, we see that children are overcoming
many of the limitations in their reasoning about the social world. They
are less egocentric but sometimes still have difficulties with role taking
and communication. They can take intentions into account in their moral
judgments. They also are increasingly aware of the subtle social relation-
ships in the family, peer group, and larger society. In addition, children
are beginning to sort out their various social identities. Piaget found
that young children tended to draw two circles side by side to represent
F I G U R E 2 . 1
A typical error on the water- level problem during the preoperational period.
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Description of the Stages c 51
Geneva and Switzerland. Nine- year- old Pierre correctly drew the for-
mer as a smaller circle inside the latter but still was struggling to apply
his class- inclusion concept to social understanding:
What is your nationality? —I am Swiss. —How come? —Because I live
in Switzerland. —Are you also Genevan? —No, that’s not possible. . . . I’m
already Swiss, I can’t also be Genevan.
Two other 8- year- olds also do not quite have it right:
Do you know any foreigners? —Yes . . . those who live far away. —For
example, if you travel to France, could you also become a foreigner
in certain situations? —No, I’m Swiss. —A Frenchman, could he be a
foreigner? —Oh! Yes, a Frenchman is a foreigner. —And in France is a
Frenchman a foreigner? —Oh yes. —What is a Frenchman in Switzerland?
—French, but also a little Swiss if he’s here.
(Piaget, 1965/1995, pp. 252, 263, 265)
This list of acquisitions could continue to the end of this book, but the
examples we have considered are representative. Two points about con-
crete operational acquisitions should be kept in mind. First, they do not
develop at the same time. In fact, some concepts, such as conservation
of weight, often do not appear until near the end of the period. Second,
each cognitive acquisition develops over a period of time. At first, it is
transitional in nature and is demonstrated only part of the time. It grad-
ually strengthens, stabilizes, and generalizes to a variety of situations.
In summary of Piaget’s stages to this point, children move from an
understanding of the world based on action schemes, to one based on
representations, to one based on internalized, organized operations.
Thought now is decentered rather than centered, dynamic rather than
static, and reversible rather than irreversible. For the first time, the lawful
nature of the world seems to be reflected in a logical system of thought.
Thought is in tune, in equilibrium, with the environment. However, the
concrete operations are still “concrete.” They can be applied only to con-
crete objects— present or mentally represented. They deal with what
“is” rather than what “could be.” The final step is to apply the operations
to purely verbal or logical statements and to the possible as well as the
actual. This story unfolds as we turn to formal operations.
Formal Operational Period (Roughly 11 to 15 Years)
During the concrete operational period, mental operations are applied
to objects and events. Children classify them, order them, and reverse
them. During formal operations, adolescents carry concrete operations
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52 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
one step further. They can take the results of concrete operations and
generate hypotheses about their logical relations. Thus, we now have
operations on operations; children can think logically and abstractly
about events, even hypothetical ones.
More specifically, formal operational thought resembles scientific
thinking. Adolescents formulate a hypothesis about a present or potential
event and test this hypothesis against reality. If necessary, they can gen-
erate all possible outcomes at the beginning. Piaget typically presented a
problem from physics or chemistry and observed how adolescents went
about solving it. The problem- solving process, rather than the correct
answer, is of interest.
A prototypic task is the pendulum problem. An adolescent observes
an object hanging from a string and attempts to discover what deter-
mines how fast the object swings. She is shown how to vary the length
of the string, the height from which the pendulum is released, the
force of the push on the pendulum, and the weight of the object. One
or several of these variables might control the speed of the swing.
Concrete operational children experiment with the variables and may
even arrive at the correct answer (the length of the string), but their
approach is haphazard; they have no overall plan. They do not vary one
factor while holding the other factors constant in order to systemati-
cally isolate the critical factor. For example, they may compare a long,
light pendulum with a short, heavy one and conclude that both factors
are important. In contrast, formal operational adolescents imagine all
possible determinants of the rate of swinging before they begin, sys-
tematically vary the factors one by one, observe the results correctly,
keep track of the results, and draw the appropriate conclusions. By
testing predictions from each hypothesis, they demonstrate hypothetico-
deductive thought. More generally, as Flavell expressed it, “Reality is
thus conceived as a special subset within the totality of things which
the data would admit as hypotheses; it is seen as the ‘is’ portion of a
‘might be’ totality, the portion it is the subject’s job to discover” (1963,
pp. 204–205).
Piaget posed several other problems:
1. Determine which mixture of five colorless liquids produces a yellow color.
2. Discover which variables (for example, weight, length, types of material)
cause a rod suspended over water to bend down far enough to touch the
water.
3. Discover and state the law governing the relationship between the angle at
which a billiard ball hits the table wall and the angle of its rebound.
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Description of the Stages c 53
4. Solve a geometric proof.
5. Discover proportional relationships (for example, 16 is to 4 as 4 is to 1).
6. Evaluate syllogisms, such as “All children hate spinach; girls are children;
therefore, girls hate spinach.”
It should be noted that direct instruction in scientific thought is not
necessary for the development of formal operations. Rather, years of
common, unremarkable experiences contribute to this achievement. As
Einstein remarked: “The whole of science is nothing more than a refine-
ment of everyday thinking.”
As in the concrete operational period, Piaget applied logicomath-
ematical models to the child’s thought. He identified a system of 16
underlying mental operations he thought necessary for solving the vari-
ous problems he presented. One operation, for example, is conjunction,
which refers to the co- occurrence of x and y. In the problem of what
causes rods to bend, a conjunction outcome would be great length, great
bending.
In addition to these operations, Piaget’s logical model included a
system of rules for manipulating the logical relations identified by these
operations. For example, in a weight- balance problem, an imbalance
can be negated by subtracting the extra weight from the heavier side or
adding more weight to the lighter side.
The ability to consider abstract ideas, the future, and various possi-
bilities is evident in adolescents’ social world. They dream about their
futures and imagine themselves in various occupational and social roles.
They may experiment with some of these roles just as they experiment
with hypotheses about physical events. They are concerned with the
world of ideas. With their friends, they debate various moral and polit-
ical issues, such as whether wars can ever be moral, whether abortions
should be legal, whether there are basic inalienable human rights, and
what an ideal community would be like. They can consider these issues
from different perspectives and see how the issues are related to a larger
set of social relationships. However, there is still a lingering egocentrism.
Adolescents are impressed with the power of thought and naively under-
estimate the practical problems involved in achieving an ideal future for
themselves or for society. They feel that the sheer force of their logic
will move mountains. Piaget noted that this starry- eyed egocentrism is
squelched when adolescents undertake their first real job!
One further difference between concrete operational thought and
formal operational thought has implications for both social and physical
development. Adolescents can reflect on their own thinking (and that
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54 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
of others). For example, they can think about propositions, which are
thoughts. Or, in the social realm, we find the following line of thought:
“He’s thinking that I’m thinking that he’s thinking about her.”
By achieving formal operations, adolescents complete their cognitive
structures. The various concrete operational logical systems have been
combined to create a single, tightly organized system of thought— a uni-
fied whole. Thought is logical, abstract, and flexible. Thinking continues
to develop throughout adulthood as formal operations are applied to
more and more content areas and situations. Egocentrism continues to
decline as people broaden their experiences in the world of work and
social relationships. However, Piaget thought that these changes after age
15 entail a change not in the structure of thought but only in its content
and stability.
An Overview
Now that we have reached the height of Piaget’s theory, it would be good
to look back over our climb. Perhaps the best way to highlight the differ-
ences between periods is to see how a typical child in each period would
understand several aspects of reality. First, what is an “object” for a child
in each stage? During the sensorimotor period, an object that at first is
simply a stimulus for feeding a reflex becomes something on which one
can act. Then an object becomes an independently existing entity that is
separate from one’s actions and can be mentally represented. For a pre-
operational child, an object can represent another object, can undergo
physical changes while maintaining its identity (if not its amount), and
can be joined with other objects to form a category of objects. During
the period of concrete operations, various operations manipulate the
representation of an object; for example, any changes in the object can
be reversed, and the object can be fit into a hierarchy of categories.
Finally, formal operations involve higher- order operations that allow
further mental manipulations of the representation of the object. All the
object’s possibilities can be examined scientifically.
Another way of slicing the periods vertically is to consider how a child
in each period would attack a specific problem. Consider what would
happen if we gave children in each stage a tub of water and a number
of small objects of various densities, sizes, weights, shapes, and colors.
Infants would immediately splash, throw the objects, push the objects to
the bottom of the tub, and probably attempt to eat the objects. Toward
the end of the sensorimotor period, children might drop the objects
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Memory c 55
from various heights and note that the bigger, heavier objects make
bigger splashes than do the smaller, lighter objects. They might also
notice that some objects sink while others do not. Preoperational chil-
dren might imagine that the objects are boats or fish. They would notice
that some objects float while others sink, but they would be content to
change their reasons from case to case. They might claim that one object
floats because it is little, another because it is dry, another because it is
a boat, and so on. Concrete operational children are bothered by incon-
sistencies that did not bother them in the previous stage, such as the
fact that some small objects sink while other small objects float. They
make comparisons between objects, but they are neither systematic nor
exhaustive. For example, they do not hold size constant while varying
weights. However, they do develop several categories of “sinkability,” for
example, always floats (lightweight), always sinks (heavy), and sinks or
floats depending on the materials (small objects, lids). Formal opera-
tional adolescents have both a plan and the necessary operations to solve
the problem. They systematically vary the factors to determine their
influence and use the results to test their hypotheses. They know that
density is the proportion of weight to volume and that the relative den-
sity of the object to the water is the critical factor. Adolescents are able
to form a proportion made up of two other proportions: the density for
the objects and for the water. These are operations on operations. This
general law allows them to predict whether any particular object will
sink or float.
Memory
Some of Piaget’s most dramatic claims stem from his work on mem-
ory. Consider the following typical experiment by Piaget and Inhelder
(1969): They showed children an array of 10 sticks of various sizes that
were ordered according to size. A week later they asked the children to
draw from memory the array of sticks they had seen. Developmental
differences emerged. In general, 3- and 4- year- olds drew a few sticks
having the same length. The 5- and 6- year- olds tended to draw some tall
and some short sticks. Most 7- year- olds could draw the original array
correctly. Piaget and Inhelder concluded that the children had processed
and interpreted the original array in terms of their present understand-
ing of ordered relations. Only when this understanding is fully achieved
can the child accurately remember the array. Thus, memory reflects and
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56 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
depends on the entire cognitive structure. Memory is active understand-
ing rather than a static, passive state— a camera.
Although this is an interesting set of results, the children’s behav-
ior six months later when they returned was even more surprising.
Although the children were not shown the sticks again, this time 75 per-
cent of the children drew arrays that were more advanced cognitively
than those they had produced six months earlier. For example, a child
who originally lined up three tall sticks of the same height and three
short sticks of the same height later made a row of three tall sticks,
three medium- size sticks, and three short sticks. Piaget’s interpretation
was that such improvements are due to development in their cognitive
structures during those six months. Current cognitive structures are
applied to the memory process. Note that improvement in memory
over time is the opposite of what one would expect from most theories
of memory or from common sense: a memory trace fades over time.
Unfortunately, other researchers have not always replicated Piaget’s
results. There is more support for the age differences in memory than
there is for improved memory of the materials after further cognitive
development (see Liben & Bowman, 2014, for a review and critique).
Still, Piaget’s claim that our knowledge influences, and thus biases, what
we know is central to much current research and theorizing on memory
development (see Chapter 7).
Piaget offered the following memory from his second year of life to
show that memory can be unreliable:
I was sitting in my pram, which my nurse was pushing in the Champs
Elysées, when a man tried to kidnap me. I was held in by the strap fas-
tened around me while my nurse bravely tried to stand between me and
the thief. She received various scratches, and I can still see vaguely those
on her face.
(1945/1951, p. 188)
When Piaget was 15, his parents received a letter from the nurse
shortly after she had joined a religious order. She said she wanted to
return the watch that had been given to her as a reward for protecting
little Jean from the kidnapper. The truth was that she had made up the
story that Piaget so vividly “remembered.” Piaget believed that he had
created a visual memory from the story his parents had told him as
a child.
In addition to studying memory performance, Piaget examined chil-
dren’s concepts of memory. This topic was rediscovered by develop-
mental psychologists 50 years later and labeled “metamemory,” which
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Mechanisms of Development c 57
is described in Chapter 7. A sample of Piaget’s work is the following
interview with an 8- year- old innatist:
Memory is something in the head which makes us think.—What do you think
this memory is like? —It is a little square of skin, rather oval, and inside there
are stories (les histoires).—What are they like? —They are written on the
flesh. —What with? —Pencil. —Who wrote them? —God, before I was
born, he put them there.
(1926/1929, p. 52)
Mechanisms of Development
Piaget recognized that it was important not only to describe cognitive
stages but also to explain how and why children develop through those
stages. In other words, by what processes does a child’s thinking prog-
ress? How do new forms of thinking emerge? What facilitates or con-
strains the transition from step to step? Emphasizing the grand stages,
which span several years each, can make us forget that thought actually
develops in the moment- to- moment, everyday encounters between
children and their physical and social environments. Stagelike changes
ultimately are due to millions of these minidevelopments.
In Piaget’s theory, these small steps are driven by certain functional
invariants. The functional invariants are thinking processes— organization,
adaptation, and equilibration— that operate throughout development.
Piaget drew on these processes from biology that define the relation-
ship between the organism and the environment. Our thinking, like the
circulatory system and the digestive system, has innate tendencies to be
organized and adapted to the environment. With apologies to Descartes,
it could be said that “I am, therefore I think.”
Cognitive Organization
Cognitive organization, described in the earlier section on structural-
ism, is the tendency for thought to consist of systems whose parts are
integrated to form a whole. These systems, in turn, are coordinated;
there are interrelationships among cognitive activities. The mind is not
a grab bag of facts. Rather, it is a coherent view of the world. This view
becomes more and more coherent and interrelated as children develop.
For example, a young infant has separate structures for sucking objects
and for grasping them. Only later are these two structures organized
into a higher- order structure that allows coordinated reaching for an
object and bringing it to the mouth.
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58 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
Development through the stages involves changes in the nature of
cognitive organization as the structures of thought change from stage
to stage. As development proceeds, thought may be organized into
schemes, functions, concrete operations, or formal operations. Thus, an
infant’s sucking on a toy and Einstein’s insights into relativity both reflect
cognitive organization. In principle, one could trace a line of develop-
ment from the former to the latter.
Cognitive Adaptation
The other basic functional invariant, cognitive adaptation, pertains to a fit
between the mind and the environment: Intelligent behavior is behavior
that is appropriate to the demands of the environment. Adaptation and
organization are closely related:
Organization is inseparable from adaptation: They are two complemen-
tary processes of a single mechanism, the first being the internal aspect
of the cycle of which adaptation constitutes the external aspect. . . . The
“accord of thought with things” and the “accord of thought with itself
” express this dual functional invariant of adaptation and organization.
These two aspects of thought are indissociable: It is by adapting to things
that thought organizes itself and it is by organizing itself that it struc-
tures things.
(1936/1952b, pp. 7–8)
Adaptation involves two complementary processes: assimilation and
accommodation. Assimilation is the process of fitting reality into one’s
current cognitive organization. In every cognitive encounter with
objects or events, there is a degree of “bending” or distorting of expe-
rience as people attempt to incorporate, understand, or interpret this
experience. In other words, people apply what they know in order to
understand objects and events. To quote Anaïs Nin, “We don’t see things
as they are, we see them as we are.”
Accommodation is the other side of the coin. This term refers to adjust-
ments in cognitive organization that result when reality does not fit our
expectations. Every object has special characteristics that eventually
must be taken into account. In a sense, accommodation occurs because
of failed assimilation, when the current structure cannot understand a
particular object or event. The resulting reorganization of thought leads
to a more satisfactory assimilation of the experience. Then that object
or event is never again experienced in quite the same way. As Oliver
Wendell Holmes commented, “Man’s mind stretched to a new idea
never goes back to its original dimensions.”
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Mechanisms of Development c 59
Assimilation and accommodation are closely intertwined in every
cognitive activity from birth to death. Attempts to assimilate reality
necessarily involve slight changes in the cognitive structures as these
adjust to the new elements. In true Piagetian style, both a biological
example and a psychological example are needed. In the biological
realm, food is assimilated into the body as it is changed into a form the
body can use. As Piaget expressed it, “A rabbit that eats a cabbage doesn’t
become a cabbage; it’s a cabbage that becomes rabbit— that’s assimila-
tion” (quoted in Bringuier, 1980, p. 42). The digestive system accom-
modates to food by adjusting the mouth opening, chewing, secreting
digestive juices, contracting the muscles of the stomach, and so on. Thus,
the digestive system both changes and is changed by an environmental
event, the presentation of food.
In the psychological realm, consider an infant who has happened onto
a sheet of newspaper for the first time. In an attempt to make sense
of this new experience, she runs through her repertoire of actions on
objects. She applies her current cognitive structures (schemes). She
grasps the paper, hits it, sucks it, turns it over, shakes it, and puts it
over her head, in her attempts to fit this new object into something she
already knows (assimilation). However, a newspaper has certain charac-
teristics foreign to her existing schemes. She is forced to stretch or reor-
ganize (accommodate) these schemes in small ways: Her ideas about the
way things sound when they are shaken must be altered to include the
rustle of a newspaper. The light weight and the new feel and sight make
further demands on her mind. Some properties (for example, ripping
the paper) may be quite foreign and startling.
These varying degrees of discrepancy between current schemes
and the experience at hand raise the issue of what the limitations are
to accommodation. Piaget’s answer is that only moderately discrepant
events or characteristics can be accommodated to; great leaps are not
possible. If reality is too different from the person’s current level of
understanding, she cannot bridge the gap. Thus, development necessarily
proceeds in small steps.
To illustrate this gradual, continual development through accommoda-
tion, consider what would happen if children of various ages were given
a horseshoe- shaped metal magnet for the first time. Six- month- olds
might accommodate to the unfamiliar metallic taste, the peculiar (horse-
shoe) shape, and the sound of the magnet being dropped. However, they
cannot accommodate to its magnetic properties. Three- year- olds, if
given an assortment of objects, might accommodate to the fact that some
of the objects cling to the magnet and might entertain explanations such
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60 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
as “stickiness” and “wanting to stay together.” Nine- year- old children
might construct the concept that only metal objects are pulled to the
magnet and might notice the conditions in which this occurs— through
glass, water, and certain distances. Only adolescents could accommo-
date by formulating an abstract theory of magnetism and simultaneously
consider all of the variables involved, such as the size and shape of the
magnet and the distance from the object. Thus, accommodation always
occurs in small steps and is relative to the present cognitive level.
In summary, assimilation and accommodation are present in every act
and stimulate cognitive development. Attempts to apply one’s current
intellectual structures typically are only partially successful because most
encounters with the environment are new in some way. As a result of
this failure to “understand” the object or event, minor cognitive adjust-
ments or accommodations are made. These push children to a slightly
more advanced cognitive level, one step closer to reality. However, this
new level of understanding makes them aware of other discrepancies
in experience, and again assimilation presents new elements and again
accommodation occurs. Each accommodation makes new accommo-
dations possible in the future. This spiral continues in our moment- to-
moment encounters with the environment throughout our lives.
Cognitive Equilibration
Organization and adaptation imply a third functional invariant, equilibra-
tion. Both mollusks and human cognition are self- regulating equilibration
systems. In Piaget’s view, every organism strives toward equilibrium with
the environment and equilibrium within itself (among elements of the
cognitive system). When assimilation and accommodation are in bal-
anced coordination so neither one is dominant, equilibrium is achieved.
This balance is achieved through the development of organized struc-
tures that provide ways of interacting with the world. A change in either
the organism or the environment leads to a state of disequilibrium,
which must be corrected. It should be clear from other parts of Piagetian
theory that equilibrium is dynamic rather than static. There is constant
activity, but there is a balance, a pattern, to this activity.
For example, in the liquid- conservation task, children are in disequi-
librium if they switch back and forth between saying that the tall thin
one has more because the liquid is higher or the short fat one has more
because the liquid is wider. Acquiring the mental operation, compensa-
tion, allows them to integrate information about the two dimensions.
One dimension compensating for the other eliminates the contradiction
and re- establishes equilibrium.
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Mechanisms of Development c 61
Equilibration, while one of the most important concepts in the
theory, is probably also the most difficult and evasive. Part of the diffi-
culty may lie in the fact that equilibration can refer to several spans of
time, ranging from a fraction of a second to a number of years. In each
case, there is a period of equilibrium, followed by a state of disequilib-
rium, followed by equilibration, which leads again to equilibrium at a
higher cognitive level.
Piaget seems to have at least three spans of time in mind when he
applies the notion of equilibrium:
1. A moment- to- moment equilibration process occurs as assimilation and
accommodation operate in children’s daily activities, even the most mun-
dane. Temporary disequilibrium occurs when children encounter new
properties of objects that do not fit into their present cognitive structures.
Once the assimilation– accommodation process occurs and discrepancies
are resolved, equilibrium is again achieved.
2. Equilibration refers to moving toward the final level of achievement with-
in each period or stage. A child enters a new period in a state of relative
disequilibrium because the old cognitive organization has broken down
but the new one is still incomplete and unstable. By the end of this new
period, a child has achieved equilibrium with respect to the period’s new
structures. For example, at the end of the sensorimotor period, a child
is in equilibrium with the environment in terms of action schemes.
Equilibrium is re- achieved in each period at a higher and higher level of
abstraction.
3. The entire course of cognitive development can be seen as a process of
equilibration as the child proceeds through increasingly “better” forms
of equilibrium. The most complete equilibrium is achieved when formal
operations bring fully reversible and abstract thought. The earlier states of
equilibrium, because they are incomplete, inevitably break down at some
point. In a sense, each period or stage eventually self- destructs.
For Piaget, equilibration is the grand process that integrates and regu-
lates all of the elements of development— physical maturation, expe-
rience with the physical environment, and the influence of the social
environment. These forces together propel children through the stages.
Section Overview
Perhaps the best way to summarize this section on mechanisms of devel-
opment is to relate it to the earlier sections of this chapter. Knowledge
of the world develops through a series of discrete states of equilib-
rium (stages) between the organism and the environment. This is the
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62 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
essence of Piaget’s genetic epistemology. Mental structures, in equi-
librium, are constructed as children interact with physical objects and
people in an organized way. Here we see Piaget’s structuralism. In the
innate tendencies toward organization and adaptation (assimilation and
accommodation), we see Piaget the biologist explain how minds adapt to
the environment. Finally, the particular stages are an inevitable outcome,
given the nature of the human organism (its physical structures and cog-
nitive functions) and the nature of the environment.
Position on Developmental Issues
This book’s Introduction identified four basic developmental issues
on which each theorist takes a stand. Using these issues, we can view
Piaget’s theory from a new perspective. The issues also provide a means
for comparing the diverse theories covered in this volume.
Human Nature
Piaget’s worldview clearly was organismic rather than mechanistic or
contextual. He posited an inherently active organism. Children tire-
lessly explore, hypothesize, test, and evaluate; they do this either overtly
(particularly in the sensorimotor period) or covertly (as in the manip-
ulation of symbols, concrete operations, and formal operations). No
external motivation is necessary. Children are intrinsically motivated;
schemes are used simply because they exist. Once activated, they tend
to be repeated. In other words, “To be is to do.” The Piagetian child is a
self- regulating, organized whole striving to maintain equilibrium both
internally and with the environment by correcting cognitive imbalances.
These tendencies toward inherent activity and self- regulation cause
continual change. The organismic worldview also can be seen in the fact
that the parts can be understood only in terms of the whole. Any one
behavior, scheme, or operation is influenced by and derives its meaning
from the whole structure. The same behavior (for example, swinging a
pendulum) has a different meaning for a 2- year- old and a 12- year- old.
Qualitative Versus Quantitative Development
Although Piaget saw both qualitative and quantitative changes, he
emphasized qualitative changes in structures from stage to stage. Just as
the colored plastic fragments rearrange themselves when a kaleidoscope
is turned, so does the organization of thought change to form new
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Posit ion on Developmental Issues c 63
patterns as the child develops. Quantitative changes occur as schemes,
operations, or other cognitive skills become stronger, more easily acti-
vated, more efficient, and more consistent. Other quantitative develop-
ments are the increased number of schemes in the child’s repertoire or
the number of “facts” known. A child who can name the capitals of all
the states has more information at hand than the child who can name
only five capitals. Of course, it should be kept in mind that these facts
are always assimilated into structures that undergo qualitative changes.
Qualitative and quantitative changes build on each other during
development. A qualitative change in structure makes possible certain
quantitative changes. For example, once class inclusion is understood,
children can quickly learn about the classifications and relationships in
many different content areas, such as animals, people, trees, shapes,
and colors. Quantitative increases in amount of information, in turn,
may pave the way for further qualitative change as new information
challenges the present structures. For example, talking with peers
and adults rapidly expands children’s knowledge and challenges their
present understanding. This new information can stimulate subsequent
qualitative change as the system attempts to resolve the contradictions
in children’s knowledge.
Whether we see quantitative or qualitative change in Piaget’s theory
depends, in part, on the unit of time we select. If we look at changes
over minutes, days, and weeks, we are struck by the gradual nature
of development. If we look at changes over months and years, we are
struck by the qualitative changes from stage to stage or period to period.
For example, from age 4 to 5, children may become more consistent
in their grouping of objects according to shape; this is a quantitative
change. However, the change from age 5 to 7, when they can sort objects
into hierarchies of classes— for example, animals, mammals, brown
mammals, and so forth— is qualitative.
Nature Versus Nurture
Piaget was an interactionist through and through. Cognitive develop-
ment is a by- product of the intertwined influences of innate and expe-
riential factors. Innate factors include physical structures (for example,
the structure and positioning of the particular species’ eyes), reflexes,
physical maturation, and the invariant functions (organization and adap-
tation). Given these innate factors and the nature of the physical and
social world, development inevitably proceeds in the way it does. It
could not be otherwise.
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64 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
Piaget proposed the following four- factor “formula” for development:
Development = Physical maturation + Experience with the physical
environment + Social experience + Equilibration
1 The first factor, physical maturation— of the brain, the muscular sys-
tem, and the like— creates new possibilities for the cognitive system
and requires certain adjustments of that system. For example, when
physical maturation permits walking, new vistas open up for toddlers. As
children actively exploit this new skill, they are forced to assimilate and,
whenever possible, accommodate to new experiences.
2 Regarding experience with the physical environment, Piaget empha-
sized logicomathematical experience. This term refers to reflecting on
one’s own actions on objects rather than on the objects themselves.
To illustrate, Piaget referred to a friend’s recollection from childhood:
He was seated on the ground in his garden and he was counting pebbles.
Now to count these pebbles he put them in a row and he counted them
one, two, three up to 10. Then he finished counting them and started to
count them in the other direction. He began by the end and once again
found he had 10. He found this marvelous. . . . So he put them in a circle
and counted them that way and found 10 once again.
(1964a, p. 12)
The child reflected on the results of repeatedly counting and arrang-
ing the pebbles and concluded that number is constant despite physical
rearrangements. He discovered something (number) that is not intrinsic
to the objects.
3 Social experience includes the cultural or educational environment.
For example, other people transmit knowledge, either directly, in
conversations, or through books, television, and so on. In this way,
children can benefit from the experience of others. Of course, a child
must be cognitively advanced enough to assimilate the information if it is
to be of value. Social experience can also impede learning; not all adult
products provide good models to learn from, as seen in a sign that defies
class- inclusion logic: “Please do not feed birds or animals.”
These three factors are universal. Given the similarities among
cultures in children’s physical maturation, the physical world, and,
in some ways, the social environment, it is not surprising that the
four major periods proceed in the same order in all cultures studied.
However, given cultural differences, one would expect that, within a
stage, some concepts might develop earlier in some cultures than others.
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Applications c 65
For example, in Mexico, children aged 6 to 9 who grow up in pottery-
making families are more likely to be conservers of substance than those
who grow up in families engaged in other activities ( Price- Williams,
Gordon, & Ramirez, 1969). This finding suggests that experience with
clay promotes the development of this concept (often assessed with clay
as the medium). In addition, Piaget recalled that his daughter Jacqueline,
born in the winter, was often bundled up in a carriage, so had less
opportunity than children born in warmer weather to develop eye– hand
coordination.
4 The fourth factor, equilibration, ties together and controls the inter-
action of innate and experiential factors. Maturation, experience
with the physical environment, and the influence of the social envi-
ronment constantly cause momentary disequilibrium. In this way, they
force the cognitive system to change, to adjust. Through re- establishing
equilibrium, the cognitive system reaches a higher level.
What Develops
For Piaget, the essence of cognitive development was structural change,
in the schemes and logicomathematical structures. Structural change
gives meaning to, and influences change in, the content of thought. Thus,
Piaget emphasized change on a molar level as children construct a model
of reality, which leads to change at more molecular levels.
The question of what develops is tied to Piaget’s methodology. He
relied on observations, interviews (the clinical method), and assessment
situations in which the experimenter participates. In this way, he kept
the organization of the thought processes as intact as possible; too much
experimental interference or control would distort the child’s normal
line of reasoning.
Applications
Educators have applied Piaget’s theory to instruction. One example is
his notion of “readiness”—that children can profit from instruction only
if they are cognitively ready to assimilate the new information to their
present cognitive structures or accommodate their structures to the
experience. Instruction in calculus would not be successful with most
5- year- olds. Related to this, teachers should teach concepts in a particu-
lar sequence of developmental steps, as they naturally would be learned.
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66 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
Another important notion is that learning is most likely to occur when
children actively participate and, for children who have not yet reached
formal operations, when teachers present problems in a concrete rather
than abstract way. Importantly, for true understanding, children must
learn the concepts underlying mathematical and scientific knowledge
rather than just memorize facts. A 2- year- old who can count to 10 may
not actually understand numbers. Piaget would be critical of “teaching
to the test.” He criticized typical educational assessments for focusing on
correct answers rather than on children’s thought processes for reaching
the answers. In short, a teacher mainly provides guidance and resources
so that children can teach themselves.
The neo- Piagetians, to be described later in this chapter, would add
a focus on teacher support for the child’s fragile new concepts, for
example, encouragement, modeling, hints, or collaboration. They also
would encourage teachers to make sure that problems to be solved are
presented in a way that does not overload the child’s cognitive capacity.
Finally, since different children may follow different developmental
pathways to acquiring a concept, it is important for teachers to be aware
of these individual differences in ways of learning.
Evaluation of the Theory
When Piaget’s first writings on children appeared, he was appalled that
people evaluated them as though they were final statements on cognitive
development rather than the tentative positions he intended them to be.
In fact, he continued to modify his theory even into his eighties. After
this section on strengths and weaknesses, we will look at some of the
modifications that attempt to address some of the weaknesses.
Strengths
We focus on four strengths of Piaget’s theory: its recognition of the cen-
tral role of cognition in development, its discovery of surprising features
of young children’s thinking, its wide scope, and its ecological validity.
Recognition of the Central Role of Cognition c Cognition now is
such a central part of the study of development that it is hard to imag-
ine that this was not always the case. If a developmental psychologist
were somehow plucked out of the 1950s and set down today, he would
be bewildered by the talk around him. He would hear psychologists
discussing children’s “theories,” strategies, cognitive structures, plans,
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Evaluation of the Theory c 67
and representations, instead of stimulus generalization, mean length of
utterance, mental age, conditioning, and discrimination learning. To a
great extent, Piaget is responsible for this change. He altered the course
of psychology by asking new questions that made developmentalists
wonder why they had ever asked the old questions in the first place.
Once psychologists looked at development through Piaget’s eyes, they
never again saw children in quite the same way.
Both the state of academic psychology and the history of developmen-
tal psychology in the United States created a state of readiness for the
assimilation of Piaget. Academic psychology had pushed behaviorism in
general and learning theory in particular to their limits and found them
wanting. Even when learning theory was modified by such notions as
verbal mediation, social reinforcement, modeling, intrinsic reinforce-
ment, and attention, it did not completely satisfy psychologists. There
was dissatisfaction with the explanation of language development in
terms of imitation, practice, and reinforcement. At the same time, alter-
native cognitive approaches were emerging, such as Noam Chomsky’s
transformational grammar and computer scientists’ work on informa-
tion processing.
Within developmental psychology, until the 1950s researchers could
be found less often in departments of psychology than in “child insti-
tutes” or departments of home economics, pediatrics, public health,
education, clinical psychology, and nursing. Developmental psychol-
ogists were concerned with poor nutrition, physical and intellectual
disabilities, learning disabilities, and emotional disorders. Because of
this physical and ideological separation from psychology departments,
many developmental psychologists did not become immersed in the
behaviorist– experimental zeitgeist of academic psychology of the times
and kept one foot in the laboratory and one foot in real- life settings. In
addition, developmental psychologists at that time were primarily inter-
ested in collecting normative data— descriptions of the behaviors that
could be expected at each age. For all these reasons, there was room for
Piaget’s naturalistic, descriptive approach. The field of developmental
psychology was ready for Piaget.
A newcomer to developmental psychology might wonder why Piaget
had produced almost a lifetime of work before American academics
became interested in him. Certainly the state of academic psychology at
that time, described above, provides part of the answer. A further rea-
son is the language barrier. Until the 1960s, much of Piaget’s work had
not been translated into English. An additional language problem is that
Piaget’s writings are difficult to understand in any language. Fortunately,
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68 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
several developmental psychologists in the United States served as lit-
eral and psychological translators of Piaget’s work in the late 1950s and
early 1960s. In particular, John Flavell’s timely book, The Developmental
Psychology of Jean Piaget (1963), made Piaget understandable to English-
speaking psychologists.
The rest, as they say, is history. Psychology witnessed a flurry of
Piagetian replication studies, attempts to fit Piaget into the existing field
of developmental psychology, and efforts to train children to acquire
various Piagetian concepts, especially conservation. Researchers con-
ducted laboratory studies of variables such as the nature of task mate-
rials and instructions, the scoring criteria, and the socioeconomic level
of the children. Piagetian- influenced research peaked in the late 1970s
through the early 1980s when approximately one- third of the articles
in major developmental journals cited Piaget (Iaccino & Hogan, 1994).
Piaget’s theory spread into areas such as social development, clinical psy-
chology, and education. This was the “Piagetian stage” of developmental
psychology.
The purpose of this historical side trip is to show the impact of a
theory that recognized the central role of cognition in development.
Piaget searched for the modes of thinking underlying the overt behavior
studied by behaviorists and by child psychologists constructing norms
of development. This focus on cognition provided a new perspective
and inspiration for a generation of developmental psychologists. As
Lourenco and Machado observed, “Paraphrasing Einstein on Euclid, if
Piaget failed to kindle your youthful enthusiasm then you were not born
to be a developmental psychologist” (1996, p. 157)
Discovery of Surprising Features of Children’s Thinking c Piaget’s
main legacy may be his rich description of what it is we develop. The
thousands of observations by Piaget himself plus the thousands of studies
inspired by him constitute a remarkable body of information. Regardless
of the final judgment on his theoretical claims and the exact ages at
which each concept is acquired, his detailed, sensitive, and astute obser-
vations remain with us.
Piaget revealed new developmental phenomena, many of which
strike people as surprising, or counter to common sense. Especially
notable are the following: Young infants often act as though they do not
think that objects are permanent. Preschoolers believe that rearranging
objects can change their number and assert that the wrongness of an act
depends on how much damage resulted. More generally, most concepts
not only take longer to develop than we might think but also go through
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Evaluation of the Theory c 69
a number of interesting steps along the way. A further surprise is that
children think about such a wide variety of things. Children’s thinking
ranges from pondering the origin of the universe to solving the prob-
lem of how to open doors without dropping what they are holding,
from penetrating the nature of society’s moral system to determining
the speed of the swing of a pendulum. In a discipline that has few real
“discoveries” to rival the discovery of a new planet or the structure of
DNA, Piaget’s surprises about cognitive development are refreshing and
his observations remarkable, especially considering that they came from
seemingly mundane, everyday behavior.
Wide Scope c Piaget’s theory is ambitious, drawing its net over behav-
ior ranging from playing with pebbles to causal reasoning, from the
sucking reflex to formal operational structures. The theory attempts
to describe and explain both cognitive stages and transitions between
those stages. Piaget not only tackled cognitive development but also
its implications for other areas of development, such as social and
emotional development and learning. He also contributed to other
disciplines, such as epistemology, philosophy of science, and education.
In Piaget we catch a glimpse of how a complete theory of development
might look.
The theory’s wide scope obviously increases its attractiveness. At the
same time, it increases its vulnerability, as will be seen in the section on
weaknesses. The theory may try to do too much.
Ecological Validity c Every psychologist has an intuitive list of what a
good theory should do. Many lists would include the requirement that
the theory tell us about the real world of children. Although even the
most basic research in laboratories has some relevance for day- to- day
behavior, some approaches have a closer relationship than others to
common, everyday behaviors. Piaget’s theory seems to rate well in this
respect. The focus is on children’s adaptation to the world they encoun-
ter every day. Infants try to grasp a rattle just out of reach, replace a
pacifier, and figure out where a ball has rolled. Preschoolers divide their
cookies with friends, try to express their ideas to others, and chastise
those who break the rules of games. Schoolchildren struggle with math
problems, try to make sense of social rules, and find their way around
their neighborhood or city.
The ecological validity of the theory is more striking for infancy than
for the later stages of development. When studying children beyond
infancy, Piaget tended to interrupt the flow of behavior with questions
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70 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
or even pose problems from the beginning. The reason is that infants’
thinking is expressed in their overt actions, whereas older children’s
thinking is more covert and must be prodded.
Weaknesses
Although Piaget’s theory broke much new ground, it has been heav-
ily criticized as well. The theory provides an easy target because of its
methodology, wide scope, and ties to biology and philosophy. We exam-
ine the following weaknesses: inadequate support for the stage notion,
inadequate account of mechanisms of development, need for a theory of
performance, slighting of social and emotional aspects of development,
underestimation of abilities, and methodological and stylistic barriers.
Lourenco and Machado (1996) can be consulted for a Piagetian defense
against some of the criticisms described below as well as other criticisms.
Inadequate Support for the Stage Notion c The strongest attacks on
Piaget’s theory concerned his notion of stages, the heart of the theory.
Are there, in fact, broad stretches during development that have charac-
teristics that apply to all the psychological events during that period? Or
does the notion of stages simply confuse and mislead by oversimplifying
development and claiming more coherence among concepts than there
actually is? It is not clear whether Piaget actually thought that the logical
structure of each stage should lead to similarity in thought over a variety
of content areas, or whether his logical models were just idealized depic-
tions of each stage. Stages based on logical models might work best as
a heuristic that suggests what to look for and provides a framework for
interpreting behavior. Perhaps the problem of interpreting what Piaget
meant is that “Piaget used too much logic for psychologists and too
much psychology for logicians” (Lourenco & Machado, 1996, p. 156).
The evidence does not support a strong structural version of stages,
in the sense of concurrent changes across all content areas. However,
Piaget himself acknowledged that a structure may apply only to a par-
ticular content area and may have to be constructed anew in various
domains during a stage. He referred to horizontal décalages that occur
when a general concept emerges earlier on some tasks than others. For
example, in the case of conservation, the conservation of substance
typically develops a year or two before conservation of weight. He
also probably would not have been surprised by child prodigies whose
cognitive achievements in one particular area, such as math, are much
more advanced than they are in other areas of thinking. Thus, a weaker
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Evaluation of the Theory c 71
structural version of stages may still be viable; some unevenness across
domains would even be expected. However, inconsistency over trials in
applying even a single concept, such as number conservation, poses a
problem even for this weaker version. For instance, Siegler (1995) found
that slightly over half of his 5- year- olds classified as nonconservers had
generated a correct answer and satisfactory explanation on at least one
pretest problem. Thus, variability is as common as consistency, which
contrasts with Piaget’s emphasis on variability mainly during transition
from one period to another. One kind of inconsistency, described later,
is when children demonstrate a concept with simpler task demands
earlier than with more complex ones. Another form of inconsistency is
that “formal operational” adults who can test hypotheses like a scientist
in some situations often are poor at doing so regarding matters about
which they have intuitive, often erroneous, theories (Kuhn, 1989). They
even ignore or distort data that contradict their beliefs. Given these
inconsistencies, is the mind less a coherent cognitive system than a “col-
lection of different and unrelated mindlets” (Flavell, 1992) devoted to
different contents?
Even if one accepts a weaker stage notion, the problem remains
that Piaget did not provide a satisfactory account of what determines
whether a structure will be applied to a particular content area. When
should we expect generalization, and when should we not? The neo-
Piagetians, described later, helped fill this gap.
It is difficult to decide whether the notion of stages is wrong or sim-
ply incomplete. Are the logicomathematical structures a philosopher’s
dream, or, as described at present, are they simply too vague, general, and
distant from behavior? Looft and Svoboda voiced some of these doubts:
While reading Piaget’s most recent writings one sometimes acquires an
eerie, cold feeling that something very strange is going on in this man’s
work. In his early writings we read about delightful children playing on
the banks of Lake Geneva, expressing their surprise and exhilaration as
they make new discoveries about their little worlds. Today we are pre-
sented with some sort of cybernetic automata, regulating themselves and
pushing themselves to ever higher levels of differentiation and complex-
ity. In short, it would seem that as Piaget’s theory has evolved over the
past five decades to higher and higher levels of abstraction, people have
somehow dropped out and have been replaced by sterile logicomathe-
matical structures.
(1971, p. 15)
Later researchers suggested modifications of Piaget’s notion of
stages, while still retaining his emphasis (e.g., Flavell, 1971b, 1982).
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72 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
For example, stagelike, qualitative changes appear to be causally linked
to more gradual, quantitative sorts of developmental changes, such as an
increasing attentional capacity or an increasing stability and generality of
concepts. Also, because the development of cognitive items of a partic-
ular stage is an extended process, these items may not become tightly
organized and interrelated until the very end of that stage. In fact, chil-
dren may not even achieve the “full functional maturity” of a stage until
after that stage has officially ended. Finally, concepts or structures that
characterize a stage often are only roughly synchronous in their devel-
opment. For example, two concepts might begin their development at
the same time but complete it at different times. Or they might begin
and end their development at different times but have a considerable
temporal overlap.
Even though the stages may be less coherent units than Piaget thought,
they still are useful ways to organize a large number of diverse behaviors.
They are convenient points of reference for accounting for the order-
liness of thought. As Flavell and Wohlwill concluded, “To paraphrase
Voltaire’s dictum concerning the deity: if there were no such structures
in the mind of the child, we should have to invent them, to account for
the degree of consistency and orderliness that we do find in his cognitive
development” (1969, p. 94).
As suggested earlier, the most reasonable way to use Piaget’s notion
of stages may be to look for stagelike changes limited to a particular
content area. Each domain may develop somewhat independently of
the others, and thus we would have domain- specific knowledge. This
possibility was explored by the neo- Piagetians and by information-
processing knowledge- based approaches (see Chapter 7). In the latter
view, a child shifts from novice to expert status after experience in a
particular domain such as chess, soccer, or dinosaurs. Domain- specific
knowledge also is posited by core knowledge approaches (Chapter 9),
certain evolutionary approaches (Chapter 5), and the “theory theory” (of
mind, biology, physics) approaches (Chapter 9).
Inadequate Account of Mechanisms of Development c We need
clarification not only of the criteria for stages but also of mechanisms
that drive development both within a stage and from stage to stage. How
do children acquire new concepts and ways of thinking? Although Piaget
considered explanations of change quite important, he more successfully
described than explained development. Functional invariants, such as
assimilation and accommodation, provide at best a general framework
with which to examine cognitive change. There are no specific, precise
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Evaluation of the Theory c 73
statements as to how sensorimotor thought becomes preoperational
thought or how preoperational thought becomes concrete operational
thought. Furthermore, although the equilibration process is an intui-
tively appealing idea, it is not clear how children’s awareness of a contra-
diction would lead them to the solution that resolves the contradiction
(Bryant, 1986). Simply knowing that something is wrong does not iden-
tify the cause of the problem. Moreover, young children do not seem to
be very good at detecting logical inconsistencies that might cause cog-
nitive conflict. Not until age 6 do children see a problem with the claim
that a man is both tall and very short (Ruffman, 1999).
One way to identify mechanisms of change is to supply certain expe-
riences and see whether they cause cognitive change. The logic is that
the experimental conditions that stimulate a new concept might also
operate in this way in children’s daily lives. Hundreds of training stud-
ies looked at conditions such as creating cognitive conflict, teaching
underlying operations such as reversibility or compensation, redirecting
attention to the relevant feature, such as number, or ensuring memory of
relevant information. Even Piagetians, especially Inhelder, studied how
training studies stimulate learning (Inhelder, Sinclair, & Bovet, 1974).
Unfortunately, training studies only minimally illuminated mechanisms
of development. First of all, even if we find that training based on one
of Piaget’s mechanisms of development (for example, cognitive conflict)
causes the child to acquire the concept, there is no guarantee that chil-
dren progress by this mechanism in real life. Second, when a training
study does succeed, that success may be based on mechanisms other than
those the investigators thought they were providing. Gelman’s (1969)
training redirected the child’s attention from irrelevant dimensions (for
example, length of a row of objects) to the relevant dimension (number).
However, this procedure’s success could have stemmed from cognitive
conflict created when the child’s initial answer did not consistently lead
to reinforcement (Beilin, 1971). Third, there is not a specific account of
why a particular training experience stimulates change in some children
but not others. In general, the older children are, the more likely they
are to acquire the concept as a result of training, presumably because
they are closer to acquiring the concept naturally. However, more
refined predictions are more difficult because it is not clear how to assess
children’s degree of readiness.
Training studies, especially in the United States and England, also
were used to try to disprove Piaget’s theory by showing that a concept
of one stage could be taught to children in an earlier stage, for example
teaching conservation to nonconservers. However, Piaget was dubious
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74 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
about the value of trying to intensively teach concepts to children and
cautioned that “each time one prematurely teaches a child something he
could have discovered for himself, that child is kept from inventing it and
consequently from understanding it completely” (1983, p. 113).
Need for a Theory of Performance c Piaget created an elaborate
system of cognitive structures that represent children’s knowledge
about the world. He also provided a rich description of behavior. There
is, however, a missing link: a detailed account of exactly how the struc-
tures are translated into specific problem- solving strategies “on line” in
a particular context. Such a theory of performance would explain how
children’s knowledge is expressed in their behavior at any particular
time, with particular materials, in a particular context. To illustrate, in
a conservation task, a child must be able to understand the task instruc-
tions, attend to number and ignore other attributes such as color and
the salient length dimension, be able to count, and have the working
memory capacity to remember the equivalence of the rows, the type of
transformation, the questions asked (Miller, 1978). Variables that influ-
ence these processes might include, for example, the salience of each
attribute (shape, color) in the materials, familiarity of the materials, the
amount of information to remember, and the complexity of instructions
about the task. These factors may account, in part, for the extended,
gradual, uneven development of concepts. For example, it may be that
the early, fragile form of a concept can be used only if there are not large
demands on the child’s memory, attentional capacity, and verbal ability.
The neo- Piagetians (e.g., Fischer, Case), described later in this chapter,
have examined performance factors.
Piaget recognized the importance of these cognitive activities, and
in his later years, he and his colleagues studied aspects of performance
such as strategies for gathering relevant information (Inhelder & Piaget,
1980; Piaget, 1981/1987). Piaget thought that it was more important
to describe development and to identify general cognitive structures
first. In contrast, certain other theoretical approaches discussed later
in this book, particularly information processing, Gibson’s perceptual
learning, and learning theory, focus on performance. Such theories may
eventually provide the missing link between structures and behavior in
Piaget’s theory.
Slighting of Social and Emotional Aspects of Development c Piaget
thought that social and emotional influences on cognitive development
were very important. Social experience was one of the variables in his
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Evaluation of the Theory c 75
developmental equation, described earlier. Interacting with other people
provides new information to be assimilated. Conversations with parents
may be especially important for learning about things that cannot be
seen, such as religion (e.g., heaven, God’s special powers) and certain
scientific concepts, such as the round shape of the earth or the brain
basis of thinking (Harris & Koenig, 2006). Recent research shows that
children are selective about whose information they trust (Koenig &
Sabbagh, 2013). They are more likely to accept new information from
people who have been correct in the past, have no apparent ulterior
motive, and are similar to themselves.
Another way that social influences are important is that a concept
may be expressed earlier in a social context, as when Piaget’s daughter
Jacqueline showed a more advanced object concept when she played
peek- a- boo skillfully with her mother at 8 1/2 months than when tested
on nonhuman objects (Piaget, 1937/1954). Regarding affect, Piaget
thought that it was very intertwined with intelligence: “Feelings express
the interest and value given to actions of which intelligence provides the
structure” (1945/1951, pp. 205–206). In a sense, emotions provide
the energy behind cognition. For example, feelings influence children’s
choice of what to apply their structures to; a child with a passion for
airplanes is likely to learn a great deal about them.
For Piaget, the social realm was important not only as an influence on
cognition but also as the content of cognition, for example, the concepts
of morality and of national identity described earlier. More generally, he
thought that cognitive structures are applied to social, as well as nonso-
cial, content.
Despite the importance that Piaget assigned to the social and emo-
tional realms, he paid relatively little attention to them, or to sociohis-
torical influences, in his work. It has been said that Piaget’s epistemic
subject has no social class, sex, nationality, culture, or personality— and
also has no fun (Murray, 1983, p. 231).
Fortunately, other researchers have filled in the gaps or corrected
Piaget’s account of social cognition. Kohlberg (1969) adopted Piaget’s
stage approach to moral judgments and expanded and modified the
model considerably. Social cognitive researchers have addressed chil-
dren’s concepts of self, other people, minds, and social interaction (e.g.,
Banaji & Gelman, 2013). Some work has examined peer interactions,
thought by Piaget to be important for creating cognitive conflict that
could cause cognitive progress. For example, interactions between non-
conservers and conservers prior to deciding on a mutually agreed- upon
answer tend to be tilted toward the conserver. These interactions often
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76 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
are very brief— in one study (Russell, 1982) an average of 40 seconds,
consisting of little more than the conserver saying, “Same size, OK? . . .
Ready!” Finally, the cultural and person- in- context approaches discussed
later in this volume greatly expand our knowledge of sociocultural influ-
ences on cognitive development.
Underestimation of Abilities c Piaget likely underestimated chil-
dren’s cognitive abilities at each age. The “miracle baby” (Gopnik, 1994,
p. 133) experiments suggest that babies know a lot more than Piaget
thought. For example, Piaget’s requiring infants to search for a hidden
object before being credited with the concept of object permanence
may have underestimated their competence. Baillargeon (1987) found
that 4- month- old infants, who should be too young to understand object
permanence, looked a long time (i.e., were surprised) when a screen
falling away from them seemed to pass through a box (now out of view)
they had seen there earlier. Other examples appear later in this chapter
in the “Contemporary Research” section. This “baby assault on Piaget”
(Rochat, 2012, p. 71) questioned Piaget’s belief that infants have to con-
struct the foundations of a coherent world over the first two years of life.
Similarly, with preschoolers, work on children’s “theory of mind”
(see Chapter 9) suggests that by age 4 or 5 children know more about
another person’s perspective than Piaget thought. They know, for
example, that another child would think that a crayon box holds crayons
rather than candles, even though they themselves know it holds can-
dles. Also, with young children, the verbal nature of much of Piaget’s
testing raises the possibility of underestimating children’s knowledge if
they do not understand the language used during testing, for example,
the meaning of “same number” and “amount.” Or children may not be
able to express in words their ideas about quantity, the origin of the
universe, the nature of dreams, and so forth. For instance, children may
have the concept of conservation but not be able to give an adequate
reason for their answer— one of Piaget’s criteria for conservation. Or
the standard Piagetian procedures may actually be tapping into children’s
understanding of conversation. An adult asking children about quantity
twice (before and after the transformation) may cause children to think
that they should change their answer (Siegal, 1991). Children may think
that when an authority figure asks a question a second time, this usu-
ally means that the first answer was not satisfactory. In all these ways,
Piagetian procedures may underestimate children’s knowledge.
This concern about tasks’ verbal requirements led to a number of inter-
esting attempts to devise nonverbal, or at least less verbal, procedures.
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Evaluation of the Theory c 77
Psychologists cleverly devised ways of using expressions of surprise
(Gelman, 1972), heart rate changes (Bower, 1974), and choice of
(more) candy to take home (S. A. Miller, 1976) to assess for certain
concepts. For example, if an experimenter surreptitiously removes a
toy mouse, 3- year- olds are surprised by this changed number of mice
(Gelman, 1972), indicating some understanding of number. Some of the
studies employing nonverbal assessments found better performance than
did Piaget, but others did not.
Underestimation also can come from complex procedures. One way
to simplify the task is to use simpler materials. For example, young chil-
dren show greater knowledge about counting when there are only a few
objects than when there are many (Gelman & Gallistel, 1978).
What should we conclude from these many demonstrations that
Piagetian concepts appear to emerge earlier than Piaget thought if
motor, verbal, and information- processing demands are reduced or
eliminated? One possible conclusion is that Piaget did in fact underesti-
mate children’s competencies. Some psychologists see this as damaging
evidence against Piaget’s theory. For example, unearthing the early com-
petencies in infancy has led some developmentalists to argue for innate
predispositions that permit the early, rapid acquisition of core knowl-
edge about language, mental states, and objects and their behaviors (e.g.,
Spelke, Bernier, & Skerry, 2013). However, recall that Piaget’s main
claims concerned the sequence in which concepts are acquired rather
than the particular ages, which he thought would vary. Thus, showing
that an ability emerged earlier than Piaget claimed is not necessarily
damaging to his theory.
A more intriguing conclusion about these earlier competencies is that
they may be less advanced versions of, and precursors of, the later, more
advanced concepts described by Piaget. For example, young infants’
apparent understanding of object permanence actually may reflect a
competency that is more perceptual than conceptual (e.g., Bremner,
Slater, & Johnson, 2014). And preschoolers’ successful performance
on modifications of concrete operational tasks actually may reflect only
preoperational concepts, such as the function, described earlier, rather
than concrete operational concepts (Lourenco & Machado, 1996). That
is, the simplified task provides so much perceptual support that the con-
ditions theoretically necessary for concrete operational reasoning are
not present.
The differences in the methodology of Genevan Piagetians com-
pared to researchers in other countries reflect different goals of assess-
ment. Piaget especially wanted to avoid “false positive errors,” namely,
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78 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
concluding that children have the concept when in fact they do not.
Thus, he sometimes even considered it desirable to have complex mate-
rials, a misleading visual array, and heavy verbal demands so that only
children who see the concept as logically necessary will prevail. In con-
trast, the other camp is more concerned about “false negative errors,”
concluding that children do not have the concept when in fact they do.
In any case, research on early competencies has been quite fruitful,
for it has revealed positive acquisitions during the infancy and preschool
years that complement Piaget’s emphasis on the deficiencies of young
children. For example, it turns out that preschoolers know a great
deal about number (e.g., Nunes & Bryant, 2015). Gelman and Gallistel
(1978) found a sequence of simple principles of counting, such as the
principle that numerals must always be used in the same order. That is,
children who say “1, 2, 6, 9” follow this counting principle correctly
if they always use these numerals in this order for counting. These
early principles supplement Piaget’s account of the full- blown concept
of number acquired several years later. Techniques that simplify the
Piagetian tests are more sensitive to earlier forms of concepts than are
Piaget’s procedures.
It is interesting, however, that in addition to finding Piagetian under-
estimations, researchers also have found overestimations. For example,
as discussed earlier, adolescents and even adults often fail to use formal
operational reasoning. In fact, Piaget (1972) later concluded that the
stage continued until age 20 or so.
Methodological and Stylistic Barriers c Piaget’s critics attack his
methodology not only with respect to issues of underestimation and
overestimation but also because much of it does not meet the conven-
tions of developmental science. In his infancy research, Piaget observed
his own three children. Unfortunately, he did not have 40 or 50 children
of his own to give us a more respectable sample size. The small number
of research participants, the possible biases in interpreting the behav-
ior of one’s own children, the absence of measures of reliability from
two independent observers, and the lack of control over the children’s
immediate environment, possible only in a laboratory, did not endear
Piaget to American experimental psychologists. However, subsequent
studies by others, with more participants and better- controlled testing
situations, generally have replicated the sequences of development,
though not always the exact ages at which the changes occur.
In his work with older children, Piaget often tested large samples
of children (for example, 2,159 for Early Growth of Logic in the Child
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Evaluation of the Theory c 79
(1964b)!). He usually employed the clinical method. Although this
method has certain advantages, such as flexibility in tailoring questions
to the particular answers given by each child, it also has a number of
disadvantages. Two main disadvantages are the danger that examiners
may be too leading in their questions or not leading enough and that
different children often are asked slightly different questions. Uniform
instructions, materials, and measures of response are the backbone of
testing in experimental psychology. We are asked to make the leap of
faith that Piaget was in fact a sensitive and accurate observer. Piaget
himself seemed aware of these problems:
It is so hard not to talk too much when questioning a child, especially for
a pedagogue! It is so hard not to be suggestive! And above all, it is so hard
to find the middle course between systematization due to preconceived
ideas and incoherence due to the absence of any directing hypothesis!
(1926/1929, p. 9)
Piaget’s reporting of his experiments also is frustrating to contempo-
rary psychologists. He typically did not report the number of children,
their race or socioeconomic level, and details of the testing procedure.
Sometimes it is even difficult to tell whether Piaget was referring to
hypothetical children or children he had actually tested. He was not
impressed with tightly controlled laboratory experiments and statis-
tical analysis. In his words, “acute observation, especially when made
by [a good observer] . . . , surpasses all statistics” (1936/1952b, p. 72).
Instead of presenting statistical summaries of the findings, Piaget provides
sample protocols, which he interpreted at great length. The reader has
no idea whether these protocols are representative of all children tested.
What are we to make of these characteristics of Piaget’s methodology
and writing? Flavell (1963) concluded that Piaget mainly wanted to sat-
isfy his own curiosity, not the requirements of the scientific community.
Thus, he played by his own rules when doing research and wrote almost
as though he were talking to himself. After all, epistemology, not devel-
opmental psychology, was his passion.
Although Piaget’s methodology and reporting are annoying to anyone
trying to understand and evaluate his theory, they may be somewhat
responsible for Piaget’s success. His qualitative methods captured the
richness of children’s thinking, which sometimes is lost when quantita-
tive methods are used. If Piaget had used standardized procedures from
the beginning, solidly confirming each finding, he might have missed
some fascinating facets of cognitive development and not have pro-
gressed as far as he did.
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80 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
Piaget’s Own Modifications of His Theory
Piaget considered himself one of the primary revisionists of “Piaget’s
theory.” Translations of his later works led to some modifications of the
“classic Piaget” (see Müller, Carpendale, & Smith, 2010). Although some
of this more recent work was presented throughout this chapter, several
theoretical changes should be highlighted, particularly regarding devel-
opmental change, equilibration, and the logicomathematical model.
In his later years, Piaget (1975/1985) put much less emphasis on
stages. In fact, Vuyk concluded that Piaget “now considers development
a spiral and though one may call a stage ‘a detour of the spiral,’ this
indicates that periods of equilibrium are relatively unimportant” (1981,
p. 192). Piaget began to view development as less steplike, with longer
transition periods between stages. He also increased his attention to
mechanisms of cognitive change, especially the equilibration process.
He further worked out the equilibration processes. In particular, he
emphasized mental actions that compensate for the ways the envi-
ronment does not fit into current cognitive structures and reflective
abstraction. In reflective abstraction, children construct new knowledge by
taking their knowledge to a higher level and reorganizing it at that level.
Piaget gave the example that young children can know how to get from
home to school in a practical way, using cues to guide them from one
point to another. In reflective abstraction, this knowledge is projected
onto a representational level— an overall cognitive map of the spatial
relations between home and school (Montangero & Maurice- Naville,
1997, p. 58).
Piaget also worked out a new way of describing developmental
change, both within a stage and over all the stages: intra-, inter-, and trans-
changes. Knowledge about properties of objects (intra) leads to knowl-
edge about relations between object properties or actions (inter) and
then to a structure that organizes these relations (trans). For example,
a child moves from “A car can be ridden in,” to “Cars and buses can be
ridden in” and thus go together, to “Cars and buses and other vehicles are
modes of transportation within a hierarchical logical system.”
Piaget expanded on the role of “possibilities” (the way things might
be) and “procedures” (strategies) in the process of development. This
contrasts with his earlier emphasis on logical necessity. A new cogni-
tive structure generates new possibilities, which takes children beyond
current reality and permits them to try out new procedures on objects.
As an example of the increasing awareness of possibilities during
development, Piaget (1954/1981) showed children a box with only one
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Piaget’s Own Modifications of His Theory c 81
side visible under a cloth. At age 5 or 6, children would accept only a
single possibility for the color of the hidden side of the box— the same
color as the visible side. Thus, a sense of necessity occurs in young chil-
dren because they can imagine only a single possibility. By age 7 to 10,
children recognized multiple, though limited, possibilities: the hidden
side might be “green, violet, blue, white, yellow . . . that’s all” (Piaget,
1954/1981, p. 44). At age 11 to 12, children realize that the number
of possibilities is essentially unlimited. This development is interesting
because the concept of unlimited possibilities cannot be observed in the
environment. It must be constructed internally.
Piaget further explored the contradiction aspect of equilibration
(1974/1980). He presented a row of seven disks, each of which was
slightly, but imperceptibly, larger than the one before it. Because the last
and largest disk was unattached, it could be moved to, and compared
with, each of the six disks attached to the board. Thus, the contradiction
facing the child was that any two adjacent disks appeared to be equal in
size but the disk at the end of the series was obviously larger than the
first disk. Three stages of understanding contradiction emerged. In the
first stage, young children were unaware of the contradiction. Next,
children had some awareness of the contradiction, but their attempted
solutions were not satisfactory. For example, a child might categorize
the disks as small ones and large ones, thereby accounting for some of
the perceived equivalences between adjacent disks (both are “small”)
and also explaining the difference in size of the first (“small”) and last
(“large”) disk. Finally, by age 11 or 12, children resolved the contra-
diction and re- established equilibrium by creating a new structure—
quantified seriation of size.
Piaget’s most radical changes were in his logicomathematical model
of thinking, though his death prevented him from completing the proj-
ect (Beilin & Fireman, 2000, p. 239). He considered that logic could
come from the meanings of objects, developed from infants’ actions.
Specifically, infants learn that one action on an object is related to other
actions; the meaning of actions comes from “what they lead to.” That
is, one action implies another action, in a sort of “logic of meaning in
actions,” a “ psycho- logic” on objects. For example, infants who push
an object away from themselves may infer that the object also can be
pulled back. Another example is that “if I release the car down the
ramp it will crash into the house at the bottom.” This action- based logic
later leads to a logic of operations, such as when the pushing– pulling
relation leads to the reversal of a mental action. Remarkably, Piaget
perceived in infants’ coordinations of their actions (a logic of meaning)
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82 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
a sensorimotor counterpart to the 16 binary combinations of formal
operations thought.
In category theory, Piaget’s previous emphasis on action in the form
of mental transformations was supplemented with “correspondences”
between two static states (Piaget, 1979). Comparisons of static states
are central, as when a preoperational child sees the similarity between
a currently perceived object and a previously encountered one, and
thereby assimilates the current one. The current object or event is recog-
nized, categorized, or characterized; it therefore “corresponds” (is seen
as similar) to other objects or events. Or a child may perceive that each
of five dolls of increasing size maps onto five dresses of increasing size
(Davidson, 1988). Detecting correspondences can lead a child to notice
a transformation. For example, when a picture corresponds to the same
picture hung upside down, a mental rotation links the two states and
underlies their correspondence.
Piaget’s final contributions have had little influence on developmental
psychology. The reasons may be (a) doubts about the whole enterprise of
logical models and stage theories and (b) the emergence of other attrac-
tive theories of cognitive development, discussed in later chapters, that
have offered new perspectives and tasks.
The Neo- Piagetians
Many of the problems and limitations raised about Piaget’s theory have
been addressed by a group of developmental psychologists labeled “ neo-
Piagetian.” They are Piagetian in their belief in structural change and in
children’s active construction of some sort of stages. In particular, they
believe that lower- level concepts are integrated to form more complex
higher- level concepts. However, they are “neo” in their inclusion of
information- processing constructs (see Chapter 7) such as skills, limited
memory capacity, and domain- specific concepts. Domain- specific con-
cepts or cognitive structures are those that pertain only to a particular
area or areas, such as role taking or number. Thus, a careful analysis of
particular tasks is necessary. In contrast, Piaget emphasized the domain-
general application of cognitive structures. Neo- Piagetians also are “neo”
in that they draw on the social- contextual idea (see Chapter 4) of social
supports for emerging cognitive skills and on dynamic systems theory
(see Chapter 9). We examine the theories of Robbie Case (e.g., Case,
1998; Morra, Gobbo, Marini, & Sheese, 2008) and Kurt Fischer (e.g.,
Mascolo & Fischer, 2015), two main neo- Piagetians (see Morra et al.,
2008, for other neo- Piagetian theories).
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The Neo- Piagetians c 83
Robbie Case
Case, like Piaget, addressed cognitive changes from one level to the next.
Case, however, attributed much of such change to increased working mem-
ory capacity or, in his words, executive processing space: “the maximum num-
ber of independent schemes a child can activate at any one time” (1985,
p. 289). This processing space determines how many things a child can think
about at the same time and use for further processing. For Case, children’s
thinking develops due to their increased efficiency of using their working
memory capacity, rather than to Piaget’s equilibration process. Capacity
can increase in two ways. First, practice with a skill, such as counting,
makes it less effortful and more efficient, thus freeing previously needed
capacity. A given amount of capacity goes much further if many elements
can be processed, rather than a few. This increase in available capacity can
be used for additional cognitive activities, for example, both counting and
remembering. The faster children can count objects, the better they are at
remembering the number of objects in sets in a counting span test (Case,
1985). Second, brain maturation increases the amount of information
children can handle. Increased myelination (insulation of neurons) and per-
haps increased neural connections between the frontal and posterior lobes
increase the efficiency and integration of cognitive functioning. Spurts in
neurological maturation are correlated with cognitive spurts (Case, 1985).
Case differed from Piaget in his view of how children’s mental struc-
tures should be modeled. Case remarked that “it seemed that Piaget’s
theory was better equipped for representing the structure in the mind
of logicians than the structure in the minds of young children” (1992,
p. 6). Rather than draw on symbolic logic, Case used constructs from
the information- processing framework, particularly (a) children’s rich
networks of concepts and their relations and (b) executive control struc-
tures, which help children deal with specific problem- solving situations.
He viewed children as problem solvers, with these control structures as
their tools. Using these control structures, children can set goals, acti-
vate procedures (sequences of schemes) in novel ways for reaching these
goals, and evaluate the results of these procedures. Children also can
restructure successful procedures so that they later can produce them
intentionally, and practice and integrate successful procedures until they
are consolidated. For example, with respect to counting, children set a
goal (determining the number of objects), generate counting procedures
for attaining it, evaluate their success, “mark” the successful sequence,
and integrate the successful counting procedures.
When children experiment during attempts to solve problems, they
explore objects, observe and imitate other people, and interact with
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84 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
others as together they solve a problem. For example, children might learn
about counting by using their own verbal labels as they touch each object
during problem solving, counting different types of objects during explor-
ing, observing others count, and trying to count a large set with the help
of an adult. If children have the necessary processing capacity, they can
take advantage of these experiences to construct more advanced executive
control structures (for example, procedures for determining quantity).
Case addressed the debate about general versus domain- specific cog-
nitive structures by proposing a small set of central conceptual structures
at an intermediate level of generality. They are less general than Piaget’s
stage structures but more general than a single task. Each central con-
ceptual structure is a representational system of a domain of knowledge
such as number, space, or social interaction that should permit a child
to apply that knowledge to all tasks in that domain. Thus, children look
stagelike, showing similar thinking, across tasks calling for the same
central conceptual structure. In contrast, children do not look stagelike,
showing different types or levels of thinking, across tasks requiring dif-
ferent central conceptual structures.
Central conceptual structures interpret specific tasks in the domain
and assemble problem- solving procedures for these tasks (the executive
control structures mentioned earlier), a process that can cause cognitive
change at this specific level. These specific level changes, along with
increased capacity, in turn stimulate changes in the central conceptual
structure for that domain. In this way, they bootstrap each other during
development.
Case thought that, on a given task, children develop in a qualitative
stagelike way, as they learn to use one dimension or component, then
two, and then integrate them. For example, when told to tell a story
about a little child and an old horse, young children relate a social situa-
tion with no mention of motives, whereas slightly older children create a
story around the intentions of the central character. Later, children create
a chain of two or more event sequences in which the first sequence does
not lead to goal satisfaction, while the second sequence does. Finally, at
the integrated level, children coordinate multiple attempts at satisfaction
into an overall, complex, organized plot. As another example, the repre-
sentations of spatial relations in Chinese children’s drawings show a sim-
ilar sequence (see Figure 2.2): (a) no real concern with spatial relations,
(b) placement of objects into a single spatial dimension, (c) depiction of
both foreground and background, and (c) creation of a coherent, unified
picture.
Case’s theory is an interesting attempt to integrate a structural model
and a processing model of development. He showed how limits in
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The Neo- Piagetians c 85
processing capacity and social experience limit logical reasoning and con-
strain what the child can learn at any developmental level. By the same
token, an increase in capacity creates a new opportunity for the further
development of logical thinking. He examined a variety of skills, such as
spatial representation, social cognition, eating with utensils in infancy,
using vocalizations for social purposes, manipulating other people’s
feelings, storytelling, understanding emotions, and judging intelligence
in others.
Kurt Fischer
Fischer agrees with Case in many ways. Fischer’s particular contribution
is that he addresses one of the main challenges to Piaget’s stage theory—
the observed variability in children’s behavior, when Piaget would
F I G U R E 2 . 2
Typical pictures drawn by children aged 4(a), 6(b), 8(c), and 10(d) in Nanjing, China, when
told to “draw a picture of a mother and a father holding hands in a park. A baby is in front of
them and a tree is very far away behind them.”
[Reproduced with permission from “The role of central conceptual structures in the development of children’s
thought,” by Robbie Case and Yukari Okamoto, in Monographs of the Society for Research in Child
Development, 1996, 61(1–2), Serial No. 246, p. 139. © 1996 by the Society for Research in Child Development
with permission from Wiley Publishers.]
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86 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
predict stagelike consistency. In Fischer’s view, “Variations in develop-
mental level are routine and pervasive and they need to be explained,
not ignored” (Fischer & Hencke, 1996, p. 209). Fischer’s dynamic
structuralism posits that children’s thinking can be variable, but also struc-
tured and predictable. Thus, Fischer, like Case, keeps Piaget’s notion of
cognitive structures but argues that they are not static; whether children
express them or not depends on the support in a particular social setting.
Children gradually construct their thinking and learning skills as they
use them in activities in various contexts. A skill, defined as “the capacity
to act in an organized way in a specific context” (Fischer & Bidell, 2006),
includes abilities such as storytelling, counting, forming relationships
with others, and reading. A child may show variability in the use of a skill
across contexts, as when a child may be able to add numbers at school
when watching a teacher’s actions but not when doing homework alone
at home. Fischer called a child’s variability in performance a developmen-
tal range. At one end of the range, with contextual supports such as social
prompts or physical cues, children operate at their maximal, optimal level.
At the other end, in a setting devoid of meaning, value, or support, or
under conditions of fatigue, emotional stress, or distraction, children are
unlikely to express their skill. Children can even operate beyond their
optimal level with adult social scaffolding, in which an adult more fully
participates in the child’s activity by providing instruction or carrying
out part of the action (see also Vygotsky’s “zone of proximal develop-
ment,” Chapter 4). In short, children’s level of thinking has to do with
the fit between children and their environment, not the children alone.
A child also may show variability across skills, such that the child’s
thinking seems to be at different cognitive levels in different domains.
Children are most likely to be advanced in a skill, such as counting, if
they are raised in an environment with support for developing and using
this skill, such as when parents play counting games with their children.
Such children may be less advanced with respect to other skills, such
as reading, generally considered to be in the same stage, if they have
had little support or training for those skills. Thus, children are not “in”
one stage or another. Rather, they will show various levels of cognitive
functioning across various domains, depending on the opportunities for
developing a particular skill in their social environments. On the other
hand, thinking can appear stagelike and domain general if there is sup-
port in many domains.
Fischer uses the term dynamic skills because children are constantly
having to adjust their skills to changing conditions and people and even
to reorganize their skills. They use “not only their brains but also their
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The Neo- Piagetians c 87
bodies, the objects and people around them, and the roles, norms,
and values of their culture” (Fischer & Bidell, 1998, p. 545). Through
studying children’s actions in context, Fischer tries to map the “dynamic
structures” of human behavior. He draws on dynamic- systems theory
(see Chapter 9) to capture the orderly patterns of development within
children’s variable behavior.
Still another aspect of variability in Fischer’s model is that a child may
follow several different developmental routes for different skills, and
different children may follow different pathways to one particular skill.
He contrasts his view with traditional metaphors of development, such
as a ladder, in which all children begin at one point and move from one
formal structure to the next to a final point. He offers an alternative
metaphor— a “developmental web”: “Unlike the steps in a ladder, the
strands in a web are not fixed in a determined order but are the joint
product of the web builder’s constructive activity and the supportive con-
text in which it is built (like branches, leaves, or the corner of a wall,
for a spider web)” (Fischer & Bidell, 2006, p. 319). Thus, like a spider
who must shift the direction and form of a web when a nonsupportive
leaf breaks off, young children who develop their storytelling skills in a
particular direction but find that their parents ignore this emergent skill
may turn to their peers for listeners. Because adults and peers provide
different sorts of feedback and support for this emerging skill, the chil-
dren develop this skill along a different developmental pathway, perhaps
toward more violent action and less coherence in the stories. In other
words, different children encounter different settings that impact skills
differently. Another example is that abused children are not simply
socially unskilled but have developed alternative cognitive and social
pathways to cope with their abuse. Thus Fischer provides a way to think
about individual differences not only in how advanced children are
along a normative pathway but also in terms of how children’s pathways
can differ.
Like Piaget and Case, Fischer believes that children develop through
a sequence of tiers. Fischer proposes four tiers of increasing complexity
from birth through early adulthood— reflexes, sensorimotor actions,
representations, and abstractions (Mascolo & Fischer, 2015). Moving
from one tier to the next involves cognitive reorganization, much as in
Piaget’s theory, and spurts in performance. Within each of the four tiers,
children go through the same sequence of four levels: single sets, then
mappings (coordination) between sets, then a system of mappings, then
a system of systems. This system of systems then becomes the first level
(single set) of the next tier. For example, in the sensorimotor actions
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88 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
tier, a single action, such as an infant reaching, is followed by a two-
action connection in which an infant reaches for a ball in order to look at
it. Next come connections between two- action systems, such as moving
a rattle in various ways in order to look at different parts of it. Finally,
a system of action systems (level 4) becomes level 1 (a single representa-
tion) of the next tier— the tier of representations. This new tier permits
a coordination of two or more action systems from the sensorimotor
tier, as when a toddler pretends that a doll is walking. This cycle of levels
is then repeated: single representations, then two connected represen-
tations, systems of representations, then, systems of representational
systems (level 4 of the representational tier).
As another example, single representations of doctor and patient
become mapped into each other in the doctor– patient roles; during play,
the doctor doll gives medicine to the patient doll after she complains of
a stomachache. Later, children coordinate two mappings and perhaps
show a person in two roles simultaneously (e.g., doctor and father).
Finally, the various roles of two or more people are integrated into a
system of representations, which also is a single abstraction for the next
tier, and so on.
A child might appear to advance in a stagelike way when simultane-
ous changes in several domains, such as spatial understanding, object
permanence, and pretend play, merge to cause a developmental spurt.
A period of rapid brain maturation also could cause rapid changes across
many domains. At other times, development across domains occurs at
different times, and thus thinking does not seem stagelike.
Note that these tiers become increasingly abstract and bear a marked
similarity to Piaget’s stages. Fischer’s contribution regarding stages is to
show the same sequence of substages across all four tiers, and in diverse
content areas such as gender- role development, reading, emotional
development, adolescents’ relationships, and planning.
Neo- Piagetian Themes
In summary, neo- Piagetians enrich and specify Piaget’s theory, rather
than contradict it. Their main contributions are to draw on information-
processing and dynamic systems theories to (1) propose a promising set
of processes, such as social support and increases in working memory,
that account for developmental change and intrachild and interchild
variability, and (2) clarify and refine the notion of stages, for example,
by attempting to differentiate domain- general and domain- specific
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Contemporary Research c 89
achievements. As Flavell observed, “Cognitive development might
appear to be more general- stagelike than many of us believed, if only we
knew how and where to look” (1982, p. 1).
Contemporary Research
In a broad sense, much of the current research on cognitive development
is Piagetian. Although many psychologists claim that the influence of
Piagetian theory has waned greatly, this decline may be more apparent
than real. Even though there are few explicitly Piagetian studies, partic-
ularly with Piagetian tasks such as conservation and class inclusion, many
Piagetian concepts, from object permanence to scientific reasoning, are
still studied. Moreover, so many of Piaget’s assumptions about the nature
of cognitive development are assimilated into the thinking of researchers
that Piaget’s ongoing influence often is not recognized. As Flavell notes,
“I think we are in more danger of underappreciating Piaget than of over-
appreciating him, for much the same reason that fish are said to underap-
preciate the virtues of water” (1996, p. 202). Examples of this pervasive
but invisible Piagentian presence are the following: It is taken for granted
that children actively construct knowledge rather than simply absorb
information; to a great extent children teach themselves. Researchers
routinely search for an organized conceptual minisystem underlying
several different behaviors in a particular domain, for example, the orga-
nized theorylike understanding underlying children’s grasp of the nature
of mind— theory of mind (see Chapter 9). They also regularly look at
the sequence in which concepts in a particular domain are acquired, for
example, studies of the order in which children acquire various theory-
of- mind concepts in various cultures (Shahaeian, Peterson, Slaughter, &
Wellman, 2011). Researchers look for the processes by which a new
concept arises from a previous one, and try to identify when a child is
ready to learn. Developmentalists also continue to be informed by the
“wrong” or “cute” notions that preschool children have about the world
that are a symptom of a complex, probing intellectual system trying to
make sense of the world. Finally, researchers continue to try to teach
new concepts before they are acquired naturally, in part to test the limits
of, or constraints on, the ability to learn.
These Piagetian influences particularly play out in three topics today:
infants’ advanced competencies, children’s domain- specific concepts,
and mechanisms of development. These topics address three current
areas of contention: How early are various concepts acquired? To what
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90 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
extent is knowledge organized by domains versus applied to multiple
domains? How can we account for new knowledge? These lines of
research began in earlier challenges to Piaget’s theory (especially the
stage notion), described previously in this chapter, thus setting in motion
major themes in developmental research today.
Infants’ Advanced Competencies
New methods not available to Piaget, particularly measuring infants’
longer looking time at events that violate their expectations, continue
to detect seemingly remarkable knowledge in infants that Piaget thought
developed much later. Young infants appear to imitate others, detect
their intentions, understand physical qualities of objects such as perma-
nence and containment, and categorize objects (including people). One
striking example is that infants seem to understand adults’ intentions,
even if they do not see adults achieve their goal, as when 7- month-
olds reach for an object that they saw an adult reach for unsuccessfully
(Hamlin, Hallinan, & Woodward, 2008). In contrast, they do not imitate
an action with an ambiguous goal, even if the adult successfully attained
the goal. That is, they can analyze the goals of even uncompleted actions
and imitate only those behaviors that are goal directed, regardless of
whether they are successful. Another example is that 6- month- old
infants’ looking shows that they can discriminate between small sets of
numbers, such as 1 versus 2, 2 versus 4, and 4 versus 8, indicating some
sense of number (Starr, Libertus, & Brannon, 2013). Infants also appear
to form concepts of categories such as shapes and animals (Sloutsky,
2015). For example, infants are familiarized with exemplars from a cat-
egory, such as dogs, and then presented with a new category member
and a noncategory object. Given infants’ preference for novelty, their
looking at the noncategory object is taken as evidence that infants have
constructed a category of dogs. Finally, infants seem to have some moral
sense— a tendency to see certain actions and people as good or bad.
They can infer intentions from the behaviors of puppets or animated
shapes that help or hinder someone’s behaviors toward a goal (Hamlin,
2013). For example, infants watched a puppet unsuccessfully attempt to
climb a hill, and either a “helper” aided the climber by bumping him up
or a “hinderer” bumped the climber back down the hill. Even 5- month-
olds seemingly detected the positive motive of the “helper” and pre-
ferred (i.e., they reached for) the helper rather than the hinderer. Infants
also seem to approve of retribution against those with these antisocial
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Contemporary Research c 91
mental states. For instance, when they had to take a treat away from
someone, they took it from the bad individual (Hamlin, Wynn, Bloom, &
Mahajan, 2011).
The debate continues over whether these seemingly precocious
concepts are simply earlier, more perceptual, versions of concepts that
Piaget thought emerged later (e.g., Bremner et al., 2014) or are the
same concepts, but detected earlier due to more sensitive assessments.
Early detection of a perceptual discrepancy may lead to a later concep-
tual understanding.
Domain- Specific Concepts
Having turned away from grand stage approaches, researchers continue
to study the development of an organized understanding specific to a
particular domain, in domains examined by Piaget, particularly number,
moral reasoning, space, biology, physics, and people. They also research
other topics mapped out by Piaget, such as scientific reasoning, symbols,
social understanding, and reasoning (e.g., Liben & Müller, 2015). Much
of this contemporary work falls within the theory theory approach (see
Chapter 9), which examines children’s organized “foundational” con-
cepts about physics, psychology, and biology that are important to learn
quickly early in life, in order to adapt and thrive. Knowing that objects
fall down rather than up, distinguishing between animate and inanimate
objects, and understanding others’ intentions and beliefs are examples.
These organized, coherent systems of knowledge about a domain obvi-
ously retain important elements from Piaget’s theory.
Mechanisms of Development
Cognitive developmentalists today continue Piaget’s quest for the mech-
anisms that move cognitive development along. Of particular interest are
increases in working memory, speed of processing, a growing knowledge
base in particular domains, inhibitory control of thinking, and brain
maturation (Keating, 2012). Although Piaget considered maturation
an important contributor in his formula for development described
earlier, only recently has it been possible to examine brain maturation
(see Chapter 5). Developmental cognitive neuroscience, particularly
neuroimaging methods such as fMRI, is documenting the role of brain
functioning in children’s cognitive development (see Johnson & de
Haan, 2015, for an overview). For example, maturation of the cerebral
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92 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
cortex correlates with cognitive milestones during development (Sowell
et al., 2004).
One powerful mechanism of cognitive development due to the matu-
ration of the frontal cortex is the inhibition of dominant but less mature
responses. On Piaget’s A- not- B task described earlier, infants’ tendency
to look under the first hiding place rather than the final one may indi-
cate not a lack of understanding of object permanence, but rather their
inability to inhibit their highly practiced tendency to search the first hid-
ing place (Diamond, 1985). Moreover, studies of brain activity related
to inhibition show that children have to be able to inhibit their length-
equals- number strategy before they can give a conservation answer
on a conservation- of- number task (Linzarini, Houdé, & Borst, 2015).
Interestingly, adults also show a pattern of brain activity suggesting that
they have to inhibit a childlike nonconserver tendency that competes
with their logic- based concept of conservation. Thus, mechanisms of
development operate not only by leading children to new concepts but
also by helping them leave behind old ways of thinking.
Piaget’s constructivist approach to explaining development is cap-
tured in the neuroconstructivism approach ( Karmiloff- Smith, 2012). The
process of development is key to understanding adult brains. The brain
is constantly changing and reorganizing due to two- way interactions
among genes, brain, cognition, behavior, and environment during devel-
opment. Small initial differences in the focus of various brain regions,
when combined with experience during development, result in special-
ized regions. Moreover, neurodevelopmental disorders are due to small
initial differences between typically and atypically developing children in
brain functioning or environments that, over the course of development,
cascade into much larger differences in brain functioning, cognition, and
behavior.
Other research on the process of change from one cognitive level to
another has tried to identify conditions in which children are most likely
to advance cognitively from new experiences or direct instruction. An
example is children who give the wrong answer on a conservation task
but show their correct implicit understanding in their hand gestures
(Church & Goldin- Meadow, 1986). Some widen the space between
their hands, indicating their awareness of the increased width of the con-
tainer of liquid even though their answer is based on how high the liquid
rises. These children progressed more after conservation training than
did nonconservers whose hands agreed with their words by indicating
liquid height. Such work on discordant representations provides a new
perspective on cognitive readiness to learn from experience and thus
advance cognitively.
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Summary c 93
SUMMARY
Piaget’s theory posits universal, invariant stages in how children acquire
knowledge about the world (genetic epistemology). In the first two years
of life, children construct sensorimotor schemes based on physical action
upon the world. The schemes become more intentional and integrated
during that time. During the preoperational period, approximately age
2 to 7, children exploit their newly acquired symbolic ability. Despite
the limitations of egocentrism, rigid thought, and limited role- taking
and communication abilities, children combine symbols into semilog-
ical reasoning. During the concrete operational period, roughly age 7
to 11, children acquire logicomathematical structures. Now thought is
operational and consequently more flexible and abstract. Actions are still
the main source of knowledge, but the actions now are mental. Finally,
during the formal operational period, age 11 to 15, these operations are
no longer limited to concrete objects. Operations can be performed on
operations, verbal propositions, and hypothetical conditions.
These stagelike changes involve changes in the structure of thought.
Thought becomes increasingly organized, always building on the struc-
ture of the previous stage. Evidence for these structural changes comes
from observations of infants and from interviews or problem- solving
tasks with older children.
Movement through the stages is caused by four factors: physical
maturation, experience with physical objects, social experience, and
equilibration. Experience brings cognitive progress through assimilation
and accommodation. These functional invariants help children adapt to
the environment by strengthening and stretching their current under-
standing of the world.
Piaget viewed children as active and self- regulating organisms who
change by means of interacting innate and environmental factors. He
emphasized qualitative change but identified certain quantitative changes
as well. The essence of cognitive development is structural change. Piaget
drew on the equilibration model and the logicomathematical model to
describe these changes. His theory has contributed many educational
concepts, for example, “readiness to learn” and the “active learner.”
The theory’s main strengths are its recognition of the central role
of cognition in development, discovery of surprising features of young
children’s thinking, wide scope, and ecological validity. The main
weaknesses include its inadequate support for the stage notion, inad-
equate account of mechanisms of development, need for a theory of
performance, slighting of social and emotional aspects of development,
underestimation of abilities, and methodological and stylistic barriers.
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94 c PIAGET’S COGNITIVE- STAGE THEORY AND THE NEO- PIAGETIANS
Some of these problems have been addressed by the neo- Piagetians,
particularly Case and Fischer, who include the contributions of working-
memory capacity and cultural support to the variability and consistency
of children’s thinking. In addition, Piaget himself continued to modify his
theory in his later years, particularly with respect to the nature of logic
and the mechanisms of development.
Today, researchers continue to examine the key issues of cognitive devel-
opment identified by Piaget and by those who challenged and expanded
his theory. Particularly active areas include infants’ advanced competen-
cies, domain- specific concepts, and mechanisms of development.
What should be our final judgment on Piaget’s theory? This flawed but
amazingly productive theory gives us a framework for viewing the rich-
ness and complexity of cognitive development. Even when it has failed,
for example, by providing no adequate explanation for conservation
despite hundreds of studies, the theory has led to interesting discoveries
about development. Examples include surprisingly sophisticated infant
knowledge and rudimentary numerical skills in preschoolers that may
lead to conservation. Furthermore, the theory has raised issues that all
theories of development must address. In short, we must pay attention
to this “giant in the nursery” (Elkind, 1968).
SUGGESTED READINGS
Much interesting material about Piaget can be found on the website of
the Jean Piaget Society: http://piaget.org/
Numerous books and articles have been written about Piaget and
research that his work stimulated. The following are a good start:
Martí, E. & Rodríguez, C. (Eds.). (2012). After Piaget. New Brunswick,
NJ: Transaction Publishers.
Müller, U., Carpendale, J. I. M., & Smith, L. (Eds.). (2010). The
Cambridge companion to Piaget. New York: Cambridge University Press.
Lourenco, O., & Machado, A. (1996). In defense of Piaget’s theory: A
reply to 10 common criticisms. Psychological Review, 103, 143–164.
The following books by Piaget are two of his more readable and clearly
written publications:
Piaget, J. (1967). Six psychological studies. New York: Random House.
Piaget, J., & Inhelder, B. (1969). The psychology of the child. New York:
Basic Books.
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Freud’s and Erikson’s
Psychoanalytic Theories
I dreamt that it was night and that I was lying in my bed . . . . Suddenly the win-
dow opened of its own accord, and I was terrified to see that some white wolves
were sitting on the big walnut tree in front of the window. There were six or seven
of them. The wolves were quite white, and looked more like foxes or sheep- dogs, for
they had big tails like foxes and they had their ears pricked like dogs when they
pay attention to something. In great terror, evidently of being eaten up by the
wolves, I screamed and woke up.
—“The Wolf Man” QuoTed in freud, 1918 (1955e, p. 29)
The most significant sex difference was the tendency of boys to erect structures,
buildings, towers, or streets . . . The girls tended to use the play table as the interior
of a house with simple, little, or no use of blocks . . . . Simple enclosures with low
walls and without ornaments were the largest item among the configurations built
by girls. However, these enclosures often had an elaborate gate . . . A blocking of
the entrance or a thickening of the walls could on further study be shown to reflect
acute anxiety over the feminine role.
—erikson, 1963, pp. 102–105
Se
rg
ey
N
iv
en
s/
Sh
ut
te
rs
to
ck
C H A P T E R 3
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96 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
P
sychoanalytic theory has great historical significance for develop-
mental psychology. To meet the source of the theory, we move
from Geneva to Vienna, where Freud spent most of his life. We
also move our focus from cognitive development to personal-
ity development. The development of the theory followed a tortuous
course, full of dazzling insights, diverging ideas, and clashing person-
alities. Although many figures are responsible for the psychoanalytic
movement, we must limit our attention to the main ones who influenced
developmental psychology— Sigmund Freud, who began the movement,
and Erik Erikson, who subsequently constructed a life- span view of
development. Both proposed that personality development proceeds
through a series of stages. In each stage, the child copes with certain
conflicts stimulated, to a great extent, by biological changes during
development. Freud’s theory, although developed prior to Piaget’s the-
ory, is presented here after the Piagetian chapter because Freud’s stage
theory can be more easily understood after the fuller discussion of issues
about stages in the Piagetian and neo- Piagetian tradition. This chapter
proceeds in the following order for both the Freud and Erikson sections:
biography, general orientation, description of stages of development,
mechanisms of change, the theory’s stand on critical issues, applications,
contemporary research, and evaluation.
FREUD
Biographical Sketch
Much of the material in this section comes from Ernest Jones’s three-
volume biography (1953, 1955, 1957) of Freud. Sigmund Freud
(1856–1939), an Austrian neurologist, was the father of psychoanalytic
theory. He was the eldest of eight children born to a wool merchant
and his wife. Freud believed that he was a favored child and that great
things were expected of him. As he expressed it, “A man who has been
the indisputable favorite of his mother keeps for life the feeling of a
conqueror, that confidence of success that often induces real success”
(quoted in Jones, 1961, p. 6). He had a voracious appetite for books on
history and philosophy, as did Piaget. He and a friend taught themselves
Spanish so that they could read Don Quixote in the original. In secondary
school, he read an essay by Goethe on nature that awakened an interest
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Biographical Sketch ▶ 97
in science. He entered medical school with the goal of becoming a
researcher. It is interesting, given the eventual focus of his theory, that
his first major research project was on the structure of the testes in eels.
The goal of becoming a research scientist had to be set aside when his
poor economic situation and barriers against advancement for a Jew in
academia forced him to enter private practice, where he used his neuro-
logical training to treat “nervous disorders.” At the time, this branch of
medicine was at a very primitive level, and its practitioners could give
little help to the mentally ill. Doctors typically prescribed hydrother-
apy (various types of baths) and electrotherapy (mild electric currents
passed through the body).
Freud was fascinated with hysteria, a disorder characterized by such
symptoms as paralysis, numbness, squinting, and tremors. His contact
with the French neurologist, Jean Charcot, and the Viennese physician,
Josef Breuer, aroused his interest in a possible new treatment, hypnosis.
Charcot could produce symptoms of hysteria in people by means of
hypnotic suggestion, which suggested that the malady had a psycho-
logical basis. As Freud began to use hypnosis with his patients, he was
impressed that they could recall important incidents and feelings while
under hypnosis that were otherwise inaccessible. This was the puzzling
observation that Freud developed his theory to explain: How and why
do we hide parts of our past from ourselves? Despite the general belief
among neurologists that hypnotism was fraudulent and dangerous,
Freud enthusiastically experimented with this technique: “There was
something positively seductive in working with hypnotism. For the first
time there was a sense of having overcome one’s helplessness; and it
was highly flattering to enjoy the reputation of being a miracle- worker”
(1925/1959, p. 17).
Freud also was influenced by Breuer’s discovery that symptoms of
hysteria could be alleviated simply by having his patients talk about
(and “relive”) their emotion- laden experiences from early life. With a
sense of excitement, Freud experimented with what Breuer called the
“talking cure.” In a letter to his friend Wilhelm Fliess in 1895, Freud
described how psychology possessed him: “A man like myself cannot
live without a hobbyhorse, without a dominating passion: in fact, with-
out a tyrant, to use Schiller’s expression, and that is what it has become.
For in its service I know no moderation. It is psychology” (quoted in
Jones, 1961, p. 226).
Freud’s study of his patients’ dreams and childhood memories led to
his first major publication, The Interpretation of Dreams (1900/1953a).
Although this book was ignored by medical and scientific circles, as well
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98 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
as by the general public, Freud was not discouraged. He produced a suc-
cession of fascinating books in the following years and eventually began
to attract a small following, including Carl Jung and Alfred Adler. The
new psychoanalytic movement strengthened, even while the European
medical establishment spurned it. A turning point came in 1909, when
the eminent American psychologist G. Stanley Hall invited Freud to
speak in the United States. As Freud described it, “In Europe I felt as
though I were despised; but over there I found myself received by the
foremost men as an equal” (1925/1959, p. 52). Interestingly, he was not
enamored of American culture, and told his biographer “America is a
mistake; a gigantic mistake, it is true, but none the less a mistake” (Jones,
1955, p. 60). He appeared on the cover of Time magazine in 1924 and
began to achieve international recognition. Psychoanalysis began to
influence not only psychiatry and the social sciences but also fields such
as literature, art, ethics, and education. “Subconscious” and “ego” became
household words. A popular song cautioned, “Don’t tell me what you
dream’d last night/For I’ve been reading Freud!” (Burnham, 1979,
p. 129). Of course, much of the reaction was far from positive; many
people were shocked at the claim that children have a sexual nature. The
attacks on psychoanalytic theory continued throughout Freud’s lifetime.
Freud’s theory evolved over the years. In fact, he made some basic
changes in his views when he was in his seventies. By the end of his
life, his psychoanalytic writings filled 23 volumes. When the Nazis took
over Austria in 1937, he was forced to flee to England, where he died
in 1939.
Freud’s notion that behavior and development are directed by pow-
erful unconscious drives shook 20 th- century thought. Concepts such as
infantile sexuality, the anal personality, and the teeming desires of the
unconscious jarred a Victorian society that covered piano legs to hide
their nakedness. Freud’s view of the human potential for destructive
behavior could not be so easily dismissed after two world wars and
the political crimes of the times. It was a theory whose time had come.
Regardless of one’s judgment about the scientific merit of the theory,
it is, without doubt, the most widely influential psychological theory in
history. Its impression on society may equal that of Marx and Darwin.
The theory’s influence reached into nearly every area of 20 th- century
thought. Freud described unconscious motivation in the areas of anthro-
pology (Totem and Taboo, 1913/1955c), art (“The Moses of Michelangelo,”
1914/1955d), religion (The Future of an Illusion, 1927/1961c), literature
(“Dostoevsky and Parricide,” 1928/1961d), sociology (Civilization
and Its Discontents, 1930/1961e), and history (Why War? 1933/1964b).
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General Orientation to the Theory ▶ 99
The general public became familiar with many of his ideas. Slips of the
tongue became more embarrassing than before, and people began to
take their dreams seriously. The belief that weaning and toilet training
should not be sudden and harsh is often attributed to Freud’s ideas.
Freud’s work on emotional and nonrational aspects of personality
significantly influenced psychology and psychiatry, especially in child
and adult therapies. Various followers further developed his theory
and, in some cases, broke away from Freud. Some of the best- known
neo- Freudians were Carl Jung, Otto Rank, Alfred Adler, Karen Horney,
Harry Stack Sullivan, Erik Erikson, Melanie Klein, Anna Freud, Heinz
Hartmann, and David Rapaport. Their work led to the various branches
of psychoanalysis found today. Over the years, psychoanalytic theories
increasingly emphasized rational, reality- oriented thought and close
social relationships.
Freud’s stage theory deeply influenced developmental psychology
in the 1940s and 1950s. Most prominent were Erikson’s stage theory
of psychosocial development; direct observations of children by Anna
Freud, Ernst Kris, Sybill Escalona, and Rent Spitz; John Whiting and
Irvin Child’s cross- cultural work; and John Bowlby’s early studies on
infant social attachment (see Chapter 5). Psychoanalytic theory also
touched the early work of social learning theorists (see Chapter 6).
Today, Freud’s theory remains a vital force within child clinical
psychology, child psychiatry, and counseling psychology. However,
developmental experimental psychology has ignored Freud’s theory for
decades, in part because his theory is not based on scientific evidence.
In the major journals of contemporary developmental research, one
rarely finds “tests” of the theory or references to psychoanalytic work.
However, as with Piaget, some of his ideas, such as the special impact
of early social experiences and identification with parents, are so much
a part of developmental psychology that his contributions are no longer
recognized as being specifically his.
General Orientation to the Theory
Accounts of Freud’s theory are somewhat contradictory, because various
sources give differing accounts and because Freud revised his ideas over
the years. Fortunately, despite changes in the details of the system, there
is constancy in the general approach. Six general characteristics emerge:
a dynamic approach, a structural approach, a topographic approach,
a developmental stage approach, a normal– abnormal continuum, and
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100 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
psychoanalytic methods. We look at each of these characteristics and,
when useful for clarifying the theory, compare them with those of
Piaget’s theory.
Dynamic Approach
Freud noted powerful drives in his patients, which led him to see per-
sonality as dynamic. He described his theory as “a sort of economics of
nervous energy” (quoted in Jones, 1953, p. 345). This nervous energy is
variously termed psychic energy, drive energy, libido, and tension. Analogous
to energy in physics, psychic energy builds up and can be distributed,
tied to certain mental images, transformed, and discharged. Psychic
energy is a general energy source that can be likened to an electricity
supply, which can be used to toast bread, shave, bake, and so forth (Hall,
1954, p. 84). Thus, psychic energy can be used to write a book, jog,
watch television, and make a bookcase.
In the same way that physical energy is transformed but not
destroyed, psychological energy is transformed into anxiety; displaced
into a physical structure that causes a symptom, such as paralysis; or
transformed into a thought, such as an obsession. The pleasure principle
states that whenever possible, energy is discharged without delay. The
organism strives toward the immediate, direct reduction of tension,
which reduces pain and produces pleasure. Hunger leads to eating; the
need to suck leads to sucking one’s thumb. In the reality principle, small
amounts of energy are discharged, but only in an indirect route, and
after a delay. The mental apparatus scans reality and evaluates various
possible courses of action before allowing energy to be discharged. For
example, an angry child may tell his friend he is angry with him rather
than hit him and risk punishment.
Where does this psychological energy come from? The human body
has certain instincts (biological drives) that make demands on the mind.
Freud posited two basic instincts— Eros (sex, self- preservation, love, life
forces, striving toward unity) and the destructive instinct (aggression,
undoing connections, the death instinct, hatred). Freud assigned the
term libido to the available energy of Eros. There is no analogous term
for the energy of a destructive instinct. His interest in the destructive
instinct came late in life and is attributed to his horror at the atrocities
of World War I and the anti- Semitic feelings of his times.
Instincts involve excitation in some region of the body, particularly
the oral, anal, and genital areas for the sex drive. The change in the site
of excitation underlies the movement from stage to stage, as we shall see
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General Orientation to the Theory ▶ 101
later. This internal excitation stimulates the mind and creates a “need.”
In the close interplay between mind and body, psychic energy is derived
from biological energy. The aim of the sex drive, or of any instinct, is to
remove this bodily need, discharge tension, and experience pleasure.
This ultimate goal is achieved through such subordinate goals as finding
and investing energy in sexual objects, either a real person or object or
a representation of a person or object. Libido becomes attached to or,
in Freud’s terminology, cathected to an object. Infants cathect to their
mother and other objects that satisfy their needs.
Drives can be satisfied either fully or in a partial and roundabout way.
Freud believed that da Vinci’s interest in painting Madonnas was a way
of partially satisfying his desire for his mother, from whom he had been
separated early in life. One object can substitute for another object, as
when an adult’s oral needs are satisfied by playing a trumpet. In some
cases, a culturally or morally “higher” goal object is substituted for the
truly desired object. This is labeled sublimation. An angry person might
sublimate his desire to attack other people by painting violent scenes.
Another common type of object substitution is compensation, in which
people make up for their failure in one area by applying themselves in
another area. A 5-foot, 6-inch basketball player may eventually become
a sports announcer.
Structural Approach
The previous section creates the image of a human hydraulic system with
powerful forces surging through the body and the mind. The other part
of the story is the psychological structures through which these forces
flow. These structures mediate between the drives and behavior. There is,
then, an architecture of the mind. Mental processes take place within the
structures, between the structures, and by means of the structures. There
are three major structures: the id, ego, and superego. Roughly speaking,
the id is the seat of biologically based drives, the ego is the mechanism
for adapting to reality, and the superego is analogous to the conscience.
We examine each “province of the mind” (Freud, 1933/1964a, p. 72) in
turn and then portray their overall organization.
Id ▶ As the novelist Peter De Vries humorously expressed it in Forever
Panting, “‘Id’ isn’t just another big word.” The id is the seat of innate
desires and is the main source of psychic energy. It is the “dark, inac-
cessible part of our personality . . . a chaos, a cauldron full of seeth-
ing excitations” (Freud, 1933/1964a, p. 73). The id wants immediate
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102 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
satisfaction, in accordance with the pleasure principle described earlier.
The energy of the id is invested either in action on an object that would
satisfy an instinct or in images of an object that would give partial satis-
faction. For example, infants may satisfy their oral- hunger drive directly
by sucking a nipple and receiving milk or partially and indirectly by
imagining a bottle of milk. This hallucinatory wish fulfillment is called
primary- process thought.
In contrast to young infants, older infants, children, and adults have
an ego and a superego in addition to an id. The id, however, continues to
operate throughout life, especially in our nighttime dreams, daydreams,
imagination, and impulsive, selfish, and pleasure- loving behavior. The id
has been called the “spoiled child of the personality” (Hall, 1954, p. 27).
Much of Freud’s knowledge about the id came from his study of
dreams. The desires of the id appear in dreams in either an obvious or a
disguised fashion. One does not need psychoanalytic training to interpret
a hungry person’s dream about a chocolate cake. However, some urges
are so threatening that they must be rendered less obvious. According to
Freud, clothes and uniforms sometimes represent nakedness; water can
stand for birth; a journey can mean death.
Ego ▶ In the beginning, there is id. The id, armed with primary- process
thought (hallucinatory wish fulfillment), makes its demands. However,
babies soon discover that thinking something does not make it so. The
image of the mother and milk and the memory of warmth do not quiet
the pangs of hunger. They learn that there is a difference between images
and reality, between the self and the outer world.
The id’s inability to always produce the desired object leads to the
development of the ego. The ego, the mind’s avenue to the real world,
is developed because it is needed for physical and psychological sur-
vival. It aids in survival because it possesses secondary- process thought.
Secondary- process thought is rational and includes intellectual activities
such as perception, logical thought, problem solving, and memory. It is
more organized, integrated, and logical than primary- process thought,
in which contradictions abound. Most of the intellectual abilities studied
by Piaget would fall into Freud’s ego domain. The ego is the executive
who must make the tough, high- level decisions. It evaluates the present
situation, recalls relevant decisions and events in the past, weighs var-
ious factors in the present and future, and predicts the consequences
of various actions. The ego’s decisions are aided by feelings of anxiety,
which signal that certain actions would be threatening. Above all, the
ego’s decision making involves the delay of energy discharge, the reality
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General Orientation to the Theory ▶ 103
principle mentioned earlier. Freud described the thinking of the ego as
“an experimental action carried out with small amounts of energy, in the
same way as a general shifts small figures about on a map before setting
his large bodies of troops in motion” (1933/1964a, p. 89).
The small quantities of energy at the disposal of the ego come from the
id. As the ego acquires more and more energy and gains experience using
secondary- process thought during development, it becomes stronger
and more differentiated. Of course, the ego, with its secondary- process
thought, does not replace the primary- process thought of the id. Rather,
it simply adds another level to thought. Gratification can be achieved
either by finding appropriate real objects in the environment after a delay
or by hallucinating and dreaming. Throughout life, we use a mixture of
primary- and secondary- process thought. However, as development pro-
ceeds, the secondary- process aspects of thought become more dominant.
The ego serves “three tyrannical masters”: id, superego, and external
world (Freud, 1933/1964a, p. 77). Freud described the ego’s position
in an analogy:
The ego’s relation to the id might be compared with that of a rider to
his horse. The horse supplies the locomotive energy, while the rider has
the privilege of deciding on the goal and of guiding the powerful animal’s
movement. But only too often there arises between the ego and the id
the not precisely ideal situation of the rider being obliged to guide the
horse along the path by which it itself wants to go.
(1933/1964a, p. 77)
The ego mediates between the id and the external world: “Thus the ego
is fighting on two fronts: it has to defend its existence against an external
world which threatens it with annihilation as well as against an internal
world that makes excessive demands” (Freud, 1940/1964c, p. 200).
These constant threats and dangers from the id and the environment
arouse anxiety. When possible, the ego tackles the problem in a realistic
way, using its problem- solving skills. However, when the anxiety is so
strong that it threatens to engulf the ego, defense mechanisms come into
play. They control and thereby alleviate anxiety by distorting reality in
some way. Although defense mechanisms allow only partial satisfaction
of the drives, for the organism in a state of tension, some satisfaction is
better than none. Freud and his daughter, Anna Freud, identified several
defense mechanisms.
For example, repression involves preventing a threatening thought from
reaching consciousness. The principle seems to be “What we don’t know
can’t hurt us” (Hall, 1954, p. 85). If anxiety- arousing thoughts cannot
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104 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
surface, we do not experience anxiety. For example, to avoid anxiety,
we forget to pay a bill that would put a severe strain on the budget.
Freud thought there was massive repression of memories of childhood
sexuality once children reach grade- school age. Only with great diffi-
culty could Freud help his adult patients recover early painful memories.
Freud’s ideas about repression developed from his observations in ther-
apy. When a patient reported her thoughts during “free association,” she
would often stop abruptly and claim that her mind had suddenly gone
blank, just at the moment when important memories of the past seemed
about to emerge. As Nietzsche remarked, “One’s own self is well hidden
from oneself: of all mines of treasure one’s own is the last to be dug up.”
If people depend too heavily on this defense mechanism, they may
develop a repressed personality: withdrawn, inaccessible, nonspontaneous,
and rigid. Also, there can be some loss of contact with reality as they make
serious and frequent mistakes in remembering, speaking, and perceiving
or develop symptoms of hysteria. For example, hysterical deafness may
prevent a person from hearing something she does not want to hear.
Two other defense mechanisms are reaction formation (acting the oppo-
site of the way one feels) and regression (returning to an earlier form
of behavior). For example, a young child who feels angry and insecure
when parents switch most of their attention to a newborn sibling may
shower the newborn with extravagant affection (reaction formation) or
start crawling or sucking her thumb again (regression).
In the defense mechanism fixation, one component of personality
development comes to a halt. A portion of the libido remains tied to an
earlier period of development and does not allow the child to proceed
fully to the next stage. Fixation can occur when the present mode of
satisfaction, for example, sucking a breast or bottle, is so gratifying that
the child does not want to give it up, even under pressures to become
weaned. Fixation can also occur when the next step appears to be too
frightening or demanding or unsatisfying. The initiation of toilet training,
if too harsh, may cause a toddler to remain partially in the oral stage
rather than progress through the anal stage. Fixation is tied to regression
in that a person is more likely to regress in the face of a barrier if there
has been fixation at an earlier point in development.
Defense mechanisms are a necessary evil. We need them to deal
with high anxiety but at the cost of “wasting” our energy when it could
be put to better use in ego development, for example, for creative
thought or the development of problem- solving skills. Furthermore, if
too much energy is tied up in the defense mechanisms, personality may
not develop normally because the person distorts reality and deceives
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General Orientation to the Theory ▶ 105
himself. This situation makes subsequent adjustments to reality even
more difficult.
Superego ▶ The superego is the last to develop. It arises when children
resolve their Oedipus complex and develop identification with their
parents. That story is told in the section on stages.
The superego is composed of two parts: the conscience and the ego
ideal. In general, the conscience is negative, and the ego ideal is positive.
The conscience is composed of the parents’ prohibitions, their “Thou shalt
nots.” Just as the parent has punished the child for his transgressions, so
does the conscience punish the person with feelings of guilt, the “acci-
dental” cutting of one’s finger, or intentionally self- destructive behavior.
Curiously, the superego often becomes even more severe than the par-
ents were. The ego ideal refers to standards of conduct toward which the
child strives. Just as the child has been rewarded for certain behavior by
the parents, she is rewarded by the ego ideal with feelings of self- esteem
and pride. These are echoes of early years when a parent said “Good
girl!” to the young child.
The superego opposes both the id and the ego. It rewards, punishes,
and makes demands. The superego watches over not only behavior but
also the thoughts of the ego, and even considers thinking as bad as doing.
The superego is society’s way of achieving order. Unrestrained sexual
and aggressive behavior would destroy the always tenuous social struc-
ture. Freud noted that if the ego represents the “power of the present”
and the id represents the “organic past,” then the superego represents the
“cultural past” (1940/1964c, p. 206).
Structural Relationships ▶ We have dissected the personality into
id, ego, and superego. However, personality is an organized whole—
a unique constellation of forces and structures. Freud sketched out
the relationship among the mental “areas,” as seen in Figure 3.1. He
cautioned that we should not regard the id, ego, and superego as sharply
F I G U R E 3 . 1
In Freud’s sketch of the structure and topogra-
phy of the mind, which also depicts the process
of repression, the label “pcpt.-cs.” refers to
the perceptual- conscious, usually called the
conscious.
[“Diagram on p. 98”, from New Introductory Lectures on
Psycho-Analysis, by Sigmund Freud, translated and edited
by James Strachey. Copyright © 1965, 1964 by James
Strachey. Used by permission of W.W. Norton & Company,
Inc. and Random House Ltd.]
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106 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
defined areas and certainly not as locations in the brain. Rather, they are
“areas of color melting into one another as they are presented by modern
artists” (Freud, 1933/1964a, p. 79). The superego, for example, blends
into the id and, in fact, is intimately related to the id. This close rela-
tionship is most clearly seen in the Oedipus complex, discussed later, in
which strong urges in the id necessitate the development of the super-
ego and are subsequently controlled by the superego. Or in another
instance, the id and superego may join forces in attacking supposedly
“immoral” persons as in witch burning or the cruelty of the Inquisition
(Hall, 1954, p. 48).
These structures contain a closed- energy system, in which a certain
amount of energy is distributed to the three parts. A gain in energy in
one part strengthens that part but at the same time weakens the other
parts. Under ordinary circumstances, the three systems work together
as a team in relative harmony rather than war against each other.
The ego is central in this structural relationship. It is brought into all
conflicts between the id and the superego because each is trying to use
the ego to meet its own needs. The ego must both obey and control the
id, superego, and external reality. It survives by compromising. If the id
says “yes” and the superego says “no,” then the ego says “wait” (Hall,
1954, p. 47). Freud summed up this relationship as follows:
Thus the ego, driven by the id, confined by the super- ego, repulsed by
reality, struggles to master its economic task of bringing about harmony
among the forces and influences working in and upon it; and we can
understand how it is that so often we cannot suppress a cry: “Life is
not easy!”
(1933/1964a, p. 78)
Yet Freud remained optimistic about human reason:
The voice of the intellect is a soft one, but it does not rest till it has gained
a hearing. Finally, after a countless succession of rebuffs, it succeeds. This
is one of the few points on which one may be optimistic about the future
of mankind, but it is in itself a point of no small importance.
(1927/1961c, p. 53)
Topographic Approach
Everyone is a moon and has a dark side which he never shows to anybody.
—Mark TWain
Freud’s observations that his patients seemed to have “areas” of their
mind that were inaccessible to them led him to develop a geography
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General Orientation to the Theory ▶ 107
(or topography) of the mind, which is depicted in Figure 3.1. The map of
the mind displays three regions: the unconscious, preconscious, and con-
scious. The unconscious is largely unknown territory; the preconscious
and, especially, the conscious have familiar terrains.
1 The unconscious consists primarily of thoughts and feelings that are
repressed and therefore unknown. This material is incapable of
breaking into consciousness without certain changes or interven-
tions, such as an increase in the drive, a weakening of ego defenses, or
the guidance of a therapist.
2 The preconscious is capable of becoming conscious because it is not
actively barred from consciousness. It is a great deal closer to the
conscious than is the unconscious. Preconscious thought becomes
conscious by forming mental images or linking up with language.
3 The conscious (or perceptual conscious) is synonymous with what
a person is aware of at the moment. It is a “highly fugitive state”
(Freud, 1940/1964c, p. 159) because thoughts can rapidly slip back
and forth between the preconscious and the conscious. Since energy is
required for a thought to enter into consciousness, only a few thoughts
can be conscious at any one time.
Freud used a metaphor to describe the relationship between the
unconscious and the preconscious and conscious:
Let us therefore compare the system of the unconscious to a large
entrance hall, in which the mental impulses jostle one another like sepa-
rate individuals. Adjoining this entrance hall there is a second, narrower,
room— a kind of drawing- room— in which consciousness, too, resides.
But on the threshold between these two rooms a watchman performs his
function: he examines the different mental impulses, acts as a censor, and
will not admit them into the drawing- room if they displease him.
(1917/1963b, p. 295)
Returning to Freud’s sketch, we see how the id, ego, and superego
(structures) are related to the unconscious, preconscious, and conscious
(topography). All the id resides in the unconscious. The unconscious id
is a large area, and in fact Freud corrected his drawing by noting that
the space taken up by the unconscious id should have been much greater
than that of the ego or the preconscious. If the mind is like an iceberg,
then the conscious is only the exposed tip of the iceberg; most of the ice-
berg (the unconscious) remains hidden. Both the ego and the superego
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108 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
span the three layers. For example, the ego is unaware of the action of
its defense mechanisms.
Developmental changes occur in the relative size of the unconscious,
preconscious, and conscious. An infant’s mind is almost completely
unconscious. With increasing age, the preconscious and conscious
occupy more and more of the mental territory. Even among adults,
however, the unconscious is the largest area.
Although Freud described the unconscious, preconscious, and con-
scious as though they were separate entities, he constantly noted that no
such separation exists. Rather, he was simply abstracting three aspects of
mental functioning. Reading obituaries in the newspaper can be traced
to both unconscious (fear of death) and conscious (keeping track of
elderly friends) motivations.
Freud placed great importance on the role of the unconscious: “For the
property of being conscious or not is in the last resort our one beacon-
light in the darkness of depth- psychology” (1923/1961a, p. 18). The
notion that there is a vast unconscious that controls behavior emerged
from Freud’s early psychoanalytic sessions with his patients. Patients had
sexual fantasies or impulses of which they were unaware but which led
to certain inexplicable behavior. For example, a patient with a healthy
visual system was unable to see because seeing was too painful; seeing
activated painful memories in the unconscious. Additional evidence for
the existence of an unconscious came from posthypnotic suggestion, in
which patients perform some action that was suggested to them while
under hypnosis, or from slips of the tongue, accidents that were not
really accidental, selective forgetting (as when someone forgets a dental
appointment), and dreams.
Stage Approach
Freud made two bold claims about human development. One is that the
first few years of life are the most important years for the formation of
personality. The other claim is that this development involves psycho-
sexual stages.
The notion that early experience is crucial seems obvious and non-
controversial to the modern student of development. This idea, however,
had not really been taken seriously until Freud systematically developed
it. According to Freud, a behavior can be understood only if one knows
how it developed in the person’s early history. Both normal behavior and
abnormal behavior have their roots in the early years, when the basic
structure of the personality is laid down. The early interactions between
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General Orientation to the Theory ▶ 109
children’s drives and their social environment set the pattern for later
learning, social adjustment, and coping with anxiety.
It is interesting that a therapist who studied and treated adults would
develop a theory of child development. Early in his work, Freud discov-
ered that attempts to trace the cause of a disturbed personality usually
led to traumatic, unresolved sexual experiences of childhood. The distant
past was very much alive in his patients’ current lives in dreams, anxiety
from repressed childhood desires, and defense mechanisms acquired in
childhood. From information revealed in sessions with patients, Freud
was able to reconstruct the sequence of stages of childhood.
Freud, like Piaget, focused on stages. We look at the general nature
of the five stages here and leave a fuller description for later. Each
stage is defined in terms of the part of the body around which drives
are centered. The eye of the storm shifts from the oral to the anal to
the phallic area during the first five years. Then a period of latency in
middle childhood is followed by the genital stage of adolescence. Each
stage presents new needs that must be handled by the mental struc-
tures. The way in which these needs are met (or not met) determines
not only how drive satisfaction is achieved but also how children relate
to other people and how they feel about themselves. Children develop
characteristic attitudes, defenses, and fantasies. Unresolved conflicts
in any stage may haunt people throughout their lifetimes. This is one’s
personality.
Because the movement from stage to stage is biologically determined,
it occurs whether or not there is unfinished business in the stage that is
ending. This notion of stage development is very different from Piaget’s,
in which one stage must be essentially completed before the next stage
may begin. The two theories, however, coincide in their claim that the
stages follow an invariant order. For Freud, the invariant order comes
almost entirely from physical maturation. For Piaget, it comes not only
from physical maturation but also from physical and social experiences
and innate ways of functioning mentally.
The two theories differ in the relationship between the stages. In
Freud’s theory, each stage is characterized by one dominant trait (for
example, anal concerns) but does not form a tightly knit, structured
whole, as does a stage in Piaget’s theory. Freud’s stages form layers,
with each stage only loosely integrated into the next, in contrast to the
reorganization of previous knowledge in each of Piaget’s stages. Also in
contrast to Piaget’s stages, one stage does not contain the germ of the
next. The oral stage does not become the anal stage in the way that con-
crete operations become (are transformed into) formal operations.
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110 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
Although a stage builds upon and is dominant over the previous stage,
it does not completely replace that stage, according to Freud. No stage
is ever given up entirely. Freud offered a simile of an army that advances
into new territory but leaves forces en route to send on supplies or
provide a place to retreat to if difficulties arise. In the same way, a child
can escape unbearably tense experiences by regressing to earlier behav-
ior, such as sucking the thumb or hallucinating the desired object. Also,
earlier modes of satisfaction may be retained, as when thumb sucking
persists throughout the preschool years. Or, anal concerns may still be
present, but they are suppressed, sublimated, and displaced until they
bear little resemblance to their earlier form (for example, giving gifts
in adulthood). There is a partial integration in the last stage, the genital,
when the component instincts (oral, anal, and phallic) merge to form
adult genital sexuality.
Normal– Abnormal Continuum
Psychologists often understand behavior through comparisons— of
cultures, of humans with other primates, and of atypical with typical
development. Just as today psychologists might draw on research with
children with autism to better understand typical development, Freud
drew on his interactions with people with malfunctioning personalities
to develop a theory of normal development. For example, patients suf-
fering from delusions of being observed by unknown persons who dis-
trusted them and expected them to transgress and be punished clarified
the workings of the conscience in what he considered normal people.
The only difference was that the internal was projected to the external
in “abnormal” cases. Freud explained the value of studying abnormal
behavior:
Pathology, by making things larger and coarser, can draw our attention
to normal conditions which would otherwise have escaped us. Where
it points to a breach or a rent, there may normally be an articulation
present. If we throw a crystal to the floor, it breaks; but not into hap-
hazard pieces. It comes apart along its lines of cleavage into fragments
whose boundaries, though they were invisible, were predetermined by
the crystal’s structure. Mental patients are split and broken structures
of this same kind. . . . They have turned away from external reality, but
for that very reason they know more about internal, psychical reality
and can reveal a number of things to us that would otherwise be inac-
cessible to us.
(1933/1964a, pp. 58–59)
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General Orientation to the Theory ▶ 111
Freud argued not only that atypical personalities heighten our under-
standing of typical development but also that there is no sharp cleavage
between the abnormal and the normal. Abnormal and normal person-
alities obey the same principles and merely occupy different positions
along a continuum ranging from the very disturbed to the very healthy.
In an abnormal personality, psychological processes simply are exagger-
ated or distorted. A person with depression is only more depressed than
most people. A sadistic killer has a strong, uncontrolled aggressive drive.
An amnesiac must repress all of a painful past. Yet every normal person-
ality has traces of depression, aggression, and unaccountable forgetting,
as described in the appropriately titled The Psychopathology of Everyday Life
(Freud, 1901/1960). When reality becomes too painful or impulses of
the id intensify, the ego’s frantic attempts to keep in touch with reality
or fortify the barriers against the id or superego ultimately fail. Neurotic
symptoms or even a psychosis results. In Freud’s words, “The threatened
ego throws itself into the arms of the unconscious instinctual forces in a
desperate revolt” (1933/1964a, p. 16).
Methodology
It might seem odd that Freud did not study children directly as he built
a theory of development. His rationale for studying only adults was that
our childhoods remain with us always, in that our adult personalities
are residues of our childhoods. In addition, his patients happened to be
adults rather than children. For these reasons, he devoted his efforts
to developing methods for eliciting information about childhood from
adults. Freud also conducted a self- analysis, beginning in 1897 and con-
tinuing throughout his life. He reserved the last half hour of each day for
this purpose. This increased his confidence, if not that of the scientific
community, in his theory of personality.
Freud’s methods of free association and dream analysis at first shocked
the psychiatric profession and the public but eventually won the accep-
tance of many therapists. The method of free association requires that
patients verbally report their ongoing stream of thought. The patient
would relax, usually on the famous couch, in a quiet room, while Freud
sat near the patient’s head but out of sight. He instructed his patients
to report every thought, regardless of how trivial it seemed, omitting
or censoring nothing. This relaxed, accepting state promoted the ego’s
relaxation of control over unconscious thoughts. Repressed thoughts
might then emerge, though often in disguise. Occasionally, if the patient
fell silent, Freud would ask a question or even “lay on hands”—put his
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hand on the patient’s forehead— and tell the patient that new memories
would come.
The theoretical rationale for the free- association technique is as
follows: Freud believed that every psychological event has a meaning.
That is, a thought or feeling is caused; it does not occur randomly. If
one thought typically leads to another, there is a reason for it— they are
connected in some way. If a patient talked about her deceased father
and then abruptly changed the subject to a planned trip, Freud inferred
that she was troubled by her father’s death. (Freud thought that a jour-
ney is often a symbol for death.) In this way, he abstracted common
themes underlying seemingly unrelated thoughts or behaviors. More
generally, he tried to describe the organization of the patient’s mind.
The central concepts of Freud’s theory arose from the free- association
sessions.
A second method is dream analysis. If all thoughts are causally related
and significant, then psychologists cannot ignore dreams. During dreams,
the usual psychological controls are “sleeping” and thus allow disturbing
unconscious thoughts to be expressed and wishes to be fulfilled. These
thoughts, however, are often disguised until they are unmasked during
psychoanalysis. For example, kings and queens might represent parents,
little animals or vermin might stand for siblings, and snakes and trunks
might represent sex organs (Freud, 1916/1963a, pp. 153–157).
In summary, Freud’s methodology was to listen to troubled adults
talk. He did not perform controlled experiments and, unlike Piaget, did
not observe children’s behaviors. Instead, he studied individual adults in
depth, sometimes spending hundreds of hours with a single patient. As
if putting together a jigsaw puzzle, he put together pieces of information
from patients’ free associations, dreams, expressions of emotion, use of
defense mechanisms, slips of the tongue, and so on:
He that has eyes to see and ears to hear may convince himself that no
mortal can keep a secret. If his lips are silent, he chatters with his finger
tips; betrayal oozes out of him at every pore. And thus the task of making
conscious the most hidden recesses of the mind is one which it is quite
possible to accomplish.
(Freud, 1905/1953b, pp. 77–78)
Freud organized this information into a coherent picture in his case
studies. Several long case studies were published and became well
known. For example, the “Rat Man” (1909/1955b) had the obsession
that his father and girlfriend would be punished with hungry rats fas-
tened to their buttocks. The “Wolf Man” (1918/1955e) reacted to
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Description of the Stages ▶ 113
viewing the “primal scene” (sexual intercourse between his parents) by
dreaming about wolves (see the dream report at the beginning of this
chapter).
Description of the Stages
Oral Stage (Roughly Birth to 1 Year)
During infancy, the mouth rules. Oral experiences introduce a baby to
both the pleasure and the pain of the world. Pleasure flows from the
satisfaction of the oral drives. Sucking, chewing, eating, and biting give
sexual gratification by relieving uncomfortable sexual excitations. The
oral activities cause pleasant sensual feelings in the lips, tongue, and
membranes of the mouth. These pleasant feelings need not be linked
with the satisfaction of hunger because the oral activities themselves are
satisfying. The outcome of all of this, in Freudian terminology, is that
libidinal energy is cathected (invested) in the oral erogenous zone. The
salient social and nonsocial experiences in the oral stage center around
oral concerns.
In addition to experiencing oral pleasure, an infant feels pain from
frustration and anxiety. Sexual tensions are pleasant if they are satisfied
but painful if they are not and continue to intensify. A preferred object,
such as a nipple, may not be present at the moment an infant wants
it. She must wait, a situation that she finds frustrating and anxiety arous-
ing. She may lapse into hallucinatory wish fulfillment as she imagines
the desired nipple. Or she may suck her fingers, a blanket, or a soft toy.
Still, satisfaction is not complete. Other frustrations come when parents
demand that the nighttime feeding be given up, that certain objects not
be chewed because they are unsanitary or unsafe, and, especially, that the
breast or bottle be given up for the cup. The cultural demands of one’s
society are expressed through the parents. Parents teach the infant how
to satisfy her drives in ways that are acceptable to the society. Conflict is
inevitable. In small ways, the infant discovers that life has its frustrations
as well as its pleasures, its “downs” as well as its “ups.” She develops ways
of coping with these frustrations that will form the basis for her later
personality.
As babies seek gratification and valiantly struggle to overcome barri-
ers to this satisfaction, there is an important psychological principle at
work: Infants are in developmental trouble if they obtain either too little
or too much oral gratification. The side effects of too little gratification
are frequent anxiety, continual seeking of oral gratification in later years,
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114 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
and pessimism. Too much gratification may make it difficult for children
to shift their cathexes to new objects, as demanded by a new stage. In
this case, fixation can occur. Furthermore, relatively minor anxiety in a
later stage may cause regression to highly cathected objects of the oral
stage. For example, the initiation of toilet training during the anal stage
may cause a child to return quickly to thumb sucking. The goal, then,
is to achieve an optimal level of oral gratification so that one need not
carry unfulfilled needs into later stages or feel unwilling to move on to
a new stage.
Each of several oral “modes of functioning” during infancy forms a
prototype (model, plan, or blueprint) for adult personality: (1) taking
in, (2) holding on, (3) biting, (4) spitting out, and (5) closing (Hall,
1954, p. 104). Infants learn characteristic oral reactions in each of these
types of situations, which lead to certain attitudes, behaviors, and life
goals in adulthood:
1. The infant who found pleasure from taking in food becomes an adult who
voraciously “takes in,” or acquires, knowledge or power and who incorpo-
rates or identifies with significant other people.
2. Trying to hold on to the nipple when it is removed may lead to determi-
nation and stubbornness.
3. Biting is the prototype for destructiveness, “biting” sarcasm, cynicism, and
dominance.
4. Spitting out becomes rejection.
5. Closing the mouth firmly leads to rejection, negativism, or introversion.
Note that these adult behaviors range from the literally oral, as in
smoking, nail biting, and eating, to the metaphorically oral, as in being
gullible (swallowing anything) and obstinate (holding on). These modes
of functioning also show that humans are both positive and negative
about others. Just as an infant both sucks and bites a nipple, a person may
both love and hate another person.
All these characteristics are found in every personality to some degree.
However, some people have a personality structure that is dominated by
one or several of these prototypes from the oral modes. In particular,
certain traits may dominate because of extremely pleasant or unpleasant
experiences in infancy. For example, an infant with unaffectionate par-
ents may become an adult who seeks to “take in” love symbolically by
acquiring power or vast amounts of money.
Perhaps the most momentous event of the oral stage is the formation
of attachment to the mother (though fathers’ contributions are also
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Description of the Stages ▶ 115
addressed today, e.g., Parke, 2013). Freud proclaimed that the mother’s
importance is “unique, without parallel, established unalterably for a
whole lifetime as the first and strongest love- object and as the prototype
of all later love- relations” (1940/1964c, p. 188). Because typically it is
the mother who satisfies needs such as food, sucking, and warmth, she
becomes the primary love object in an infant’s life. An infant invests a
great deal of libidinal energy in her. Emphasizing the importance of an
emotional attachment to the mother is one of Freud’s main legacies to
the field of developmental psychology, and it inspired Spitz’s (1945)
work on disturbed mother– infant relationships. After observing that
many infants left in foundling homes became depressed and that some
even died, Spitz concluded that the lack of mothering contributes to
psychological and health problems. Subsequently, Bowlby’s (1958) sem-
inal work on attachment (see Chapter 5) led to research by many other
investigators in recent years.
Although it may seem counterintuitive, attachment seems to lead
to an infant’s healthy sense of separateness from his mother. Winnicott
(1971) stressed that this gradual differentiation is necessary for a clear
sense of self and for normal interpersonal relations later. Before this
differentiation, an infant– mother matrix gives little sense of separa-
tion of the self and the world. What Winnicott called “ good- enough
mothering” involves a synchrony, or match, between an infant’s needs
and spontaneous behaviors and the caretaker’s activities. Consequently,
the infant feels omnipotent because he can magically obtain his every
desire. However, babies inevitably encounter delays in gratification,
interact with various “ not- me” objects, and discover their own resources
for interacting with the world, thereby developing their ego. This
process of individuation can be threatening, and in severe cases, child
psychosis results from a faulty individuation process (Mahler, Pine, &
Bergman, 1975). Object loss, particularly the real or perceived loss of
the mother, is one of the most significant events that can occur in early
life. Fortunately, the “holding environment” with the mother, as well as
“security blankets” or other cuddly, comforting objects, provide a secure
base and ease the separation process.
Mothers also design “play dialogues,” which involve a mutual reg-
ulation of the interaction between themselves and their infants. A
mother uses her infant’s gaze and state of arousal as cues for the timing
and intensity of her facial expressions and talking (Stern, 1974, 1985,
1995). Thus, the ideal mother tries to avoid both stimulus overload and
boredom. The important outcome is that in the context of a social rela-
tionship, children use feedback regarding their effect on the mother to
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116 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
construct their self- concept. In other words, babies express and define
their true selves by being with their mother and seeing the effects of
their spontaneous actions toward her.
Thus, attachment is a vital process for development because it serves
as a building block for later social relationships. Furthermore, it facil-
itates a mother’s attempts to socialize her child by using her attention
to reward desirable behavior. However, in Freud’s somewhat pessimistic
theory, all silver linings are covered by clouds. Thus, attachment has
its dangers. If the attachment is too strong, infants may become overly
dependent on their mother or anxious about her possible rejection of
them. Then, later in life, they may develop a generally passive personal-
ity, depending on others to do things for them and even do their thinking
for them.
Anal Stage (Roughly 1 to 3 Years)
By the end of the oral stage, infants have developed the rough outlines
of a personality. This personality consists of attitudes toward themselves
and other people, mechanisms for achieving gratification within the
demands of reality, and interests in certain activities and objects. As
maturation moves infants to the anal stage, the concerns move from the
oral area to the anal area. The new needs of this stage set in motion new
conflicts between children and the world. The way in which children
resolve these new conflicts further differentiates and crystallizes the
rudimentary personality structure. The expression of oral needs does
not stop, of course. Children simply face a new set of needs and demands
that require their immediate attention.
The physiological need to defecate creates tension, which is relieved
by defecation. This anal stimulation and subsequent reduction of tension
produces pleasure. As in the oral stage, the erogenous zone brings frus-
tration and anxiety as well as pleasure. Society, as represented by the
parents, demands toilet training, and thus self- control. Consequently,
the desire for immediate gratification is frustrated. In a small but
momentous way, children enter into conflict with authoritarian adult
society. Children all over the world face and resolve this conflict in some
way. Obviously, many variables affect how much conflict a child feels and
how she adapts to the demands placed on her. These variables include the
age at which toilet training is begun, how strict or relaxed the training
is, and the mother’s attitude toward defecation, control, and cleanliness.
If toilet training is particularly harsh or premature or overempha-
sized by the parents, defecation can become a source of great anxiety
for children. This anxiety can generalize to other situations in which an
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Description of the Stages ▶ 117
external authority makes demands or children must control their own
impulses. Some children react to strict toilet training by defecating at
inappropriate times or places, such as the supermarket. The child may
become a messy, dirty, and irresponsible adult or, at the other extreme, a
compulsively neat, orderly, and obstinate adult. These potential negative
outcomes in the anal stage certainly are not comforting to the prospec-
tive parent!
As in the oral stage, the goal is to allow enough, but not too much,
gratification and to develop enough, but not too much, self- control.
If this goal is adequately achieved, a child will have developed a more
mature ego because it has been sharpened by its confrontation with real-
ity. A child who survives the anal period relatively unscathed is ready to
tackle the third stage, the phallic stage, when it arrives.
Phallic Stage (Roughly 3 to 5 Years)
The child’s solution to problems of the oral and anal stages sets a pattern
for solving later problems of adjustment. This development is continued
in the phallic stage, so named because the possession of the phallus in
boys and its absence in girls is a major concern of children, according to
Freud. In this stage, pleasures and problems center on the genital area.
The problem of this stage is that the sexual urge is directed toward the
parent of the other sex. In boys, this situation is the well- known Oedipus
complex. (In Greek mythology, Oedipus killed his father and married his
mother.)
Freud emphasized the development of boys more than girls in the
phallic stage because he believed that the conflict is more intense for
boys. A young boy has sexual desires for his mother and does not want to
share her with his father. At the same time, the boy fears that the father,
in retaliation, will castrate him. As a way out of this highly anxious sit-
uation, the boy represses both his desire for his mother and his hostility
toward his father.
The most important outcome of the Oedipus complex is that a boy
comes to identify with his father. That is, he develops a strong emotional
bond with the father, strives to be like him, and “internalizes” him— his
beliefs, values, interests, and attitudes. Identification is very important
because it serves as a basis for much of socialization. In particular, the
development of the superego and behavior considered appropriate to
one’s sex are by- products of this identification. The superego increases
the child’s self- control and adherence to the parents’ morality.
Identification is a reasonable solution to the demands of the ego and
id in this stage. The ego is partially satisfied because anxiety is reduced.
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The id is partially satisfied because a boy can “have” the mother vicari-
ously through the father. Again, as children try to cope with both their
drives and the prohibitions of society, they achieve a compromise solu-
tion that advances their psychological maturity.
Freud argued that, in comparison with boys, girls face a similar, but
much less intense, conflict during the phallic stage. He proposed that
a girl desires her father and experiences penis envy as she realizes that
the father has a prized object that she does not have. In Freud’s words,
“She makes her judgment and her decision in a flash. She has seen it
and knows that she is without it and wants to have it” (1925/1961b,
p. 252). The girl begins to feel that she has been castrated and blames her
mother for this loss because she “sent her into the world so insufficiently
equipped” (p. 254).
As in the case of boys, society does not allow the full expression of the
sexual desire for the parent. However, because castration is not possible,
girls feel less threat from the mother than boys do from the father. Freud
thought that since there is less anxiety and consequently less repression,
girls have a weaker identification with the mother than boys do with the
father. Freud then concluded that girls have a weaker conscience than
do boys, a claim that is not supported by research. Freud’s views on the
Oedipus complex and penis envy are perhaps the most controversial
aspect of his theory and have been rejected by many.
In actuality, there is always identification with both parents. Both
sexes retain a strong cathexis for the mother because she is the most
important object in the two previous psychosexual stages.
In psychoanalytic sessions, Freud found powerful and lasting influ-
ences from the phallic stage. For example, women often had disturbing
sexual fantasies about their fathers that had never been resolved. More
generally, lasting attitudes toward the opposite sex and toward people in
authority could be traced to this stage.
With the achievement of identification and the waning of the phallic
stage, children’s basic personality is set, and conflicts are resolved in
characteristic ways. Personality changes, but it does so primarily by fur-
ther differentiation of the basic structure.
Period of Latency (Roughly 5 Years to the
Beginning of Puberty)
After the Sturm und Drang of the first three stages, there is a period of rel-
ative calm, when sexual drives are repressed and no new area of bodily
excitement emerges. Children conveniently “forget” the sexual urges
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Description of the Stages ▶ 119
and fantasies of their earlier years. They turn their thoughts to school
activities and play, primarily with children of the same sex. This is a time
for acquiring cognitive skills and assimilating cultural values as children
expand their world to include teachers, neighbors, peers, club leaders,
and coaches. Sexual energy continues to flow, but it is channeled into
social concerns and into defenses against sexuality. Thus, the ego and
superego continue to develop.
Genital Stage (Adolescence)
The sexual impulses, which were repressed during the latency stage,
reappear in full force as a result of the physiological changes of puberty.
These sexual impulses are fused with the earlier ones but are now
channeled into adult sexuality. Love becomes more altruistic, with less
concern for self- pleasure than in earlier stages. The choice of a partner is
influenced by attitudes and social patterns developed in the early years.
For example, a woman may choose a “father figure.”
Although some internal conflict is inevitable throughout life, a rela-
tively stable state is achieved by most people by the end of the genital
stage. Typically, an individual achieves a fairly strong ego structure that
makes coping with the reality of the adult world possible. One import-
ant achievement is a balance between love and work.
Case Study of “Little Hans”
The above outline of the psychosexual stages cannot capture the vivid,
powerful conflicts that operate in an individual child’s life. Thus, we turn
to one of Freud’s most famous case studies, the “Analysis of a Phobia in
a Five- Year- Old Boy” (1909/1955a) or, as it is more commonly known,
“Little Hans.” This case study was unique because it was Freud’s only
analysis of a child and because Freud conducted the analysis by mail in a
series of letters with the boy’s physician- father, who made the observa-
tions. The study was a central force in the formation of one of Freud’s
most important developmental concepts: identification.
When Hans was 5 years old, anxiety attacks, a phobia, and a fantasy
appeared. His phobia, the fear that a horse would bite him or fall down,
was so strong that he would not leave his house. He was especially afraid
of horses that pulled heavy loads in carts or vans or were white with
a black muzzle and wore blinders. In Hans’s fantasy, during the night
“there was a big giraffe in the room and a crumpled one; and the big one
called out because I took the crumpled one away from it. Then it stopped
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120 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
calling out; and then I sat down on top of the crumpled one” (quoted in
1909/1955a, p. 37).
After sifting through the evidence, Freud identified three themes: an
Oedipus conflict, sibling rivalry, and fear of punishment for masturba-
tion. Thus, in the phobia, the horse represented Hans’s father, who had
a mustache (a black muzzle around the horse’s mouth) and eyeglasses
(blinders) and was, as Hans remarked, “so white” (like the white horse).
Hans feared that the horse would bite (castrate) him because of his sexual
longing for his mother and his masturbating. Anxiety about masturbation
may have been prompted by his mother’s threat that if his masturbation
continued, she would send him to the doctor to cut off his “widdler.”
The fear that a horse might fall down was interpreted as a fear that his
father might die or go away, as he sometimes wished when he wanted
his mother alone. Significantly, Hans had remarked, “Daddy, don’t trot
away from me” (p. 45). The giraffe fantasy might be interpreted as a wish
for possessing the mother, as Hans imagined he sat on the smaller giraffe
(mother), which he had taken from the larger giraffe (father). Note the
phallic symbol in the giraffe’s long neck.
Hans’s feelings of loss of attention and love after the birth of his sister
were expressed in the fear that a cart might be upset and spill its con-
tents (his mother might give birth again). In the fantasy, Hans destroyed
his younger sister when he sat on her (the small giraffe).
Hans eventually identified with his father, thereby resolving his con-
flicts and recovering from his fear of horses. He continued to develop a
healthy personality and later became an opera producer. More recently,
interesting material uncovered about the Little Hans case stimulated
several fascinating papers (King, Neubauer, Abrams, & Dowling, 2007).
Mechanisms of Development
Both Freud and Piaget have a “trouble” theory of development.
Development proceeds because of disturbances to the system (disequi-
librium). Development is hard work, because children must continually
try to re- establish a state of relative calm. For Freud, emotion- laden
thoughts rather than objective information about the physical world
cause the disequilibrium. He was more concerned with psychologi-
cal pain than logical inconsistency, with energy in repose than mental
actions in balance. Freud’s equilibration system is less open (less respon-
sive to external information) than Piaget’s. Piaget spoke of continual
assimilation and accommodation as new experiences are encountered.
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Mechanisms of Development ▶ 121
In Freud’s system, there is more resistance to change. The system is also
closed in that there is a certain amount of energy that can be changed in
form but never in amount.
Freud identified several sources of conflict or psychological disruption
that stimulate development— physical maturation, external frustrations,
internal conflicts, personal inadequacies, and anxiety (Hall, 1954, p. 72):
1. Maturation involves changes in the nervous system, motor development,
hormonal changes, drives, and so on. Each change brings new possibilities
and new problems. As we saw earlier, the drives are particularly important.
These maturational forces both propel children into activity as they try to
satisfy the drives and move them from stage to stage as the bodily site of
pleasure changes.
2. External frustrations come from people or events that do not allow the
immediate expression of needs. They cause a painful buildup of tension and
force children to delay and detour their discharge of energy.
3. Internal conflicts arise from the battle among the id, ego, and superego or,
more specifically, between drives and forces of repression.
4. Personal inadequacies are certain skills, knowledge, expertise, or experience
that the person needs but lacks. For example, a child may want to join a
peer group but be too shy to enter the group or too clumsy at the game
they are playing.
5. Finally, anxiety is an unpleasant feeling that occurs when the child antici-
pates physical or psychological pain. The fear of losing a valued love object
is a common example.
All these elements cause an unpleasant state of tension, which the child
attempts to rectify in accordance with the pleasure principle and the real-
ity principle. These disturbances, however, merely initiate change. Other
mechanisms actually accomplish change. The ego has the primary respon-
sibility for guiding the course of change. Its perceptual and cognitive sys-
tems gather relevant information about the current situation, recall useful
information from past experiences, and use whatever defense mecha-
nisms are most appropriate. The ego develops methods for keeping dis-
tressing sexual thoughts from becoming conscious and placates the id and
superego. The ego, then, mediates change from moment to moment. The
accumulation of these small changes adds up to long- term change. Over
time, the ego gathers strength, and personality crystallizes and becomes
further differentiated into complex attitudes, interests, and behaviors.
Several developmental acquisitions also serve as mechanisms of fur-
ther development. The most notable are attachment and identification.
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122 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
As mentioned earlier, both lead to other important acquisitions,
such as gendered behaviors and moral development in the case of
identification.
Position on Developmental Issues
Human Nature
Hall and Lindzey summarize Freud’s view of the person as
a full- bodied individual living partly in a world of reality and partly in a
world of make- believe, beset by conflicts and inner contradictions, yet
capable of rational thought and action, moved by forces of which he has
little knowledge and by aspirations which are beyond his reach, by turn
confused and clearheaded, frustrated and satisfied, hopeful and despair-
ing, selfish and altruistic; in short, a complex human being.
(1957, p. 72)
This description of the conflicted, contradictory nature of humans
stands in sharp contrast to Piaget’s rational human, calmly searching for
epistemological truth in a predictable world. Freud was concerned with
emotions, particularly their role in forcing the development of personal-
ity and thought as children strive to cope with these emotions. By nature,
people have strong passions that color their perceptions throughout life.
Freud’s theory has elements of both the mechanistic and organismic
worldviews. It is mechanistic in its likening of psychological energy to a
hydraulic system. It is organismic in its view of the mind as a structured
whole consisting of id, ego, and superego in a dynamic balance that
changes developmentally. However, for Freud, a psychological being is a
loosely organized whole rather than the tightly knit, integrated, equili-
brated whole of strongly organismic Piagetian theory.
Although human beings are passive in that drives force them into
action, they are active, and therefore organismic, in their attempts to
cope with these drives and maintain a state of equilibrium. The ego,
in its executive role, actively organizes incoming information from the
self (for example, anxiety about some impending event) and the social
environment, and directs the behavior chosen. Still, for Freud, children
act because drives force them to act, whereas for Piaget, children act
because they are inherently active and self- regulated.
Qualitative Versus Quantitative Development
As in Piaget’s theory, the stagelike changes proposed by Freud imply
that development involves qualitative change. There is a change in which
aspect of the sexual drive is dominant: the oral, anal, phallic, or genital.
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Applications ▶ 123
There is also qualitative change in the psychological organization as
new acquisitions, such as defense mechanisms and the superego, appear.
Still, there is some quantitative change, as the developing child exhib-
its a gradual strengthening of the ego, superego, and various defense
mechanisms.
Nature Versus Nurture
It typically is claimed that Freud has a biologically based theory of
development. Although he emphasizes maturation and the biologically
based drives, he also sees experience as quite important: “The constitu-
tional factor must await experiences before it can make itself felt; the
accidental factor must have a constitutional basis in order to come into
operation” (Freud, 1905/1953b, p. 239). Although drives derive from
a person’s biological nature, their expression is always modified by the
social milieu. The people or objects available and the behaviors allowed
by parents or other authorities direct the satisfaction of the drives. The
demands of civilization are as real as the demands of the body. Within
the category of nurture, Freud saw the experiences of the first five years
of life as especially important, particularly relationships with parents,
mainly mothers.
What Develops
The essence of development is the emergence of structures— the id,
ego, and superego— that channel, repress, and transform sexual energy.
These structures and their dynamic processes are both affective (emo-
tional) and cognitive. Although Freud typically is not considered a
cognitive psychologist, in many ways he was. Thought— whether uncon-
scious, preconscious, or conscious and whether primary or secondary
process in nature— always accompanies feeling.
Applications
This chapter provides many examples of applications of Freud’s theory
to clinical practice. These applications continue today with adults and
children, and include even parent– infant psychotherapy (Dugmore,
2014). The Little Hans case study shows how one might analyze a single
child in depth. Freud’s message for parents is to be sensitive to the con-
flicts among id, ego, and superego in their child and to provide support
for the resolution of these conflicts. A secure attachment between parent
and child is particularly important, as is the later relationship during
children’s identification with their parents.
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124 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
Freud’s claim that people can repress painful memories for years
has arisen again in recent clinical and legal issues about adults’ recall,
decades later, of childhood sexual abuse. Freud at first believed his
patients’ accounts of these events but later concluded that it was unlikely
that there were so many Viennese parents who had sexually abused their
children. He then viewed these memories as fantasies or perceptions dis-
torted by sexual desire, but he still thought that, true or false, they were
important because they affect the course of personality development.
This issue about his patients has never been resolved, and psychologists
today continue to debate the accuracy of recovered memories of early
abuse (see Chapter 7).
Evaluation of the Theory
Although rejection of certain aspects of Freud’s theory is reasonable,
experimental psychologists’ overall rejection of the theory may have
deprived the field of a valuable perspective on development. Despite
the paucity of research today that is explicitly Freudian, this approach
can provide some insights into current issues in developmental psychol-
ogy. Thus, the following section on strengths focuses on two that are
of potential contemporary relevance, namely, the theory’s discovery of
central developmental phenomena and its focus on nonlogical thought.
Strengths
Discovery of Central Developmental Phenomena ▶ Although
Freud’s influence is rarely acknowledged explicitly in current develop-
mental research, many core concepts were introduced or significantly
developed by him: developmental stages, psychological structures,
unconscious motivation, and the importance of early experience. In
addition, the theory stimulated research in the areas of moral devel-
opment, sex typing, identification, parent– child relations, attach-
ment, aggression, and self- regulation. These remain active areas of
research today.
Focus on Nonlogical Thought ▶ Psychoanalytic theory’s focus on
emotions and nonlogical thought could enrich contemporary cognitive
approaches, which focus on rational problem solving: how thought
becomes increasingly organized, efficient, abstract, and objective. This
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Evaluation of the Theory ▶ 125
type of thought characterizes that of an adult scientist, the goal of
cognitive development in Piaget’s view. This viewpoint emerged clearly
in Piaget’s emphasis on logical operations and on concepts of the phys-
ical world. The information- processing approach, described in a later
chapter, also pictured a developing child as an organism that relentlessly
searches for truth in an increasingly efficient and rational way. Although
this view characterizes part of cognitive development, it does not tell
the whole story. Humans probably are not as rational as these theories
propose. As Wason and Johnson- Laird express it, “At best, we can all
think like logicians; at worst, logicians all think like us” (1972, p. 245).
Irrational thought processes are as important as the more frequently
studied rational ones; in fact, the former may occur more frequently
than the latter. Thus, Freud’s theory poses two challenges for devel-
opmentalists. One challenge is to study how emotions affect thinking
in children. Do children reason differently when angry or frustrated
than when calm? A second challenge is to examine whether the men-
tal processes underlying primary- and secondary- process thought and
the defense mechanisms differ from the mental processes described
by Piaget and the information- processing psychologists. For example,
how is Piaget’s notion of mental reversibility related to Freud’s notion
of reaction formation, in which a negative attitude toward a person or
an object is transformed into a positive attitude? Are conflicting feelings
and logically contradictory ideas resolved in the same way? What are the
mental processes underlying self- deception? What cognitive acquisitions
are necessary for understanding displaced aggression (taking one’s anger
out on an innocent person)?
Psychoanalytic theory also suggests that the content of children’s
thought is more wide ranging than recent research would indicate.
Freud would point out that children do not think only about quantity,
spatial relationships, justice, objects, and causality. They also try to
understand, and mentally adjust to, the violence on television or in their
home, love, bullying, their parents’ physical and emotional relationship,
their own sexual or aggressive feelings, the tendency of adults to say one
thing and do the opposite, frustration when their needs are not met, and
failure in social interactions. Adding this content to the logical, rational,
linear thinking studied by Piagetian and information- processing theorists
(see Chapter 7) would give a more balanced view of children’s thinking.
This suggested new direction for research on cognitive development
is particularly promising because it is compatible with current interest
in social cognition, especially children’s theory of mind (understanding of
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126 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
people’s mental states). Such research seldom addresses the problematic
or troublesome content of thought just described. A child’s theory of
mind would influence his understanding of the psychological defenses
used by others as well as himself, desires, the nature of dreams, and the
distinction between fantasy and reality.
Weaknesses
Freud made it difficult for anyone to criticize his theory: “No one has a
right to join in a discussion of psycho- analysis who has not had particu-
lar experiences which can only be obtained by being analyzed oneself ”
(1933/1964a, p. 69). Nevertheless, we now critically look at two weak-
nesses of the theory: uncertain testability of central claims concerning
development and overemphasis on childhood sexuality.
Uncertain Testability of Central Claims Concerning Development ▶
The scientific community requires that theories be based on empirical
observations that can be replicated by other scientists. Freud’s method-
ology makes this type of data gathering nearly impossible. His methods
of free association and dream analysis pose three major difficulties:
1. According to Freud, these methods require that the experimenter be
trained in psychoanalysis. Because such training is a long, expensive pro-
cess, few people would be qualified to test the theory. Furthermore, those
who are psychoanalytically trained tend to be “believers.” An involved,
possibly biased participant– observer, who selectively records the patient’s
responses, is a dubious source of objective data for testing the theory.
2. Freud’s methods lend themselves to experimenter error. Freud made notes
about the psychoanalytic sessions after they occurred, often hours later. It
is ironic that someone who demonstrated the distortions of memory in
his patients should be so oblivious to that possibility in himself. There is a
danger that he selectively remembered only that which fit into his theory.
Another source of experimenter error is the possibility that the patient’s
line of thought is influenced by the nature of the therapist’s questions or
even the timing of his grunts and silences.
3. Adults’ recollections of childhood and recent dreams are unlikely to be
completely accurate. Introspection has a poor reputation in psychology. It
is not easy to report objectively even one’s current mental state or recent
dream states; mental states from 50 years earlier pose even more difficul-
ties. Freud himself knew that these verbal reports were not reliable, but
he felt that the patient’s experience of the earlier events, whether accurate
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Evaluation of the Theory ▶ 127
or distorted, is what was most relevant to therapy. Still, the fact that ther-
apists usually cannot know whether the reports are accurate limits their
assessment of the patient’s perception of reality.
The problem of definition also poses a challenge to experimental
psychologists. There are many vague, imprecise, poorly defined terms
because Freud used analogies to communicate the meaning of the terms.
Also, many of Freud’s notions have an uncertain relationship to observ-
able behavior, in part because of the considerable distance between the
two. A therapist takes verbal reports, nonverbal behavior (for example,
facial expressions, crying, and physical accidents), dreams, and forget-
ting and interprets them in terms of distant theoretical concepts, such as
defense mechanisms, drives, and unconscious motivation. For example,
Freud made a large jump from a patient’s dream about an oven to the
interpretation that this image represents the uterus.
One way to state the problem with Freud’s methods is that in Freud’s
system, a psychological attribute can refer to several different behaviors.
An “anal personality” can be expressed in either a compulsively neat or
an overly messy person. Or a patient’s problem can be diagnosed as an
Oedipus complex if he either talks constantly about his mother or never
mentions her (due to repression). Conversely, a particular behavior can
stem from several different psychological attributes, as when an inability
to eat can stem from hysteria (perhaps caused by a fear of seeming to be
pregnant) or paranoia (perhaps a fear of being poisoned). It is unclear
how one would “test” these notions.
There have been numerous attempts to test Freud’s theory either
clinically, often with hypnosis or projective tests in which the subject
must interpret inkblots or pictures, or experimentally (e.g., Fisher &
Greenberg, 1996). However, the procedures may not adequately test the
theory. For example, exposing a boy briefly to an aggressive, hostile male
adult and subsequently observing how much the boy imitates the male’s
behavior is not a fair test of the notion that the Oedipus complex leads to
identification with the aggressor. The long- term, emotionally powerful
experiences of real life cannot be translated easily into brief, simplistic,
experimental episodes. In short, psychologists are in a bind:They cannot
adequately test the most crucial theoretical notions outside the psycho-
analytic session, but the psychoanalytic session does not lend itself to
experimental procedures.
Even if the theory cannot be tested scientifically, it can serve as a
springboard for more limited, testable hypotheses. For example, in
the 1950s, learning theorists took Freudian notions such as sex typing,
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128 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
dependency, identification, and defense mechanisms and studied their
development within a learning framework (see Chapter 6). Also, hypno-
sis has been used to test hypotheses concerning the unconscious. Reyher
(1967) provides an example. Hypnotized college students were told a
story designed to arouse unconscious Oedipal feelings. They were told
they would not remember anything about the story after awakening but
would have strong sexual feelings when certain words were mentioned
after they awakened. As predicted, the critical words, but not neutral
words, aroused sweating, trembling, and guilt, indicating unconscious
conflicts.
Freud’s notion of the scientific approach differed from that of the sci-
entific community. He looked for converging evidence for a particular
interpretation. If dream reports, memories from childhood, physical
symptoms, slips of the tongue, and accidents all suggested that the
patient had not resolved her feelings of sibling rivalry in childhood, then
Freud believed he had proved his case. He integrated facts from several
sources to form a consistent picture. He felt that his interpretations
were further bolstered if several patients illustrated the same relation-
ship between variables. For example, patients with paralysis of a limb
(hysteria) often reported unresolved sexual conflicts from childhood.
The lack of experimental rigor was not of great concern to Freud. His
goal, after all, was to provide clinical insights that would help him for-
mulate a theory that would improve therapy.
Overemphasis on Childhood Sexuality ▶ Freud’s emphasis on sex-
uality brings to mind the greeting card that begins, “ SEX— Now that I
have your attention . . .” Not surprisingly, claims about childhood sex-
uality both captured the attention of psychologists and the public and
alienated many. Freud’s answer to those who saw little evidence that
sexuality pervades childhood was that his critics were repressing their
own strong sexual memories from childhood!
For most developmental psychologists, claims about infantile sexu-
ality in normal children strain the theory’s credibility. The bulk of the
developmental research of the last 50 years portrays infants and chil-
dren as curious, self- motivated, social creatures who seek stimulation
and relationships, rather than driven, anxiety- ridden beings who seek
the reduction of tension. Research on infants’ surprisingly sophisticated
concepts, described in Chapter 2, shows that even a young infant is much
more than id.
Freud’s theory demonstrates the mutual constraints among culture,
method, data, and theory (see Chapter 1). His data on the sexual
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Contemporary Research ▶ 129
fantasies of neurotic middle- and upper- class adults during the sexually
repressive Victorian era may have little generality to children developing
today. Furthermore, the specific claims about sexuality may reflect the
biases of a male- oriented society. Years ago, Horney (1967) suggested
that one could find as much evidence for womb envy in boys, due to their
inability to have children, as for penis envy in girls. Still, it is possible
to reject Freud’s primary focus on sexual content without rejecting the
entire theory. Also, it is possible to recast some of Freud’s claims about
childhood sexuality in fruitful ways. For example, an influential critique
of Freud’s analysis of girls’ development has focused on gender differ-
ences in the development of relationships. Chodorow (1978) proposed
that infant boys and girls become attached to their mother but later fol-
low different developmental pathways. Boys are encouraged to separate
themselves from their mother and establish autonomy, whereas girls are
encouraged to develop further their close relationship with their mother.
Consequently, the self- concept of girls, but not boys, may be based on a
sense of relatedness that directs girls toward interpersonal relationships.
Given increased flexibility in gender roles in recent decades, this gender
difference may be much weaker now.
Contemporary Research
The most active current Freudian- inspired topic in developmental
psychology is early relationships, reflecting Freud’s emphasis on early
social experience, emotional relationships with parents, and infants’
construction of representations about significant others. A main shift in
psychoanalytic theory after Freud’s death was object relations theories
and related approaches, particularly relational theories. Object relations
refers to “enduring patterns of interpersonal functioning in intimate
relationships and the cognitive and emotional processes that mediate
those patterns” (Westen, Gabbard, & Ortigo, 2008, p. 67).
In developmental psychology, infants’ mental representation of the
parent– infant relationship is depicted, from Bowlby’s study of infants’
attachments (see Chapter 5), as internal working models (for a recent
review, see Sherman, Rice, & Cassidy, 2015). An infant constructs inter-
nal working models— a mental representation of a significant adult,
of herself, and of their interactions— as she becomes attached to her
caregivers (mothers usually are studied). This representation includes
certain assumptions and expectations about whether the parent will be
responsive to her needs and whether the infant herself is worthy of love.
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130 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
This internal working model is a cognitive framework that serves as a
template for the development of later relationships, especially peer and
romantic relationships. The model generates expectations about these
relationships and affects the person’s interpretation of others’ behav-
iors. Mental models also affect one’s self concept, as well as behaviors
directed toward others, for example, how the person reacts to the per-
ceived threat of rejection. These ways of relating to others then confirm
and thus perpetuate children’s expectations about self and others. That
is, people make decisions that are consistent with working models,
which in turn solidify these models. In this way, disturbed relationships
can lead to disturbed working models and thus to psychopathology, as
when expectations of rejection and abuse from others may lead to with-
drawal and depression.
Working models also spill over later into parents’ relationships with
their children. For example, pregnant women’s reports of the security
or insecurity of their childhood attachment to their mother are related
to the types of attachment relations they then form with their own
infants (Steele, Steele, & Fonagy, 1996). For instance, some mothers
respond more sensitively to their infants than do others. A mother’s
mode of communication then biases her child’s development of working
models (Bretherton & Munholland, 1999), and the cycle continues. In
this way, secure or insecure relationships are transmitted from one gen-
eration to the next. Clearly, the infant and preschool years are a critical
time for the development of working models that are the foundation for
social relationships throughout the lifetime. This work is consistent with
Freud’s claim that stable personality patterns begin to develop during
early childhood and continue into adulthood. Of course these patterns
can change somewhat during adulthood, due to social experiences.
Recent theoretical work that attempts to bring together contempo-
rary attachment theory and psychoanalytic approaches emphasizes the
importance of the mother’s and infant’s awareness of each other’s men-
tal states, especially intentionality, in developing a secure and trusting
relationship (Fonagy & Campbell, 2015). Children need to experience
their mothers as accurately reflecting their emotional state. When a
mother who is sensitive to the child’s mental states mirrors the child’s
anxiety, this experience helps the child represent, organize, and under-
stand his experience and his emotion. In contrast, a mother’s inappro-
priate, confusing reactions to the infant’s behavior may, over time, lead
to child psychopathology. More generally, it is essential to develop an
information- processing system capable of representing experience and
controlling one’s cognition, and thus regulating the self.
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Contemporary Research ▶ 131
Neuroimaging research has explicitly tied evidence of infants’
implicit, unconscious processing of emotions in the right brain hemi-
sphere to psychoanalytic theory (Schore, 2014). Healthy mother– infant
attachment, developed through well- regulated emotional interactions,
appears to facilitate the development of infants’ processing of emotional
information in the mother’s voice, face, and touch. This developed cir-
cuitry in turn supports further social interaction and infants’ emotional
self- regulation, including coping with stressors. Insecure attachments
may make babies vulnerable to psychopathology. According to this
“neuropsychoanalysis,” the attachment relationship is a major organizer
of brain development; it promotes the development and maintenance
of neural networks in the right hemisphere. More generally, one of the
hottest areas of current developmental research is on developmental
social (or affective) cognitive neuroscience (see Chapter 5). Topics such
as the processing of emotional information and the often unconscious
role of emotions in cognitive processing now can be examined in terms
of neural pathways.
Another active area of research examines, more generally, the effects
of early social experience on later outcomes, especially psychopatho-
logical ones, a central concept in Freud’s theory. Recent research on the
effects of early social and emotional experiences on later development
has profited from methodological and statistical breakthroughs that
have generated powerful predictive models (e.g., Fraley, Roisman, &
Haltigan, 2013). Applying these models to longitudinal data provides
more precise predictions from early to later development. These tech-
niques identify direct pathways, as when early disordered parent– child
relations directly predict later psychopathology, and indirect pathways
as when this relation is mediated by another factor. The main current
challenge is to identify these mediators, and thus the developmental
mechanisms by which early experience is somehow carried forward to
later childhood or adulthood. Chapter 5 will address possible biological
mechanisms by which early chronic stress or trauma is translated into
negative physiological changes and even changes in gene expression,
resulting in poor health or psychological outcomes. That is, children
carry this early experience throughout childhood through their bodies.
Alternatively, early cognitive change may mediate the later outcomes.
Early trauma can cause children to expect uncertainty and danger, thus
heightening their attention to potential threats. For example, early mal-
treatment may cause biased attention to angry faces and resulting intense
negative affect, which in turn may contribute to aggression problems
(Shackman & Pollak, 2014).
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132 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
Still another main Freudian- inspired area of contemporary research is
renewed interest in the distinction between conscious and unconscious
processes. It appears that consciousness plays a much smaller role than
cognitive psychologists have believed. Much of the brain’s work occurs
at the unconscious level (Morsella, Godwin, Jantz, Krieger, & Gazzaley,
in press). Consciousness is “just a bit player” (Kluger, 2015) that might,
for example, initiate a motor behavior after all the hard unconscious pro-
cessing work is done. Another example is implicit memory, which refers
to memory without awareness. For instance, people remember how to
ride a bicycle or play the piano without consciously thinking about it or
verbalizing it. Recently, connectionist models of thinking in cognitive
science (see Chapter 7) posit that we construct concepts as we detect,
without our awareness, regularities in objects and events, such as extract-
ing what is common across many dogs to form the concept of “dog.”
ERIKSON
Powerful theories spawn “neo’s”: neo- Piagetians, neo- Freudians, neo-
behaviorists, and so on. Freud’s theory, despite its limitations, inspired
a diverse group of brilliant and creative theoreticians, researchers, and
therapists. They stretched, patched, and rearranged Freud’s vision in two
main ways that had consequences for developmental psychology.
First, several neo- Freudians, especially Hartmann (1958), stressed the
development of conflict- free ego functions, such as perception, memory,
and logical thought. Whereas Freud’s ego defends and inhibits, the neo-
Freudian’s ego integrates and organizes personality. The emphasis on the
ego’s cognitive processes as a way of adapting to reality can be found in
works by Rapaport (1960), Gill (1959), and Klein (1970). Furthermore,
White (1963) identified such ego satisfactions as exploration and com-
petence at performing tasks well. These satisfactions are independent of
satisfactions of the id. It is clear that psychoanalytic theory can address
normal, as much as abnormal, behavior. (See Palombo, Bendicsen, &
Koch, 2009, for an account of psychoanalytic approaches since Freud.)
Second, many neo- Freudians moved away from Freud’s emphasis
on biology and emotional disorders, and considered the vast influence
of society on normal development, including the importance of social
relationships. The trends toward ego and social– cultural influences came
to developmental psychology largely through the work of Erik Erikson,
and we now look at his contributions.
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General Orientation to the Theory ▶ 133
Biographical Sketch
Erik Erikson was born in 1902 in Germany. His wanderlust and desire
to be an artist drew him away from formal schooling. After several years
of drifting, studying art, and painting children’s portraits, Erikson was
hired to teach art and other subjects to children of Americans who had
come to Vienna for Freudian training. This accidental entry into the vig-
orous Freudian circle led to his studying at the Vienna Psychoanalytic
Institute. His own psychoanalysis, part of the usual training program,
was conducted by Anna Freud. Erikson also learned from Freud himself
and other gifted analysts.
The threat of fascism brought Erikson to the United States in 1933.
Despite his lack of a college degree, he became Boston’s first child ana-
lyst and obtained a position at the Harvard Medical School. Later he held
positions at several eminent institutions, including Yale, Berkeley, and
the Menninger Foundation. During the McCarthy era, Erikson’s (1951)
concern that California’s loyalty oath was a danger to personal and aca-
demic freedom precipitated his move back to the East Coast and to the
Austen Riggs Center in Stockbridge, Massachusetts, to Harvard, and to
several other eastern universities. He died in 1994 at age 91.
These diverse settings, from clinician’s chair to professor’s podium,
fueled an energy that spread Erikson’s interests over a remarkable
area. He studied combat crises in troubled American soldiers in World
War II, child- rearing practices among the Sioux in South Dakota and
the Yurok along the Pacific Coast, and the play of disturbed and typi-
cally developing children. He also studied the conversations of troubled
adolescents suffering identity crises and social behavior in India. These
observations molded his ideas, which he expressed in many publications,
including the well- known Childhood and Society (1963) and Identity: Youth
and Crisis (1968). He was concerned about the rapid social changes in
America and wrote about issues such as the generation gap, racial ten-
sions, juvenile delinquency, changing gender roles, and the dangers of
nuclear war. He was a gifted author whose writings have been described
as “Freud in sonnet form” (Hopkins, 1995, p. 796). It is clear that psy-
choanalysis had moved far from a doctor’s couch in Vienna.
General Orientation to the Theory
Erikson accepted the basic notions of Freudian theory: psychological
structures, the unconscious and conscious, drives, psychosexual stages,
the normal– abnormal continuum, and psychoanalytic methodology.
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134 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
However, he expanded Freud’s theory by constructing a set of eight
psychosocial stages covering the life span, by studying the development
of identity, and by developing methods that reach beyond the structured
psychoanalytic setting used with adults. A look at these three contribu-
tions serves as an orientation to the theory. He has been described as
“a moralist, artist, and intellectual trying to deal with a culture that has
begun to lose its power as an instrument for fulfilling the potential and
the aspirations of those who live within it” (Bruner, 1987, p. 8).
Psychosocial Stages
Erikson’s work in various cultures convinced him of the need to add
a life- span psychosocial dimension to Freud’s theory of psychosexual
development. In Table 3.1, columns A to D describe several aspects of
Erikson’s theory, and column E names the Freudian psychosexual stage
corresponding to each of Erikson’s psychosocial stages. The difference
between psychosexual and psychosocial components can be seen in
Erikson’s (1959, p. 115) contrast of a toddler’s oral pleasure when mak-
ing speech sounds (psychosexual component) with the role of speech
communication in shaping his relationship with his parents and signifi-
cant others (psychosocial component).
In the psychosocial view, physical maturation has personal and social
repercussions. Maturation brings a new skill that opens up new possibili-
ties for a child but also increases society’s demands on him, for example,
pressure to talk instead of cry when he wants something. There is a “fit”
between children and their culture. Societies have evolved agreed- upon
ways of meeting children’s new needs in each step of their maturation.
These include parental care, schools, social organizations, occupations, a
set of values, and so on. Erikson spoke of a “cogwheeling” of life cycles,
as when adults’ needs to become caretakers coincide with children’s
needs for caretaking. In other words, each child is a life cycle in a “com-
munity of life cycles” (Erikson, 1959, p. 121). A child is surrounded by
others who are also passing through various stages. While the culture,
over many generations, has adapted itself to the needs of children, each
child in turn adapts himself to the culture, as when a new kindergartner
adjusts to a bewildering new set of experiences called “school.”
Psychosocial development is culturally embedded in two ways. First,
although children in all cultures go through the same sequence of stages,
each culture has its own idiosyncratic way of directing and enhancing
a child’s behavior at each age. For example, Erikson observed that the
Sioux allowed nursing for several years in the spirit of overall generosity
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General Orientation to the Theory ▶ 135
that pervaded the Sioux value system. They also thumped the teething
male babies on the head for biting the mother’s nipples in the belief that
their crying rage would turn them into good hunters, and they trained
their girls to be bashful and afraid of men in preparation for serving their
hunter- husbands. Second, cultures change over time. Institutions that
meet the needs of one generation may prove inadequate for the next.
Industrialization, urbanization, immigration, the Depression, and the
civil rights movement brought changes in what children needed to be
taught in order to develop a healthy personality at their time in history.
Psychosocial development proceeds according to the epigenetic prin-
ciple, a term derived from epi, which means “upon,” and genesis, which
means “emergence.” This principle is borrowed from fetal development:
Somewhat generalized, this principle states that anything that grows has
a ground plan, and that out of this ground plan the parts arise, each part
having its time of special ascendancy, until all parts have arisen to form
a functioning whole. At birth the baby leaves the chemical exchange of
the womb for the social exchange system of his society, where his grad-
ually increasing capacities meet the opportunities and limitations of his
culture.
(Erikson, 1968, p. 92)
Like the fetus, the personality becomes increasingly differentiated and
hierarchically organized as it unfolds in, and is shaped by, a particular
environment. As summarized in Table 3.1, this unfolding involves several
dimensions. There is movement through a set of psychosocial “crises”
or issues as the child matures, and there is an expansion of his radius of
significant relations. Other dimensions include the translation into the
child’s terms of certain elements of social order or structure and the
progression through a set of psychosocial modalities or ways of “being”
and interacting in society. Put succinctly, the child has inborn laws of
development “which create a succession of potentialities for significant
interaction with those who tend him” (Erikson, 1968, p. 52).
We now look at the general nature of the eight stages and leave a
specific description of each stage for a later section. Maturation and
society’s expectations together create eight crises, or issues, that a child
must resolve. Each issue is most evident at a particular stage in the life
cycle but appears in some form throughout development. For example,
autonomy is the dominant concern of the second year of life, but it is
prepared for in the first year and elaborated on in later stages.
Erikson described each crisis in terms of a dimension with both pos-
itive and negative outcomes possible, for example, autonomy versus
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136 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
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04_MIL_7898_ch3_095_152.indd 136 1/8/16 2:05 PM
General Orientation to the Theory ▶ 137
shame and doubt. Ideally, a child develops a favorable ratio, in which
the positive aspect dominates the negative. For instance, a person needs
to know when to trust and when to mistrust but generally should have
a trusting attitude toward life. If the childhood crises are not handled
satisfactorily, a person continues to fight his early battles later in life.
Many adults are still struggling to develop a sense of identity. Erikson
optimistically claimed that it is never too late to resolve any of the crises.
With respect to the integration of successive stages, Erikson’s theory
lies between that of Piaget, with his tight integration, and that of Freud,
with his loose integration. Each stage builds on the previous stages and
influences the form of later stages. As Erikson expressed it, “Each stage
adds something specific to all later ones, and makes a new ensemble out
of all the earlier ones” (quoted in Evans, 1967, p. 41).
Emphasis on Identity
Today you are you! That is truer than true! There is no one alive who is you- er
than you!”
— dr. seuss, Happy Birthday to You!
In contrast to Freud’s concern with how people defend themselves from
unpleasant tension, Erikson takes a more positive approach. He holds
that a main theme of life is the quest for identity. This term refers to
“a conscious sense of individual identity . . . an unconscious striving for
a continuity of personal character . . . a criterion for the silent doings
of ego synthesis . . . a maintenance of an inner solidarity with a group’s
ideals and identity” (Erikson, 1959, p. 102). Stated differently, identity
is the understanding and acceptance of both the self and one’s society.
Throughout life, we ask “Who am I?” and form a different answer in each
stage. If all goes well, at the end of each stage, a child’s sense of identity
is reconfirmed on a new level. Although the development of identity
reaches a crisis during adolescence, Erikson notes that it begins when a
baby “first recognizes his mother and first feels recognized by her, when
her voice tells him he is somebody with a name and he’s good” (quoted
in Evans, 1967, p. 35).Thus, identity is transformed from one stage to
the next, and early forms of identity influence later forms. This process
is similar to the reworking of a concept (such as causality) in each suc-
cessive stage in Piaget’s theory.
Erikson, the wandering youth and the American immigrant, had felt
marginalized in society. As a part of two cultures, he lived with the need
to establish an identity: “As an immigrant . . . I faced one of those very
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138 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
important redefinitions that a man has to make who has lost his land-
scape and his language, and with it all the ‘references’ on which his first
sensory and sensual impressions, and thus also some of his conceptual
images, were based” (quoted in Evans, 1967, p. 41). His conversations
with Huey P. Newton (Erikson, 1973) demonstrated that he was partic-
ularly sensitive to the problems that minority groups have when trying
to form an identity. He began using the term “identity crisis” to describe
the loss of identity he observed in World War II soldiers. He saw a sim-
ilar problem among troubled adolescents “who war on their society”
(Erikson, 1968, p. 17). Eventually, Erikson realized that the problem of
identity appears, though usually on a smaller scale, in all lives. He also
recognized that identity is a central problem of modern times: “If the
relation of father and son dominated the last century, then this one is
concerned with the self- made man asking himself what he is making of
himself ” (quoted in Evans, 1967, p. 41).
Expansion of Psychoanalytic Methodology
Erikson contributed to three methods for studying development:
direct observation of children, cross- cultural comparisons, and psy-
chobiography. His early experiences with children and his contact with
Anna Freud, who was developing child observations and play therapy,
immersed him in the world of both normal and disturbed children from
the beginning of his career. In moving from the clinician’s couch to the
playroom, he asserted that “we must study man in action and not just
man reflecting on reality” (quoted in Evans, 1967, p. 91).
Erikson’s writings are sprinkled with contrasts between cultures.
He was fascinated with how the solutions to the challenges of universal
stages vary from culture to culture. His forays into cultural anthropology
pointed out the limitations of classic Freudian theory, which was based
almost completely on psychologically troubled patients in turn- of- the-
century Vienna.
Some of Erikson’s most interesting writing is found in his “psychobi-
ographies.” These are analyses of the psychosocial development of well-
known people, which show how a single person can represent the central
preoccupation of a society at a particular time. Erikson believed that
Hitler’s rise illustrates the meshing of an individual’s particular needs for
identity and a nation’s need for a more positive identity (Erikson, 1963).
In Young Man Luther (1958), Erikson described a troubled youth who
defied his strict father who wished him to study law, rebelled against the
authority of the church, and followed a belief that gave him an honest sense
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Description of the Stages ▶ 139
of identity. Other historical “patients” include Maxim Gorky (1963) and
George Bernard Shaw (1968). His biography Gandhi’s Truth (1969) won a
Pulitzer Prize and the National Book Award in philosophy and religion.
Description of the Stages
Erikson divided the entire life cycle into “the eight ages of man.” Each of
the eight ages has a critical issue, a lifelong ego concern that reaches a
climax. (Table 3.1 provides an overview of each stage.)
Stage 1: Basic Trust Versus Basic Mistrust (Roughly
Birth to 1 Year)
In Table 3.1, we see that the critical issue is trust, and the main task of
infancy is to acquire a favorable ratio of trust to mistrust. If the balance
is weighted toward trust, a child has a better chance of weathering the
later crises than if it is weighted toward mistrust. Erikson defined basic
trust as “an essential trustfulness of others as well as a fundamental sense
of one’s own trustworthiness” (1968, p. 96) and the sense that “there is
some correspondence between your needs and your world” (quoted in
Evans, 1967, p. 15).
Infants with an attitude of trust can predict that their mother will feed
them when they are hungry and comfort them when they are frightened
or in pain. They will tolerate having their mother out of sight because
they are confident she will return. The mother, then, is all important,
as in Freud’s theory. Babies also develop trust in themselves from the
feeling that others accept them and from increased familiarity with their
bodily urges. This faith in themselves and their small world corresponds
to religious faith in the “cosmic order” of the universe (column C). From
the mother’s side of the interaction, there must also be trust— trust
in herself as a parent and in the meaningfulness of her caretaking role.
Erikson (1950) referred to a remark from Benjamin Spock: “To be a
good parent you have to believe in the species— somehow.”
Some mistrust is necessary at all ages in order to detect impending
danger or discomfort and to discriminate between honest and dishonest
persons. However, if mistrust wins out over trust, the child, or later
the adult, may be frustrated, withdrawn, suspicious, and lacking in self-
confidence.
The specifically oral experiences— sucking, biting, teething, and
weaning— are prototypes for the psychosocial modality of getting and
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140 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
giving (Table 3.1, column D). Babies “take in,” or “incorporate,” stimu-
lation through all the senses, much as a Piagetian child “assimilates.” By
taking from the mother and the world, babies are laying the foundation
for their later role as a giver to others.
Stage 2: Autonomy Versus Shame and Doubt (Roughly 2 to
3 Years)
Further neurological and muscular development permit walking,
talking, and the potential for anal control. As children become more
independent physically and psychologically, there are new possibilities
for personality development. At the same time, however, there are new
vulnerabilities, namely, anxiety over separation from parents, fear that
anal control may not always be possible, and loss of self- esteem when
failure does come.
A clash of wills is inevitable. Erikson referred to the “sinister forces
which are leashed and unleashed, especially in the guerrilla warfare of
unequal wills; for the child is often unequal to his own violent drives,
and parent and child unequal to each other” (1959, p. 66). Ideally, par-
ents create a supportive atmosphere in which children can develop a
sense of self- control without a loss of self- esteem.
While the positive component of this stage is autonomy, the neg-
ative components are shame and doubt: “Shame supposes that one is
completely exposed and conscious of being looked at— in a word, self-
conscious . . . ‘with one’s pants down.’ Shame is early expressed in an
impulse to bury one’s face, or to sink, right then and there, into the
ground” (Erikson, 1959, pp. 68–69). Doubt has to do with the unknown
“behind” that the child cannot see yet must try to control. Shame and
doubt about one’s self- control and independence come if basic trust was
insufficiently developed or was lost, if bowel training is too early or too
harsh, or if the child’s will is “broken” by an overcontrolling parent.
The culture, expressed through the parents, shapes and gives meaning
to the toddler’s new competencies. For example, cultures vary in how
much they pressure toward early anal control. Erikson pointed to the
machine age’s ideal of a “mechanically trained, faultlessly functioning,
and always clean, punctual, and deodorized body” (1959, p. 67). This
attitude contrasts to the lack of concern with such matters in the Sioux
culture, where children simply imitate older children in order to achieve
bowel control by the time they begin school.
The psychosocial modality is holding on versus letting go, the counter-
part to retention and elimination. This ambivalence pervades the child’s
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Description of the Stages ▶ 141
behavior and attitude. For example, toddlers often zealously hoard toys
or other objects and anxiously guard them in their hiding place but then
casually throw them out the window of a moving car or give them to a
friend. One morning a mother is late to work because her 2- year- old
adamantly insists on buttoning every single shirt button himself, while the
next morning the young Dr. Jekyll– Mr. Hyde screams with rage because
his mother has not helped him get dressed. Failure to coordinate the
opposing tendencies to hold on and let go can lead to the “anal personality”
described by Freud— overcontrolled, compulsive, messy, stingy, or rigid.
In this second stage, children encounter rules such as when they can
have bowel movements or which areas of the house they are allowed to
explore. These rules are an early hint of the “law and order” society they
will face (column C of Table 3.1). The issue here, according to Erikson,
is “whether we remain the masters of the rules by which we want to
make things more manageable (not more complicated) or whether the
rules master the ruler” (1959, pp. 72–73). In a well- functioning society,
the sense of autonomy encouraged in children is maintained throughout
their lives by that society’s economic and political structures.
Stage 3: Initiative Versus Guilt (Roughly 4 to 5 Years)
“Being firmly convinced that he is a person, the child must now find out
what kind of a person he is going to be. And here he hitches his wagon
to nothing less than a star: he wants to be like his parents, who to him
appear very powerful and very beautiful, although quite unreasonably
dangerous” (Erikson, 1959, p. 74). The theme of this stage is children’s
identification with their parents, who are perceived as big, powerful,
and intrusive. Erikson accepted the basic outline of Freud’s account of
how children achieve identification through the Oedipus complex, but
he emphasized the social components more than the sexual. As we saw
in Freud’s theory, identification brings with it a conscience and a set of
interests, attitudes, and sex- typed behaviors.
The basic psychosocial modality is “making,” namely, intrusion, taking
the initiative, forming and carrying out goals, and competing. We might
conclude, with T. S. Eliot in “The Love Song of J. Alfred Prufrock,” that
the stage- 3 child dares to disturb the universe. The child intrudes “into
other bodies by physical attack . . . into other people’s ears and minds
by aggressive talking . . . into space by vigorous locomotion . . . into the
unknown by consuming curiosity” (Erikson, 1959, p. 76). This initiative
is supported by advances in mobility, physical dexterity, language, cog-
nition, and creative imagination.
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142 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
Children settle somewhere along a dimension ranging from successful
initiative to overwhelming guilt due to an overly severe conscience that
punishes sexual fantasies and immoral thoughts or behavior. In addition
to guilt, another danger is that children may forever feel that they must
always be doing something, always competing, always “making,” in order
to have any worth as a person. For this stage the related elements of
social order are “ideal prototypes” (column C)—social roles such as
police officer, teacher, astronaut, president, and “hero.”
Stage 4: Industry Versus Inferiority (Roughly
6 Years to Puberty)
The “industrial age” begins. Children now want to enter the larger world
of knowledge and work. Their theme is “I am what I learn” (Erikson,
1959, p. 82). The great event is entry into school, where they are
exposed to the technology of their society, such as multiplication tables,
maps, and microscopes. Learning, however, occurs not only in school
but also on the street, in friends’ houses, and at home.
Successful experiences give children a sense of industry, a feeling of
competence and mastery, while failure brings a sense of inadequacy and
inferiority, a feeling that one is a good- for- nothing. Children strive to
make things well and complete what they have begun. The years spent
establishing basic trust, autonomy, and initiative were preparation for
this energetic entry into our technological society. Erikson noted that
this stage differs from the first three in that “it does not consist of a swing
from a violent inner upheaval to a new mastery” (1959, p. 88). It is a
calmer period, a time of psychosexual latency.
Stage 5: Identity and Repudiation Versus Identity Diffusion
(Adolescence)
Erikson quoted a saying that hangs in a cowboy bar in the West: “I ain’t
what I ought to be, I ain’t what I’m going to be, but I ain’t what I was”
(1959, p. 93). In an earlier section, we saw that the quest for identity is
the undercurrent running through all the stages. The trust, autonomy,
initiative, and industry of earlier stages contribute to a child’s identity.
In the fifth stage, however, this concern reaches a climax. Rapid phys-
iological changes produce a “new” body with unfamiliar sexual urges.
These changes, along with social pressure to make rational and edu-
cational decisions, force adolescents to consider a variety of roles. The
basic task for them is to integrate the various identifications they bring
from childhood into a more complete identity. Erikson emphasized that
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Description of the Stages ▶ 143
this whole (the identity) is greater than the sum of its parts (previous
identifications). This reassembled identity is appropriate for the new
needs, skills, and goals of adolescence. If adolescents cannot integrate
their identifications, roles, or selves, they face “identity diffusion.” The
personality is fragmented, lacking a core. Erikson quoted Biff in Arthur
Miller’s Death of a Salesman: “I just can’t take hold, Mom, I can’t take hold
of some kind of a life” (1959, p. 91). The problem may be exacerbated by
one’s minority- group status, uncertainty about one’s sexual orientation,
an overly strong identification with a parent, or too many occupational
roles from which to choose.
The psychosocial modality of this stage is to be oneself or not to be
oneself. Hamlet’s “to be or not to be” soliloquy voices this alienation and
role confusion (Erikson, 1968). Youths seek their true selves through
peer groups, clubs, religion, political movements, and so on. These
groups provide opportunities to try out new roles much in the way
someone might try on jackets in a store until finding one that fits. The
ideology of society, this stage’s counterpart in the social order, guides
this role playing by conveying which roles are valued by society.
Stage 6: Intimacy and Solidarity Versus Isolation (Young
Adulthood)
Only if a reasonably well- integrated identity emerges from stage 5 can
psychological intimacy with other people (or even oneself) be possible.
If a youth fears that she may lose herself in someone else, she is unable to
fuse her identity with someone else. Although young people usually form
important romantic relationships during this time, their friendships and
even their access to their own intimate feelings and thoughts also mark
this stage. These relationships, by enhancing one’s own identity, further
the growth of personality. One aspect of intimacy is the feeling of soli-
darity of “us” and the defense against “them,” the threatening “forces and
people whose essence seems dangerous to one’s own” (Erikson, 1959,
pp. 96–97). If a youth’s attempts at intimacy fail, she retreats into isola-
tion. In this case, social relationships are stereotyped, cold, and empty.
Stage 7: Generativity Versus Stagnation and Self- Absorption
(Middle Adulthood)
Generativity refers to “the interest in establishing and guiding the next
generation” (Erikson, 1959, p. 97) through child rearing or creative
or productive endeavors. Simply bearing children does not, of course,
ensure that a parent will develop a sense of generativity. Faith in the
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144 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
future, a belief in the species, and the ability to care about others seem
to be prerequisites for development in this stage. Instead of having chil-
dren, one may work to create a better world for the children of others.
Stage 7, then, provides the mechanism for the continuity of society
from generation to generation. A lack of generativity is expressed in
stagnation, self- absorption ( self- indulgence), boredom, and lack of psy-
chological growth.
Stage 8: Integrity Versus Despair (Late Adulthood)
In this final stage, people must live with what they have built over their
lifetime. Ideally, they will have achieved integrity. Integrity involves the
acceptance of the limitations of life, a sense of being a part of a larger his-
tory that includes previous generations, a sense of owning the wisdom of
the ages, and a final integration of all the previous stages. The antithesis
of integrity is despair— regret for what one has done or not done with
one’s life, fear of approaching death, and disgust with oneself.
Mechanisms of Development
The epigenetic principle describes the forces that underlie movement
through the stages. Physical maturation writes the general timetable for
development. Within these limits, one’s culture pushes, slows down,
nurtures, and destroys. In Erikson’s view, society exerts its influence
on the developing organism at many levels, ranging all the way from its
abstract ideology to a parent’s caress. Other Eriksonian mechanisms of
development come from Freud: drives, frustrations from external and
internal forces, attachment, and identification. However, Erikson made
little use of Freud’s tension- reduction equilibration process. Instead, he
viewed development as the resolution of conflict from opposing forces.
A child integrates holding on and letting go, initiative and guilt, the bio-
logical and psychological, and so on.
Erikson (1977) also elaborated on a more specific mechanism of devel-
opment: play. Play is used in a broad sense to mean the use of imagina-
tion to try out ways of mastering and adapting to the world, to express
emotions, to re- create past situations or imagine future situations, and
to develop new models of existence. Problems that cannot be solved in
reality can be solved through doll play, dramatics, sports, art, block play,
“playing house,” and so on. Play, however, is not limited to children. Play
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Posit ion on Developmental Issues ▶ 145
includes Einstein visualizing a model of time and space, an adolescent
fantasizing about entering various occupations, or a man rehearsing what
he will say to his boss the next day. Play is often ritualized and becomes
a somewhat formal, enduring, culturally agreed- upon way of interacting
with others. For example, an adolescent who is “messing around” with
his friends is acquiring culturally approved patterns for interacting with
other people. Another example is that the child care rituals of infancy
pass on “proper” ways of recognizing and greeting other people. Rituals
are mechanisms of development because they bring humans in every
stage into the cultural mainstream and provide ready- made solutions to
the problems of everyday life.
Position on Developmental Issues
Erikson’s position on the four issues is close to Freud’s but differs in
emphasis. Erikson, like Piaget, had a more optimistic view of human
nature. Children and adults not only seek to avoid pain but also actively
seek to develop a positive sense of identity. The existential human is in
a process of “becoming” throughout life. This development is primarily
qualitative because changes are stagelike, but it is also somewhat quan-
titative in that one’s identity becomes stronger and one’s convictions
solidify.
Unlike Freud’s theory, Erikson’s has elements of the contextualist
worldview. He saw a changing child in a changing world and a system of
culturally constructed contexts devoted to the socialization of children
into that culture. The nature of these settings contributes to, and affects
the resolution of, the crisis of each stage.
Like Freud, Erikson believed that nature determines the sequence
of the stages and sets limits within which nurture operates. Heredity
ensures that certain crises arise, but the environment determines how
they are resolved. Erikson, however, more than Freud, emphasized the
role of culture in nurturing and shaping development. Not only the
person’s past and present but also society’s past and present influence
the developing person. In addition, Erikson rejected Freud’s claim
that development is essentially complete after the first five years of
life. Development is a lifelong process; sometimes childhood conflicts
are not resolved satisfactorily until adulthood. Finally, for Erikson, the
essence of development is the formation of an identity that gives coher-
ence to one’s personality.
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146 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
Applications
As mentioned earlier, Erikson applied his theory to problems such
as adolescent identity crises, conflict between generations, post- war
adjustment of soldiers, race relations, and child rearing. Today, counsel-
ors continue to draw on his work on adolescence in particular to help
young people form a coherent identity and successfully make personal
and occupational decisions. Adults can facilitate their children’s develop-
ment by helping them achieve a balance between each end of the contin-
uum in each stage, such as between trust and healthy mistrust.
Evaluation of the Theory
Because Erikson’s theory is an extension of psychoanalytic theory, much
of the earlier evaluation of Freud’s theory is relevant here. Instead of
reiterating those comments, the present section focuses on the unique
strengths and weaknesses of Erikson’s theory.
Strengths
Expansion of Psychoanalytic Theory ▶ By widening the empirical
base of psychoanalytic theory, Erikson increased its credibility and appli-
cation. He added the psychosocial to the psychosexual, the cultural to
the biological, the ego identity to the ego defenses, the normal to the
abnormal, the cross- cultural to the culture- specific, child observations
to adults’ reconstructions from childhood, and adult development to
child development. The theory is remarkable in its power to integrate a
wide variety of situations. Erikson’s version of development seems well
grounded in the everyday lives of the majority of people as they struggle
to find coherence and meaning in their lives. He “looks for the hopeful
and active part of the person and for how human experience and human
potential are organized in the communal environment, within a radius
of significant social encounters” (Schlein, 1987, p. xxv). This broadened
psychoanalytic framework has been a valuable heuristic for counseling
and therapy. Erikson’s emphasis on culture and life- span development
was especially important for developmental psychology, and contrib-
uted to today’s life- span approach. However, his work stimulated little
research on the specific claims of his theory, such as the ordering of the
stages or, at a more concrete level, sex differences in children’s play.
Broad Perspective ▶ Erikson’s relevance for contemporary views of
development lies in the broad perspective he gives to children’s behavior.
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Evaluation of the Theory ▶ 147
He has been described as “perhaps one of the last great synthesizers in
the behavioral sciences” (Hopkins, 1995, p. 796). A specific behavior of
a specific child is influenced by his past history, the present situation,
and the past and present history of his own culture and even the world
society. All levels of society, from international relations to the nation’s
political structure to the interaction within the family, influence behav-
ior. Erikson’s writings conjure up the image of a system of interlocking
forces uniting the child and the universe, the distant past and the distant
future. Although many developmentalists agree with this position, with
few exceptions (see Vygotskian and sociocultural theories in Chapter 4)
they do not seriously examine these social and historical variables.
Instead, the behavior of children is typically studied in isolation.
Weaknesses
Lack of Systematicity ▶ Erikson’s theory is a loose connection of
observations, empirical generalizations, and abstract theoretical claims.
Consequently, it is difficult to state his claims in a way that can be
tested or relate his empirical findings to the more abstract levels of the
theory. As with Freud, much of the problem lies in the methodologi-
cal inadequacies, particularly the lack of controlled experimentation.
In Erikson’s case, the observations are laden with interpretations that
are difficult to evaluate. For example, in Erikson’s observation at the
beginning of this chapter, do boys build towers because of their phallic,
intrusive orientation, as Erikson claimed, or simply because they like to
knock tall things down? His psychobiographies are fascinating but are
necessarily speculative. A related problem is that the terms he selects
can be confusing. For example, “generativity” and “integrity” do not
have their usual meanings.
Lack of Specific Mechanisms of Development ▶ It became clear
in the earlier section on mechanisms of development that Erikson did
not explain in any detail how a child moves from stage to stage or even
how he resolves the crisis within a stage. He states what influences the
movement (for example, physical maturation, parents, cultural beliefs,
the extent to which earlier crises were resolved) but not specifically how
the movement comes about. By what mechanisms does an infant learn
when to trust and when to mistrust? Why does the resolution of the
initiative– guilt polarity lead to the industry– inferiority conflict rather
than to some other conflict? The validity of many of Erikson’s notions,
such as the conflict- resolution model, rests on the ability to describe in
detail the mechanisms of development.
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148 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
Contemporary Research
Unlike Piaget and Freud, Erikson emphasized development over the
entire life span, a thriving area of research today. Some contemporary
research continues to examine Eriksonian issues, such as generativity
and adult development. For example, adults who feel they have a pur-
pose in life live longer than their counterparts (Hill & Turiano, 2014).
As the number of elderly adults has increased, researchers have become
increasingly interested in this final phase of life. And as more and more
people attend college and delay marriage, parenthood, and entry into
full- time employment in industrialized societies, researchers have iden-
tified a new phase in the life span between adolescence and young adult-
hood, called emerging adulthood (Arnett, 2015a).
During this developmental phase, from the late teens through the
mid- 20s, many young people are adults in terms of age but are not yet
adults in terms of achieving financial independence, living independently
from parents, and establishing a family. Although college undergraduates
have been convenient sources of research participants for years and data
on them is the basis of most of our knowledge about many areas of psy-
chology, this now also is seen as an age group undergoing development.
They are continuing to explore their identities in work and relationships
and to develop a philosophy of life. Emerging adulthood is marked
by identity exploration, instability, focus on self, feeling in between
childhood and adulthood, and a focus on possibilities (Arnett, 2015a).
Despite the instability and uncertainty they face, emerging adults are
skilled at living with contradictory emotions. For the most part, they
are confident though cautious, and optimistic though aware of the uncer-
tainty of success.
Consistent with Erikson’s focus on culture, researchers have stud-
ied cultural variation in emerging adulthood. For example, in Europe,
identity development is focused on freedom and leisure, whereas Asian
countries tend to focus on values of family obligation (Arnett, 2015b).
The stage of emerging adulthood primarily is found in economically
developed countries, does not yet exist in developing countries, and is a
recent phenomenon in some countries. For example, in Japan few young
women could, until recent years, go against convention and stay single
for a long period of time and thus have a time of emerging adulthood
(Rosenberger, 2007). In the United States, emerging adulthood is expe-
rienced differently by youths in various racial and ethnic populations
(Syed & Mitchell, 2013). For instance, those of Latin American or Asian
(especially East Asian) backgrounds often feel torn during emerging
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Contemporary Research ▶ 149
adulthood between their sense of duty to enter the roles that their fami-
lies desire for them and their wish to explore other identities and careers
(Fuligni, 2007).
A main active area of current research is identity development
during adolescence and early adulthood (e.g., McLean & Syed, 2015).
For example, Marcia (Kroger & Marcia, 2013; Marcia, 1967, 2007)
has expanded two of Erikson’s notions, crisis and commitment: “Crisis
refers to times during adolescence when the individual seems to be
actively involved in choosing among alternative occupations and beliefs.
Commitment refers to the degree of personal investment the individ-
ual expresses in an occupation or belief ” (1967, p. 119). The presence
or absence of crisis or commitment defines four identity statuses. An
identity- diffused person, because she has experienced neither an identity
crisis nor a commitment, is easily influenced by others and may change
her beliefs often. A foreclosure person has made commitments without
experiencing an identity crisis. She unquestioningly accepts beliefs, atti-
tudes, and an occupation based on the views of others. An example is
entering a career that her parents want for her. A moratorium person is in
a state of identity crisis and is not yet able to make commitments. Thus,
she is still searching. Finally, an identity- achieved person has successfully
passed through an identity crisis and has made a set of personal commit-
ments. Young people tend to make progress through the four statuses,
but many still are not identity achieved by young adulthood (Kroger,
Martinussen, & Marcia, 2010). Much of the research examines the dif-
fering backgrounds and characteristics of adolescents and adults in the
four identity statuses. For example, achieving identity is associated with
having a secure attachment style and having achieved intimacy (Arseth,
Kroger, Martinussen, & Marcia, 2009).
Contemporary research on identity, a key Eriksonian concept,
explores diverse developmental pathways to achieving identity as a func-
tion of gender, race, ethnicity, class, sexual orientation, and nationality,
and their intersections. Achieving an integrated identity is particularly
challenging for those who hold minority status in these categories.
Immigrant youth, in particular, may face not only the usual identity
developmental task of adolescence and early adulthood, but also, like
Erikson himself, the challenges of adjusting to a new culture.
Common challenges to this adjustment include economic difficulties
and ethnic and racial stratification. Some studies find that retaining the
cultural values of one’s culture of origin is a buffer against the strains of
identity development in immigrant youth. That is, developing an ethnic
identity and not completely assimilating into dominant U.S. culture can
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150 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
protect against negative outcomes. For example, the development of
ethnic and racial identity is associated with positive psychosocial, aca-
demic, and health risk outcomes among African- American adolescents
( Rivas- Drake et al., 2014). Moreover, retaining the value of family
obligation— respecting, supporting, and caring for one’s family— is asso-
ciated with healthy psychological development in Mexican- American
adolescents (Telzer, Tsai, Gonzales, & Fuligni, 2015). Finally, the fact
that first- generation Asian- Americans endorse model minority pride
more strongly than second- generation Asian- Americans shows that the
generational status of immigrants influences how they cope with social
marginality (Mahalingam, 2006).
SUMMARY
Two of Freud’s ideas formed the backbone of developmental psychol-
ogy. First, he proposed that the first few years of life are critical because
one’s basic personality is formed during that time. Second, he believed
that personality is developed as a child copes with an invariant sequence
of conflicts. Each conflict involves a different domain: oral, anal, phallic,
and adult genital. The way that children satisfy the drives in each stage
forms the basis of their personality. Although Freud’s psychosexual focus
has little influence today in academic psychology, the notion of stages has
greatly influenced research and therapy with children. Also, his account
of attachment has stimulated current research on internal working
models and their long- term effects on development.
Using an energy model from physics, Freud described a system of
psychological energy that is distributed, transformed, and discharged
within a psychological structure. This structure consists of the id,
ego, and superego in a delicate balance. The ego considers its available
defenses, its perceptions of reality, the demands of the id for drive
reduction, and the prohibitions of the superego before deciding on a
course of action. Most of the “mind” is unconscious because knowledge
of the thoughts and wishes hidden in the id, ego, and superego would
cause unbearable anxiety.
Most of Freud’s evidence came from his patients’ free associations
concerning their childhood, dreams, and present concerns. Freud
believed that the workings of abnormal minds clarify the nature of nor-
mal personality because there is a continuum of behaviors ranging from
the abnormal to the normal.
Freud viewed humans as driven by instincts but actively trying to
cope with various internal and external conflicts. He stressed qualitative,
04_MIL_7898_ch3_095_152.indd 150 1/9/16 12:12 AM
stagelike changes in development but also included quantitative change.
Although he emphasized biological influences, especially drives, he also
recognized the role of experience, particularly social experience in the
first five years of life. The essence of development is the emergence
of psychological structures that mediate all experience and behavior.
Freud’s theory introduced new psychological phenomena to Western
culture and has the potential to broaden future research on cognitive
development by including emotion- laden thoughts and defense mech-
anisms. However, the theory has methodological inadequacies, and its
claims may not be testable. In addition, its focus on infantile sexuality has
limited its acceptance in academic psychology. Contemporary research
on attachment, effects of early experience on later outcomes, and
unconscious mental processes indicates that many of the developmental
issues raised by Freud are still relevant.
What is Freud’s heritage for developmental psychology? He began
by asking why his patients suffered and ended by giving us a new per-
spective on human development. Hall and Lindzey noted that whereas
Freud may not have been the most rigorous scientist or theorist, “he was
a patient, meticulous, penetrating observer and a tenacious, disciplined,
courageous, original thinker” (1957, p. 72).
Erikson’s psychosocial theory of development modified Freudian
theory in two important ways. First, Erikson identified important social
influences on development throughout the life span. His research in
various cultures and social settings within a culture suggests that every
society tries to deal with the biologically based changes occurring during
development. Ideally, there is a fit between a child’s needs and the soci-
ety’s needs at each point in development. In each of eight stages, there is
a psychosocial crisis in which there are two possible extreme outcomes:
(1) trust versus mistrust, (2) autonomy versus shame and doubt, (3)
initiative versus guilt, (4) industry versus inferiority, (5) identity and
repudiation versus identity diffusion, (6) intimacy and solidarity versus
isolation, (7) generativity versus stagnation and self- absorption, and (8)
integrity versus despair. Eriksonian- inspired research on identity con-
tinues today.
Erikson’s second major contribution to psychoanalytic theory is his
notion that life is a quest for identity. Thus, he focused on ego processes.
The work on both social and ego processes greatly expanded psychoana-
lytic theory and provided a broad perspective on development. However,
the theory is rather unsystematic and lacks specific mechanisms of devel-
opment. Erikson’s influence can be seen in contemporary research on
emergent adulthood and the diversity of identity development.
Summary ▶ 151
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152 ▶ FREUD’S AND ERIKSON’S PSYCHOANALYTIC THEORIES
Freud and Erikson produced different yet complementary perspec-
tives on development. A remark by Kierkegaard expresses an integration
of the two views: “Life can only be understood backwards; but it must
be lived forwards.”
SUGGESTED READINGS
This paperback is a short, lucid introduction to Freud’s theory:
Hall, C. S. (1954). A primer of Freudian psychology. New York: World.
This book describes various psychoanalytic theories of development:
Palombo, J., Bendicsen, H. K., & Koch, B. J. (2009). Guide to psycho-
analytic developmental theories. New York: Springer Science+Business
Media.
Because Freud was a talented and provocative writer, his ideas should be
explored in his own writings:
Strachey, J. (Ed. and Trans.). (1953–1966). The standard edition of
the complete psychological works of Sigmund Freud (24 vols). London:
Hogarth Press. Particularly recommended are “An Outline of Psycho-
Analysis” (Vol. 23, pp. 144–207), “New Introductory Lectures on
Psycho- Analysis” (Vol. 22, pp. 5–182), and any of the case studies.
This book provides a nice introduction to Erikson’s theory:
Stevens, R. (2008). Erik Erikson: Explorer of identity and the life cycle.
New York: Palgrave Macmillan.
Three of Erikson’s books provide readable accounts of his ideas:
Erikson, E. H. (1963). Childhood and society (2nd ed.). New York:
Norton.
Erikson, E. H. (1968). Identity: Youth and crisis. New York: Norton.
Erikson, E. H. (1982). The life cycle completed: A review. New York:
Norton.
Erikson’s psychobiographies are a source of fascinating reading, espe-
cially this Pulitzer Prize- winning one:
Erikson, E. H. (1969). Gandhi’s truth. New York: Norton.
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Vygotsky and the Sociocultural
Approach
The experimenter has removed a crayon of a needed color before the child begins
to draw. The child talks to himself: Where’s the pencil? I need a blue pencil.
Never mind, I’ll draw with the red one and wet it with water; it will
become dark and look like blue.
—Vygotsky, 1962, p. 16
Mothers and their children construct a jigsaw puzzle together.
A 2- year- old:
C: Oh. (glances at model, then looks at pieces pile) Oh, now where’s this one go? (picks
up black cargo square, looks at copy, then at pieces pile)
M: Where does it go on this other one? (child puts black cargo square back down in
pieces pile, looks at pieces pile)
M: Look at the other truck and then you can tell. (child looks at model, then glances
at pieces pile, then looks at model, then glances at pieces pile)
C: Well . . . (looks at copy, then at model) . . . I look at it. . . . Um, this other puzzle
has a black one over there. (child points to black cargo square in model)
M: Um- hm.
C: A black one . . . (looks at pieces pile)
M: So where do you want to put the black one on this puzzle? (child picks up black
cargo square from pieces pile, looks at copy)
C: Well, where do you put it there? Over there? (inserts black cargo square correctly
in copy)
M: That looks good.
—Wertsch, 1979, p. 13
A 4- year- old:
C: I’ll tell you when I need help, Mom.
—Wertsch & hickmann, 1987, p. 261
Se
rg
ey
N
iv
en
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to
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C H A P T E R 4
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154 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
D
evelopment is not just about individuals. It is also about their
surroundings, including the other people in their lives. An infant
is born with biologically based potential and tendencies but
would become a different adult in China, Uganda, and Texas. Yet,
most of the theories that have influenced developmental research in the
Western world have viewed individuals as separate from their social and
physical environments. These theories, such as Piaget’s, depict devel-
opment primarily as an individual activity. Most approaches view the
environment as simply an “influence on” an individual’s development. In
North America in particular, a democratic political philosophy, a focus
on the rights of individuals, and, historically, the romantic ideal of a
lone explorer separated from family in search of new land have directed
developmental psychologists to an isolated autonomous individual. The
environment simply facilitates or restricts development.
In contrast, a number of other social belief systems and their cor-
responding psychological theories, many of them Eastern, challenge
this view (e.g., Markus & Kitayama, 2010). Of this group, the most
influential for present- day developmental psychologists is the approach
developed by the Soviet psychologist Lev Vygotsky and, more generally,
sociocultural theorists. In the Vygotskian– sociocultural view, humans
are embedded in a sociocultural matrix and human behavior cannot be
understood independent of this ever- present matrix. As Bhaskar said,
“To think of contexts as existing in addition to or apart from practices
is like imagining smiles alongside or beside faces” (1983, p. 87)—like a
Cheshire cat in Lewis Carroll’s Alice’s Adventures in Wonderland.
Like Erikson’s theory, Vygotsky’s theory directs our attention to cul-
tures other than our own in order to more clearly see the role of culture
in development. The theory complements Piaget’s theory by looking at
how culture might account for children showing greater understanding
in some contexts than in others— the domain- specific concepts discussed
in the chapter on Piaget. The neo- Piagetians, particularly Fischer, drew
on Vygotskian theory to explain variability in development. Vygotsky
and the socioculturalists point out that a culture defines what knowledge
and skills children need in that culture and gives them tools such as lan-
guage, technology, and strategies for functioning in that culture. Thus,
the sociocultural approach balances the Piagetian (and Freudian) focus
on the individual.
Chapters 2–4 present the “Big 3” theorists in the history of devel-
opmental psychology. These theorists provide three very different
perspectives on development, which provide a foundation for the rest
of the book. Freud emphasized biological forces that mold personality,
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Biographical Sketch c 155
Vygotsky focused on cultural contributions to cognition, and Piaget
took an interactionist stance regarding biology and the environment.
The organization of this chapter is as follows: First, in true Vygotskian
style, a biographical sketch gives a cultural and historical perspective on
Vygotsky. Much of the material for this sketch came from Luria (1979),
Cole and Scribner (1978), and Wertsch (1985). Next is a general ori-
entation to sociocultural theory, followed by sections on mechanisms of
development, the theory’s position on developmental issues, applica-
tions, and strengths and weaknesses. Final sections describe the contex-
tual approach, which is closely associated with sociocultural approaches,
and contemporary research.
Biographical Sketch
Lev Semyonovich Vygotsky was born in 1896, the same year as Piaget,
into an intellectual Russian Jewish family. His large family valued stim-
ulating conversations while having tea around the samovar. By age 15,
Vygotsky was called the “little professor” because of his reputation as
a leader of student discussions (Wertsch, 1985). He often organized
debates and mock trials in which his friends took the roles of historical
figures such as Aristotle and Napoleon (Wertsch, 1985). Vygotsky was
well educated. He received a degree in law from Moscow University
but also read widely in literature, linguistics, psychology, the arts, social
science, and philosophy. He later wrote his dissertation on Shakespeare’s
Hamlet. He expressed this interest in language and literature in his
later work on cognitive development. Vygotsky taught psychology at a
teacher’s college in a provincial town in western Russia. In his work, he
encountered children with disabilities such as blindness, deafness, and
intellectual delay. As he sought ways to help these children fulfill their
potential, his theory developed.
Vygotsky’s systematic work in psychology began in 1924 when the
Russian psychologist Alexander Luria, impressed by the brilliance of
one of Vygotsky’s lectures, obtained a position for him at the Institute of
Psychology in Moscow. Luria described this event starring an unknown
young teacher from the provinces:
When Vygotsky got up to deliver his speech, he had no printed text from
which to read, not even notes. Yet he spoke fluently, never seeming to
stop and search his memory for the next idea. . . . Instead of choosing a
minor theme, as might befit a young man of twenty- eight speaking for
the first time to a gathering of the graybeards of his profession, Vygotsky
chose the difficult theme of the relation between conditioned reflexes
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156 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
and man’s conscious behavior. . . . It was clear that this man from a small
provincial town in western Russia was an intellectual force who would
have to be listened to.
(1979, pp. 38–39)
Vygotsky’s speeches continued to inspire his listeners in the following
years. Students sometimes even listened to his lectures through open
windows when the auditorium was overflowing.
Vygotsky, Luria, and Leontiev, the “troika” of the Vygotskian school
(Luria, 1979), enthusiastically constructed a new psychology based on
Marxism as part of the construction of a new socialist state following
the Russian Revolution. As Luria described it, “Our aim, overambitious
in the manner characteristic of the times, was to create a new, com-
prehensive approach to human psychological processes” (1979, p. 40).
Vygotsky’s lack of formal training in psychology was not a problem to
such a radical group! It was largely because of the great social upheaval
that Vygotsky was able to develop his theory and influence the psychol-
ogy and education of the times (Wertsch, 1985).
The work of Vygotsky and his colleagues shows the close connection
between economic/political systems and psychology. They wanted to
change citizens’ thinking from a feudal (landlords and serfs) mentality
of helplessness and alienation to a socialistic mentality of self- directed
activity and commitment to a larger social unit based on sharing, cooper-
ation, and support. In the new Soviet view, each person was responsible
for the progress of the whole society. A main goal was to eliminate the
massive illiteracy of Soviet society. In reaction to previous Russian psy-
chologists, Vygotsky and his colleagues constructed a cultural– historical
view of developmental psychology and emphasized higher mental activ-
ities such as thinking, memory, and reasoning. Vygotsky drew on Pavlov’s
work on “higher nervous activity” and was aware of European psycholo-
gists such as Piaget, Binet, and Freud. In fact, several of his publications
critiqued Piaget (e.g.,Vygotsky, 1962).
Vygotsky extended Marx and Engels’ ideas about economics and
politics to psychology in three main ways, all of which will be described
more fully later. First, he extended to human development their argu-
ment that humans transform themselves, as well as nature, through
labor and tool use. The hand creates the mind. The mode of economic
production— for example, socialist, capitalist, or feudal— determines
people’s working conditions and social interactions. These experiences
in turn shape their cognition— cognitive styles, attitudes, perception
of reality, and beliefs. Vygotsky applied to children’s development this
fascinating idea that the labor system creates the social structure, which
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Biographical Sketch c 157
in turn creates the fundamental nature of human thinking: Children’s
interactions with others and the culture’s “psychological tools,” such
as language used in these interactions, shape children’s thinking. In an
analogy with labor, children’s actions with these tools create thought.
Thus, both Piaget and Vygotsky thought that interaction with objects and
materials direct cognitive development, but Vygotsky emphasized social
interaction. Also, Vygotsky pointed out the cultural origins of physical
objects such as machines and toys.
Second, Vygotsky argued that the economic collectivist principle of
shared goods runs parallel to socially shared cognition. The adult col-
lective is responsible for sharing its knowledge with children and other
less advanced members of society in order to advance their cognitive
development. Third, Vygotsky used the Marxist principle (from Hegel)
of dialectical change— that all phenomena constantly undergo change
and move toward a synthesis of conflicting, contradictory elements.
For Vygotsky, this process constitutes development. Human thought,
like other phenomena, can be understood only by examining its his-
tory. Conflict can occur between developing psychological structures,
between a currently held concept and a new one, between children and
their environment, between nature and nurture, and so on.
Vygotsky remained interested in education, especially of those with
mental and physical disabilities and medical problems such as blindness,
aphasia, and severe intellectual disability. In fact, he undertook medical
training for several years. He established several research laboratories,
some of them dedicated to the study of children with physical or mental
problems. Vygotsky lectured widely, conducted research continually, and
published approximately 180 works on topics as diverse as intellectual
disabilities, language, deafness, play, emotions, personality, concepts,
multilingualism, memory, mathematics, perception, and attention.
Other interests included schizophrenia, negativity in adolescents, the
psychology of art, and even creativity in actors.
In the early 1930s, Vygotsky fell victim to the political strife sur-
rounding Stalin’s rule. The government accused him of being a “bour-
geois psychologist” of the ilk of Piaget and other suspect Western
psychologists. In fact, Vygotsky was viewed suspiciously for often refer-
ring to these writers. The government also criticized him for suggesting
that nonliterate minority people in the remote, nonindustrialized parts
of Russia had not yet developed the intellectual prowess of those in
more modern sections. Particularly suspect was his interest in intellec-
tual testing— a “pedagogical perversion” denounced by the Communist
Party. The party blacklisted him during the Stalinist purges, as it did many
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158 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
psychologists. From 1936 to 1956, the government banned his work,
though his writings continued to circulate underground. Vygotsky’s
influential book Thought and Language was published in Russia in 1934,
the year of his death. He died of tuberculosis at age 37 after only 10 years
of professional work in psychology— though they were 10 quite remark-
able years. Vygotsky’s early brilliance and premature death led him to
be called the “Mozart of psychology” (Toulmin, 1978). His theory “was
sketchily proposed by a young genius in a mortal race with tuberculosis,
during an intellectual revolution on foreign soil, over a half- century ago”
(Rogoff & Göncu, 1987, p. 23).
Vygotsky’s ideas continued through the work of Luria and others, par-
ticularly those in the Soviet Union who were building a “theory of activity.”
Only a few short articles by Vygotsky were available in English until a
translation of Thought and Language was published in 1962. The efforts of
several scholars, including Michael Cole, Barbara Rogoff, James Wertsch,
Jean Valsiner, and Ann Brown in the United States, made Vygotsky’s ideas
more accessible to the English- speaking world. The sociocultural approach
inspired by Vygotsky is a major current theoretical perspective, and
Vygotsky’s work continues to influence educational practices. Both the
growing racial and cultural diversity of children within the United States
and the globalization of contemporary life make it imperative that we
understand cultural contributions to development. We need Vygotsky’s
theory to help us conceptualize development in our changing world.
General Orientation to the Theory
Vygotsky and present- day sociocultural psychologists share certain
assumptions, which will be described below. However, they have dif-
ferences, mainly in emphasis. The main characteristics are the child- in-
activity- in- cultural- context as the unit of study, the zone of proximal
development, the sociocultural origins of mental functioning, the
mediation of intellectual functioning by tools provided by culture, and
sociocultural methodology.
Child- in- Activity- in- Cultural- Context as the Unit of Study
Sociocultural psychologists view a child- in- context participating in
some activity as the smallest meaningful unit of study. This may not
seem like a radical concept because psychologists often talk about social
or cultural influences. However, the sociocultural approach differs from
these other approaches in two ways. One is the view that it is a distortion
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General Orientation to the Theory c 159
to separate individuals from their sociocultural contexts. When other
approaches address social influences, they are separating person from
context and then asking how the context influences the person. Instead,
sociocultural approaches see individuals as always fused, or embedded,
in some culturally infused context. The second difference is the focus on
activity. People do something in some setting for some purpose, and this
is how children are socialized into the culture— through daily activities
with other people in the culture. Both of these ideas are illustrated in the
following exchange between a mother and her 24- month- old:
M: Did you like the apartment at the beach?
C: Yeah. And I have fun in the, in the, in the water.
M: You had fun in the water?
C: Yeah. I come to the ocean.
M: You went to the ocean?
C: Yeah.
M: Did you play in the ocean?
C: And my sandals off.
M: You took your sandals off?
C: And my jamas off.
M: And your jamas off. And what did you wear to the beach?
C: I wear hot cocoa shirt.
M: Oh, your cocoa shirt, yeah. And your bathing suit?
C: Yeah. And my cocoa shirt.
M: Yeah. Did we walk to the beach?
C: Yeah.
(Hudson, 1990, pp. 181–182)
A theorist, such as Piaget, focused on an individual, would ask what the
child knows and how well she remembers, and perhaps how the mother
influences her thinking. However, this is somewhat a distortion of the
event, because the dyad together is carrying out the process of remember-
ing. It is hard to say what knowledge or memory skills are in the child’s
head because the child’s mind extends beyond her skin: Her remem-
bering flows into her mother’s as her mother’s remembering flows into
hers. In short, there is no universal child developing in a vacuum. Rather,
the mind is inherently social: “The path from object to child and from
child to object passes through another person” (Vygotsky, 1978, p. 30).
The child, the other person, and the social context are fused in some
activity. One might say that the mind is “socially distributed” (Hutchins,
1991). This observation also illustrates that children become members
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160 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
of their culture by engaging in the activities of the culture. The mother
is conveying to the child that it is important to remember shared activ-
ities, that the child is capable of remembering more than she does at
first, that the child’s efforts at remembering are valued, and perhaps
that family vacations are important. These cultural beliefs typically are
not conveyed explicitly and directly but rather are expressed in people
playing, talking, or working together. In other words, enculturation is
not something that happens to children; it is something that children do.
Cultural practices, which occur routinely in daily life in the culture,
include sleeping arrangements, games, household work with adults,
conversation patterns, storytelling, classroom instruction, and family
mealtime. Children actively engage in these practices in order to achieve
goals— planning a birthday party, trying to convince their parents to buy
them a bicycle, attempting to remember which friend borrowed their
baseball glove, and figuring out whether they have enough money to buy
a candy bar. Social problem solving and communicating one’s feelings
and desires to others are not just “special cases” of predominantly “cold”
cognition unrelated to personal needs; they are the fabric of everyday
life and the essence of cognition.
In sum, children actively participating in culturally organized activities
try to make sense of them and the larger society. In this way, cognition
develops— as a by- product of engaging in these cultural routines. Thus,
cognition is a dynamic process of trying to understand rather than a set
of static stored knowledge. Much of development has to do with changes
in what cultural practices they can engage in and how they participate in
them. Older children can participate in some activities, such as going to
the mall with friends or playing in a band, that younger children cannot.
Cooking with a parent eventually leads to cooking alone. These changes
in participation cause, and are caused by, increased knowledge and skills.
Doing creates knowledge and knowledge makes doing possible.
Now we turn to a more explicit definition of culture. Although there
are different definitions of culture, a common one is that culture consists
of shared beliefs, values, knowledge, worldview, structured relation-
ships, skills, ways of doing things (customs), and socialization practices.
Cultures also have shared symbols, such as spoken and written language,
images, and narratives, to make sense of their experiences. All of this
is passed on to children at many levels, ranging from engagement in
societal- level institutions such as schools, to family routines such as shar-
ing stories, to interactions with another person, such as a parent. In the
United States, culture creates settings such as malls, suburbs, schools,
and movie theaters, and artifacts such as tools, computers, television,
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General Orientation to the Theory c 161
and art. The culture organizes these settings, which can be seen, for
example, in the different kinds of instructional practices in the schools of
different cultures. As children participate in these activities and settings,
they assimilate these beliefs and develop the cognitive system necessary
to support the belief system.
The various levels of cultural settings form a system in which changes
at one level affect the other levels. A recession may cause parents to lose
their jobs. This may lead to tension at home, which in turn may cause a
child to have problems at school. Such rippling effects can move in the
opposite direction as well (from developing child to culture) and bring
about social change. Thus, individuals and cultural communities mutu-
ally create each other.
Within the overall culture, ethnic subcultures or various family
structures (traditional, single parent, blended, gay) present different
contexts. For example, processes of child rearing differ among different
races, ethnicities, social classes, dual- career versus one- career families,
rural versus urban communities, single- versus two- parent families, and
so on. These aspects of culture influence (1) what children think about
and acquire skills in (for example, academics, sports, weaving); (2) how
children acquire information and skills (for example, explicit instruction
versus learning by observing); (3) when in development children are
allowed to participate in certain activities (for example, adult work, sex,
care of younger siblings); and (4) who is allowed to participate in certain
activities (for example, only one gender, certain social classes).
Culture also incorporates physical and historical influences. The cli-
mate, type of terrain, urban or rural setting, population density, health
care, and physical risks are intertwined with social contexts. Culture
is, to a great extent, a group’s response to its physical ecology, which
biases toward certain forms of economic activity, such as farming or
industry. These activities in turn dictate a particular social organization
and division of labor, which in turn influence child- rearing practices,
which influence children’s concepts. Vygotsky also emphasized that the
history of a culture powerfully shapes all levels of context. Wars, natural
disasters, revolutions, economic depressions, and civil rights movements
reverberate at all contextual levels. At any one point in history, a culture
is both a product of its own history and a provider of settings that shape
children’s development and, consequently, the future of the culture.
Vygotsky and his colleagues provide a striking illustration of how
socioeconomic– cultural change brings psychological change in a nat-
urally occurring experiment involving illiterate peasants working on
small farms under a feudal lord in a remote area of the Soviet Union
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162 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
(Luria, 1976). As part of the movement toward a modern socialist
state, the peasants became involved in collective farming practices that
required meetings to plan production and make other decisions. They
also learned to read and write. Among the illiterate peasants without
these new experiences, classification, concept formation, reasoning,
and problem- solving skills were concrete and practical. For example,
when told that all bears in the far north are white, the peasants would
not predict what color a particular bear there would be. A typical reply
was, “I don’t know what color the bears there are; I never saw them”
(p. 108). After even minimal schooling, the farm workers, in contrast,
could consider this logical problem in the abstract and give an answer
based on logic. It should be noted that Vygotsky may have overestimated
the concreteness of the peasants’ thinking (Cole, 1988). More recent
research in traditional societies shows that such groups do think in a log-
ical abstract manner in certain contexts. The schooling and training may
simply have taught the peasants to use their abstract thinking in contexts
in which they previously did not use it.
A main current discipline associated with the Vygotskian approach
is cultural psychology. Earlier, cultural psychologists studied culture by
comparing cultures and emphasizing differences in behavior between
cultures. In fact, the field often was called cross- cultural psychology. This
approach considered culture to be yet another independent variable that
affects individual psychology, the dependent variable. However, from
a cultural psychology perspective, this view is problematic. As noted
earlier, culture cannot be separated out and treated as an external fac-
tor; culture is everywhere, and it is a system of meaning that serves to
organize all experience. That is, culture can be studied even within a
single culture. Researchers need not only to identify cultural differences
in practices (regular, organized activities) but also to understand the
processes by which culture permeates all settings; particular cultures are
only particular cases of culture. For example, as discussed later in this
chapter, parents convey cultural values to their infants by directing their
attention to particular aspects of the setting. In the above conversation
between mother and child, culture, through the mother, organized the
child’s experience and nurtured her development. Another difference
between the cultural and cross- cultural approaches is that cross- cultural
studies tend to take a task or procedure that had been studied in one
culture to another culture in order to compare the outcomes: “When
inconsistent, they are interpreted as cultural idiosyncrasies of the non-
Western children” (Gauvain & Perez, 2015, p. 856). In contrast, cultural
psychologists tend to select a task or procedure that makes sense within
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General Orientation to the Theory c 163
whatever culture is being studied. In this way, they try to understand a
culture on its own terms.
These two approaches have attracted developmentalists because they
show that the way of developing in one’s own culture is only one of
many possible ways to develop. If Piaget surprised us by showing that
our thinking is rooted in infant motor behavior and Freud shocked us
by showing us our darker unknown side, then sociocultural approaches
challenged us by showing that culture permeates every part of our lives.
As noted earlier, the more “distant” levels of culture, such as cultural
beliefs about what kinds of skills children should acquire, often reach a child
through the immediate social situation in which a child engages in activi-
ties with a parent, sibling, or peer who encourages these skills. Vygotsky
expressed this process in his most well- known concept within developmen-
tal psychology— the zone of proximal development, our next topic.
Zone of Proximal Development
Vygotsky defined the zone of proximal (nearby) development as the
distance between a child’s “actual developmental level as determined by
independent problem solving” and the higher level of “potential devel-
opment as determined through problem solving under adult guidance
or in collaboration with more capable peers” (1978, p. 86). A more
competent person collaborates with a child to help him, through guided
practice, move from where he is now to where he can be with help.
This more advanced person accomplishes this feat by means of prompts,
clues, modeling, explanation, leading questions, discussion, joint partici-
pation, encouragement, and control of the child’s attention. As Vygotsky
explained, “learning awakens a variety of internal developmental pro-
cesses that are able to operate only when the child is interacting with
people in his environment and in cooperation with his peers” (1978,
p. 90). The more skilled adult or peer builds on the competencies the
child already has and presents activities supporting a level of competence
slightly beyond where he is now.
One example of the zone is the observation at the start of this chapter
in which a mother, helping her child construct a puzzle identical to a
completed model, directs his attention to particular puzzle pieces in the
model, points to corresponding pieces in his puzzle, and says the names
of parts of the puzzle. The mother engages in “building bridges” (Rogoff,
1990, p. 8) between the child’s present abilities and new skills. She does
this by arranging and structuring his behavior in the task. An example
from infancy is that parents draw their infants’ attention to important
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164 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
aspects of the environment by carrying them close to, or pointing to,
certain objects and events.
Evidence that guided participation through the zone of proximal
development can be more beneficial than working on one’s own comes
from Freund (1990). Children ages 3 and 5 helped a puppet move his
furniture into his new house— basically a sorting task in which dollhouse
furniture was sorted into a living room, kitchen, and so on. The experi-
menter told the children to put the objects into the rooms in which they
belonged. A child could, for example, place a sofa, chair, small table,
and lamp into one room and label it a living room. In the same way,
children formed other rooms as well. This procedure assessed how well
they could perform on their own— their current level of functioning.
Next, half of the children interacted with their mothers on easy and dif-
ficult versions of the task. The latter had more rooms and more objects.
The experimenter instructed the mothers to help their children but
not explicitly teach them. The other half of the children spent this time
working on the tasks by themselves rather than with their mothers; the
experimenter did, however, give them the correct solution at the end. In
a posttest, the children performed a similar task on their own.
The children who had worked on the problem with their mothers
performed at a more advanced level on the posttest than the children
who had practiced on their own, even though the latter had been given
the correct solution by the experimenter. Mothers acted in the way
advocated by Vygotsky for optimal movement through the zone of
proximal development. In particular, they adjusted their behavior to
the child’s cognitive level. For example, they gave more specific content
(such as “That stove goes in a kitchen”) to the 3- year- olds than to the
5- year- olds. Mothers gave the older children more general help such as
planning and keeping the goal in mind (e.g., “Let’s make the bedroom
and then the kitchen”). Mothers’ sensitivity to the 3- year- olds’ greater
potential on the easy task than the hard one led them to give these
general prompts to some extent on the easy task. Mothers tended to
talk more in the difficult version. Thus, the mothers were giving their
children as much responsibility as they thought they could handle, given
their age and the difficulty of the particular task. They tried to structure
their children’s activities so that the children could move through the
zone and gradually take on more responsibility for placing the objects.
The children also contributed to the exchange by actively attempting to
solve the problems and adjusting their behavior in response to feedback.
The zone has an emotional plane as well as an intellectual one. For
preschoolers who have trouble regulating their negative emotions
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General Orientation to the Theory c 165
(frustration and anger), focusing their attention, and controlling their
own behavior, it is especially important to engage in somewhat struc-
tured planning activities with their mothers, working together toward
some goal (Perez & Gauvain, 2009). Importantly, the better emotional
functioning in these goal- oriented collaborations was associated with
improved school performance.
Each culture has its own “cultural curriculum” (Rogoff, 1990,
p. 190). Children in various cultures learn skills valued by the culture—
weaving, hunting, sorcery, healing, reading, taking a bus, or operating
computers— by observing others and responding to their informal
instruction. For example, a nomadic tribe of magicians and other enter-
tainers in Pakistan highly values the skills of careful observation, refined
visual discrimination, sensitivity to the characteristics of other people,
and selective attention to the important aspects of a task (Berland, 1982).
When adults were tested on a conservation task, if even a single grain
of rice spilled out during the pouring or a few drops of water remained
in the transfer container, they judged that there now was less. As one
adult explained, “When there is little food and many stomachs, our eyes,
ears, and noses are more sensitive than goldsmiths’ scales” (p. 174). The
adults engage in everyday activities with children that encourage these
perceptual skills, which are relevant to their nomadic life (for example,
acute awareness of surroundings) and magic performances (for example,
control of the audience’s attention). Thus, adults provide “ user- friendly”
contexts that help children perfect skills that are needed to survive or
succeed in the culture.
Vygotsky described the relation between the actual and the potential
levels as follows:
The zone of proximal development defines those functions that have
not yet matured but are in the process of maturation, functions that will
mature tomorrow but are currently in an embryonic state. These func-
tions could be termed the “buds” or “flowers” of development rather than
the “fruits” of development. The actual developmental level characterizes
mental development retrospectively, while the zone of proximal devel-
opment characterizes mental development prospectively.
(1978, pp. 86–87)
Vygotsky and other socioculturalists believe that development can
be understood only by looking directly at the process of change, not
at a static child frozen in one developmental moment. In other words,
“It is only in movement that a body shows what it is” (Vygotsky, 1978,
p. 65). Process is more important than product (for example, correct or
incorrect answers). Socioculturalists look directly at a child’s series of
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166 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
actions and thoughts as she tries to solve a problem and, in the process,
advance her own thinking. Rather than focus on what concepts a child
“has,” they examine what a child actually does over time when involved
in an activity, typically with other people and objects.
The above descriptions of parents teaching in the zone with much ver-
bal interaction and direct instruction is typical of a European- American
dyad. The interaction may differ in other cultures, for example, indig-
enous communities of the Americas (Rogoff, 2014). In such cultures,
most of the child’s learning takes place through the child watching the
mother and other adults doing important daily activities. In Rogoff’s
(1990; 2014) extension of the notion of the zone to include guided
participation, children can learn from skilled adults or more competent
peers by engaging in everyday activities, practices, and collaborative
problem solving—“learning by observing and pitching in” (Rogoff,
2014). Learning is a natural by- product of involvement in these tasks.
Any verbal explanation occurs naturally while they are working collab-
oratively rather than as part of intentional instruction. Interactions in
the zone do not have to be verbal, especially those involving infants and
young children. Adults guide children’s participation in these activities,
helping them adapt their knowledge to a new situation and encourag-
ing them to try out their emerging new skills. Children share in the
views and values of the more expert partner, offer their own views, and
engage “in the process of stretching their concepts to find a common
ground” (p. 196).
For example, Mayan girls learn how to weave, an important skill in
that culture, by watching their mothers and other adult women weave on
a loom. By age 5, they are plaiting long leaves on a play loom fashioned
from pieces of thread they find. By age 7, they weave, with help, on real
looms, and by age 9, they weave simple items alone (Rogoff, 1990).
Rogoff uses the metaphor of apprenticeship. These cultural apprentice-
ships “provide the beginner with access to both the overt aspects of the
skill and the more hidden inner processes of thought” (p. 40). Mayan
girls not only learn how to weave, but also to plan the pattern, relate
the parts to the whole, and think about the relations between their hands
and the thread. Their behaviors resemble “those appropriate for anyone
learning in an unfamiliar culture: stay near a trusted guide, watch the
guide’s activities and get involved in the activities when possible, and
attend to any instruction the guide provides” (Rogoff, 1990, p. 17).
Learning within the zone is possible in part because of intersubjectivity—
shared understanding, based on a common focus of attention and a com-
mon goal, between a child and a more competent person. For infants
and young children, this person usually is a parent because their frequent
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General Orientation to the Theory c 167
experience together builds these shared understandings. For example, in
a laboratory classification task, a mother related the task to the kitchen
in the child’s home: “We’re going to organize things by categories. You
know, just like we don’t put the spoons in the pan drawer and all that
stuff ” (Rogoff & Gardner, 1984). It is important to note that intersubjec-
tivity not only contributes to learning from social interactions but also
results from these interactions. Each builds on, and contributes to, the
other throughout development.
Sociocultural psychologists sometimes use the metaphor of “scaffold-
ing.” Much as a temporary framework supports workers and materials
involved in work on a building, more skilled people temporarily support
a child’s emerging skills. They structure the interaction and adjust their
degree of support according to how much help the child needs. It must
be emphasized, however, that the child’s behavior affects the adult’s
behavior as much as the adult’s behavior affects the child. Children
actively contribute to their own learning in that, motivated to learn,
they “invite” the adult to participate, actively construct new knowledge,
and gradually take on more responsibility for carrying out the activity.
Thus, they “collaborate.”
Although the zone usually refers to child– adult or child– skilled- peer
interactions, Vygotsky actually had a broader definition in mind. The
zone can refer to any situation in which some activity is leading children
beyond their current level of functioning. Thus the zone can operate
during play, work, school studies, and other activities. Play supports
young children’s emerging ability to use objects in a symbolic way—
to substitute one object for another and thereby separate the object’s
meaning from the object itself. When children “ride” a stick, they sepa-
rate the stick from its usual meaning. They can think of a stick as both a
stick and a horse. Play creates a zone of proximal development for these
children for they can operate at a higher level than is possible in nonplay
activities: “In play it is as though he were a head taller than himself ”
(Vygotsky, 1978, p. 102).
The Sociocultural Origins of Individual Mental Functioning:
The Intermental Constructs the Intramental
Children are not expected just to act like others in their cultural community; they are
expected to think like them, too.
—gauVain & Perez, 2015, p. 863
What happens to children cognitively when they interact with adults?
Vygotsky’s answer is that interaction between a child and an adult or
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older child on the intermental ( between- minds) plane becomes inter-
nalized into the child’s mind, the intramental ( within- mind) plane.
External interaction becomes internal interaction. In this sense, thinking
is always social and reflects the dyad’s culture. Culture flows through
adults to children. Thinking, remembering, and attending are activities
not only of an individual; they first were carried out between individ-
uals. A mental activity “appears twice, or on two planes. . . . It appears
first between people as an intermental category, and then within the
child as an intramental category” (Vygotsky, 1960, pp. 197–198).
This movement from the intermental to the intramental is related to
the first two characteristics described in this section. First, it explains
why a child- in- activity- in- context is the smallest possible unit to study.
Intramental activity cannot be divorced from intermental activity between
children and other people, as in the vignette of the mother and child
remembering together. Second, the internalization of social processes
occurs during a child’s movement through the zone of proximal devel-
opment. Children eventually internalize the more advanced mode of
problem solving that was first supported socially. As Vygotsky expressed
it, “Children grow into the intellectual life of those around them” (1978,
p. 88). They actively internalize both social nonverbal interaction and the
language involved. In a sense, children mentally interact with themselves
as they did earlier with other people. Learning to have a conversation with
someone else leads to the ability to mentally talk to oneself when thinking
through a problem; an external dialogue becomes an internal dialogue.
In this way, children gradually take on more and more responsibility for
problem solving and become self- regulated rather than other- regulated.
Different types of settings offer different types of interpsychological
activities. Teacher– student cognitive activities may be more formal,
verbal, and objective than parent– child or older- peer– younger- peer
activities. Abstract thinking may emerge from the first, whereas intui-
tive, concrete thought may be more prevalent in the latter two. Because
children encounter a variety of settings, they incorporate a variety of
mental processes (Tulviste, 1991).
Both Vygotsky and Piaget emphasized the active internalization of
interaction between a child and the world. However, Vygotsky stressed
the internalization of patterns of social interaction and languge, whereas
Piaget was more interested in the internalization of regularities in
the child’s motoric interactions with physical objects. For Piaget, for
example, physical reversibility, such as crawling from A to B and back to
A or pouring liquid from container A to B and back to A, later becomes
the important concrete operation of mental reversibility. The process,
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General Orientation to the Theory c 169
but not the content, is similar for Vygotsky. For Vygotsky, the structure
of conversations becomes the structure of thought. Although Piaget also
recognized the influence of other people on a developing child, he did
not address the pervasive impact of culture or how a changing society
can lead to cognitive change.
Intramental processes and structures do not copy intermental ones
perfectly. Rather, intermental processes are transformed during the
internalization process. Thus internalization is active, not passive. For
example, inner speech, to be described later, is an abbreviated, personal
version of external speech. Rogoff emphasizes that children actively
constrain what they retain from social exchanges, a process that she
calls appropriation. During a shared activity a child assimilates (much as
Piaget uses the term) certain meaning but not other possible meanings.
Rogoff (1990) uses an analogy of the constant exchange of water and air
between the body and the environment. Just as bodies filter and trans-
form air and water to meet biological needs, so do our minds actively
and selectively assimilate the social activities in our “social sea” to our
current needs and abilities. The child learns something and can now
better handle another, similar situation.
A child’s selective appropriation of a new idea from a social exchange
can be seen in the following conversation between a mother (P. Miller)
and her (then) 4- year- old daughter:
M: What do you think you’d like to be when you grow up?
C: A mommy!
M: That’s nice . . . but if you want, you can be a mommy and some-
thing else.
C: I just want to be a mommy.
M: You know, I’m a mommy and a teacher— two things. You could do
that too.
C: I just want to be a mommy.
(This continues for a while until the child concedes— sort of.)
C: Okay . . . I’ll be a mommy and a bird!
The child appropriated certain meanings from this conversation and
ignored other aspects of the mother’s meaning.
Tools Provided by a Culture Mediate Intellectual Functioning
As mentioned earlier, Vygotsky and other Soviet social theorists claimed
that humans create themselves (that is, their intellectual functioning)
through activity: “Humans master themselves from the outside— through
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psychological tools” (Vygotsky, 1981, p. 141). Peers and adults assist in
this self- shaping process by helping children learn how to use their cul-
ture’s psychological and technical tools. Psychological tools include lan-
guage systems, counting systems, writing, diagrams, maps, conventional
signs, and works of art. Other examples are various strategies for learn-
ing, attending, or memorizing taught in school. Some tools that influ-
ence thinking are physical devices such as computers and robots. Tools
have ideas and skills built into them. For example, research shows that
playing video games sometimes improves cognitive functioning (Best,
2014). People use psychological tools to control thought or behavior,
just as they use technical tools such as axes, plows, and bulldozers to
control nature.
Each tool involves a different cognitive skill or style. For example,
the invention of paper influenced cognition by making the rote memo-
rization of oral texts less important; using computers for writing made
it possible to reorganize ideas in a manuscript quickly. We know little
about the effects of electronic tools on thinking: Has the Internet altered
children’s cognitive strategies for seeking information? Does the organi-
zation of websites affect children’s cognitive maps of domains of knowl-
edge? Are social networking sites changing children’s social cognition?
It has been argued that new media communication technologies are
making children and adolescents more individualistic (Manago, Guan, &
Greenfield, 2015).
These examples show that a culture’s tools connect children, through
their activities, with the physical and social world. A culture creates
these tools to help people master the environment, the favored tools are
passed on to children during social interchanges, and in turn, the tools
shape children’s minds. Children use tools to help themselves think; the
tools actually transform thought. For example, once children learn to
use language to help them remember, the nature of remembering may
change to a more verbal form.
Different cultures emphasize different kinds of tools (for example,
verbal or nonverbal), skills (reading, mathematics, or spatial memory),
and social interaction (formal schooling or informal or formal appren-
ticeships) because of different cultural needs, values, and resources.
Rogoff (1990) noted that in 1744 a group of North American Indians
politely declined an invitation from commissioners from Virginia to
send boys to William and Mary College. The Indian leaders explained
that several of their youths who had been instructed in such institutions
returned “ignorant of every means of living in the woods; unable to bear
either cold or hunger; knew neither how to build a cabin, take a deer, or
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General Orientation to the Theory c 171
kill an enemy . . . neither fit for hunters, warriors, or counselors; they
were totally good for nothing” (Drake, 1834, p. 25).
Cultures differ in the type of tools provided by schooling. A culture
that emphasizes the memorization of religious texts instills differ-
ent cognitive skills than a culture with schools stressing conceptual
understanding and scientific reasoning. The latter are intellectual skills
needed in a highly technological society relying heavily on abstract
thinking and communication through books and other symbolic media.
Language also may be more necessary for learning in industrialized
cultures because children are separated from adults and thus have
little opportunity to learn by observing and participating in adult daily
activities. In contrast, indigenous cultures may provide opportunities
for children to learn nonverbally by simply watching the adults around
them— observing their actions, direction of gaze, and facial expres-
sions (Rogoff, 2014).
Verbal tools are not even helpful for some tasks. As an example,
Australian aboriginal children of desert origin outperformed European-
Australian children at memorizing a visual array (Kearins, 1981). The
European- Australian children tried to use verbal mediational strategies,
such as rehearsing the names of the items, which were ineffective for
this type of task. The aboriginal children were more successful because
they used relevant visual strategies, developed to help them find their
way around the desert.
For Vygotsky, language is the most important psychological tool for
development. It frees us from our immediate perceptual experience and
allows us to represent the unseen, the past, and the future. Acquiring
language transforms the process of thinking. In Vygotsky’s words, “Just
as a mold gives shape to a substance, words can shape an activity into a
structure” (1978, p. 28). Language goes into the mental underground
to direct thinking, control the child’s behavior, and organize categories
of reality. Again, the intermental becomes intramental. When children
use language, they are using a system of meanings constructed by their
culture. In this way, they use the lens of their culture to make sense of
their experiences.
Language also transforms the way children use technical tools. It reor-
ganizes and controls their behavior with these objects, thus permitting
new forms of problem solving. For example, Vygotsky (1978) described
Levina’s observations of children trying to obtain a piece of candy out of
reach in a cupboard. Preschoolers typically first tried to get the candy
silently and then began to talk aloud to themselves about the problem.
Eventually, the speech became more planful and addressed, for example,
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the possible usefulness of a stool and a stick. Vygotsky concluded:
“Children not only speak about what they are doing; their speech and
action are part of one and the same complex psychological function,
directed toward the solution of the problem at hand. . . . Children solve
practical tasks with the help of their speech, as well as their eyes and
hands” (pp. 25–26). Language is a tool and works in conjunction with
other tools.
Vygotsky thought the route toward using language as a cognitive tool
is as follows: Speech and thought at first are independent. Babbling and
other such sounds are speech without thought. Infants’ sensorimotor
thinking, from Piaget’s work, is thought without speech. Vygotsky felt
that speech and thought begin to merge at around age 2. At that time,
“the knot is tied for the problem of thought and language” (Vygotsky,
1962, p. 43). Children learn that objects have names, and thus they use
words as symbols. Next, at about age 3, after children learn to talk,
speech between people splits into communicative speech to others
and private speech (sometimes called “egocentric speech” or “speech for
self ”). In private speech, children talk aloud to themselves in a running
dialogue but use this speech to guide their thinking, to think through a
problem and plan their actions. An example mentioned earlier is chil-
dren talking to themselves while trying to obtain out- of- reach candy. By
approximately age 7, private speech becomes inner speech. Children now
can silently “think in words,” though inner speech is more abbreviated,
idiosyncratic, and fragmented than spoken language. Just as children
earlier used language only to influence others, they later use it in private
and inner speech to influence themselves. In this way, internalized lan-
guage reflects its social origins: “When children find that they are unable
to solve a problem . . . instead of appealing to the adult, children appeal
to themselves” (Vygotsky, 1978, p. 27). The intermental becomes the
intramental; interpersonal communication is internalized into intraper-
sonal communication.
Note that in form (auditory spoken), private speech is like speech
between people. However, in function it is like inner speech because
both serve to direct thinking and behavior. Private speech is spoken
because children do not yet fully differentiate speech for others (com-
municative speech) and speech for self. As evidence, Vygotsky observed
that children produced less private speech in situations in which com-
munication with others was impossible or difficult (a noisy room, a deaf
or foreign- speaking peer, no one present) or undesirable (a stranger
present). When children differentiate speech for others and speech for
self, private speech becomes inner speech.
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General Orientation to the Theory c 173
Vygotsky found that private speech increased when he made the task
more difficult so that children could not solve it with other available
tools. Some of Vygotsky’s manipulations were to remove paper or a
pencil of a needed color before a child began to draw, as seen in the
protocol at the beginning of this chapter. With these impediments, pri-
vate speech nearly doubled among 5- to 7- year- olds (Luria, 1961).
Recent research on private speech ( Alderson- Day & Fernyhough, 2015;
Winsler, Fernyhough, & Montero, 2009) generally supports Vygotsky’s
predictions that such speech first increases during development and then
decreases (as it becomes inner speech), and is much more prevalent
when solving difficult tasks. This research also reveals, more specifically,
how private and inner speech facilitate executive control of thought,
by aiding working memory, shifting from one way of thinking about a
problem to another, and inhibiting behaviors that interfere with task
performance. Moreover, on some difficult tasks private speech actually
continues into adolescence or even adulthood. We might expect to see
adults muttering to themselves while filling out income tax forms or
assembling a bookshelf.
Although Piaget also studied private speech, he thought it simply
reflected the child’s egocentric inability to adapt communication to the
listener. It has no cognitive use to children. In contrast, Vygotsky thought
that such speech helps children direct their problem- solving activities.
Another difference is that Piaget thought that private speech just fades
away, whereas Vygotsky thought it becomes inner speech. More gener-
ally, Piaget and Vygotsky have very different views of the relationship
between language and thought. Piaget thought that cognition is prior to,
and broader than, language. Children develop through the sensorimotor
period before acquiring language, and language is but one expression of
the emerging ability to use symbols around 18 to 24 months. In contrast,
Vygotsky felt that language and thought begin independently and then
partially merge, to the benefit of cognition.
Speech and thought never completely overlap, even in adults. There is
always some nonverbal thought, such as that involved in tying one’s shoes
or playing the piano, and some nonconceptual speech— rote verbaliza-
tions such as saying a familiar address. Even when thoughts are expressed
in words, they are never the same thing, according to Vygotsky. There
is always a hidden subtext in our speech. For example, Vygotsky (1962)
described a passage by Dostoevsky in which six drunken workmen
conduct a brief, but complex, conversation, though the only word they
speak is a single profane word. Depending on the way it was spoken, it
indicated contempt, doubt, anger, delight, and so on. The developmental
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174 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
implication is that language acquisition is more than learning language
structure and word meanings; it also requires that the child understand
intonations of speech and the dynamics of social contexts and infer the
mental state (e.g., belief or emotion) of the speaker. Vygotsky was years
ahead of his time in this very contemporary- sounding view of language
pragmatics and understanding mental states (theory of mind).
Methodology
For Vygotsky, methods must capture the dynamic nature of develop-
ment and social interaction. He favored a dynamic assessment of children’s
potential developmental levels rather than only a static assessment of
their actual levels. He felt that what children can do with the assistance
of others (the zone of proximal development) is a better reflection of
their intellectual ability than what they can do alone. A child “is” what
he “can be.” A dynamic assessment directly measures children’s readiness
or potential for learning rather than the products of previous learning.
Standardized intelligence tests assess the latter.
One can assess the zone of proximal development in several ways. For
example, an adult might provide an increasingly specific series of clues
and determine how many are needed for a child to solve the problem.
Using this approach, Ferrara, Brown, and Campione (1986) asked chil-
dren to pretend they were a spy who wanted to send a message in a secret
code. To figure out the code, they had to find the pattern in a series of
letters and add the next four letters, for example, “NGOHPIQJ _ _ _ _.”
The first clue was “Is this problem like any other you’ve seen before?” A
later clue was “Point to the N and O in the alphabet . . . and to the G and
H . . . . Does that help at all?”
Vygotsky’s studies of the zone illustrate his more general method of
studying development by looking at change during one or several exper-
imental sessions. This is called the microgenetic method, which also is used
in contemporary research on cognitive development (see Chapter 7).
The researcher studies the process of problem solving and tries to cap-
ture a “developmental moment.” For example, Vygotsky set up obstacles
that disrupted routine procedures of problem solving and observed the
child’s attempts to cope with this change (see the first observation at the
beginning of this chapter). Or he provided various materials or tools
that could be used for problem solving and then observed how children
of different ages selected from, and used, these objects. Because the
task typically exceeded children’s cognitive level, they must construct a
new skill. For example, Vygotsky gave children a task with blocks (now
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General Orientation to the Theory c 175
cleverly called “Vygotsky blocks”) that could be solved on a nonsymbolic
(perceptual, e. g., color) or symbolic (conceptual, i.e., word) basis. By
observing children’s choice of blocks, response to feedback, and remarks
while thinking about the problem, Vygotsky inferred the small cognitive
advances emerging during the session as children gradually learned to
use the symbolic feature to solve the task.
Contemporary sociocultural research often uses conventional obser-
vational methods to study dyads or larger social groups, rather than a
child alone. Young children often show greater social cognition in family
contexts in their daily lives than they do when tested individually in the
laboratory. At home, they effectively use their social intelligence on what
matters most to them emotionally— their own rights, needs, and inter-
ests. For example, Dunn (1988) described a 24- month- old whose older
sister had three imaginary friends— Lilly, Allelujah, and Peepee. The
younger child taunted her sibling by announcing that she was Allelujah!
This rather advanced understanding of what would upset her sister and
the ability to pretend to have a different identity are skills that are more
advanced than those usually seen in the laboratory in children this young.
As mentioned earlier, cultural psychologists often compare children
in two or more countries or study some cultural difference within one
region. As an example of the latter, one could compare children of the
same socioeconomic level who attend school and some who do not to
clarify the effects of schooling. However, such studies must be inter-
preted carefully, because unschooled children, who appear to perform
poorly, may simply be unfamiliar with the language and procedures of
testing— the “rules of the game” of testing. Moreover, a culture’s move
to formal schooling typically is confounded with other changes, such as
a shift away from subsistence agriculture, large families, and sole use of
indigenous language. Thus, it is difficult to determine whether cognitive
change reflects schooling or other cultural changes.
Researchers also study the effects of societal changes, such as urban-
ization and globalization, on children. They may compare generations of
children over decades or several generations at a single point in time (see
the later section on social change). Finally, other sociocultural methods
include ethnographies (interpretive descriptions of a culture) and other
interpretive methods, often taken from cultural anthropology.
Researchers must be very careful when choosing the methods for
assessing abilities in cultures other than their own (for a review, see van
de Vijver, 2015). Consider how one might assess whether a person can
classify objects in an abstract way, characteristic of adults in literate soci-
eties. Cole, Gay, Glick, and Sharp (1971) reported that African Kpelle
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176 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
farmers, when asked to put together the items that go together, sorted
20 objects into functional groups (for example, knife with orange, potato
with hoe) rather than into abstract categorical groups (for example,
foods, tools). Knife and orange go together, for example, because you
cut an orange with a knife. (Such functional groupings are also typical
of young children in literate societies.) At one point, the experimenter
happened to ask how a fool would do it. The farmers immediately put
the foods together, the tools together, and so on, as adults in literate
societies would! It should not be concluded that people do not possess a
particular cognitive skill when they do not demonstrate it. They may be
capable of abstract thinking but simply consider other ways of thinking
to be more useful for certain everyday activities. Cultural groups differ
in cognitive functioning not so much in what processes they possess as
in which settings they use them in— which psychological tool they select
from their cognitive toolkit in a particular setting (Wertsch, 1991).
Similarly, the selection of tasks to assess a particular ability, such as
intelligence, should reflect the culture’s definition of this ability. For
instance, adults in a Ugandan village describe an intelligent person as
slow and careful, whereas westernized groups emphasize speed of think-
ing (Wober, 1972). In a number of African communities, intelligence
is defined as socially responsible intelligence— perceptive social cogni-
tion plus readiness to put this knowledge into action (Super, Harkness,
Barry, & Zeitlin, 2011). Such a person would have a sympathetic under-
standing of the world and an ability to attain social goals. Parents see this
intelligence in their children when they carry out their household chores
without being told and without supervision. Although Western parents
would value this kind of behavior in their children, it likely would be
viewed as obedience much more than intelligence.
Mechanisms of Development
Vygotsky focused on change and its mechanisms, more than on the
outcome— the child’s level of performance. For Vygotsky, development
follows a dialectical process of thesis (one idea or phenomenon), antithesis
(an opposing idea or phenomenon), and synthesis (resolution), which
produces a higher- level concept or more advanced functioning. An
example is a spontaneous, intuitive concept versus a scientific concept.
These opposing elements confront each other, intertwine, and become
transformed into a new and higher level. Thus, conflict and its resolution
play a major role in development. Vygotsky’s dialectical process often
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Posit ion on Developmental Issues c 177
occurs when children interact with adults or more advanced peers, play,
or use technological and psychological tools.
This idea that there is continual conflict punctuated by momentary
stable structures is similar to Piaget’s notion of equilibration. However,
Piaget did not include a changing society as a possible source of disequi-
librium. That is, he saw an active changing organism but a somewhat
static environment. Vygotsky, of course, assigned a major role to social
forces, such as parental guidance, teacher instruction, and language.
Another difference is that Piaget emphasized how a child works out
the conflict himself, whereas Vygotsky emphasized the collaboration of
people or ideas in this process, perhaps while moving through the zone
of proximal development.
Another mechanism of development is the internalization (or appro-
priation) process, as the intermental becomes intramental. Language
(or other cultural tools) and nonverbal learning from observing other
people’s activities contribute to the process of change. Once inner
speech and various skilled activities are acquired, they in turn stimulate
more advanced thinking.
Language also is a mechanism by which children can advance their
intersubjectivity, which permits further learning. In conversations, chil-
dren compare their own mental state with that of someone else, detect
a discrepancy, and attempt to understand that person’s mental state. This
is illustrated in the following exchange in which a young girl is trying to
understand what her mother has in mind:
C: 1, 2, 3, 4. (counting the insect’s legs)
M: 5. I think he’s having a bad day.
C: Because he’s, because he’s?
M: Because he’s missing a leg. He should have six.
(Ensor & Hughes, 2008, p. 213)
Position on Developmental Issues
Human Nature
Sociocultural theories obviously fall within the contextualist world-
view. Human nature is created in the medium of culture and thus can
be understood only in cultural context. Humans are not independent
entities that engage their environment; they are part of it— a person-
in- context. A child is an active, inherently social organism in a broad
system of interacting forces in the past, present, and future. A child’s
actions occur in the context of others’ actions. Children actively seek
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178 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
out, and respond to, a variety of social and physical contexts. These
activities in turn change children cognitively, and this subsequently
changes the nature of their future activities. Children cognitively
transform their social experiences rather than passively internalize
them. They contribute to, and select from, their participation in cul-
tural practices and thus transform the interpersonal plane into the
intrapersonal plane.
Qualitative Versus Quantitative Development
In Vygotsky’s view, development is both quantitative and qualitative, with
periods of calm alternating with periods of crisis or “turning points . . .
spasmodic and revolutionary changes” (1978, p. 73). In a dialectical
process, two elements may develop in a quantitative way, but then, as
a result of the process of synthesis, a qualitatively new form emerges.
Important examples of qualitative change are the acquisition of inner
speech, moving from an intuitive, spontaneous concept to a scientific
(logically defined) concept, and progressing from concrete perceptual to
abstract categories. During such qualitative changes, the psychological
system reorganizes itself.
Although socioculturalists typically do not posit stages of develop-
ment, they are not opposed to them. Vygotsky and his colleagues did
sketch out some possible themes for stages: affiliation (infancy), play
(early childhood), learning (middle childhood), peer activity (adoles-
cence), work (adulthood), and theorizing (old age).
Nature Versus Nurture
Although socioculturalists mainly study cultural processes, they see
nature and nurture as intertwined. Vygotsky stated that biological and
cultural forces “coincide and mingle with one another. . . . The two lines
of change interpenetrate one another and essentially form a single line
of sociobiological formation of the child’s personality” (1960, p. 47).
Thus, for socioculturalists, the question is not “how much” culture
affects development; rather, the question is, “By what process do biology
and culture co- construct development?” New information from neuro-
science and genetics (see Chapter 5) documents that the environment
(organized by culture) alters brain organization and the expression of
genes. In recent years, a new field, cultural neuroscience (Chiao, Cheon,
Pornpattananangkul, Mrazek, & Blizinsky, 2014), has been documenting
differences in brain organization, functioning, and development that
result from cultural diversity in experience.
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Applications c 179
Even biological influences are mediated by culture, as when the
impact of a newborn’s sex on subsequent development depends on the
culture’s views about gender roles. Also, cultures can vary in their reac-
tions to an infant’s temperament. In many cultures, parents prefer an
“easy” baby who is calm, attentive, and easy to care for. However, a study
of Brazilians who live a hard life in the harsh environment of the slums
found a preference for “fighters”:
I prefer a more active baby, because when they are quick and lively they
will never be at a loss of life. The worst temperament in a baby is one
that is dull and morto de esprito [lifeless], a baby so calm it just sits there
without any energy. When they grow up they’re good for nothing.
( Scheper- Hughes, 1987, p. 194)
Socioculturalists consider certain aspects of nurture as especially
important: verbal interaction and collaborative activities with others,
formal and informal learning from others, and the use of technical and
psychological tools. Vygotsky, of course, also emphasized the sociohis-
torical forces expressed in the environment, although today little atten-
tion is given to these forces. Finally, Vygotsky pointed out that people
change their environments to some extent through the use of technical
and psychological tools.
What Develops
The Vygotskian view of what develops is very broad, from cultural–
historical change to change over one’s lifetime to microgenetic moment-
to- moment change. An active- child- in- cultural- context is the unit
that develops. This unit constructs a variety of cognitive skills, most
importantly a system of meaning and its psychological tools— a cul-
turally constructed system of knowledge. Goals, values, and motiva-
tion are inseparable from cognitive activity, and thus follow a parallel
developmental course. Development has no universal ideal endpoint;
what constitutes an ideal endpoint depends on the goals of a particular
culture. This contrasts with the way Piaget privileged thinking like a
scientist. However both Vygotsky and Piaget favored higher mental func-
tions, particularly abstract concepts.
Applications
Vygotsky’s notion of the zone of proximal development has important
implications for both assessment and instruction (e.g., Wass & Golding,
2014). Assessments should measure not what children know and
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180 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
understand right now, the typical approach of such tests, but what they
can know and understand with help. Dynamic assessments often reveal
performance gains that are undetected by standard assessments. This is
especially true of “underachievers,” who do not typically work up to
their ability level. To illustrate how dynamic and traditional assessments
can lead to different conclusions, Vygotsky presented the following
example:
Imagine that we have examined two children and have determined that
the mental age of both is seven years. This means that both children solve
tasks accessible to seven- year- olds. However, when we attempt to push
these children further in carrying out the tests, there turns out to be an
essential difference between them. With the help of leading questions,
examples, and demonstrations, one of them easily solves test items taken
from two years above the child’s level of (actual) development. The other
solves test items that are only a half- year above his or her level of (actual)
development.
(1956, pp. 446–448)
These two children with the same score obviously are not the same cog-
nitively. One can proceed far with help, and thus is said to have a “wide”
zone; the other cannot and thus has a “narrow” zone.
Similarly, instruction, whether formal schooling or informal appren-
ticeships, should be based on children’s potential level (their “readiness”)
more than on their actual level. Specifically, teachers should assign the
hardest tasks that students can do with teacher assistance. They should
provide only enough assistance to ensure that students can gradually
take on more responsibility and eventually complete the task on their
own. Teaching and learning are a cooperative, collaborative enter-
prise, involving a shift from teacher- regulated activity to the student’s
self- regulation. There are recent attempts to capture these features in
computerized instruction. Such programs guide the student’s learning,
provide feedback, and pace learning activities (De Marsico, Sterbini, &
Temperini, 2013).
Teacher- student collaboration and tailoring of instruction to an indi-
vidual child’s potential is difficult to achieve in large classrooms, where
teachers often have to spend more time trying to control children’s
attention, motivation, and learning. A greater focus on teachers con-
trolling the learning process characterizes the instruction traditionally
found in Western schools— what Rogoff (2014) calls “ Assembly- Line
Instruction.”
Children also can learn through peer collaborative learning, in which
students work together and learn from each other. An increasingly
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Applications c 181
popular form of instruction thought to encourage collaborative learn-
ing is called “ problem- based learning.” A small group of students works
together to extend their current knowledge and to apply it to solving
a problem. For example, in one study with adolescents (Peace & Kuhn,
2011), a problem involved a letter from the International Institute
of Parapsychology to a physics class asking whether electromagnetic
theories can support the existence of phantoms in the Matusita House
(a Peruvian urban legend). This problem required knowledge about
electromagnetic fields and the ability to apply this knowledge to the
specific circumstances of the problem. The students together generated
solutions and provided empirical and logical support for them, thus
solidifying and extending their understanding of physics.
Vygotsky thought schooling was very important because in this way a
culture turns children’s intuitive, concrete concepts based on everyday
experience into formal abstract scientific concepts (even though they need
not have science content). In contrast, spontaneous concepts are intuitive,
concrete concepts based on everyday experience. For example “grand-
mother,” as a spontaneous concept, is defined as “She has a soft lap”
(Vygotsky, 1978, p. 50). As a scientific concept, “grandmother” is under-
stood as an abstract familial relationship that includes many different
specific people, some of whom may not have soft laps. Vygotsky thought
that scientific concepts formed one of the most powerful psycholog-
ical tools developed by modern society. Through language, children
enter into this type of thinking with their teachers and subsequently
internalize it.
However, “development in children never follows school learning the
way a shadow follows the object that casts it” (Vygotsky, 1978, p. 91).
Rather, children’s minds are “ready” to accept this overlay; abstract
thinking simply formalizes their preexisting intuitive concepts from
everyday experience. Scientific concepts handed down from above by
teachers meet children’s intuitive concepts halfway and become inter-
twined with them. Scientific concepts become more concrete, and
spontaneous concepts become more logical and abstract. Vygotsky gave
the example that when teachers introduce the abstract concept of social
class conflict, children use their concrete personal knowledge (“sponta-
neous concept”) of poor and rich people to assimilate the new concept.
As intuitive concepts are transformed into scientific concepts, they are
decontextualized— taken from the child’s concrete experience into a
context- free formal system. Children then use the scientific concepts
in a variety of contexts. This “meeting of the minds” that character-
izes the interaction between teachers and students during the process
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182 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
of acquiring scientific concepts is yet another example of both the
social nature of learning and movement through the zone of proximal
development.
Another important message from cultural research for teachers is
that in many cultures children are taught behaviors that, in a school or
testing setting, would make it appear that they do not know something.
Examples are not to talk back to a person of higher status, not to act
in a way that would draw attention to themselves, not to initiate a con-
versation, not to appear to be a fool by giving an obvious answer, and
not to produce information that the questioner might not have. Navajo
children, for example, tend to pause when they answer a question,
which gives a non- Navajo teacher the impression that they have finished
their answers. Thus, they often are interrupted before they have finished
their answers (White & Tharp, 1988). As another example, children
from traditional cultures in Belize, Nepal, Kenya, and Samoa rarely ask
“Why?” questions (Gauvain, Munroe, & Beebe, 2013), which might be
misinterpreted as a lack of intellectual curiosity.
Evaluation of the Theory
The strengths of the sociocultural approach are widely acknowledged
today. Thus, they will be described briefly, and more attention will be
paid to weaknesses, particularly limitations, with an eye toward needed
future research. The strengths are the theory’s attention to the social–
cultural context, integration of learning and development, and sensitiv-
ity to the diversity of development. Weaknesses include the vagueness of
the notion of the zone of proximal development, insufficient attention
to issues of development in the zone, difficulties of studying cultural–
historical contexts, and failure to provide a legacy of prototypic tasks
revealing interesting developmental phenomena.
Strengths
Attention to Social– Cultural Context c Vygotsky is the main devel-
opmental theorist to seriously address the broader sociohistorical con-
text of development. He wove together insights from history, sociology,
economics, political science, linguistics, biology, art, and literature
into psychology. This broader context is not simply another “influence”
on children. Rather, it defines children, their activities, and develop-
ment: Development occurs at the child– society border rather than in
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Evaluation of the Theory c 183
the individual child. This notion is very difficult for the Western mind
to assimilate. We tend to dichotomize the individual and the external
world, including society, and to situate development within the indi-
vidual. Thus, by “correcting” theories focused on individuals, Vygotsky’s
view challenges our basic assumptions about psychological development
and how to study it.
Vygotsky’s theory gives us a different perspective on major develop-
mental milestones. For example, the significance of attachment is that
it serves not only to establish a foundation for later social relationships
and to develop a sense of trust in others but also to involve infants in
shared activities with adults and the cultural practices of society. In this
way children acquire language and other cultural tools.
The theory provides a set of theoretical concepts to guide research
on developmental mechanisms underlying change: movement through
the zone of proximal development, intersubjectivity, and internaliza-
tion. The next step is to identify the specific processes involved in dynamic
interchanges between child and culture as they co- construct her devel-
opment. For example, what happens cognitively moment to moment
when a parent and a child have a conversation? Is being able to infer the
other person’s mental state— her emotions or knowledge— a cause of,
or result of, intersubjectivity and internalization? What motivates chil-
dren to move through the zone?
Integration of Learning and Development c A main theoretical
contribution is the account of the relations between development and
learning— one of the most important issues of development. Vygotsky
argued that learning drives development. As children learn (proceed
through the zone of proximal development), they achieve a higher level
of development. In turn, children’s level of development affects their
readiness to learn a new concept. This theoretical focus on change, along
with the method of dynamic assessment, makes this a truly developmen-
tal theory (but see the section on weaknesses below).
Children learn how to use materials and people in their specific cir-
cumstances to obtain goals: “Cognitive development consists of coming
to find, understand, and handle particular problems, building on the
intellectual tools inherited from previous generations and the social
resources provided by other people” (Rogoff, 1990, p. 190).
Sensitivity to Diversity of Development c Most developmental
theories focus on universal aspects of development. In contrast, socio-
cultural psychologists acknowledge both individual differences within
a culture, such as wide versus narrow zones, and differences among
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184 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
cultures. This sensitivity to diversity is quite important, because most
of the knowledge base of contemporary developmental psychology
comes from research on Western (mostly North American) children—
the “weirdest people in the world”—white, educated, industrialized,
rich, and of democratic origin (Henrich, Heine, & Norenzayan, 2010,
p. 61). Yet, this group is a small minority of the world’s children. Even
in the U.S., as of 2014 only 52 percent of children were non- Hispanic
White (Federal Interagency Forum on Child and Family Statistics,
2015), and that percentage continues to decline. For a satisfactory the-
ory of development, it is important to know which developmental find-
ings are universally true and which vary across cultures and subcultures.
Shweder et al. (2006) used the phrase “one mind, many mentalities” to
express the idea that the mind is both universal and specific to its cultural
milieu. Different historical and cultural circumstances may encourage
different developmental routes to a developmental endpoint.
Weaknesses
Vagueness of the Notion of the Zone of Proximal Development c
There are two main ambiguities or limitations of Vygotsky’s concept
of the zone (Paris & Cross, 1988). First, knowing only the width of
children’s zones (how far they can go with help) does not provide an
accurate picture of their learning ability, style of learning, and current
level of development compared to other children of the same age. For
example, children who have narrow zones may have so little inherent
learning ability that they are unable to profit from assistance. These chil-
dren may be functioning at a very low level. Or children with narrow
zones may be successful independent learners who nearly have achieved
their potential. Consequently, social assistance helps them only slightly.
Similarly, low- achieving children who have wide zones may be unable to
solve problems independently and so rely on help from adults. Or high-
achieving children may have wide zones because they have high learning
ability but, due to low motivation or lack of appropriate learning strate-
gies, rely on adults for help. Thus, having a wide zone (or a narrow zone)
can be desirable or undesirable, depending on its causes. Moreover, chil-
dren may appear to have a narrow zone simply because adults have failed
to provide appropriate instruction. In short, simply assessing children’s
zones provides a very incomplete developmental picture.
Second, the zone has problems of measurement. Although the met-
aphor of a spatial zone implies a metric of distance, there currently
is no metric for determining this “distance” (Paris & Cross, 1988).
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Evaluation of the Theory c 185
For example, one child needs help sounding out words during reading, a
second child needs help connecting ideas across sentences, while a third
only needs encouragement. Even if these children need an equal num-
ber of prompts, do they actually have equally wide zones? No common
scale exists for answering this question. Vygotsky sometimes measured
the zone in terms of age, such as when a child with an actual level of
functioning of age 6 and a potential level of functioning of age 9 has a
zone of 3 years. Yet this is a very global metric, and it cannot be assumed
that the difference of three years between ages 2 and 5 is equal to that
between ages 6 and 9.
There are still other issues about the zone notion. One, mentioned
earlier, is that the exact psychological processes involved in internaliza-
tion of the intermental to the intramental (Vygotsky) or appropriation
of a shared activity (Rogoff) remain unclear. For example, what sorts
of mental representations of social interaction do children form? Also,
we know little about the generality and stability of an individual child’s
zone. Does a child tend to have a wide zone (or a narrow zone) across
most domains? Is the size of the zone a stable individual characteristic
that is constant over the years? Is improvement resulting from the zone
long- lasting? Can it generalize to other similar situations?
Another limitation is that most of our knowledge about the zone
concerns mother– child and, to a lesser extent, peer dyads. Do father–
child, adult– infant, sibling, and multiperson units operate in the zone
in different ways? Also, not all parents are eager and competent guides,
and children reared in hostile environments may learn not to seek con-
texts with adults. Finally, we know little about the role of affect in the
zone. Children often have a preexisting emotional (positive or negative)
relationship with the people in these contexts that colors the nature of
their social interaction. A child asks her mother to show her how to ride
a bicycle because she wants to be able to engage in this activity with her
friends. Another child is asked by a disliked relative to listen to instruc-
tions on using a vacuum cleaner so that she can help clean the house. The
nature of learning in the zone will differ in these two cases.
Insufficient Attention to Developmental Issues c Although
Vygotskian theory is a quintessential developmental theory, in some
ways the approach does not really seem very developmental. As
Bronfenbrenner noticed decades ago, “In place of too much research on
development ‘out of context,’ we now have a surfeit of studies on ‘con-
text without development” (1986, p. 288). We need a more develop-
mental account of both contexts and children. Regarding contexts, we
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186 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
have little description of contexts of children of various ages or devel-
opmental levels, and how that varies, or is the same, across cultures.
A culture has different expectations for children of different ages and
thus places them in different settings. As children grow older, the culture
puts new pressures on children and grants them new social freedoms.
Society introduces older children to schooling, work responsibilities,
clubs, and organized athletic and social activities. It allows or encourages
different activities at different ages.
Similarly, children’s abilities, needs, and interests at each age influence
the nature of the settings they seek out and the effect that a particular
setting has on them. We have little idea how a child’s cognitive level both
permits and constrains processes in the zone of proximal development.
We do know, for example, that among children who cannot count by
themselves, 4- year- olds are more likely to shift to counting with their
mothers’ help than are 2- year- olds (Saxe, Guberman, & Gearhart,
1987). Profiting from hints, modeling, direct instruction, and explana-
tions requires certain developing cognitive skills such as attention, mem-
ory for action sequences, mental imagery for comparing the actions of
the self and others, verbal encoding, and inference of intentions. Which
activities are most effective for learning surely differ for children of dif-
ferent cognitive or social developmental levels. For example, modeling
may be a more effective clue than verbal explanation for 4- year- olds
because of their limited verbal comprehension. Language development
also is important in that children’s improved ability to use their own
language to regulate their behavior would facilitate moving through the
zone (Luria, 1961). Vygotsky suggested that, in addition to emerging
speech, mobility after the first few months of life dramatically changes
children’s potential for social interaction and the kinds of settings they
can enter. Thus, Vygotskian theory would be more developmental if we
knew more about the impact of developing skills on learning in the zone.
Vygotsky’s concept of intersubjectivity has been transformed into
a developmental account by Tomasello (2014; see also Chapter 5). He
emphasizes the development of shared intentionality, of being able to
understand and establish common ground in order to be able to engage
in cultural learning. The origins of this ability may lie in infancy, when
parent and infant have shared attention on some object. In one account,
during development, the main mechanism of cultural learning is imita-
tion, then instruction, then collaboration (Tomasello, Kruger, & Ratner
(1991). Children become increasingly able to take the perspective of
other people. Nine- month- olds can acquire new behaviors through
imitation because they understand that people are intentional agents.
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Evaluation of the Theory c 187
They know what goal the other person is trying to achieve through his
behavior. Around age 4, children see others as having representations of
the situation and try to reconcile it with their own. As a result, they can
benefit from instruction from others and can internalize the instructions,
which is similar to Vygotsky’s notion of internalizing dialogue. By age 6,
they can engage in collaboration with a peer at their level of competence
because they can integrate the mental perspectives of two people who
can think about each other’s thinking. With a peer they co- construct
knowledge and internalize the co- construction. In this model, inter-
subjectivity, because it permits social perspective taking, is central to
cultural learning.
The overall point here is that a child’s cognitive and physical develop-
mental level influences (1) what contexts a child enters, (2) the nature of
the social– cognitive processes involved in the dyadic interaction, (3) the
amount, speed, and type of learning in the zone, and (4) the effect of
sociohistorical events on the child. Children of different developmental
levels bring to a setting different knowledge, motives, reasoning skills,
attentional biases, metacognition, social skills, language ability, self-
concept, and so on.
Difficulties of Studying Cultural– Historical Contexts c Nearly
all developmental psychologists would agree that it is important to
examine the social, cultural, and historical contexts of development. Yet
few studies do this. Why this discrepancy between attitudes and behav-
ior? A main reason is the practical difficulty of conducting this type of
research. Observing parent– child or older peer– younger- peer dyads
in action is difficult and time consuming. Investigators must develop a
sensible classification system for coding the behaviors, use this system to
code the videotaped interactions, establish interrater reliability, and then
code all of the tapes. Cross- cultural research often requires expensive
travel, extensive learning about the other culture, careful translation
of materials, and identification of appropriate testers. And it is difficult
to interpret cultural differences in the results because they could be
caused by many differences between the cultures. It is even more diffi-
cult to study historical influences because the relevant events no longer
are occurring. Also, it is difficult to detect which of the many differing
aspects of a major historical event, for example, an economic depres-
sion, is responsible for the behavior. The links between broad historical–
cultural forces, such as class struggles, racial unrest, and marginalization
of certain groups, and specific parent– child interactions, in particular,
need to be worked out better.
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188 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
No Legacy of Prototypic Tasks Revealing Interesting Developmental
Phenomena c One reason that Piaget’s theory stimulated much pro-
ductive research by others is that he provided several tasks that revealed
interesting, even surprising, developmental phenomena. The conserva-
tion, object permanence, spatial perspective- taking, and class inclusion
tasks come to mind. These served as arenas for fruitful empirical skir-
mishes for many years. Similarly, information- processing investigators
(see Chapter 7) developed problem- solving, attention, and memory
tasks; ethology (Chapter 5) had imprinting, attachment, and peer-
dominance hierarchies; social learning (Chapter 6) had imitation para-
digms; and Gibson (Chapter 8) had the visual cliff and infant locomotor
tasks. No such prototypic tasks from sociocultural approaches have
caught the imagination of current developmentalists and stimulated an
outpouring of research. Vygotsky typically described his tasks and pro-
cedures in a very sketchy way and presented little or no data, relying
instead on general summaries. His studies were more like pilot studies,
or demonstrations used to illustrate what he saw as the basic principles
of cognition and development. Given the urgency of his mission and his
chronically poor health, he directed his energy toward opening up new
lines of research rather than fully examining any one area.
A Related Approach: Developing- Person-
In- Context
Closely associated with Vygotsky– sociocultural approaches are contextual
approaches, which emphasize the settings in which people develop (e.g.,
Lerner, 2006). Contextualism arose in reaction to the decontextualized,
reductionist (nonholistic) laboratory studies of children that dominated
the 1960s and 1970s. Like Vygotsky and the sociocultural psychologists,
contextualists insist on the situated nature of all behavior and thinking
and often study behaviors in everyday contexts. An additional contri-
bution of person- in- context approaches is that they typically describe
multiple levels of contexts in which developing children are embedded.
Contextualists also examine whether one context supports another. For
example, do parents ensure that children do the homework assigned at
school? Contextual approaches have extended their inquiry throughout
the life course and looked at the links between a changing person and a
changing world (Elder, Shanahan, & Jennings, 2015).
Another important notion in person- in- context approaches is the
goodness of fit between a child and her context. A particular school may
work well for one child but not another. A poor but talented musician is
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A Related Approach: Developing- Person- In- Context c 189
more likely to obtain the needed musical training in a culture that values
and supports its musical culture.
The discussion here will focus on one of the most influential contextual
models— Urie Bronfenbrenner’s bioecological theory (Bronfenbrenner &
Morris, 2006), earlier called ecological- systems theory. The Russian- born
Bronfenbrenner created the groundbreaking field of human ecology and
was a co- founder of Head Start. He advanced developmental psychology
by providing a coherent framework for understanding development in
context. He viewed the context of development as a set of nested struc-
tures, like nested Russian wooden dolls. Bronfenbrenner posited four
levels of contexts that influence children, ranging from the immediate
face- to- face interaction with another person, the level “closest” to the
child, to very general cultural belief systems, the level “furthest” from
the child. By including sociology, anthropology, economics, and political
science in these contexts, he built bridges between psychology and these
disciplines.
As Bronfenbrenner (1989a, pp. 226-229) described these layers:
1
A microsystem is a “pattern of activities, roles, and interpersonal rela-
tions experienced by the developing person in a given face- to- face
setting.” The setting includes (a) particular physical and material
features and (b) other people with particular temperaments, personal-
ities, and systems of belief. A child’s home, school, and peer group are
important microsystems. Transitions from one microsystem to another
can be difficult, for example from elementary school to middle school.
2
The mesosystem includes “the linkages and processes taking place
between two or more settings containing the developing person.”
For example, we might ask whether the peer group and school
system support or contradict the parents’ value system. Thus, a meso-
system is a system of microsystems.
3
The exosystem “encompasses the linkage and processes taking place
between two or more settings, at least one of which does not
ordinarily contain the developing person.” Events in this system
“influence processes within the immediate setting that does contain that
person.” An example is the relation between the home and the parent’s
workplace. A stressful work environment may increase a parent’s irrita-
bility at home, which could lead to child abuse. In this level are the major
institutions of society, such as the economic system, transportation
system, local government, and mass media. As an example of the latter,
watching television may interfere with family interaction.
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190 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
4
The macrosystem “consists of the overarching pattern of micro-,
meso- and exosystems characteristic of a given culture, subcul-
ture, or other broader social context.” Of particular importance
are the “belief systems, resources, hazards, life styles, opportunity
structures, life course options, and patterns of social interchange that
are embedded in each of these systems.” The macrosystem is a general
cultural “blueprint” that helps design the social structures and activities
occurring at lower, more concrete levels. This blueprint influences how
parents, teachers, and significant others in the child’s life “consciously
or unconsciously define the goals, risks, and ways of raising the next
generation.”
There tends to be consistency among the important settings of a par-
ticular culture. Bronfenbrenner pointed out that within a given society,
one elementary school classroom looks and operates much like every
other. The nature of the prototypic classroom reflects unstated beliefs
of the society, for example, an emphasis on individual learning versus
collaborative learning, or self- esteem versus group solidarity.
These four levels change over time, as parents and children age,
schools incorporate more testing, the economy waxes and wanes, and
the population and its belief systems become more diverse. Also, a
change in any level causes changes in the other levels. For example, in
the macrosystem the Great Depression and World War II (Elder et al.,
2015) obviously changed family structure and functioning and thus
children, through parents losing their jobs, a decline in family income,
loss of parents and siblings in the war, and the entry of women into the
labor force. As a contemporary example, the emergence of electronic
social networks has changed social interaction in the other levels. Other
examples appear in the Social Change section below; modernization
and globalization are changing the contexts of development in cultures
around the world.
Causality lies in the other direction as well. As children develop in
a particular sociohistoric time, they change the contexts at all levels.
Moreover, children to some extent select their contexts of development.
For example, personal attributes encourage or discourage reactions
from other people that facilitate or damage psychological development
(see also Bandura’s “triadic reciprocal determinism” in Chapter 6).
A fussy baby, a scowling preschooler, or a hyperactive school- age child
may discourage attention from adults. A happy, smiling baby, an affec-
tionate preschooler, or a good- natured, calm 8- year- old has the opposite
effect and thus creates a different environment for herself. She is likely
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A Related Approach: Developing- Person- In- Context c 191
to respond in kind to warm social attention, setting in motion a chain of
reciprocal exchanges that chart a course of development for her that is
rather different from that of the other kind of child.
Another way in which children shape their contexts is that they display
individual differences in their tendency to approach or avoid particular
aspects of the social and physical world. Temperamental differences are
expressed in social extroversion, shyness (avoiding social stimulation),
resistance to changes in the environment, a high activity level, and so on.
Consequently, different children seek out different types of contexts and
thus engage in somewhat different developmentally relevant activities.
One child may prefer to be a “ child- in- structured- quiet, two- person
context,” whereas another may tend to be a “ child- in- unpredictable,
loud, multiperson context.” In this way, different skills and learning
styles may develop.
Bronfenbrenner’s final accounts (e.g., Bronfenbrenner & Morris, 2006)
before his death in 2005 have an even more developmental and inter-
active flavor. In his bioecological model of a changing organism in a
changing environment, Bronfenbrenner emphasized the processes by
which child and context directly (proximally) affect each other during
frequently occurring interactions. These processes are the “engines of
development” (p. 825). The specific processes during these interactions
between child and other people or objects depends on characteristics of
the developing person (such as temperament, abilities, knowledge, and
experiences) and of the environment in which the processes are taking
place. Each child has a biological potential (the “bio” part of bioecol-
ogy), whose expression depends on the contexts of the child’s devel-
opment. Taken together, interaction among these forces leads to both
stability and change in children and in the contexts in the various levels.
Bronfenbrenner was concerned about disruptive changes taking place in
contemporary society— youth crime and violence, teenage pregnancy,
poor academic performance, dropping out of school, and drugs. Such
contexts hinder development. Recent contextualist- oriented work has
studied contexts that can promote positive youth development (e.g.,
Lerner, Lerner, Bowers, & Geldhof, 2015).
Recent contextualist approaches have taken Bronfenbrenner’s theory
one step further by even more strongly emphasizing the dynamic, inter-
active nature of development. These systems theories (see Chapter 9)
envision a complex system of two- way influences among contexts, and
between contexts and children. The various levels of organization, rang-
ing from biology to culture to history, are an integrated system, in which
everything influences everything else.
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192 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
Contemporary Research
Present- day sociocultural psychologists have focused on several research
areas with direct ties to Vygotsky: collaborative problem solving,
research across cultures, social change, immigrant families, and devel-
opment through narratives and conversations.
Collaborative Problem Solving
A central idea in Vygotskian and other cultural approaches is that chil-
dren learn through collaborative problem solving with adults or more
advanced peers. Both developmentalists and educators have been partic-
ularly interested in this form of learning because collaboration is con-
sidered a “21 st- century skill” (Dede, 2010), necessary for success today.
In contemporary research, small groups of children are usually assigned
a problem and asked to work together to find a solution.
Peer collaborations differ from parent– child ones because peers’
competencies are more equal. Also, conflict may be more frequent
than with a (typically) more patient adult. Experiences within a more
equal relationship may provide opportunities to learn how to take the
perspective of others and how to resolve conflicts. As in parent– child
collaborations, a critical element is shared understanding of what the
activity is all about. Researchers have shown cognitive advance through
peer collaborations in a variety of countries. For example, collaborative
reasoning promoted moral reasoning in Chinese and U.S. fourth- and
fifth- graders (Zhang et al., 2013).
The nature of peer collaborations may differ across cultures, even
within the U.S. For example, in one study (Budak & Chavajay, 2012),
siblings aged 6 to 12 were observed while trying to solve a problem
together— putting block connectors together to form a track for mar-
bles. The African- American siblings collaborated more than European-
American siblings, who tended to divide up the activities and direct each
other when constructing the marble track. Related results were found
in a study ( Mejía- Arauz, Rogoff, Dexter, & Najafi, 2007) in which triads
of school- age children in the U.S. were shown how to make an origami
figure by the “Origami Lady” and then were left to work together. Triads
of children from indigenous heritage regions of Mexico tended to col-
laborate with each other, whereas triads of European- heritage children
tended to work alone or in dyads. Mexican- heritage triads whose moth-
ers had extensive schooling resembled the European- heritage triads or
showed an intermediate pattern. Similarly, Guatemalan- Mayan fathers
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Contemporary Research c 193
with little or no schooling encouraged collaborative problem solving in
child triads (Chavajay, 2008). Fathers with 12 or more years of educa-
tion more often encouraged a division of labor, with each child working
alone and perhaps occasionally checking in with the others. Fathers with
intermediate levels of schooling showed an intermediate pattern. Thus,
these studies show that both culture and schooling affect the tendency
to collaborate. Western schooling may be changing the collaborative
indigenous Mayan families.
Cultures vary in whether children choose to collaborate with parents
or peers, which may lead to differences in the relative influence of par-
ents and peers. For example, U.S. adolescents of Chinese, Vietnamese,
Filipino, and Mexican descent value discussions with their parents and
other relatives when making important decisions more than do adoles-
cents of European descent (Cooper, 1999). This was true even for their
degree of comfort with discussing sensitive topics such as sexuality and
school performance.
Despite the value of collaboration illustrated in many studies, overall
the evidence concerning the benefit of peer collaboration compared to
working alone is mixed (Kuhn, 2015). The outcome seems to depend
on “who is learning what and under what conditions” (p. 46). The chil-
dren’s ages and mix of abilities, instructions given to the group, and the
kind of problem to be solved all seem to be important. As Kuhn notes,
some “collaborations” are not true collaborations in which all members
work together in a coordinated manner and all members benefit. Rather,
sometimes the more knowledgeable members simply transmit their
knowledge to the rest. In these cases, the new knowledge may be super-
ficial and transient. In the more successful groups, the children engage
each other’s thinking in a deep way. Kuhn concludes that one kind of
collaborative- learning setting that does have demonstrated cognitive
benefits is argumentative discourse between members who have oppos-
ing positions. Finally, children may have to be taught how to collaborate:
“It is not enough simply to put individuals in a context that allows for
collaboration and expect them to engage in it effectively. Intellectual
collaboration is a skill, learned through engagement and practice and
much trial and error” (p. 51).
Some of the current issues in this area are the following: Do adult– child
and peer collaborations differ in their effectiveness and, if so, under what
circumstances of age, gender, setting, and expertise? Are the patterns of
thinking and talking together and the mechanisms of change different for
adult– child, sibling, and peer collaborations? Which specific aspects of
collaboration affect which specific aspects of cognitive progress?
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194 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
Research Across Cultures
Cross- cultural research is one method within cultural psychology. Such
research on cultures other than one’s own or on several cultures con-
tributes to our understanding of development by identifying what is
universal about development, what is culture specific, and what mecha-
nisms mediate the effect of culture on development. In this way, we can
see what is “invisible” in our own culture, such as the effects of school-
ing, because we are so accustomed to its presence. Thus, cross- cultural
research prevents us from overgeneralizing our findings and increases
our understanding of mechanisms of development.
Since parent– child interaction is a main mechanism by which culture
affects development, we begin by sampling research on parent– child
interaction. Included in the research are comparisons of two or more
countries, or, in a sort of natural experiment, comparisons of immigrant
parents in the U.S. with those in their culture of origin and with nonim-
migrant parents in the U.S. This latter sort of study identifies changes in
parental behavior after entering a new culture and clarifies the mecha-
nisms by which parents transmit culture.
One good example of how cross- cultural research can identify spe-
cific cultural practices that lead to particular child behaviors is infant
sleeping arrangements. These arrangements are thought to be important
because they affect parent– child interaction and influence the develop-
ment of independence. Many American babies sleep in their own beds
and, by the end of infancy, if not sooner, in a different room from the
parents. This practice seems wrong and bizarre to adults in many parts
of Asia, Africa, and Central America, where children sleep with their
parents even when there is plenty of sleeping space for separate sleeping
arrangements (Shweder, Balle- Jensen, & Goldstein, 1995). Mayan moth-
ers, for example, expressed pity for babies in the United States when
told that they sleep in their own rooms (Morelli, Rogoff, Oppenheim, &
Goldsmith, 1992). They consider this practice harmful for the babies.
Japanese parents believe that babies are born separate beings who must
be taught feelings of interdependence with other people, and sleeping
with parents is thought to encourage feelings of closeness and solidar-
ity with others in the family (Caudill & Weinstein, 1969). In contrast,
many U.S. parents believe that babies are born dependent and must
develop independence; a separate bed is thought to facilitate this. Thus,
even very early experiences are organized by culture.
Another way that culture is expressed is in adult– infant interac-
tions that shape infant attention. What a culture (through the parents)
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Contemporary Research c 195
encourages infants and children to look at is important, because this
affects what information children process and how they learn. Bornstein
and his colleagues (i.e., Bornstein, Cote, Haynes, Suwalsky, & Bakeman,
2012) have examined Japanese, American, and Japanese- American
immigrant mothers and their 5- month- old infants. This comparison
provides interesting information because both Japan and the U.S. are
child- oriented modern cultures. They found both universals and culture-
specific features in the interactions. In all groups, mothers successfully
guided their infants’ attention. Moreover, in all groups, mothers and
infants were attuned to one another. For example, mothers who encour-
aged their infants to look at them more had infants who looked at them
more. These behaviors were contingent; shortly after a mother encour-
aged her baby to look at her, the baby did so.
However, one way attention was culture specific concerned nonsocial
objects. Only in the European- American sample was there a pattern of
mothers encouraging their infants to look at objects, followed by infants
doing so. This finding may reflect cultural differences in the value placed
on nonsocial objects. Another cultural difference concerned whether the
mother or infant tended to initiate episodes of shared attention. Japanese
mothers tended to anticipate and direct their infants, perhaps encourag-
ing dependence on the mothers and thus expressing the cultural valuing
of harmony and interdependence among people. This behavior blurs
the distinction between self and other. In contrast, European- American
mothers tended to respond to their infants, perhaps as a way of encour-
aging infants’ independence and sense of personal agency. The fact that
the mother– infant interaction patterns of Japanese- Americans in many
ways were similar to those of European- Americans suggests that they
were beginning to adopt European- American cultural beliefs about
child rearing.
When Japanese children enter preschool, this setting continues to
instill the value placed on group harmony (Cole, 1992). For example,
American educators viewing a videotape of a Japanese preschool were
shocked that there were 30 preschoolers and only one teacher. In con-
trast, Japanese educators viewing the American classroom with only a
few students per teacher expressed concern for the children: “There is
something kind of sad and lonely about a class that size” and “I wonder
how you teach a child to become a member of a group in a class that
small” (Tobin, Wu, & Davidson, 1989, p. 38). In the Japanese mind,
“A child’s humanity is realized most fully not so much in his ability to
be independent from the group as [in] his ability to cooperate and feel
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196 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
part of the group” (p. 39). As Markus and Kitayama (1991) observed, in
America “the squeaky wheel gets the grease” and in Japan “the nail that
stands out gets pounded down.”
The differing orientations to one’s social group in Eastern and
Western children later is seen in their moral reasoning. Fourth- and
fifth- graders in China and the U.S. wrote a reflective essay after reading
a story involving a moral dilemma (Zhang et al., 2013). Compared to
the U.S. children, whose essays focused on self- interest (e.g., protecting
themselves), the Chinese children’s essays focused on altruistic moral
principles of upholding obligations to help friends, keeping promises,
and maintaining trust. For example, Chinese children were concerned
that not telling on a friend who cheated and lied would encourage him
to continue along a negative pathway.
The connections between cultural beliefs and cultural practices
affecting children’s attention also can be seen in work on other cultures.
In one study, children aged 5 to 11 from different cultures varied in
how much they learned by observing their sibling being shown how to
construct a novel toy, even when not instructed to observe ( Correa-
Chávez & Rogoff, 2009). Children from Guatemalan- Mayan traditional
families (with little maternal exposure to Western schooling) showed
more attention to, and learning from, the sibling’s learning activity than
did children from Guatemalan- Mayan families with extensive exposure
to Western schooling or European- American children with extensive
family exposure to Western schooling. This learning- by- observation of
others, often in a community setting, may indicate the sense of commu-
nity typically found in these villages. Community members may share
in the socialization of the young and even reprimand misbehavior in
other people’s children. Moreover, the children in these cultures often
are encouraged to participate in daily activities within the community in
contrast to the segregation of children from community work and social
activities in middle- class European- American communities. Children’s
learning through observing and pitching in, mentioned earlier, involves
helping without being asked. In order to detect what kind of help
is needed, children show “helpful attention”—being attentive to what is
going on in the context in order to detect what kind of help is needed
(López, Ruvalcaba, & Rogoff, 2015).
Culture touches concepts even as objective and universal- sounding
as mathematics. First, numerical symbol systems differ. For example,
the Oksapmin, a remote Papua, New Guinea group, traditionally have
used the names of parts of the body for their counting system. Counting
begins with the thumb of one hand and progresses through 27 separate
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Contemporary Research c 197
locations (each finger, wrist, elbow, shoulder, right ear, right eye, nose,
left eye, and so on) to the far side of the other hand (Saxe, 2012).
Interestingly, with recent changes in their economic exchange and
schooling, this system has been altered in order to solve new kinds of
mathematical problems. Thus, a culture adapts to social change by creat-
ing new mathematical representations.
Second, the form of mental calculation varies as a function of the
culture’s symbol system. In many Asian countries, people often use
abacuses to solve math problems. At least among older children who
achieve expertise, these devices encourage people to solve calculation
problems in their head by forming a mental image of the abacus (Stigler,
1984). As evidence, when people in these cultures make an error, it is
of the type that would be expected if they were reading off of a mental
image rather than the type of error made by people in cultures where
the abacus is not used.
Third, cultures vary in the contexts in which children develop mathe-
matical skills. One example comes from Saxe’s (1999) research on child
candy vendors on the streets of Brazil. These 6- to 15- year- old boys are
poor, and many have little or no schooling. Many need the money to help
their families survive and may work as many as 14 hours per day and
60 to 70 hours per week. When selling their products, they must very
quickly perform various numerical activities— purchase candy in bulk,
decide on a sale price per unit that ensures enough markup, negotiate
the price (for example, a discount for larger quantities), make change,
and so on. Despite their generally disadvantageous childhood environ-
ment, they develop impressive mental calculation abilities. They often
perform mathematical calculations in their heads, adjust for inflation,
and use a complex system to figure out markups. For example, 10- year-
old Luciano paid 7,000 cruzeiros at a wholesale store for his 30-unit
box of candy bars and must calculate how much to sell the candy for
so that he sells it quickly and makes a good profit. This competency is
especially remarkable given that, because of inflation, the child vendors
have to deal with very large numbers, often in the thousands. They have
constructed their own mathematical system and strategies that bear
little resemblance to those taught in schools. For example, a child might
use a strategy of many- to- one correspondences: setting three bars to
one 1,000 cruzeiros bill and then adding together many of these sets.
In Vygotskian fashion, older children, storekeepers, or parents serve as
social supports for the young vendors by helping them set the markup.
Developmental changes in participation in the social practice, such as
figuring out markup by oneself, lead to cognitive changes, such as an
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198 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
increasingly abstract and hypothetical selling plan. Interestingly, when
researchers ask child street vendors to solve similar math problems, but
without the vending context, they perform much more poorly; nonven-
dors show the opposite pattern (Carraher, Carraher, & Schliemann, 1985).
An example of cultural support for participation in mathemati-
cal activities is that Asian children surpass American children in their
mathematical prowess (though not in overall intelligence) (National
Center for Education Statistics, 2011). This difference is apparent even
among 4- year- olds (Paik, van Gelderen, Gonzales, de Jong, & Hayes,
2011). One cause may be that Asian mothers generally attribute math-
ematical performance to trying hard and not giving up, and they instill
these behaviors in their children. This attitude is consistent with their
cultural belief in improving oneself through hard work. In contrast,
American mothers tend to emphasize inherent ability, an attribution
that does not encourage studying hard or trying harder next time if one
does poorly on a test (Stevenson, Lee, & Stigler, 1986). Surprisingly,
American mothers tend to overestimate their children’s abilities and are
more satisfied with their children’s performance than are Chinese or
Japanese mothers. Another cultural influence may be that the Japanese
language system encourages attention to the quantitative aspect of real-
ity. Japanese has separate words for counting people; birds; four- legged
animals; broad, thin objects such as sheets of paper; and long, thin
objects such as sticks. And Japanese mothers encourage even very young
children to play counting games, such as “Let’s count birds” (Hatano,
cited in Siegler, 1998).
Social Change
In our rapidly changing world, can sociocultural research help us under-
stand the effects of cultural change on human development? Although
much of the research described in this chapter gives the impression
that cultures are static, cultures in fact change, and the world now is
undergoing rapid, permanent change. Increased industrialization and
communication with other cultures are changing the contexts of child-
hood. Parents try to raise their children to adapt to the world they will
encounter as adults, but during times of rapid change, they can only
guess at what that world will look like.
We now turn to two main models concerning the social change occur-
ring in most countries of the world— one from Greenfield (2009; 2015)
and the other from Chen (2015). Unlike Vygotsky’s focus on cognitive
change, these models emphasize changes in social behaviors as well.
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Contemporary Research c 199
Greenfield theorizes that different kinds of behaviors are adaptive in
different kinds of societies, and thus children are socialized toward these
adaptive behaviors. In her model, demographic shifts change cultural
values and learning environments, which in turn shift developmental
pathways. Many countries currently are moving from rural living, infor-
mal education at home, subsistence economy, poverty, ethnic and cul-
tural homogeneity, and low- technology environments to urban living,
formal schooling, commerce- based affluence, ethnic and cultural diver-
sity, and high- technology environments. This change is shifting cultural
values toward individualism (Zeng & Greenfield, 2015), egalitarianism
(e.g., attitudes about gender roles, Manago, 2015), and relativism.
Individualism changes children’s learning environment inside and
outside the home. Children adapt to these new social values as they are
socialized toward greater independence (for example, less body contact
and more face- to- face contact during infancy), competition, and more
abstract cognition (especially through formal schooling) (Maynard,
Greenfield, & Childs, 2015). Children’s relationships are shifting from
being lifelong, with kin or neighbors who spend their entire life in the
same community, to more fleeting relationships, often with nonrelatives,
peers (more than multiage relationships), and strangers (such as store
clerks). Exposure to others’ perspectives, perhaps in part through books
and other media, may change cognition in the direction of increased
perspective taking (Gauvain & Munroe, 2014). Among four cultures,
the most industrialized, the Samoans, outperformed children in Belize,
Kenya, and Nepal on perspective taking tasks. Children also are shifting
toward fewer opportunities to observe and thus learn from adult activi-
ties in the family and community as more adults work away from home.
As families become smaller, there is less need for children to care
for their younger siblings, and families become more child centered,
with possible effects on children’s self- concept. Mothers in the United
States perceive children’s self- esteem to be much more important than
do grandmothers, and in Taiwan, only half of the grandmothers were
even familiar with the concept of self- esteem, though most of the moth-
ers were, thus showing generational change (Cho, Sandel, Miller, &
Wang, 2005).
This pattern of social change involves the movement from collec-
tivism to individualism. Collectivism facilitates the socialization of
compliant– cooperative behaviors and forms of thinking that are bound
to a particular context. In contrast, individualism encourages indepen-
dent behavior and valuing of more abstract cognition. Garcia, Rivera,
and Greenfield (2015) studied three sites in Mexico undergoing social
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200 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
change. Over several recent decades, the children showed increased
competition and decreased cooperation when playing a game. Also, indi-
vidualism has increased in recent decades in China, as seen in changing
frequencies of Chinese words indexing individualistic or collectivistic
values in digitalized books (Zeng & Greenfield, 2015).
Greenfield has found that the most rapidly changing facet of a culture
tends to exert the main influence. For instance, over four decades in a
Mexican Maya community, more children are approaching visual prob-
lem solving in an abstract way and have shown greater understanding of
novel stimuli (Maynard et al., 2015). However, in the first two decades,
participation in commercial activity drove this change, whereas in the
second two decades, formal education was more influential. This shift
reflected first the transition from subsistence to commerce, followed by
the expansion of formal schooling.
Chen’s (2015) pluralist– constructive model proposes that immigration,
advances in information technology, and interaction among political,
economic, and cultural systems across regions have resulted in diverse
values, beliefs, and lifestyles today. Individual adaptation to social change
often involves the coexistence, and even integration, of these diverse
values and practices. Chen sees this as a positive development, for it
helps children develop flexibility in adapting to different circumstances.
Individualism helps them achieve personal goals, and collectivism helps
them develop social support systems, both so important for psycho-
logical well- being. Both one’s own interests and group harmony can be
goals. Children exposed to both collectivism and individualism ideally
will develop both the ability to work alone and with others. Although it
often is claimed that collectivist societies become more individualistic
during globalization, Chen argues that, in addition, individualistic societ-
ies become more inclusive, more accepting of differences. In these ways,
both kinds of cultural systems profit from these social changes. Thus, as
societies change, cultural values change. These are translated into changes
in the contexts in which children develop socially and cognitively.
Immigrant Families
The number of immigrant families has rapidly increased and is now a
quarter of U.S. families (Child Trends, 2015). This increase has created
the opportunity to study the process of development in the context of
adapting to a new culture. Looking at how children, adolescents, and
their families rise to the challenge of cultural adaptation also has made
it possible to expand and clarify our understanding of developmental
and family processes by studying, for example, socialization processes.
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Contemporary Research c 201
Such research can reveal new mechanisms of development or show that
the same child or parent behaviors have different meanings in different
cultures. We now turn to several examples of these contributions.
In Chapter 3, research showed that adolescents in immigrant families
face challenges in forming an identity that integrates their old and new
cultures. Here we consider that the meeting of two cultures in immi-
grant families can affect family dynamics, as well as show links between
family conflicts and mental, physical, and educational outcomes. For
example, Chinese- American adolescents and their parents have every-
day conflicts about both seemingly minor issues and acculturation- based
conflicts (Juang, Syed, & Cookston, 2012). The fact that these two types
of conflict are correlated and have similar developmental trajectories
suggests that they are related. That is, in immigrant families, everyday
conflicts may actually reflect larger issues involving conflicting cultural
values and beliefs. Moreover, these conflicts were associated with poor
psychological adjustment (though the specific pattern of predictions
varied for the two types of conflict).
A two- year longitudinal study (Juang & Cookston, 2009) showed
changes in family dynamics in Chinese- American families, a culture
wherein fulfilling family obligations is expected and valued. Adolescents
with high levels of family obligation were more protected against later
depression than those with low levels. Thus, assimilation to the major-
ity culture in the United States was not advantageous in this respect.
Moreover, adolescents showing increasing family obligation behaviors
over the two- year period also showed fewer depressive symptoms.
Interestingly, Chinese- Americans born in the United States rather than
in China held the family obligation value less strongly, a sign of a shift
away from Chinese culture to that of the United States, which values
autonomy. Overall, family obligation decreased over time, but only with
regard to behaviors— not attitudes— which suggests that it is important
to consider both attitudes and behaviors when looking at culture- related
developmental change; immigrant adolescents may continue to endorse
traditional cultural values, even if not behaviors, in a new culture.
The outcomes for children in immigrant families sometimes are neg-
ative, but there is some evidence that immigrant children actually are
doing better than children of native- born parents (Marks, Ejesi, & Garcia
Coll, 2014). Also, interesting recent work shows that bilingualism—
a characteristic that often goes along with being a child in an immigrant
family— often is associated with superior control of one’s cognitive
functioning (e.g., Bialystok, 2015). The now large body of research on
immigrant families has shown that any theorizing about immigrant fam-
ilies and developmental outcomes must consider many accompanying
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202 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
variables that are as important as, or more important than, immigration
per se (Crosnoe & Fuligni, 2012). Variables critical to child outcomes
are parents’ education before migrating, child’s birth before versus after
the family’s immigration to the U.S., the age at which the mother came
to the U.S., the part of the U.S. to which the family immigrated, gender,
and immigrant status (documented versus not).
Parents from different cultures or subcultures vary in how they
attempt to instill values in their children. One particularly compelling
case concerns Baumrind’s (e.g., 1973) often- cited research demonstrat-
ing the superiority of the authoritative pattern of child rearing (a com-
bination of firmness and support) over highly controlling or permissive
patterns for increasing achievement and independence in children. This
conclusion was questioned by the later finding (Dornbusch, Ritter,
Leiderman, Roberts, & Fraleigh, 1987) that this result more accu-
rately describes European- Americans than African- Americans, Asian-
Americans, or Hispanics. For example, the Asian- American parents were
high on control, but their children generally received high grades in
school. And controlling parents were associated with low grades among
Hispanic girls but not boys. Thus, the same parental behaviors may have
different meaning in different cultures. Parental control may be inter-
preted as negative in one culture and as caring in another.
Development Through Narratives and Conversations
Probably all cultures use narratives, or stories, for organizing experi-
ence over time, interpreting human action, maintaining social relation-
ships, and preserving culture. Through narratives, people and culture
construct each other. People’s stories contribute to the culture, and
the culture helps people make sense of their experiences and their life.
Narratives provide a way to pass on the culture; thus, they contribute
to children’s socialization and their development into members of their
cultures. As a device for socialization, these cultural practices maintain
the moral system of the culture. These myths and moral tales communi-
cate “lessons” about cultural beliefs and practices.
Cultural themes are expressed not only in narratives shared by the
entire culture but also in “family stories”—personal narratives within
families. Research comparing middle- class Chinese families in Taipei,
Taiwan, and middle- class European- American families in Chicago
(Miller, Fung, Lin, Chen, & Boldt, 2012) provides an example of how
cultures use such stories for different purposes. Chinese families used
family stories about their children as an opportunity to teach moral
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Contemporary Research c 203
lessons. Chinese families were more likely than the ones in Chicago to
tell stories about the child’s past misbehaviors and to weave into the
stories moral and social rules about these transgressions. These children
then developed the ability to initiate stories on moral topics and reason in
complex ways about their past transgressions. They also learned to listen
well to stories told by their parents, perhaps in part because listening is a
way to show respect and affection for their parents as moral authorities.
In contrast, European- American families used stories to focus on their
child’s strengths. When these families did construct stories about the
child’s misdeeds, they tended to downplay this aspect of the story. The
Chinese parents may have been operating within a Confucian emphasis
on teaching, strict discipline, social obligations, self- improvement, and
the value of feeling shame, whereas the American parents may have
been more concerned with the child’s self- esteem. Thus, cultures select
differently from the past when constructing personal narratives and,
consequently, children learn what experiences are important and how
they should assess them as well as construct their identities as members
of their families and societies and as individuals. This research provides
yet another example of how looking at cultures other than European-
American ones modifies our theories about the mechanisms by which
children are socialized.
The telling of stories also is culturally constructed in that this activity
is embedded in cultural beliefs about gender (Fivush & Zaman, 2015).
Parents are more elaborative and emotionally expressive when remi-
niscing about the past with daughters than sons. This leads to girls grad-
ually developing more elaborative and emotionally expressive personal
narratives compared to boys. Girls also seem to situate their identities
within family stories more than do boys. Moreover, when parents tell
their children stories about their own childhoods, these narratives about
mothers also are more elaborative and emotionally expressive than those
about fathers. This research is a good example of the implicit nature of
most of parental teaching about culture.
Thus, the social uses of language help children move from the private
world of infancy to the “community of minds” of their culture (Nelson,
2008). Much of development involves “meaning making” as children try
to make sense of their experiences and, through language, share these
meanings with others in conversations and stories. They form social con-
nections with other people and draw on these social guides to aid their
making sense of the world. This metaphor of the child as sense- maker
and a member of a community of minds contrasts with Piaget’s meta-
phor of the child as miniature scientist.
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204 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
Concluding Comments About Contemporary Vygotskian–
Sociocultural Research
Finally, we look at two contemporary themes about Vygotskian–
sociocultural developmental approaches. One theme concerns the assim-
ilation of Vygotsky’s theory into contemporary developmental theorizing.
The question is “How much of contemporary ‘Vygotskian’ research is
actually Vygotskian?” A second theme concerns several current trends in
developmental cultural psychology research and theorizing.
Assimilation of Vygotsky’s Theory into Contemporary Develop-
mental Theories c The assimilation of Vygotsky’s theory into contem-
porary work on developmental psychology provides an interesting case
study of how any discipline incorporates a theory from another time
and place. The assimilation usually is selective and distorted in some
way— much like the distortion that occurs when people assimilate, in
the Piagetian sense, something into their current mental structure. In
the case of Vygotsky, something is lost in the translation, so to speak.
What contemporary developmental psychology needed from Vygotsky
was a sensitivity to the social and cultural context of development and
a way to conceptualize the cultural origins of a developing mind. And
that is what we took, as seen in the studies in this chapter on the zone,
guided participation, intersubjectivity, internalization, and cultural
tools. In this sense, there now have been numerous Vygotskian studies.
However, certain main aspects of Vygotsky’s theory do not fare as well
in the Western individual- oriented worldview and so have been rela-
tively ignored. Specifically, much current sociocultural research looks at
how sociocultural settings influence behavior, how cultural differences
lead to psychological differences, and how a child’s performance shifts
from setting to setting. Few studies start with the child- in- context as the
basic unit, as noted earlier. The social context is grafted on to individual
development, rather than considered an inherent part of it.
Moreover, the notion of the zone of proximal development has been
plucked out of its social– political context. Vygotsky saw interactive
learning processes in the zone as an expression of collectivism; society
shares its mental skills during “shared consciousness” much as it shares
its material goods. In contrast, current Vygotskian research still con-
veys the impression that an individual child’s cognitive development
is guided by an individual adult rather than by society in general as a
shared endeavor.
Finally, many recent studies of the zone that are presented as Vygotskian-
inspired are little more than traditional studies of mother– child
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Contemporary Research c 205
interaction in learning situations and do not incorporate the principles
that distinguish Vygotskian studies from any study of adult– child
interaction. Researchers still view cognition as something that hap-
pens inside a child’s head— an adult simply helps put it there. Truly
Vygotskian studies must (1) look at both adult and child behavior, at
their shared understanding, and at how each adjusts to the previous
response of the other, (2) assess what a child can do both alone and
with an adult’s help, and (3) look at the gradual shift in responsibility
from adult to child over the course of the session. Such studies must
also (4) assess how the adult structures the learning process, tries to
pull the child to a slightly higher cognitive level, relates the problem
to the child’s previous experience, and adjusts the amount of help to
the difficulty of the task, and (5) examine how the culture and its his-
tory shape the nature of the parent– child interaction. Very few studies
include all five aspects.
It is not necessarily wrong to selectively assimilate a theory. Scientific
progress often comes from taking only what is most useful from a the-
ory. But it should be recognized that Vygotsky’s theory is more often
appropriated than internalized.
Current Trends in Cultural Psychology Research c Because culture
is such an umbrella term, researchers have tried to identify more spe-
cific dimensions. One example is the contrast between individualistic
cultures and collectivist ones. However, this dimension does not capture
the heterogeneity within each type of culture. As we become more
familiar with cultures around the world, we become more aware of
their subcultures and the subtle differences among them. Overly general
terms, such as “Hispanic,” mask major differences among peoples from
countries such as Mexico, Cuba, Puerto Rico, Costa Rica, and Colombia.
Even within a country, especially large ones, there can be diverse sub-
cultures. An example of a within- country difference is that preschoolers
in two quite different regions of China (Beijing and Chengdu) follow a
different sequence of theory- of- mind development (Duh, Paik, Miller, &
Gluck, 2015). Preschoolers in the traditional Chengdu region were
more advanced than Beijing or U.S. children in understanding hidden
emotions. Similarly, an adequate cultural account of development must
attend to intersections of culture with factors such as gender and social
class. For example, for young Latino immigrants in the U.S., transition
to a new culture may differ for females and males, and for lower- income
and middle- income families. Moreover, these patterns may vary as a
function of age.
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206 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
One solution to this dilemma of how to capture the diversity within
what from the outside might be seen as a single culture is the “ cultural
practice” approach (Rogoff, Najafi, & Mejía- Arauz, 2014). This approach
asks what people do— the cultural practices in which they participate—
rather than what people are (e.g., Chinese)—the “categorical box”
approach focused on language or country. Any community has a constel-
lation of social practices, which show connections among occupations,
schooling, family size, urban versus rural residence, indigenous versus
modern birthing and spiritual practices, and modes of learning (e.g.,
by observing and pitching in, described earlier). Although communities
derived from the same cultural group historically may even live in the
same city, their differing histories of cultural practices can lead to quite
different constellations of cultural practices. For example, in Guadalajara,
Mexico, among three communities with historical connections to indig-
enous communities who from the outside “are” indigenous, there is wide
variation in what they “do,” their pattern of cultural practices involving
schooling, religious festivals, and specific indigenous practices, such as
burying a baby’s umbilical cord (Rogoff et al., 2014). A group that has
experienced cultural change may show interesting transitional practices,
such as keeping the umbilical cord without knowing why or not burying
it. An individual thus may participate in two communities of practices—
indigenous and cosmopolitan— and the practices may be similar, com-
plementary, or conflicting. This cultural- practices approach provides a
way to study both stability and change over generations as communities
are touched by industrialization and technology or families emigrate.
Families immigrating to the U.S. may use a combination of their culture
of origin, for example, learning by observing and “pitching in,” and more
Westernized socialization practices. Thus, social change within a nation
or participation in two cultures after immigration can be studied by
looking at changing constellations of cultural practices.
The field appears to be in transition toward a truly cultural approach.
For many years, culture has been considered an “add on” to descriptions
of what was considered “normal” or typical development (usually from
studies of white middle- class children). However, this approach has been
challenged, because all children have a culture, and focusing on one
particular group provides only one particular view of development and
thus should not be considered the norm by which to compare other cul-
tures. Thus, the field is starting to construct a broad developmental per-
spective that starts with cultural diversity rather than ends with it. That
is, the new view is that any aspect of development can be understood
fully only by studying it in its various cultural contexts; the behavior of
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children in different cultural settings must be fully interwoven through-
out developmental science. Culture is not something separate that we
study. Also, studying a culture other than one’s own has suggested pre-
viously unstudied mechanisms of development that will lead to more
complete theories of development.
SUMMARY
Developmental sociocultural approaches have many roots, but Vygotsky
was the main historical force. Vygotsky’s theory has impacted develop-
mental research by directing attention to the cultural origins of thinking
and, more generally, stimulating researchers to consider the historical–
cultural context of development. Unlike most theories, the sociocultural
approach focuses on the child- in- activity- in- cultural- context, rather
than on the child alone. Thinking is inherently social; children use cul-
tural tools, such as symbol systems, to solve problems in their everyday
attempts to meet their goals within a social reality. Culture constructs
settings and shapes the interactions of people in them. A child’s partici-
pation in various cultural routines nurtures particular ways of thinking.
Cultural beliefs, knowledge, values, artifacts, and physical settings influ-
ence what settings children are encouraged to enter and when they can
enter them, what they learn in these settings, how they acquire skills,
and who can enter particular settings. Thus, sociocultural approaches
force researchers to reexamine dichotomies such as culture versus mind,
thought versus action, and person versus context.
Children develop in a zone of proximal development— the distance
between what a child can do without help and what he can do with help.
A more skilled person uses prompts, discussion, modeling, explanation,
and so on to guide and collaborate with children to move them through
the zone. Because the child and a familiar adult share a past and have a
common goal in the task, they have a shared understanding of the prob-
lem. Children actively contribute to their movement through the zone
by seeking out particular settings, influencing the course of the activity,
and bringing personal qualities and developmental skills to the inter-
action. Vygotsky argued that only by looking directly at moment- to-
moment change over time can we understand development; intelligence
is not what you know but what you can learn with help. Thus, only a
dynamic assessment of a child’s potential level of development, rather
than a static assessment of the current level, gives an accurate picture of
the child’s ability.
Summary c 207
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208 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
As children engage in activities with others, intermental activities,
particularly dialogue, become intramental. In this way, individual mental
functioning has sociocultural origins. Language between people even-
tually becomes spoken speech for self (private speech) and then silent,
mental, speechlike inner speech. Children internalize (Vygotsky) or
appropriate (Rogoff) information and ways of thinking from their
activities with parents, teachers, other adults, and more skilled peers.
Technical and psychological tools provided by the culture mediate intel-
lectual functioning. Language, in particular, helps children direct their
own thinking efficiently; they plan, think logically, and form abstract
concepts. However, nonverbal interaction with others encourages cog-
nitive skills as well.
The microgenetic method involves an analysis of moment- to- moment
changes as a child moves through the zone of proximal development. For
Vygotsky, the most general mechanism of development is the dialectical
process in which two contradictory ideas or phenomena are synthesized
into a new idea or phenomenon. The dialectical process operates mainly
during interaction with adults, more skilled peers, or peers of equal abil-
ity, and during play. Movement through the zone is a dialectical process
as the child collaborates with another person and they co- construct the
meaning of the task, a goal, and a solution.
Regarding the theory’s position on developmental issues, it holds a
contextualist view of human nature; human nature develops in a social
context. The temporal dimension (past, present, and future) is cross-
woven with the spatial dimension (social settings). Development is both
quantitative and, when synthesis results during the dialectical process,
qualitative. Nature and nurture also enter into a dialectical process, but
socioculturalists focus on the social strands of this process. Finally, what
develops is an active- child- in- context.
Regarding applications, Vygotsky wrote about learning in the class-
room and about children with special needs. More recent applications
focus on collaborative peer learning and the zone of proximal devel-
opment. The strengths of the sociocultural approach are its attention
to the social– cultural context of development, integration of learn-
ing and development, and attention to the diversity of development.
Weaknesses are the vagueness (or limitations) of the notion of the zone
of proximal development, insufficient attention to setting and child-
developmental aspects of the zone of proximal development, the diffi-
culties of studying cultural– historical contexts, and the failure to pro-
vide prototypic tasks revealing interesting developmental phenomena.
The developing person- in- context approach, associated with Vygotskian
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and sociocultural theories and exemplified by Bronfenbrenner, embeds
development within a social ecology consisting of various levels from
near to far. Sociohistorical events, such as the Great Depression, provide
contexts that shape development, but children are active participants in
these contexts as well.
Current Vygotskian– sociocultural research focuses on collaborative
problem solving, developmental processes in various cultures or during
times of cultural change, immigrant families, and acculturation through
narratives and conversation. Although sociocultural theory has stimu-
lated research on sociocultural influences, few studies have incorporated
the aspects of the theory that do not fit easily into the contemporary
Western cultural belief system. Vygotsky’s theory is important for
understanding development in our rapidly changing global, multicul-
tural world. The field of developmental psychology is advancing toward
a perspective in which specific dimensions of cultural diversity are
identified and cultural processes are fully integrated into any account of
development.
SUGGESTED READINGS
The following two books by Vygotsky provide a good introduction to
his theory:
Vygotsky, L. S. (1978). Mind in society: The development of higher psycholog-
ical processes. Cambridge, MA: Harvard University Press.
Vygotsky, L. S. (1986). Thought and language. Cambridge, MA: MIT
Press.
Vygotsky’s works have been collected into a series:
Rieber, R. W. (Ed.). (1987–1999). The collected works of L. S. Vygotsky
(Vols. 1–6). New York: Plenum Press.
Rieber, R. W., et al. (Eds.). (2004). The essential Vygotsky. New York:
Kluwer Academic/Plenum Publishers. This is a “Vygotsky sampler” of
his most important and interesting contributions from the above six
volumes.
The following provides a useful overview of culture and cognitive
development:
Gauvain, M., & Perez, S. (2015). Cognitive development and culture.
In R. M. Lerner (Series Ed.) & L. S. Liben & U. Müller (Eds.),
Suggested Readings c 209
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210 c VYGOTSKY AND THE SOCIOCULTURAL APPROACH
Handbook of child psychology and developmental science: Vol. 2. Cognitive
processes (7th ed., pp. 854–896). New York: Wiley.
This study of a Mayan midwife illustrates how cultural practices are pre-
served yet modified during social change.
Rogoff, B. (2011). Developing destinies: A Mayan midwife and town.
New York: Oxford University Press.
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Biological Approaches: Ethology,
Developmental Neuroscience,
Genetics
At the beginning of these experiments, I had sat myself down in the grass amongst
the ducklings and, in order to make them follow me, had dragged myself, sitting,
away from them. . . . The ducklings, in contrast to the greylag goslings, were most
demanding charges, for, imagine a two- hour walk with such children— all the time
squatting low and quacking without interruption! In the interests of science I sub-
mitted myself literally for hours on end to this ordeal.
—Lorenz, 1952, p. 42
The initial phase, that of protest, may begin immediately or may be delayed; it lasts
from a few hours to a week or more. During it the young child appears acutely dis-
tressed at having lost his mother and seeks to recapture her by the full exercise of
his limited resources. He will often cry loudly, shake his cot, throw himself about,
and look eagerly towards any sight or sound which might prove to be his missing
mother. . . . During the phase of despair, which succeeds protest, the child’s preoccupa-
tion with his missing mother is still evident, though his behavior suggests increasing
hopelessness. The active physical movements diminish or come to an end, and he may
cry monotonously or intermittently. He is withdrawn and inactive, makes no demands
on people in the environment, and appears to be in a state of deep mourning.
—BowLBy, 1969, p. 27
Adenine- Thymine
Guanine- Cytosine
Adenine- Thymine
Cytosine- Guanine
—Genetic code
Se
rg
ey
N
iv
en
s/
Sh
ut
te
rs
to
ck
C H A P T E R 5
06_MIL_7898_ch5_211_276.indd 211 1/8/16 5:10 PM
212 c BIOLOGICAL APPROACHES
D
evelopmental psychologists have not taken Shakespeare’s advice,
“Neither a borrower nor a lender be.” Some of the most fruitful
ideas about development have been borrowed from other areas of
psychology and even other sciences. Developmental psychology
has borrowed heavily from biology for clues about where to look for
connections between body and mind and behavior. In this chapter, we
look at several biological perspectives on development that are heavily
influencing developmental psychology— ethological theory (including
evolutionary psychology), developmental neuroscience, and genetics.
We focus on ethology because of its long history of contributions to
developmental psychology, especially infants’ attachment to their par-
ents, but give careful attention to recent major contributions from the
other two areas. Developmental neuroscience and genetics probably are
the fastest- growing areas within developmental psychology currently
and are changing the way developmentalists think about how nature and
nurture co- construct development. Much of the progress is due to new
tools for imaging the brain and analyzing genes, but also to new theo-
retical models that capture the complex interactions of various levels of
biology, from cells to brain organization to behavior (and back again).
This chapter first describes ethology, including evolutionary psychol-
ogy. Next is an account of developmental neuroscience, followed by
genetics. The chapter ends with models that integrate genes, brain, and
experience.
Ethology
Ethology is the study of the evolutionarily significant behaviors of a
species in its natural surroundings. As a subdiscipline of zoology, it
looks at the biological and evolutionary blueprints for animal behavior.
Ethology places humans into a broad context: the animal world and
our distant past. It is humbling to contemplate the fact that there are
more species of insects in a square kilometer of Brazilian forest than
there are species of primates in the world (Wilson, 1975). The English
geneticist Haldane, when asked about the nature of God, is said to have
remarked that he displays “an inordinate fondness for beetles” (as quoted
in Hutchinson, 1959, p. 146). The human species is just one small part
of the huge, evolving animal kingdom of approximately 3 million to
10 million species.
This section on ethology begins with a history followed by a general
orientation. Then come sections on the main contributions of ethology
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Ethology c 213
to developmental psychology, mechanisms of development, the theory’s
position on developmental issues, applications, an evaluation, and con-
temporary research.
History of the Theory
Whoever achieves understanding of the baboon will do more for metaphysics than
Locke did, which is to say he will do more for philosophy in general, including the
problem of knowledge.
—charLes darwin
Ethology is linked to the German zoologists of the 1800s who studied
innate behaviors scientifically. Darwin’s painstaking observations of fos-
sils and variations in plant and animal life added an evolutionary perspec-
tive to the field. He, along with Alfred Wallace, concluded that nature
ruthlessly selects certain characteristics because they lead to survival:
“What a book a devil’s chaplain might write on the clumsy, wasteful,
blundering, low, and horribly cruel works of nature” (Darwin, quoted in
Shapley, Rapport, & Wright, 1965, p. 446). As a result of this selective
force, species changed and sometimes differentiated into subspecies.
Thus, many animals, including humans, are related through common
ancestors. Darwin proposed that intelligence and other behaviors, as
well as physical structures, were products of evolution. If they increased
the chances of survival to the age of reproduction, they were retained; if
they did not, they disappeared. Darwin’s claim of a common ancestry of
humans and other primates was not received well in Victorian England:
Montagu (1973) related an anecdote about a shocked wife of an English
bishop. She said that she certainly hoped that the theory was false, but if
it were true, that not many people would find out about it!
Darwin’s careful observing and cataloging of plants and animals was
imitated by ethologists years later. Just as he carefully described animal
and plant life, Darwin also described his own infants’ behavior, as in the
following excerpt on fears:
Before the present one was 4 months old I had been accustomed to make
close to him many strange and loud noises, which were all taken as excel-
lent jokes, but at this period I one day made a loud snoring noise which I
had never done before; he instantly looked grave and then burst out cry-
ing. . . . May we not suspect that the vague but very real fears of children,
which are quite independent of experience, are the inherited effects of
real dangers and abject superstitions during ancient savage times?
(1877, p. 289)
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214 c BIOLOGICAL APPROACHES
Ethology as a distinct discipline began in the 1930s with the European
zoologists Konrad Lorenz and Niko Tinbergen. They developed, often in
collaboration, many of the key concepts discussed in the next section.
Their observations of species as diverse as ducklings, butterflies, and
stickleback fish gave scientific meaning to the sometimes mystical term
“instinct.” Many of Lorenz’s observations were of wild animals that wan-
dered freely in and around his home. Lorenz and Tinbergen’s work was
honored with the Nobel Prize in medicine or physiology in 1973, which
they shared with another ethologist, Karl von Frisch.
Developmental psychology was receptive to ethology because devel-
opmentalists have a tradition of naturalistic observations of children and
consideration of the biological basis of development. Many develop-
mentalists continued to conduct natural observations of children even
through psychology’s behaviorist years and welcomed ethology as a way
to correct the extreme environmentalism of learning theory. The most
important figure to bring ethology to the attention of developmental
psychologists was John Bowlby. His turning from a Freudian to an etho-
logical account of infant– caretaker social attachment in the 1950s in
England laid the groundwork for subsequent research in this area in both
Europe and North America. (His work is described later.)
The contemporary study of animal behavior has many subfields, such
as comparative psychology, behavioral ecology, and evolutionary biology.
In general, this work is more empirical and experimental and less obser-
vational, speculative, and theoretical than the earlier European classical
ethological studies. The majority of the approaches favor a reductionist
approach and study cells, neural connections, and hormones rather than
the behaviors of the whole organism in its ecological niche.
Ethology was soon joined by sociobiology, defined by its main spokes-
man, E. O. Wilson, as the “study of the biological basis of all social
behavior” (1975, p. 4). Although ethology and sociobiology overlap a
great deal, sociobiology focuses on population genetics and kin selec-
tion. Because close relatives share most of one’s genes, people can pass
on their genes not only by reproducing but also by furthering the sur-
vival of the genes of kin through altruistic behavior. Altruistic behavior
may endanger oneself but benefit the species. Sociobiology minimally
influenced developmental psychology, though there was some interest
in such topics as reproductive patterns and parenting.
Evolutionary psychology, which arose after some of the criticisms of
sociobiology as deterministic, reductionist, and socially conservative,
has had more impact on developmental psychology. This field com-
bines evolutionary biology, paleoanthropology, and cognitive psychology
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Ethology c 215
(Tooby & Cosmides, 2005). Evolutionary psychologists use primatology,
archaeological data, cultural anthropology, neuroimaging, genetic anal-
yses, and data on contemporary human universals to discover how the
mind has been shaped by natural selection to solve problems of adapta-
tion faced by our hunting- and- gathering ancestors.
A developmental perspective is important for all these approaches:
“The gap between molecular biology and natural selection will be filled by
developmental analysis of the nervous system, behavior, and psychology”
(Gottlieb, 1979, p. 169). Today, a discipline called evolutionary develop-
mental biology (or “ evo- devo”) compares the developmental processes of
various animals to determine how developmental processes evolved.
General Orientation to the Theory
Ethology is characterized by four basic concepts: (1) species- specific
innate behavior, (2) an evolutionary perspective, (3) learning predispo-
sitions, and (4) ethological methodology.
Species- Specific Innate Behavior c Ethologists focus on behaviors
that, like organs of the body, were considered primarily innate, adap-
tive, and essentially the same in all members of a species. Of course,
any “innate” behavior is influenced by the environment, because it has to
be developed within prenatal and postnatal environments. Ethologists
consider a behavior primarily innate if it has these four characteristics
(Cairns, 1979):
1. It is stereotyped in its form (that is, has an unvarying sequence of actions)
across individuals in a species.
2. It is present without relevant previous experience that could have allowed
it to be learned.
3. It is universal for the species (that is, found in all members).
4. It is relatively unchanged as a result of experience and learning after it is
established.
For example, in certain songbirds, the same song appears in all mem-
bers of the species at sexual maturity, even if they have never heard the
song sung by other members of the species. As this example illustrates,
some innate behaviors are not present at birth but appear later as a result
of physical maturation. In contrast to primarily innate behaviors, learned
behaviors vary in form from individual to individual, require relevant
previous experience, usually vary in their occurrence among members
of the species, and change as a result of subsequent experience.
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216 c BIOLOGICAL APPROACHES
Innate behaviors are termed species- specific, which means they occur
among all members of the species or at least a particular subgroup, such
as all the males or all the young. If another species also has the behavior,
two inferences are possible. One is that the two species are related, per-
haps having split into separate lines at some point in their evolution. Or,
the behavior may have evolved independently in the two species, perhaps
because they had similar physical environments and needs. For example,
in many species, the young cling to the mother’s fur— a necessity for
survival if infants must travel with their mothers as they move through-
out an area in search of food or flee from predators. Also, the same
behavior may have different meanings in the two species. An example is
tail wagging in dogs and cats, thought to indicate contentment in dogs
and conflict in cats.
Two types of innate behaviors are reflexes ( wired- in responses to stimuli)
and fixed action patterns. Examples of human infant reflexes are grasping a
finger placed in the hand, spreading the toes when the bottom of the foot
is stroked, and turning toward a nipple when it brushes the cheek. Any
long- haired parent would agree that infants are particularly likely to grasp
hair, especially during feeding. Ethologists speculate that this reflex orig-
inally served to facilitate clinging to the mother’s fur. Many such reflexes
are quite strong. A premature baby can grasp a clothesline and support its
own weight, for instance. This ability is later lost. More complex reflexes
are coordinated swimming, crawling, and walking movements when the
body’s weight is supported in newborns or young infants.
A fixed action pattern is a complex innate behavior that promotes the
survival of the individual and thus the species. It is a “genetically pro-
grammed sequence of coordinated motor actions” (Hess, 1970, p. 7) that
arises from specific inherited mechanisms in the central nervous system.
Without being taught, squirrels bury nuts, birds perform courtship
“dances,” spiders spin webs, and stickleback fish fight to protect their
territory. Fixed action patterns can become very elaborate, as when
the male bowerbird spends hours building a love nest decorated with
flowers, fruit, shells, and colorful beetles to attract a mate. He adjusts a
twig here, adds a flower there, and seemingly stops to admire his work
from time to time. Fixed action patterns involving social behavior are of
particular interest. The adaptive value of fixed action patterns lies in the
fact that they often end in eating, mating, or avoiding predators.
A fixed action pattern is elicited by a sign stimulus— a particular stim-
ulus whose presence automatically releases a particular fixed action
pattern. Lorenz (1966) likened this process to a key opening a lock. For
example, the red belly of a male stickleback fish venturing into another
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Ethology c 217
stickleback’s territory is a sign stimulus that triggers fighting behavior.
A decoy that only vaguely resembles the stickleback in shape, but is red
on its lower half, elicits this fixed action pattern, whereas an accurately
shaped decoy without the red area usually does not (Tinbergen, 1951).
Thus, the sign stimulus is specific, and sometimes it must be in a partic-
ular orientation or position. Tinbergen (1958) discovered this particular
sign stimulus when he noticed that his sticklebacks in an aquarium near
a window facing a street would become agitated at a certain time of
the day. He eventually realized that a red mail truck passed by at that
time, a stimulus that approximated the natural sign stimulus. A further
example of the specificity of the sign stimulus is that a hen will not res-
cue a distressed, flailing chick she can see under a glass bell but cannot
hear. However, she will rescue the chick immediately if she can hear the
distress cries even if she cannot see it (Brückner, 1933). When people
fish, they sometimes use lures that exaggerate the natural prey (the sign
stimuli) of larger fish.
Innate reflexes and fixed action patterns enhance young infants’ sur-
vival by allowing them to seek food and hide from predators on their
own or binding them to an adult caretaker by crying, grasping, sucking,
or smiling. This fit between the organism’s needs and its innate behaviors
is the product of a long evolutionary history. It is not always easy to infer
the adaptive value of a characteristic, however. It was once claimed that
flamingos are pink because that makes it difficult for predators to see
them against the sunset (Thayer, 1909).
Despite the focus on innate behaviors, ethologists think that learning
is important. Most behavior is viewed as an interweaving of innate and
learned components. A raven innately knows how to build a nest, but
through trial and error learns that broken glass and pieces of ice are less
suitable than twigs for this purpose ( Eibl- Eibesfeldt, 1975). An innate
skill can easily be adapted to new situations, as when English titmice
quickly learned how to use innate gnawing behaviors to open milk bottles.
Waddington (1957) proposed an influential model of how biologi-
cal regulating mechanisms constrain the course of development while
allowing for the modification of development by the environment. He
presented development as a ball rolling down an “epigenetic landscape.”
As the ball descends, this landscape becomes increasingly furrowed by
valleys that greatly restrict the sideways movement of the ball. Slight
perturbations from the developmental pathway can be corrected later
through a “ self- righting tendency,” and the ball returns to its earlier
groove. Thus, the general course of development is set, but some varia-
tion is possible because of particular environmental events.
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218 c BIOLOGICAL APPROACHES
Evolutionary Perspective c As Samuel Butler (1878) commented,
“A hen is only an egg’s way of making another egg.” Evolution involves
phylogenetic change, or change in a species over generations, in contrast
to ontogenetic change, or developmental change in a single lifetime.
Each species, including humans, is a solution to problems posed by the
environment— an experiment in nature. These problems include how to
avoid predators, how to obtain food, and how to reproduce.
The course of development within an individual follows a pattern that
was acquired by the species because it facilitated survival. The young
must adapt to their environment in order to reach the age at which they
can reproduce and transmit their genes to the next generation. Just as
certain physical characteristics, such as the upright stance and the hand
with opposable fingers and thumb, facilitated making and using tools, so
did certain behaviors, such as reflexes and fixed action patterns, facilitate
survival through mating, food gathering, and caretaking. Social behav-
iors, such as interindividual communication and cooperation, encour-
aged group cohesion and thereby increased the chances of survival. New
behaviors arose through natural genetic variations or mutations and, if
they allowed the organism to survive long enough to reproduce, were
genetically transmitted to the next generation. These successful behav-
iors gradually became more common in the whole population over many
generations. Specifically, if genes are expressed in behavior (see later in
this chapter) and if the behavior is adaptive, then it can be selected for
during evolution.
Contemporary evolutionary theory has been changed dramatically
by modern genetics. Theorists are increasingly aware of complex inter-
actions of genes and environments. As explained later in this chap-
ter, it is not just a matter of an environment simply triggering innate
behaviors. Evolutionary models now also draw on population genetics
to detect evolution by tracking changes over generations in the rela-
tive frequencies of various genes. One current notion, for example, is
that sudden changes during evolution may have been more common
than Darwin thought. Also, more attention is given now to the role
of the environment, especially social environments. After all, species-
specific behaviors have evolved within environments that are typical for
that species. In a sense, “individuals inherit not only a species- typical
genome but also a species- typical environment” (Bjorklund & Ellis,
2014, p. 230).
Humans have evolved few fixed action patterns. Rather, human plas-
ticity has evolved as a successful strategy for enabling an organism to adapt
to local conditions, including atypical environments. Plasticity refers to
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Ethology c 219
the flexibility of the brain, the hormonal system, and the expression
of genes. Plasticity starts to act even prenatally; chemical signals from
the mother may prepare a fetus for a harsh and unpredictable environ-
ment. Specifically, prenatal exposure to high levels of stress hormones
from the mother is associated with child behaviors such as high anxiety,
fearfulness, aggression, and risk taking (Pluess & Belsky, 2011), which
may be adaptive. However, infants typically delay significant changes in
their developmental trajectory to match local conditions (e.g., a harsh
or supportive environment) until they have had enough time to ade-
quately process information about their environment (Frankenhuis &
Panchanathan, 2011).
Note that both Piagetian and ethological approaches are con-
cerned with how an organism adapts to its environment. Both iden-
tify biological predispositions toward learning, for example, the
assimilation– accommodation process (Piaget) and specialized learning
abilities (ethology).
Learning Predispositions c Ethologists see the biological control
of behavior not only in largely innate behaviors acquired during evo-
lution but also in predispositions toward certain kinds of learning.
Species differ in which aspects of their behavior are modifiable, in what
kinds of learning occur most easily, and in the mechanisms of learning.
Sensitive, or critical, periods are specific time frames in which animals
are biologically ready to learn from particular experiences. During
this time, they are biologically pretuned to notice certain types of
objects, sounds, or movements, and produce certain behaviors that are
particularly susceptible to modification. After the end of the sensitive
period, animals can acquire the behavior with great difficulty or even
not at all.
An example of a sensitive period is Lorenz’s observation that, shortly
after birth, certain birds (for example, geese) are most able to learn
the distinctive characteristics of their mother and therefore their spe-
cies. During this sensitive period, the young learn to follow a stimulus
and come to prefer that stimulus— a phenomenon called imprinting.
Imprinting increases the survival of the young because it ensures that
they stay close to the parent and, therefore, near food and shelter and
far from predators and other dangerous situations. The stimulus to be
followed must meet certain criteria; for example, it makes a particular
call note or type of movement. The criteria vary from species to spe-
cies, but the mother always meets these criteria. In the wild, a row of
ducklings scurrying after their mother is a common sight. However, as
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220 c BIOLOGICAL APPROACHES
Lorenz discovered, certain “unnatural” objects also meet the criteria.
Young birds have become imprinted on flashing lights, electric trains,
moving milk bottles, and a squatting, quacking Konrad Lorenz (see the
excerpt at the beginning of this chapter). Horses and sheep have also
become imprinted on humans.
In many species, imprinting has a long- term effect on sexual behav-
ior. Lorenz (1931) discovered that jackdaws raised by humans will join
a flock of jackdaws but return to their first love, a human, during the
reproductive season. They try to attract the human with their species’
courting patterns.
Ethologists also have identified sensitive periods for behaviors such
as learning bird songs, learning to distinguish males and females of the
species, acquiring language, and forming a bond between a newborn and
her mother. For example, mother goats form a bond with their young
in the first five minutes after birth. If the young are removed right after
birth for two hours, the mother attacks them upon their return. Waiting
five minutes after birth before removal, however, leads to their accep-
tance later (Klopfer, 1971).
Developmental psychologists have drawn on the concept of a sensi-
tive period to argue that early experience is particularly important for
adult behavior, as suggested by Freud and others. Furthermore, all stage
theories claim that at each stage the child is particularly sensitive to cer-
tain experiences, such as motor exploration in the sensorimotor period
(Piaget), the meeting of one’s needs by other people in the stage of trust
versus mistrust (Erikson), and the satisfaction or deprivation of anal
drives during the anal stage (Freud). Most nonstage theories also use the
concept of readiness— the idea that a child is most likely to learn from
an experience if it comes at the optimal time. The child may not profit
from being shown how to put objects to be remembered into categories
when she is 3 years old but may have increased recall as a result of this
experience at age 6. Moreover, sensitive periods are a central notion in
prenatal development. A particular drug taken by a pregnant woman
may have no effect or a devastating effect on the fetus, depending on its
stage of development.
In addition to sensitive periods, a second way in which biology indi-
rectly affects learning is through specific and general learning skills. Each
species learns some things more easily than others. Digger wasps have
excellent spatial memory. They can inspect up to 15 nests, decide how
much food is needed by each nest, and retain this information for the
entire day. Babies may be born biologically pretuned to learning language
quickly. They rapidly acquire language early in life, show universal forms
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Ethology c 221
of early utterances, and show babbling even if their parents are deaf and
have no spoken language. Although a fear of snakes is not innate, infants
as young as 7 months are predisposed to learn to associate snakes with
fear and to respond quickly to the sight of a moving snake (DeLoache &
LoBue, 2009). Moreover, 9- month- old infants are more attentive to evo-
lutionarily fear- relevant sounds (e.g., hissing snake, crackling fire) than
to modern fearful sounds (e.g., bomb exploding, tires screeching) or
pleasant sounds (Erlich, Lipp, & Slaughter, 2013).Young infants also are
experts in processing human faces. Early on, they can categorize female
faces as attractive or unattractive (based on adults’ ratings of attractive-
ness) and even prefer the attractive faces (Langlois et al., 1987; Ramsey,
Langlois, Hoss, Rubenstein, & Griffin, 2004), well before they possibly
could have been taught about cultural norms regarding attractiveness.
In addition to these specific learning predispositions, human infants
have evolved a tremendous general ability to learn. Humans are “spe-
cialists in nonspecialization” (Lorenz, 1959). We can construct novel
solutions to problems in various types of environments and can learn
from the consequences of our behavior. We also have hands that can per-
form many different actions and a language system that permits symbolic
thought and verbal communication. The advantage of this flexibility is that
we can adjust to a changing environment. The disadvantage of flexibility
is that humans are born with few specific ready- made behaviors, such as
running, that lead to survival.
As a result of humans’ biologically based general ability to learn, we
have developed cultures to help us adapt. The culture is passed on to the
next generation by imitation, instruction, and other forms of learning.
Thus, even cultural adaptation has its biological origins.
Methodology c Ethologists rely on two general methods for study-
ing behavior: naturalistic observation and laboratory experimentation.
The insistence on observing organisms in their natural environments
most clearly differentiates ethology from related disciplines such as
evolutionary psychology and sociobiology. Ethologists’ particular ver-
sion of naturalistic observation ranks as one of their main contributions
to psychology.
Naturalistic Observation c Theories and methods are closely connected.
Given the goal of understanding a behavior by seeing its function for adap-
tation, it is necessary to observe an animal in its typical environment.
Giraffes’ long necks make sense when we see giraffes eating leaves from
tall trees; we understand young gulls’ innate “freezing” rather than fleeing
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222 c BIOLOGICAL APPROACHES
in the face of danger by noting that their nests are built on narrow ledges
or steep cliffs ( Eibl- Eibesfeldt, 1975). In contrast, learning theorists
(see Chapter 6) observed rats pressing bars and pigeons playing tennis
in the laboratory— hardly typical species- specific behaviors. Interesting
natural behaviors, such as defending a territory or building a nest, are
not likely to occur in barren laboratory cages. From the viewpoint of
ethologists, psychology has worked backward historically by performing
laboratory research before obtaining a sufficient database of naturalistic
observations.
Observations of animals in captivity are inadequate because their
behavior may be abnormal due to their atypical environment. One cause
of abnormal behavior in this setting is the absence of sign stimuli that
would release fixed action patterns. Thus, behavior is often redirected.
Animals in laboratories or poorly designed zoos may restlessly pace
back and forth, constantly rock, and kill their young. Ironically, giving
too much care to a captive animal may cause problems. Titmice in a zoo
threw their young out of the nest soon after birth. The problem was that
food was provided by the zoo. The young quickly became full, stopped
gaping, and consequently were taken for dead by the parents. Young tit-
mice in the wild never stop gaping unless they are sick or dead (Koenig,
1951). In humans, abnormal behavior— for example, rocking— has
been observed in children in unnatural environments such as orphanages
and hospitals.
Ethologists’ naturalistic observations focus on developing an
ethogram— an extensive, detailed description of the behavior of a spe-
cies in its natural environment. This inventory includes the animal’s
behaviors, the characteristics of the setting, and the events immediately
preceding and following each behavior. The ethogram spotlights adaptive
behaviors, such as nesting and food gathering, and notes their frequency,
stimulus context, function, and ontogenetic development. A complete
description of the setting is particularly important, for it essentially
defines the animal that inhabits it: “If we specify in detail the niche of
a fish (its medium, its predators and prey, its nest, etc.), we have in a
way described the fish” (Michaels & Carello, 1981, p. 14). Ethologists
sometimes study human behavior by examining contemporary hunters
and gatherers in order to understand the environment in which current
human behaviors evolved. Finally, data about the frequency of behaviors
is important for interpreting a behavior when it occurs. The problem
of not having scientific data about frequency was noted long ago by
Thorndike: “Dogs get lost hundreds of times and no one notices it or
sends a scientific account of it to a magazine. But let one find its way
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Ethology c 223
from Brooklyn to Yonkers and the fact immediately becomes a circulat-
ing anecdote” (1898, p. 4).
Interestingly, ethologists have detected previously unnoticed patterns
of behavior by speeding up or slowing down their observational videos.
For example, a slower rate revealed an unnoticed part of the flirting
sequence— raising the eyebrows for only one- sixth of a second ( Eibl-
Eibesfeldt, 1975). A fast speed showed that people who eat alone look up
and around after every few bites, as if scanning the horizon for enemies,
as baboons and chimps do ( Eibl- Eibesfeldt, 1975). This is much less
obvious at a normal speed.
Once the function of a behavior is known from the ethogram, ethol-
ogists can understand the behavior further by comparing it with similar
ones in other animals. For example, they may find mother– child attach-
ment only in species in which the young are helpless, which suggests the
reason for that behavior.
Laboratory Studies c For an ethologist, a behavior has both a phylo-
genetic cause and an immediate cause. Phylogenetically, a spider spins a
web “because” that innate food- gathering behavior has allowed the species
to survive. Immediate causes could include specific physiological events,
particular inborn neurological pathways, the presence of a sign stimulus,
or motor experience. Ethologists clarify these various causes of behav-
ior suggested by the observational studies with controlled experiments,
similar to those done by psychologists. For example, by systematically
varying stimuli, they determine which attributes of a stimulus are criti-
cal for eliciting the response. They also examine the underlying physio-
logical mechanisms. Although the laboratory experimental method is
shared with experimental psychology, ethology maintains its distinctive-
ness by the content it chooses to study: behaviors tailored to the survival
of the species.
One laboratory method associated with ethology is determining
whether a behavior is primarily innate by preventing experiences that
could teach the behavior. For example, an ethologist interested in the
origin of nut- burying behavior raised squirrels in a cage with a bare
floor and provided a diet of only liquid food. The squirrels had no
exposure to other squirrels (who could serve as models), nuts, or earth
(which could provide digging practice). Under these conditions, squir-
rels demonstrated nut- burying behaviors at the same age as do squirrels
in the wild. When presented with a nut, they dug an imaginary hole
in the concrete floor, pushed the nut into the “hole” with their snouts,
covered it with invisible soil, and carefully patted down the “soil” to
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224 c BIOLOGICAL APPROACHES
finish the job ( Eibl- Eibesfeldt, 1975). Thus, since they had no oppor-
tunity to learn this behavior, it must be an innate fixed action pattern
of the species.
Contributions to Human Developmental Psychology
Ethologists are interested in the same categories of adaptive behaviors
in humans as in other animals, for example, feeding, communication,
parent– child interaction, and reproduction. The study of children has
focused primarily on infant attachment but also has examined topics
such as peer interaction and problem solving. A look at representative
research in each of these areas will show ethology’s imprint on both the
content and the methodology of developmental research.
Infant– Caretaker Attachment
Bowlby’s Theory c John Bowlby (1907–1990), a London psychoana-
lyst, is credited with bringing ethology to the attention of developmental
psychologists. Because World War II had left many children as orphans,
there were concerns about the effects of maternal deprivation. Bowlby’s
observations of infants separated for a long time from their mothers (see
the excerpt at the beginning of this chapter) led him to conclude that
early social attachment between infant and caretaker is crucial for nor-
mal development. Infants show their attachment when they cry when a
parent leaves, smile and babble when she returns, and seek her out when
they are stressed.
Drawing on observations of mother– infant attachment in nonhuman
primates, Bowlby (1969/1982) proposed that human attachment evolved
because it promotes the survival of helpless infants by keeping them
close to their mother and thus protected from predators or exposure to
the elements. One newborn reflex related to attachment is grasping an
object such as a finger or the hair when it contacts the infant’s palm, just
as many mammalian infants stay with the mother by clinging to her hair.
Another reflex is an embracing movement in response to a sudden loud
sound or a loss of support. This reflex may have helped ancestral infants
avoid falling when the mother suddenly ran from a predator.
Of course, human infants today do not depend on these reflexes for
survival, because they need not physically attach themselves to their
parent. Of more importance to human babies are signaling mechanisms
such as crying, babbling, and smiling. These behaviors communicate
infants’ needs and encourage adults to come to infants, since young
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Ethology c 225
babies cannot go to adults. Just as following the imprinted object in
ducklings maintains proximity, signaling behaviors serve this purpose in
humans. Another ability found in young infants that may facilitate their
relationship with their parents is imitation of parents’ head movements
and tongue protrusions (Meltzoff & Moore, 1989). As infants mature,
other behaviors, such as crawling, walking, and talking, facilitate contact
between parent and child.
Research supports Bowlby’s notion that at least some signaling behav-
iors are innate (and possibly even fixed action patterns). Even infants
born blind or blind and deaf acquire a social smile at approximately
6 weeks, as do seeing and hearing infants. In fact, children blind and deaf
since birth reveal a wide range of normal behaviors, including laughing,
crying, babbling, and pouting, and typical facial expressions of fear,
anger, and sadness ( Eibl- Eibesfeldt, 1975, 1989). It is highly unlikely
that adults teach these behaviors, because smiling and laughing involve
a complex sequence of coordinated movements or sounds. Even the
possibility that blind and deaf children might learn facial expressions by
touching the mother’s face and imitating her facial movements was ruled
out by a child deaf and blind since birth who was born with no arms.
Despite these handicaps, he showed normal facial expressions. Thus,
these behaviors have a strong innate component.
Bowlby proposed that early reflexes and signaling behaviors, along
with a bias toward looking at faces, leads to an attachment to adults in
general and then, usually around 6 to 9 months of age, to one or a few
specific adults. Separation from a specific adult may be an innate “cue
to danger” that elicits signaling behavior intended to restore proximity.
The infant and adult behaviors eventually become synchronized into
an “attachment behavioral system,” according to Bowlby. The appearance
and behavior of each member elicits certain behaviors in the other. Each
member of the system comes to expect that the other will respond to its
own behavior in certain ways. Infants’ expectations are part of their inter-
nal working models, discussed in Chapter 3—mental representations of
the attachment figures, the self, and the relationship. These models help
children interpret and evaluate new situations and then choose a behavior
such as playing or seeking the attachment figure for comfort. Between
the ages of about 9 and 18 months, an infant’s various individual behav-
iors, especially sucking, clinging, crying, smiling, and following, become
incorporated into more complex, self- correcting “control systems.”
Bowlby used control- systems theory from engineering as a model
of how attachment forms an organizational system. Control systems are
goal directed and use feedback to regulate the system in order to achieve
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226 c BIOLOGICAL APPROACHES
the goal. A simple control system is a thermostat, which maintains a
particular room temperature (the goal) by comparing the actual tem-
perature (the feedback) with the desired temperature. With respect
to behavioral systems, Bowlby proposed that genetic action causes the
behavioral system to develop but that the developed system is flexible
enough to adjust to changes in the environment, within prescribed lim-
its. That is, when infants detect that the adult is too far away (feedback
to the system), they correct this state by crying or crawling, which
reestablishes contact and re- achieves equilibrium in the system. The
limits of acceptable distance vary, depending on internal factors, such as
hunger or illness, and external factors, such as the presence of an adult
stranger or other cues of danger. The development of a secure attach-
ment expands the distance acceptable by establishing the caretaker as a
secure base from which the child can explore.
Bowlby’s theory of attachment includes many ideas from ethology.
Species- specific reflexes and fixed action patterns, which are the prod-
ucts of evolution, ensure proximity to the mother. Sensitive periods
and general and specific learning abilities biologically predispose infants
and caretakers to develop a system of synchronized interactions. As in
ethological theory, Bowlby observed children (though recent research
on attachment stimulated by his theory often is conducted in a labora-
tory). His colleague, Mary Ainsworth, developed methods for assessing
attachment (see below) and provided much of the empirical evidence
for attachment theory.
The ethological account of attachment, with its focus on innate behav-
iors, obviously contrasts with learning theory’s (Chapter 6) focus on
food or physical contact as reinforcement. Although it seems likely that
pleasant interactions have a positive effect on the bond between child
and adult, ethologists point out that attachment occurs even when the
attachment object physically abuses the infant. Ethological accounts also
differ from Freudian theory’s focus on the oral drive. Finally, ethology
differs from both traditional learning and Freudian theory in stressing an
infant’s effect on the parent as much as the parent’s effect on the infant.
Bowlby later (1980) incorporated into his theory some of the notions
of information- processing theory (Chapter 7). He explained unsatis-
factory early social relationships, abnormally strong repression, and
thinking disorders in part by general principles of selective attention
and selective forgetting. For example, if young children’s attachment
behavior is continually aroused but not responded to, they eventually
exclude from awareness the sights, thoughts, or feelings that normally
would activate attachment behavior.
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Ethology c 227
Bowlby continually applied his ideas about attachment to his clinical
work. Interestingly, his final book (1991), a biography of Darwin, traced
Darwin’s chronically poor health back to his failure to fully mourn his
mother’s death when he was 8 years old.
Adults’ Responsiveness to Infants c Ethology contributed the
important idea that adults, as well as infants, are biologically predisposed
to develop attachment. A caretaker typically begins to form an emo-
tional bond to a child in the first few hours or days of life, which encour-
ages caretaking and thus enhances the infant’s survival. Babies elicit adult
attachment behavior with signaling behaviors such as smiling, looking at
the mother’s face, and babbling, or by their babyish appearance.
The words of a 1926 popular song were: “Baby face, you’ve got the
cutest little baby face” (music by Harry Akst, lyrics by Benny Davis). An
infant’s babyish appearance may elicit caretaking. The infants of many
species, especially mammals, share certain physical characteristics depicted
in Figure 5.1—a head that is large in relation to the body, a forehead that
is large in relation to the rest of the face, limbs that are relatively short and
heavy, large eyes at or below
the midline of the head, and
round, prominent cheeks— in a
word, cuteness (Lorenz, 1943).
This babyishness is exaggerated
in baby dolls for children and
in young animals in the Disney
cartoon films. Interestingly, as
Mickey Mouse became more
lovable and well behaved over
the years, his physical appear-
ance became more babyish— a
larger head with softer, more
rounded features and larger
eyes (Gould, 1980).
Infants’ smiles also may be
powerful elicitors of adults’
attention. The adaptive signifi-
cance of an infant’s smile may
be to make a tired, busy mother
of a young infant feel that those
difficult first months are worth-
while (Robson, 1967).
F I G U R E 5 . 1
Characteristics of babyishness or cuteness com-
mon to several species.
[From “Die angeborenen Formen möglicher Erfahrung,” by
Konrad Lorenz, in Zeitschrift für Tierpsychologie, 1943, 5,
235–409. Reproduced by permission of Verlag Paul Parey,
John Wiley & Sons.]
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228 c BIOLOGICAL APPROACHES
The Developmental Course of Attachment c Very young infants
are predisposed toward attachment. For example, they prefer looking
at people’s faces, and they vocalize in response to human voices. They
also are biased toward looking at biological motion rather than random
movements (Bardi, Regolin, & Simion, 2014). Early on, infants learn
to discriminate their mother’s odor from that of others. Two- week- old
breast- fed infants turned toward a pad that had been worn in their moth-
er’s underarm area rather than a pad worn by another lactating female
(Cernoch & Porter, 1985). Likewise, mothers quickly learn to recognize
their infant’s distinctive smell. Six hours after giving birth, and after
only a single exposure to their babies, blindfolded mothers could pick
out, by smell alone, their own baby from a set of three babies (Russell,
Mendelson, & Peeke, 1983).
Attachment furthers infants’ learning about their environment,
because parents serve as a “secure base” for exploration in the first year or
two of life. Children venture away to explore the next room but return
from time to time for “emotional refueling” (Mahler, 1968). If, however,
a parent’s responses to children’s signals are inappropriate (unpredict-
able, slow, abusive, or not matched to the child’s needs), children feel
insecure and are less likely to use the mother as a base for exploring
a strange environment (Ainsworth, Blehar, Waters, & Walls, 1978).
Because the appropriateness of the adult’s responses is more important
than the total amount of interaction, infants become attached to parents
who work full time, if they respond appropriately to the child’s signals.
Ainsworth (e.g., Ainsworth et al., 1978) devised the “Strange
Situation” procedure, which lasts about 22 minutes, to assess babies’ pat-
terns of attachment to their mothers. The infant, a parent, and a stranger
in a laboratory setting proceed through a sequence of episodes, gradually
moving from low stress (infant with parent) to high stress (infant alone
with stranger). Based on their reactions to these events, children are
classified into four categories. Securely attached infants (the majority of
typical middle- class samples) cry when their mother leaves and greet
her happily, for comforting, when she returns. Insecure– avoidant babies
show little emotion when the mother leaves or returns. Insecure– resistant
babies are difficult to comfort on the mother’s return and show either
anger or desperate neediness toward her. Infants who do not fit into any
of these categories (e.g., no consistent way of dealing with stress; contra-
dictory behaviors) are called disorganized or disoriented (Main & Solomon,
1990). These infants sometimes have abusive parents.
A large literature (e.g., Cassidy & Shaver, 2008) shows that a dyad’s type
of attachment depends on many factors, including parents’ sensitivity to
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Ethology c 229
the child’s needs, stresses on the family, parental psychopathology, and
child characteristics such as Down syndrome or a difficult temperament.
Universally, secure attachment is the most common pattern, mater-
nal sensitivity influences infant attachment patterns, and secure infant
attachment leads to later social and cognitive competencies (Van
IJzendoorn & Sagi- Schwartz, 2008). However, the percentage in each cat-
egory shows some variability across countries. For example, in one study
(Van IJzendoorn & Sagi, 1999), U.S. and Western European groups showed
more avoidant infants than did groups from other regions. One reason for
the great interest in attachment type is that the categories predict later
social competence. In general, secure attachment predicts effective social
functioning during childhood and adolescence, and even later, whereas
insecure attachment is associated with various sorts of later psychopa-
thology, as discussed in the chapter on psychoanalytic theory. The initial
attachment pattern sets in motion particular styles of thinking, feeling, and
relating to others that continue to influence the way children negotiate their
environments throughout development. Also, work on young children at
developmental risk, such as children with Down syndrome, cerebral palsy,
or autism spectrum disorder, promises to broaden our understanding of
the variety of social attachments and the complex interweaving of genetic
and environmental forces (Vondra & Barnett, 1999). Today, attachment is
seen as a lifelong process of forming affectionate bonds with various people,
including romantic partners. In fact, assessments of adult attachment styles
have been developed and related to various kinds of social relationships,
including parenting (Frias, Shaver, & Mikulincer, 2015).
From a contemporary evolutionary perspective, attachment styles are
different solutions to the problems in the environment faced by a child
after birth. The particular style is an infant’s attempt to adapt to her
parents’ behaviors and the resources available in the environment. For
example, parents differ in their pattern of investment in their offspring
in terms of time, effort, and resources. Infants increase their chances
of survival if they can adapt to their particular caregiving condition
(Bugental, Corpuz, & Beaulieu, 2015). If parents are heavily invested in
their children and thus are sensitive and responsive, environmental risk
decreases and children can explore more freely from their safe base.
If, because of environmental pressures such as scarce food, parents are
unable or unwilling to invest heavily in caring for their children, resistant
or avoidant attachment may be more adaptive. In resistant attachment,
clinging to the caregiver could elicit whatever meager resources are
available. In avoidant attachment, a more independent infant can try to
obtain resources from other adults.
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230 c BIOLOGICAL APPROACHES
Issues about the attachment categories include the following
(Cassidy & Shaver, 2008): How stable over time is an infant’s attachment
classification? Should attachment be measured as categories or as a con-
tinuum? How broad is the effect of the early attachment category on
later social relationships and cognitive abilities? What is the child’s active
contribution (for example, temperament) to the attachment relation-
ship? How, if at all, do child- care arrangements affect type of attach-
ment? What accounts for the variability in a child’s attachment behavior
across situations? What specific effects does parental physical abuse of an
infant have on attachment type?
Peer Interaction
Ethologists argue that children are innately predisposed toward interact-
ing with other people in adaptive ways. Ethological studies of animals’
dominance hierarchies, aggression, play, altruistic behavior, and nonver-
bal communication have provided a powerful framework for observing
and interpreting these behaviors in children in natural settings ( Blurton-
Jones, 1972; McGrew, 1972).
A basic feature of the organization of nonhuman primate groups is
the dominance hierarchy— the ranking of members of the group according
to their power, especially regarding access to resources such as food or
mates (Hinde, 1974). This hierarchy indicates who can control whom.
It is adaptive because, once established, it lessens conflicts within the
group. These dominance hierarchies also construct the social environ-
ment into which an infant is born. For example, in rhesus monkeys,
which form large and complex social groups, the matrilineal (mothers’)
dominance hierarchies affect the rank of the infant. All members of the
highest- ranking matriline, even infants, outrank lower matrilines. Thus,
a newborn “inherits” the status of the mother and outranks even adults of
lower- ranking matrilines. Dominance hierarchies even affect how moth-
ers treat their infants. High- ranking mothers are more “ laissez- faire” in
their supervision of their young than are low- ranking mothers. The lat-
ter are more limited in the social situations from which they can rescue
their infants, so they are reluctant to let them explore much (Sameroff &
Suomi, 1996).
In humans, even 15- month- old infants can infer a social dominance
hierarchy from a series of videos showing pairs of adults in which one
person was dominant over the other (Mascaro & Csibra, 2014). These
hierarchies can be seen in preschoolers’ groups (e.g., Hawley & Geldhof,
2012) and in adolescent groups, in which popular peers are looked at
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Ethology c 231
more (Lansu, Cillessen, & Karremans, 2014). Within this structure, chil-
dren learn how to use both prosocial and coercive behaviors to negotiate
status and gain access to resources (Hawley, 2014). In particular, when
children enter elementary school, they learn that they must express
dominance in more subtle ways in order to obtain resources— what
Hawley (1999) calls “competing with finesse.” Prosocial strategies, such as
persuasion, cooperation, and helping, enable children to access resources
such as toys or friends in ways that foster acceptance and maintain group
harmony. Thus, aggression, or the threat of aggression, which usually is
considered a negative behavior, actually may be a positive adaptation for
a group and also provide opportunities to acquire the skills needed later
during adulthood. Similarly, boys’ rough- and- tumble group play may
enhance their ability to compete and permit them to evaluate each oth-
er’s relative strengths, which is one basis for dominance hierarchies. Such
observations of children’s groups demonstrate several characteristics
of ethological research. Researchers observe children’s adaptive behav-
iors, typically in natural settings, and compare them with that of other
primates. In response to conflicts, such as a struggle over a toy, a child
could, for example, submit, seek help, counterattack, give up the object
or position, or make no response. The child who wins in these encounters
is considered to be the more dominant. These categories of initiated con-
flict and response to the conflict are quite similar to those used to study
dominance in nonhuman primate groups.
Individual differences in peer interaction might be explained in terms
of social defense systems that have evolved for coping with negative peer
behaviors and protecting oneself from interpersonal threat (Martin,
Davies, & MacNeill, 2014). Children select a relevant strategy from a
large repertoire of defense strategies for defusing threats from peers.
A dominant child can threaten aggression. In contrast, a low- status child
may run away, use subordination behaviors to deflect harm and social
exclusion, or warily watch the dominant group members. These behav-
iors calm down the dominant members and avoid rejection from the
group. The heightened arousal, need to be vigilant for potential violence,
and frequent activation of the social defense system, may deplete the less
dominant child’s resources that could have been devoted to other sys-
tems, such as exploring or caregiving. More secure, dominant members
of the group do not have this high cost.
The ethological approach to children’s aggression clearly contrasts
with social learning theory’s focus on how a behavior (for example,
aggression) in individual children is affected by reinforcement, punish-
ment, imitation, and self- efficacy. And, unlike Freud, ethologists focus
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232 c BIOLOGICAL APPROACHES
on interpersonal processes of aggression more than individual psycho-
logical processes. Finally, Vygotsky’s theory gives more attention to
cultural contributions to aggression than does ethology.
Evolutionary psychology has addressed gender differences in social
behaviors, especially mating strategies and parenting behaviors. Other
behaviors for which evolutionary arguments have been made are male
competition and violence; gender differences in play, risk taking, and the
ability to inhibit behaviors; and parental investment in their children,
with applications to child abuse.
Problem Solving
I gather firewood
As if I had been at it
For a million years
—wiLLiam charLesworth, one year of haiku, 1978
The human brain is designed to solve daily problems in the human-
typical environment in which the species has evolved. This view of
intelligence differs greatly from other approaches to studying this topic.
The intelligence- testing approach views intelligence as a trait on which
people differ and assesses it on tests administered by an adult, usually
in an unfamiliar setting. Laboratory studies of problem solving (see
information- processing theory in Chapter 7) examine children’s think-
ing about novel tasks, out of context, usually in a laboratory. Ethology
lies closest to Vygotsky’s theory of cognition, among the various the-
ories, in that both address the fit between children and their social
environment.
Although even Darwin (1890) studied the “mental power” of earth-
worms, most of the research on cognition falls within the more recent
evolutionary psychology framework. Evolutionary psychologists sug-
gest that cognitive mechanisms may be the missing link between evo-
lution and human behavior; that is, evolution may have led to changes
in the brain, which changed thinking, which in turn changed behavior
(Tooby & Cosmides, 2005). Complex cognitive skills must have evolved
to solve problems such as finding a mate, hunting for food, recognizing
group members, communicating with others, warding off enemies,
raising offspring, and cooperating to obtain resources. People had to
attend to, encode, process, store, and retrieve relevant information,
such as remembering specific individuals and figuring out the costs and
benefits of interacting with an individual, especially whether to risk one’s
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Ethology c 233
life to help the person. In this way, evolution selects for the neurological
mechanisms that underlie adaptive social and cognitive behaviors.
Tooby and Cosmides (2005), two main voices of evolutionary psychol-
ogy, have identified Darwinian algorithms— evolved cognitive mechanisms
specific to particular domains. The mind is like a Swiss army knife, with
different tools for performing tasks well in different domains. Examples
of these “core domains” are face recognition, language acquisition, cer-
tain characteristics of objects, and certain types of processing of social
information. The brain consists of modules that process information
in these domains with little effort. Infants are programmed to acquire
and store certain sorts of information needed for solving certain sorts
of problems. Their behaviors generated by Darwinian algorithms bear
some relation to fixed action patterns but are more flexible, less tightly
wired to particular stimuli.
It is important to note that these cognitive skills enhanced adaptation
for our ancestral hunters and gatherers: “Our psyche is not built for
the present. It resonates to the vibrations of 200,000 generations ago”
(Thiessen, 1996, p. 159). We do not do much hunting and gathering these
days. Thus, the cognitive skills underlying these activities may not lead to
survival and reproductive fitness in today’s urban habitats. Still, we do
have these ancestral ways of thinking that continue to influence our devel-
opment and behavior in a world of shopping malls and computers, and the
task of an evolutionary psychologist is to reveal how they are expressed in
modern environments. One interesting hypothesis concerning the “mod-
ernization” of an ancestral cognitive module is that a module acquired to
process information in one domain, such as the acoustical properties of
the human voice, may be applied today to another domain, such as music.
Music itself may not be essential for survival, but it may come from a
module that is (Sperber, 1994).
One modification of the Tooby and Cosmides model is Geary’s (2005)
model, in which modules within a domain are organized hierarchically.
Lower- level modules process less complex information, which is integrated
to form higher- level, more complex, and flexible modules. For example,
infants have biases that orient them to important social stimuli and lead
them to imitate others. Information obtained from these lower- level mod-
ules combines with more flexible higher- level social- cognitive mechanisms,
to help children develop an understanding of themselves and other people,
and thus adapt to various social and physical environments (Bjorklund &
Ellis, 2014). Similarly, in concepts of the physical world, infants’ surpris-
ingly sophisticated understanding of objects and the ability to use tools is
integrated into more advanced and flexible understanding later.
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234 c BIOLOGICAL APPROACHES
Mechanisms of Development
Ethologists emphasize biological processes as mechanisms of develop-
ment. Physical maturation, including hormonal changes, motor devel-
opment, and increased efficiency of the nervous system, underlies the
emergence of sensitive periods or of fixed action patterns at appropriate
times. For example, nest- building behavior surfaces when a bird matures
to the point where reproduction is possible. All of the biological mecha-
nisms of behavior interact with experience, of course. In addition, innate
general and specific learning abilities built into the nervous system allow
the organism to profit from its experience.
Position on Developmental Issues
Human Nature
Human nature is just one hodgepodge out of many conceivable.
—WiLson, 1978, p. 23
Humans are social animals with certain species- specific characteristics.
Human intelligence, language, social attachment, and perhaps even aggres-
sion and altruism are part of human nature because they serve or once
served a purpose in the struggle of the species to survive. However, humans
select from their evolutionary heritage the behaviors that best help them
adapt to local circumstances— supportive or harsh caretaking, a resource-
rich environment or poverty: “ ‘Human nature,’ then, is in part decided by
the context within which we find ourselves (Hawley, 2014, p. 5).
Identifying the theory’s worldview highlights the differences among
ethological theorists. Lorenz stressed the mechanistic, automatic, elic-
ited nature of behaviors, such as reflexes and sign stimuli that elicit fixed
action patterns. This stimulus– response model is based on early views of
how the nervous system operates. In contrast, Bowlby and many modern
ethology theorists are more organismic and draw on systems approaches.
Humans spontaneously act to meet the demands of their environment
by actively searching for the parent or playmates or by exploring. In
Bowlby’s control- systems approach, an infant seeks to maintain a certain
state, for example, an acceptable degree of proximity to the caretaker.
Finally, the theory is contextual in its focus on links between a species’
evolutionary history and the present, and on the immediate physical and
social setting, to which an organism must adapt.
Qualitative Versus Quantitative Development c Ethology allows
for both qualitative and quantitative change. It is not a stage theory and
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Ethology c 235
therefore does not posit large- scale qualitative changes in development.
Qualitative change occurs when biological maturation reaches the
point where a sign stimulus triggers a new fixed action pattern. In this
way, a new behavior appears in a more or less discontinuous fashion.
Qualitative change also occurs when a system is expressed in different
behaviors as a child develops. One such instance is attachment, the
desire for which is expressed at first by crying or smiling and later by
crawling toward the mother or talking to her. The underlying attach-
ment, however, may be changing quantitatively, usually toward increased
organization and efficiency.
Nature Versus Nurture c Like Piaget, ethology was concerned with
how an organism adapts to its environment. Both identified biological
predispositions toward learning, for example, the assimilation–
accommodation process (Piaget) and specialized learning abilities (ethol-
ogy). Although ethologists focus on the biological basis of behavior, they
are quite aware that heredity and environment are intertwined through-
out the lifespan. Indeed, any evolved behavior requires some environ-
mental input for its activation. A particular experience has more impact
if it occurs during a relevant sensitive period rather than at another time.
Moreover, a given genotype may be expressed differently in different
environments. Also, one way to think about the importance of the envi-
ronment is that it selects for or against genetic mutations that occur.
It is the fit between the genes and a particular environment that is
adaptive, not just the genes themselves. The set of human genes evolved
within a particular environment, so it is adaptive for the “expectable”
environment into which most members of the species are born. This
environment, typical for the species, provides the relevant experiences
for expressing predispositions.
What Develops c The most important behaviors to develop are
species- specific behaviors that are essential for survival. These include
such behaviors as social attachment, dominance– submission, eating, mat-
ing, social cognition, and infant care. Both general abilities to learn or
process information and specific behaviors such as fixed action patterns
or domain- specific cognitive algorithms are applied to the environment
at hand. The theory seeks to explain similarities in what behaviors are
acquired and how they develop in all humans and in both humans and
other animals. Like for Piaget, the focus has been on what is universal for
a particular species. Biology constrains the range of possible differences
between cultures or within a culture.
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236 c BIOLOGICAL APPROACHES
Applications
Ethological work on attachment has had the most impact on real- life
topics such as orphanages, adoption, day care, prolonged separation
from the mother, and early contact between mother and child. A pop-
ular current parenting approach, “attachment parenting,” encourages
parents to keep their babies close and to respond promptly and appro-
priately when babies signal their needs. For a securely attached child,
a parent serves as a safe base from which to explore the environment
and establish independence. Parents should be sensitive to their children’s
emotional needs during separation caused by hospitalization or other
traumatic events.
Bowlby found pathological behaviors in children when they did not
receive adequate attention from a caretaker early in life. A more recent
project (Nelson, Zeanah, & Fox, 2007) has shown that early social
deprivation in the institutional rearing of infants abandoned at birth in
Bucharest, Romania, had serious negative effects on brain behavior and
nearly all aspects of development. For example, almost half of the chil-
dren appeared to suffer from one or several forms of psychopathology.
However, subsequent adoption into normal families reversed some of
these adverse effects, especially if adoption occurred early on. A variety
of interventions for infants at risk for not developing secure attachment,
as well as children and adolescents with attachment issues, have proven
successful (Cassidy, Jones, & Shaver, 2013). Researchers also have
applied attachment theory to policy concerning families with working
parents, or a parent in the military or in prison (Cassidy et al., 2013).
Evaluation of the Theory
Strengths c Both realized and potential contributions of ethology to
developmental psychology are explored in three areas: theory, method,
and content.
Theoretical Contributions c Ethology broadens our perspective on
what constitutes an explanation of development. We can fully understand
children’s behavior only if we expand our vision to include a larger space
(the larger social context) and a larger time span (the history of the spe-
cies). Tinbergen (1973) identified four types of questions about the causes
of behavior that developmentalists should try to answer about their topic
of study. The questions are based in part on the time span involved, which
varies from seconds to centuries. These “four whys” pertain to causes that
are immediate, ontogenetic, functional, and phylogenetic.
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Ethology c 237
1
Immediate causes are the external or internal events that occur
directly before the behavior. They provide clues as to the causal
mechanism. An infant smiles after viewing a human face or cries as
a result of hunger pangs.
2
Ontogenetic causes encompass a longer time span— the genotype
and the environment interact to produce changes in behavior over
an individual’s lifetime. In this process, earlier events contribute to
later events, as when a secure attachment may cascade to later positive
relationships and social competence.
3
Functional causes involve the immediate adaptive value of a behav-
ior. An ethologist asks, “What is this behavior trying to achieve?”
Children behave in certain ways because they want to obtain food,
protection, desired resources, and social support.
4
Phylogenetic causes lie in the earlier forms of the behavior as it was
shaped over generations as a result of the food supply, types of pred-
ators, mating patterns, and so on. Thus, human social cognition may
have evolved because of the need for hunting and gathering together.
Most developmental research has examined immediate causes or
ontogenetic causes rather than functional or phylogenetic ones, but the
latter two are needed as well for an adequate account of development.
Knowing the function of a behavior helps the investigator relate a child’s
behavior to its natural context. For example, the way that investigators
think about children’s aggressive behavior changes if they discover that
one of its functions is to increase the overall stability and cohesiveness
of the group. The focus changes from a problem in the child to a fea-
ture of human groups. As for phylogenetic causes, among the theorists
in this book, only the ethologists and Gibson (see Chapter 8) take an
evolutionary perspective. Piaget was concerned with adaptation to the
environment but paid little attention to evolutionary processes.
Few human behaviors today are a matter of life and death, such as
avoiding predators, and children with mental disabilities, poor health,
or physical disabilities are protected, so they may survive and repro-
duce. Thus, survival of the fittest is much less apparent as an evolution-
ary force. Developmentalists may find it most useful to draw on the
concept of adaptation for understanding how a society may produce
optimal adaptation (rather than biological survival). Optimal adaptation
might include happiness, a feeling of competence at play, success at
school, and efficient use of tools such as eating utensils, scissors, and
computers.
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238 c BIOLOGICAL APPROACHES
Thinking about how a child’s behavior might be adaptive also can sug-
gest new hypotheses about development. For example, behaviors that
seem maladaptive actually may confer advantages in certain develop-
mental niches. For instance, children with a strong tendency to approach
novel but potentially dangerous situations tend to develop disruptive
behaviors (e.g., Davies, Cicchetti, & Hentges, 2015). However, this risky
behavior may be adaptive in adverse environments by making it more
likely that children will find new, resource- rich, settings ( Gatzke- Kopp
2011). Thus, ethology offers a more balanced perspective by considering
both the costs and benefits of any developmental pathway, even when
the behaviors are considered psychopathological (Martin et al., 2014).
Methodological Contributions c What can we learn from scientists
who spend hours staring at crabs and birds? Regarding developmental
psychology’s focus on laboratory research rather than naturalistic obser-
vation, Bronfenbrenner characterized the discipline as the “science of
the strange behavior of children in strange situations with strange adults
for the briefest possible periods of time” (1977, p. 513). Moreover,
developmentalists rely too heavily on the questioning of children. As
Charlesworth commented, “As soon as a research subject has the appro-
priate Piagetian operations and can talk, researchers stop observing and
start asking. It’s less strenuous that way” (1988, p. 298).
Laboratory studies tell us what can happen during the attentional pro-
cess. Ethological observation in natural settings tells us what in fact usu-
ally does happen and what function the behavior has. Ethology provides
theoretically based observational methods that can fruitfully be combined
with traditional developmental laboratory methods. As an illustration,
consider what ethologically oriented observational studies might con-
tribute to the understanding of the development of attention, typically
examined in the laboratory. Lab research assesses infants’ preferences for
attending to one of two stimuli placed in front of them or older children’s
attention to physical attributes, such as shape, color, or size. A child looks
preferentially at one object rather than another, sorts the objects, or tries
to remember them. An ethologist, in contrast, would shift the focus of
such research by asking the following questions: What types of objects or
events do children look at or listen to at home and at school? Do chil-
dren mainly look at people or nonsocial objects and events? What events
distract young children? Does efficient attention lead to efficient problem
solving or other adaptive behaviors? Does playful, exploratory attention
resemble that observed in other primates, humans of other ages, and
other cultures? Such observational studies would suggest new variables
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Ethology c 239
to be examined in depth in the laboratory. In a similar way, ethological
methods could be applied fruitfully to the other theories examined in
this volume. We know little about when and how often children engage
in problem solving (Piaget and information processing), displaced aggres-
sion (Freud), or collaborative learning (Vygotsky).
Content Contributions c Ethology has influenced developmental psy-
chology by showing the importance of behaviors such as attachment
and the structure of peer groups. A rich set of data about attachment
provided a foundation for the neuroscience and genetic research on the
long- term impact of poor early parenting described later in this chap-
ter. Similarly, the information about human phylogenetic change from
ethology and evolutionary psychology provided a backdrop for current
developmentally oriented evolutionary approaches (e.g., Bjorklund &
Ellis, 2014; Tomasello, 2014). More generally, observations of the social
behavior of other primates, especially their apparent “mindreading” of
their peers (e.g., Kaminski, Call, & Tomasello, 2008) has stimulated
similar topics in children.
Weaknesses c The following are critical shortcomings in theoretical,
methodological, and substantive areas that must be addressed by etho-
logical theory if it is to fulfill its promise as a theory of development.
Some of these shortcomings merely reflect a lack of developmental
research in certain areas; others are more serious because they reflect
the incompleteness of the theory itself.
Theoretical Limitations c Many of the ethological notions that are
most useful to developmental psychology require further elaboration if
they are to serve as specific explanations of development. For example,
by what processes do sensitive periods begin, have their effect, and end?
Are the effects of contact between mothers and their young infants due
to biological, social, or cognitive variables or all these variables in interac-
tion? What makes infants predisposed to attend to particular stimuli? The
neuroscience and genetic approaches described later are beginning to
identify the mechanisms that could answer these questions. Similarly, the
cognitive foundation for adaptive behaviors is not well worked out. For
example, by what cognitive processes do children detect and understand
a dominance hierarchy in their peer group and their own place in it? How
do children interpret social cues that could provide this information? The
development of transitive reasoning (A > B > C . . . ) may be necessary
for perceiving a dominance hierarchy (Edelman & Omark, 1973).
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240 c BIOLOGICAL APPROACHES
More specificity also is needed for theory- based predictions: What
specific aspects of a secure or insecure attachment predict specific future
social competencies? As Thompson noted, “It is as important to deter-
mine what a secure attachment does not predict to, and why, as it is to
understand its network of predictable consequences” (1998, p. 48). If
the various attachment patterns are adaptive for different environmental
situations, then the expected long- term outcomes of each attachment
type are not so obvious.
Another problem concerns identifying the function of a behavior.
The evolution of anatomical structures can be gleaned from fossils,
but we have no fossils of human behavior. At best, we can examine
other primates, contemporary hunter– gatherers, skulls, DNA, and
archeological data such as diseases, housing, cultural artifacts, age dis-
tributions, and tools. We can speculate about how an upright stance,
enlarged brain area, and increasingly sophisticated tools reflect changes
in human behavior in our history. We can hypothesize what sorts of
cognitive demands were made on early hunters and gatherers and the
extent to which these demands are similar to or differ from those in
modern human environments. What was adaptive generations ago may
not be adaptive today, however. For example, a preference for fats and
sugars was adaptive in our early history, but not now, and in fact leads
to obesity and Type 2 diabetes. As another example, attention- deficit/
hyperactivity disorder (ADHD) may consist of tendencies that were
adaptive in early humans (Jensen et al., 1997). Rapid scanning, quick
responses, and high motor activity work better for monitoring threats
and escaping from enemies than for reading and concentrating on home-
work. Moreover, the function of a behavior may be far from obvious.
“Morning sickness” and the food aversions associated with it during early
pregnancy may protect the fetus from toxic foods at a time when it is
most vulnerable (Profet, 1992). Food aversions are most common for
foods high in toxins.
Methodological Limitations c One obvious limitation to applying
ethological methods to humans is that the most critical experiments
are unethical. We cannot perform experiments such as preventing an
infant from seeing a human smile for the first few weeks of life in order
to see if the social smile is innate. In an early, misguided experiment,
Frederick II (1194–1250) raised babies in silence and near isolation to
find out if there is a “natural” human language. The babies, not surpris-
ingly, died before the outcome was clear (Wallbank & Taylor, 1960).
Instead of experiments, we must rely on naturally occurring atypical
situations, such as infants born blind or deaf, institutionalized infants,
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Ethology c 241
or infants of mothers who are hospitalized and thus absent for a long
period.
A limitation to naturalistic observation is that it is not clear what
constitutes a “natural environment” for children in a highly technologi-
cal society. Should we study children running through a meadow, sitting
in a classroom, or playing electronic games? Moreover, developing a
comprehensive ethogram of human infants would be a time- intensive,
expensive undertaking. As Charlesworth noted, “Unlike most tests,
which throw out a small net with a small mesh, the present method
throws out a big net with a small mesh and thereby catches many small
fish. Herein, of course, lies a big problem of effort and cost. The net gets
awfully heavy very quickly” (1979, p. 522). It also is not always clear
what behaviors are relevant. An observer unfamiliar with Bowlby’s work
might well record that the infant crawled to the door of the adjoining
room but would probably not record the distance between the mother
and the infant.
Content Limitations c Certain psychological phenomena that are not
consistently reflected in spontaneous overt behavior may be difficult to
study from the ethological perspective. Cognition is a good example.
A researcher might be limited to studying overt behaviors, such as
removing a physical barrier blocking a desired object. Since cognition
and motivation become more complex with increasing age, ethological
observations may in general be more informative in infants and toddlers
than in older children.
Contemporary Research
The influences of ethological and evolutionary theory on developmental
psychology can be seen most clearly in three contemporary topics—
attachment, the evolution of human cognition in social groups, and
adaptation during development.
Attachment c Research on attachment categories was presented earlier
in this chapter, and work on internal working models appeared in the
Freud section of this book. Most contemporary research on attachment
focuses less on categories of attachment and more on psychological
and biological processes involved in both child attachment and relevant
parenting behaviors. The focus is on the process of forming a socioemo-
tional relationship between parent and child, with attention given not
only to parent effects on children but also how child factors, such as
temperament, affect the parent (Laible, Thompson, & Froimson, 2015).
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242 c BIOLOGICAL APPROACHES
A typical model of the development of attachment is the following
(Cassidy et al., 2013): Children develop an attachment behavioral sys-
tem, which is an organized system of behaviors with the goal of estab-
lishing proximity with the parent in order to obtain protection. The
parent’s state of mind regarding attachment contributes to both their
caregiving behavior and their child’s attachment. The child’s attachment
consists of two- way interactions between an internal working model and
physiological processes. The child’s attachment then contributes to her
developmental trajectory— either successful psychosocial functioning or
psychopathology.
Much of the recent research identifies correlates between parenting
quality and infant attachment, or between attachment categories and
later child behaviors (e.g., empathy, compassion, altruism, internalizing
or externalizing symptoms) and adulthood functioning (e.g., roman-
tic relationships; parenting behaviors). Particularly of interest are the
mechanisms underlying these links. Recent breakthroughs in genetics
and neuroscience have provided additional levels of explanation of the
process of attachment. For example, researchers have identified geno-
types associated with the various attachment styles, particularly disor-
ganized attachment (Spangler, Johann, Ronai, & Zimmermann, 2009).
Contemporary neuroscience models of attachment generally propose
that the brain systems underlying attachment involve sensitivity to threat
in the environment and regulation of attachment- related behaviors and
emotions (Gillath, 2015). Brain imaging is clarifying the child and par-
ent neural correlates of attachment categories, such as underlying brain
networks or brain volume. For example, mothers showed different
brain responses when viewing their own 3- to 6- month- old infant’s face,
compared to the face of another infant (Esposito, Valenzi, Islam, Mash, &
Bornstein, 2015). Thus, today attachment is viewed as a process involv-
ing genetics, physiology, cognition, emotion, and behavior.
New directions in attachment research include the role of attachment
style in constructing enduring patterns of response to stress, relations
between attachment and health and immune function, school readi-
ness, and culture (Cassidy, Jones, & Shaver, 2013; Rholes & Simpson,
2015). For example, insecure attachment during childhood and adult-
hood is related to altered stress responses, which affect the immune
system and lead to poor health outcomes (Pietromonaco & Powers,
2015). Researchers also have added biological measures. Of particular
interest is the role of the neurohormone oxytocin in promoting social
bonding. For example, over the first three years of life, parents’ oxy-
tocin levels predict their children’s oxytocin levels (Feldman, Gordon,
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Ethology c 243
Influs, Gutbir, & Ebstein, 2013). The child’s social reciprocity with a
friend was correlated with the child’s oxytocin levels, the mother’s
oxytocin- related genes and hormones, and mother– child reciprocity.
One important unanswered question concerns the mechanisms under-
lying the intergenerational transmission of attachment— how a child’s
attachment category links to her adulthood attachment category, and
how the latter, through the adult’s state of mind regarding attachment,
affects her parenting behaviors and thus her child’s attachment. In other
words, what are the relations between the caretaking system and the
attachment system (Cassidy et al., 2013; Jones, Cassidy, & Shaver, 2015)?
Another important question concerns whether the findings largely based
on maternal behavior apply to fathers as well.
Evolution of Human Cognition in Social Groups c The five species
of great apes (gorillas, orangutans, chimpanzees, bonobos, humans)
share a common ancestor from approximately 15 million years ago, and
the last three share a common ancestor from about 6 million years ago
(Tomasello & Herrmann, 2010). What is unique about human cogni-
tion? The great apes have considerable genetic similarity: Chimpanzees
and modern humans, for example, share approximately 95 percent to
99 percent of their genetic material, a proportion similar to that of lions
and tigers or rats and mice (King & Wilson, 1975). The other great apes
clearly have certain humanlike cognitive and social skills and, in fact, are
surprisingly sophisticated cognitively (Call & Tomasello, 2008). They
understand the physical world much like humans do. They can count,
communicate, recognize themselves in a mirror, and understand object
permanence. They also can deceive others of their species so that they are
misled as to the location of food, engage in pretense, and predict others’
behavior on the basis of their emotional states and direction of locomo-
tion. Chimpanzees have been observed pretending to pull an imaginary
pull toy and even carefully disentangling the imaginary string (Hayes,
1951). They understand kinship and dominance relations, and they will
select an appropriate ally, such as someone dominant over their oppo-
nent. Great apes even understand certain mental states. Chimpanzees,
in a within- species competitive game, showed that they know whether
their competitor knows or does not know something, though they did
not understand false belief (Kaminski et al., 2008). Thus, “chimpanzees
know what others know, but not what they believe” (p. 224).
Human thought is unique mainly in the ability to engage in joint atten-
tion and cooperative communication, and thus coordinate efforts and
collaborate (Tomasello, 2014). These cognitive skills are possible because
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244 c BIOLOGICAL APPROACHES
humans can think about others’ perspectives, reflect on their own think-
ing, and think about others’ thinking and one’s own in a recursive way
(“He’s thinking that I’m thinking that. . . .”). That is, humans can represent
others’ thinking (including false beliefs), interpret their perspectives, and
monitor their own thoughts. These skills evolved when ancestral humans
faced problems presented by attempts to collaborate and communicate
with others. Specifically, early humans’ small social units required them
to hunt collaboratively to acquire enough food. In order to collaborate,
they had to be able to recognize others, communicate at least nonverbally,
and form long- term social relationships. Collaboration also encouraged
members to help each other so they would be available for future collab-
oration. Later, when societies became so large that members could not
know all group members, humans came to rely on information about
who belonged in their group. These ideas have generated research with
children. Infants start helping others around 12 to 18 months (Warneken,
2015). By age 3½, they act prosocially toward their collaborative part-
ners, and by age 5, both collaborating with others and belonging to the
same group (even if the assignment to a group was arbitrary— a green
group and a yellow group) led children to prefer, help, and trust their
collaborative partners (Plötner, Over, Carpenter, & Tomasello, 2015).
More generally, young children tend toward an in- group bias of liking,
acting positively to, and feeling obligations to their own group, and a
bias toward viewing out- groups negatively (Rhodes, 2013).
The economic necessity for larger groups with coordinated roles
and perspectives, shared understanding that permitted communicating
through language, and collective intentions, also led to the development
of culture— norms and institutions (Tomasello, 2014). Humans’ social-
cognitive skills permitted them to engage in cultural learning and pool
their cognitive resources. Humans can work together to create new
knowledge about objects, quantities, tools, and social relations that
cannot be created by a single individual. Cultural artifacts, such as lan-
guage and other social tools or systems of belief, were developed in each
generation and taught to the next. Although young chimpanzees can
communicate and learn how to use tools from adult chimpanzees around
them, only humans show cultural transmission— an evolved biological
mechanism that enables children to take advantage of the knowledge
and skills acquired over generations by the species. Children grow up
surrounded by the very best tools and symbols that the species has
developed. A simple example, based on evidence from physical artifacts,
is that during human evolution hammers changed from simple stones to
stones tied to sticks to modern metal hammers and mechanical hammers
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Ethology c 245
(Basalla, 1988). Humans were able to improve the tool because they
understood what the purpose of the tool was (that is, what people
intended to do with the hammer); they could go beyond simple imitation
of someone using a particular type of hammer.
As a result of this evolutionary heritage, young infants can develop the
knowledge that other humans are like themselves, with intentional and
mental properties. The mirror neuron system discussed in Chapter 6—
brain activation that is similar to that of the person observed performing
some behavior (e.g., Keysers, Thioux, & Gazzola, 2013)—may facilitate
young children’s understanding of the psychological causes of another’s
behavior. Tomasello refers to the “9-month social- cognitive revolution”
in which infants begin to understand others as intentional beings. They
see others as similarly motivated by goals and thus begin to share atten-
tion, as well as intentions, with other people, toward objects and events.
Once this social cognitive skill evolved, humans could “imagine them-
selves ‘in the mental shoes’ of some other person, so that they can learn
not just from the other but through the other” (Tomasello 1999, p. 6). In
this way, infants understand why others are using a tool or symbol— what
the person intends to do with it. With this understanding, children can
engage in cultural learning and become full participants in various cul-
tural rituals and games. Language obviously is particularly important,
for example, to ensure that children engage in complex interactions
with others that demand negotiation.
Adaptation During Development c Many species have adapted to their
environments by evolving specific innate behaviors. In contrast, humans
have adapted by evolving plasticity— flexibility in the hormonal system,
the expression of genes (see later), and, especially, the brain. Thus, in
humans, adaptation is a developmental phenomenon, as the young learn
about their environment and adapt to their particular local conditions.
The young brain exhibits flexibility, but this decreases as brain regions
becomes specialized to respond mainly to certain kinds of stimuli, such
as faces or moving bodies. This plasticity is adaptive because it keeps the
brain open to learning about the specific features of the child’s particular
environment (Bjorklund, 2007; Bjorklund & Ellis, 2014; Bugental et al.,
2015). Moreover, understanding the complex human social structure
requires a big brain, which necessitates an extended infancy and child-
hood. This extended period for maturity is a risky strategy for the human
species, because infants cannot obtain food or flee from enemies on their
own. Moreover, it takes a lot of cognitive resources to constantly scan
and evaluate environments.
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246 c BIOLOGICAL APPROACHES
Early childhood is a sensitive period during which children learn
about positive (e.g., resources) and negative (e.g., violence) aspects of
their environment and use this information to adapt by calibrating their
developmental trajectory (Bugental et al., 2015). Specifically, they learn
what physical and social resources are available in the environment, how
predictable these resources are, how trustworthy other people are,
whether close relationships are likely to last, and what threats exist.
For example, early experience with “growing up in poverty, exposures
to violence, harsh childrearing practices . . . shifts resource allocations
toward more risky and aggressive behavior, earlier pubertal timing
and sexual debut, enhanced early fertility, less stable pair bonding,
more offspring, and less parental investment per child” (Bjorklund &
Ellis, 2014, p. 237). In earlier evolutionary times, this strategy would
have maximized people’s reproductive success (Bugental et al., 2015).
It may be that the predictability of the environment is key. Having
an unpredictable, rapidly changing environment (e.g., moving a lot,
parents changing jobs frequently, divorce) from birth to age 5 is the
best predictor of this fast- track developmental trajectory (Simpson,
Griskevicius, Kuo, Sung, & Collins, 2012). Moreover, this early adaptive
strategy of impulsivity and risk taking developed in uncertain environ-
ments affects later behaviors during adulthood; how adults respond to
indicators of current resource scarcity (impulsive and risky decisions)
depends on their childhood socioeconomic status not their current one
(Griskevicius et al., 2013).
Adaptation during development is constrained by many factors, such
as species- specific genes, the child’s developmental level (e.g., how
much information about the environment can be processed), the nature
of developmental mechanisms (e.g., small rather than large leaps in
cognitive change), and characteristics of the environment (e.g., avail-
able resources). Thus, children inherit the ability to modify their own
development so that it is maximally adaptive to local conditions, but
within limits, and with the possibility of making wrong choices. Still,
this imperfect evolutionary strategy may be the best balance between
wired- in behaviors and total plasticity.
Bjorklund (Bjorklund, 2007; Bjorklund & Ellis, 2014) argues that
although some of children’s behaviors were selected for and are devel-
oping because they will lead to an adapted adult, some may have evolved
because they serve an adaptive function only at a particular time in
childhood. Certain reflexes, such as the grasping reflex, are present in
newborns but then disappear several months later after they have served
their purpose of aiding survival during that particular period. Also, the
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Ethology c 247
cognitive immaturity that goes along with brain plasticity during child-
hood allows time for play, which may provide a sense of mastery and
self- efficacy that encourages children to try out new activities and roles.
These activities and roles provide opportunities for learning new skills.
Even behaviors that seem maladaptive actually may be adaptive. For
example, toddlers’ limited working- memory capacity may be adaptive
for language learning. The reason is that restricting how much language
information can be processed simplifies the language corpus that is
analyzed, and this in turn simplifies the process of acquiring language.
Children first may acquire single syllables and then gradually deal with
more information and increasingly complex information. If children
could initially process more linguistic information, they might be over-
whelmed by the amount of information and not be able to extract any-
thing useful. In this case, less is more (Newport, 1991).
An example of immature, but advantageous, cognitive skills from the
preschool period is children’s poor awareness of their cognitive perfor-
mance, for example, their vastly overestimating how well they perform,
even after feedback that they have performed poorly (see Chapter 7).
Until approximately age 7, children unrealistically think of themselves as
“one of the smartest kids in my class” (Stipek, 1984). This seemingly non-
adaptive characteristic may in fact be quite adaptive. This Pollyanna atti-
tude may encourage them to keep trying to do activities that are beyond
their current ability level. In this way, they obtain valuable experiences
that strengthen their skills. Because they do not expect to fail, they may
not be afraid to try out a variety of new activities. This optimism and
disregarding negative feedback also may be seen when children continue
to use a good, new strategy that does not yet help them (Miller & Seier,
1994; see Chapter 7). This attitude keeps them using and thus strength-
ening the new strategy until it can help them. Another adaptive cogni-
tive immaturity may be Piaget’s notion of egocentrism. Children’s bias
toward perceiving and conceptualizing in terms of their own perspective
obviously limits social understanding and interaction, but it may help
them in other ways. Given that people tend to remember better when
they relate the information to themselves (e.g., Pratkanis & Greenwald,
1985), egocentrism actually may help young children’s recall. Thus,
although we tend to see young children’s apparent limitations as evi-
dence that they are less advanced than older children and adults, they
may be quite well adapted to the demands of their particular develop-
mental period.
In sum, ethology and evolutionary psychology have made signifi-
cant contributions to developmental psychology. They provide a larger
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248 c BIOLOGICAL APPROACHES
temporal context in which to view development. The focus on the func-
tion of molar behaviors complements the focus of most current biologi-
cally oriented developmental work on cells and the brain. We now turn
to two main contemporary biological perspectives on development—
developmental neuroscience and genetics.
Developmental Neuroscience
The human brain has evolved relatively recently:
If we compressed the 4.5 billion year history of the Earth into a 24-hour
period, the first single- cell organisms would have emerged around
18 hours ago, the first simple nervous systems separating animals from
plants would have emerged around 3.75 hours ago, the first brain would
have emerged about 2 hours and 40 minutes ago, the first hominid brain
would have emerged less than 2.5 minutes ago, and the current version
of the human brain would have emerged less than 3 seconds ago.
(Cacioppo & Cacioppo, 2013, p. 667)
The boom in research exploring the human brain began in the 1990s,
designated the “decade of the brain.” This exciting new work was stim-
ulated by new technologies of brain imaging that generate maps of
brain activity. Here are some of the more common techniques: Several
measure currents produced by electrical activity of brain neurons— for
example, electroencephalography (EEG; sensor electrodes placed on
the scalp) and magnetoencephalography (MEG). Others measure brain
activity indirectly, by assessing blood flow and oxygenation as an indica-
tor of increased neural activity— for example, functional magnetic reso-
nance imaging (fMRI) and near- infrared spectroscopy (NIRS). MRI uses
a magnetic field and pulses of radio wave energy. DTI (diffusion tensor
imaging)—a variant of MRI that detects the movement of water— can
be used to infer information about the pathways of brain white matter
(brain tissue containing nerve fibers). PET (positron emission tomog-
raphy) uses radioactive tracers in a dye injected into the bloodstream.
Each of these technologies has strengths and weaknesses for describ-
ing the structure and functioning (changes in activity) of the brain (see
de Haan, 2015). For example, some tell us more about spatial patterns
of brain activity, and others tell us more about the time course of this
activity. Techniques vary in their spatial resolution and their temporal
resolution of a moving image. Some (e.g., EEG) can be used with very
young children but are limited because they do not probe deeply into
the brain. PET cannot ethically be used with children because of the
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Developmental Neuroscience c 249
radioactive tracers. Moreover, there obviously are challenges with doing
neuroimaging with squirmy young children, but researchers are devel-
oping creative ways to do this. Thus, the choice of a technique depends
on the research question and the person’s age.
Neuroimaging methods reveal brain functioning when, for example,
a picture or sound is presented. Thus, one could compare the patterns
of brain activity in children of different ages or ability levels working
on the same task, to infer developmental differences in cognitive pro-
cessing. Or children of the same age might engage in different sorts of
tasks thought to activate different cognitive skills, such as numerical and
spatial reasoning. This approach provides information about the relations
among brain regions (and among concepts). The patterns of brain activ-
ity associated with the two tasks might show both commonalities and
domain- specific activity, thus addressing the issue of whether children’s
thinking forms a general stage or domain- specific areas of knowledge.
Neuroimaging initially focused on identifying the particular region of
the brain primarily associated with particular cognitive activities, emo-
tions, or behaviors. More recently, models depict neural networks that
may involve several regions of the brain. Also, measures have expanded
beyond detecting brain activity to include anatomical measures, such as
thickness of the cerebral cortex, that might show significant develop-
mental changes.
In addition to providing information about the brain correlates of
behavior, neuroimaging makes several contributions to assessment of
abilities. Some imaging techniques can be used with infants, which is an
important methodological contribution to developmental psychology,
given that infants have few behaviors that can be used for assessment.
Another methodological contribution is that imaging sometimes pro-
vides more sensitive assessments of social or cognitive skills that are not
yet detected by behavioral measures. For example, after an eight- month
exercise program, obese children showed brain changes in their fMRI’s
consistent with improved executive function— a change that was not
detected on standard behavioral assessments (Krafft et al., 2014).
A few words about brain anatomy and functioning can set the stage
for a discussion of brain development by showing the enormity and com-
plexity of the brain: “The brain is rather like a large, very wrinkled wal-
nut” Karmiloff- Smith (2012, p. 3). If all the surface of the brain were laid
out flat, it would be about the size of a football field. The fibers in white
matter, laid into a line, would stretch 100,000 miles, enough to circle
the earth four times. There are approximately 100 billion neurons in
the brain. Each neuron might connect to approximately 1,000 neurons.
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250 c BIOLOGICAL APPROACHES
The cerebral cortex, which is critical for humans’ advanced cognition,
language, and perception, accounts for 80 percent of the brain’s vol-
ume. For the purposes of this chapter, it is most important to know
that the frontal lobes, at the front of the brain, involve activities of great
interest to psychologists, such as thinking, intentionality, voluntary
movement, personality, and attention. As for brain functioning, this
occurs at various levels. At the cellular level, chemical substances such
as neurotransmitters (e.g., dopamine and serotonin) transmit signals
across a synapse (connection between neurons) to another nerve, muscle,
or gland. At the brain level, activated neural networks across various
regions collaborate to produce thought, feeling, or behavior. Finally, any
one region of the brain carries out many functions, though it may be
more responsible for particular functions.
The following section describes some of the main themes of brain
development and its links with behavior. It provides an overview, rather
than a detailed technical account, in order to focus on models of devel-
opmental neuroscience. These themes are derived mainly from several
recent key sources in this area (e.g., Johnson & de Haan, 2015; Stiles,
Brown, Haist, & Jernigan, 2015).
Brain Development
1
Early anatomical changes Important structural changes in the
brain occur in the first few weeks and months of life: For example,
the rapid increase in myelin (insulation around the nerve fibers)
increases the speed and efficiency of the transmission of neural signals
and thus enhances information processing (see Chapter 7). As discussed
in the neo- Piagetian section of Chapter 2, being able to think about, and
manipulate, larger amounts of information is necessary for moving to
the next cognitive level. Although this anatomical change is most rapid
in the first few years of life, the efficiency of information processing
continues to improve until late adolescence or early adulthood.
2
Strengthening or pruning of connections between neu-
rons A major task for the brain, especially in the first two years
of life, is to form connections between neurons as a result of envi-
ronmental stimulation. These neural networks, which typically involve
numerous neurons, become increasingly refined through late adoles-
cence and continue to change throughout the lifespan. Infants have many
more neurons and synapses than end up actually being used. This is one
reason why the human infant brain has so much plasticity for adapting to
local conditions. Neural pathways that are not used are pruned away— a
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Developmental Neuroscience c 251
sort of “neural Darwinism” (Edelman, 1987)—while others strengthen.
The complex relations between biology and experience can be seen
in this biologically driven overproduction of synapses early in devel-
opment, coupled with the pruning away of certain ones because they
are not stimulated by experience. An example is infants’ perception of
phonemes. Infants are born with the ability to discriminate the sounds
of all human languages, but the particular subset of these phonemes
that they still can discriminate by late infancy depends on the language
or languages to which they were exposed during early infancy. Through
pruning, they lose the ability to discriminate the phonemes of languages
that they do not hear.
The brain seems to have major periods of growth and then pruning
during the toddler years and adolescence. These periods of rapid neural
growth might indicate that some developmental change is qualitative,
especially if it involves brain reorganization, thus addressing the issue of
qualitative versus quantitative development.
3
Increased specialization At first, most areas of the cerebral cor-
tex are capable of performing a variety of functions. However, the
cortex becomes increasingly lateralized, with the left hemisphere
typically becoming more dominant. Moreover, with increasing age, brain
regions and networks become more specialized, committed to particular
activities. In general, a particular task elicits a larger, more diffuse area of
brain activity in children than in adults. That is, the engagement of neu-
ral networks becomes more specific during development. The outcome
is that brain plasticity decreases as brain regions commit to particular
tasks. This can be seen, for example, in the fact that late second- language
learners do not achieve the level of proficiency of earlier second-
language learners. Late second- language learners may even process the
second language differently from native speakers. These findings suggest
that the brain organization associated with the first language has to be
used to learn the second language later. Similarly, the greater ease of
discriminating faces from one’s own race than faces from other races,
when babies primarily have seen faces of their own race, is reflected in
different patterns of brain activity when comparing two same- race versus
two different- race faces, showing brain specialization for same- race faces
(Vizioli, Rousselet, & Caldara, 2010). The experienced brain cannot go
back to its less differentiated past.
4
Effects of environmental stimulation Normal brain devel-
opment is dependent on environmental stimulation. Without the
stimulation that a typical human environment would have, for which
the brain evolved, the brain develops differently. Most children, because
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252 c BIOLOGICAL APPROACHES
they are physically normal and are raised in an environment typical
for the species, have more or less the same sorts of experiences at about
the same time. Thus, the pruning proceeds along similar lines for most
children. However, what about atypical situations, such as children who
are deaf or blind and thus do not receive auditory or visual stimulation?
In deaf children, certain areas of the brain that normally would be
devoted to auditory processing if the brain received both auditory and
visual stimulation instead gradually become devoted to visual processing
(Neville, 1995). Conversely, in blind children, areas normally devoted
to visual processing when receiving both auditory and visual stimulation
instead are devoted over time to auditory processing. Thus, when an area
of the brain does not receive its normally expected input, it can be used
for other purposes. The brain is preset to rapidly guide children along
certain developmental paths, but it is also flexible enough to deal with
atypical circumstances. Thus, cognitive neuroscience research is about
brain plasticity as much as brain determinism of behavior.
The social environment is as important as the physical environment.
For example, infants of mothers experiencing high stress due to social
isolation have an altered development of brain inhibitory systems
(Huggenberger, Suter, Blumenthal, & Schachinger, 2013). The moth-
ers’ mental– emotional state likely decreased their verbal and nonverbal
interaction with their infants, which prevented typical pathways from
developing and instead set in motion other pathways. Recall also the
atypical developmental timetable or pathways set in motion by adverse or
unpredictable local conditions, described earlier in this chapter.
5
Constraints on brain development These constraints are
genetic, environmental, and developmental (the current devel-
opmental level of the child). Genetic constraints that impact the
structure and function of the brain are discussed in the genetics section
of this chapter. The environment sets limits on ways that the brain might
develop; it presents options, but not all possible options. Developmental
constraints, such as the current organization of the brain system, influ-
ence subsequent brain development.
6
Brain areas develop at different rates Subcortical brain areas,
associated with emotion and sensitivity to reward (e.g., the amyg-
dala and striatum) mature rather quickly. In contrast, prefrontal
areas (the front part of the frontal lobes), which support higher- level
cognition, especially control over one’s thoughts and behaviors, develop
more gradually over a longer period of time, continuing even through
early adulthood. Thus, young adolescents have an imbalance between
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Developmental Neuroscience c 253
early maturing subcortical structures that increasingly draw them into
risky, rewarding behaviors, and later maturing structures for cognitive
and emotional control that could put the brakes on these behaviors. This
asynchrony presents an interesting theoretical model to explain normal
young adolescents’ tendencies to engage in risky behaviors, followed by
decreases in risk taking in later adolescence as prefrontal areas continue
to develop (e.g., Steinberg, 2011). Given these neural findings, along
with the significant social and hormonal changes during adolescence, it
is not surprising that adolescence seems to be a time of increased vul-
nerability for psychopathology (Powers & Casey, 2015).
7
Lifespan changes Brain changes, including strengthening and
weakening of synapses, continue throughout the lifespan. The brain
is always a work in progress. During aging, the brain does, for
example, becomes smaller and there is a reduction in neurotransmitters.
However, certain experiences, such as exercise, can cause changes in the
brain that improve brain functioning during the aging years. Contrary
to prior belief, recent research shows that new neurons are created
throughout our lifetimes, even during old age. This finding questions
some of the theories of aging that focus on cognitive loss.
From these themes, the most important point may be that neurosci-
ence research shows the impact of environmental influences on the brain
as much as brain influences on behavior. The next section describes con-
tributions of neuroscience to developmental theoretical issues, including
interactions of nature and nurture.
Theoretical Issues
What can a neuroscience perspective contribute to our theoretical
understanding of development? A main contribution is that neuroscience
increases our understanding of how nature and nurture collaborate in
complex ways to drive development. The research findings reported above
show how environmental inputs to a plastic, yet constrained, brain start
a journey down a particular developmental path. Moreover, as described
later in this chapter, the brain often is the mediator between genes and
behavior, as genes affect behavior and behavior affects gene expression.
Neuroscience findings bolster theories emphasizing the evolution of
humans within social groups (e.g., Tomasello, 2014) and identifying the
importance of early social experience. A main function of the brain is
to recognize and interpret social information. Even in infancy, “babies’
brains are adapted to tap into the richest source of new information in
their early environment: other human beings” (Johnson, 2013, p. 8). As
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254 c BIOLOGICAL APPROACHES
Grossmann (2015, p. 1266) notes, “Humans are such intensely social
creatures that already as young children they outperform their closest
living primate relatives (the great apes) in terms of their social- cognitive
skills, while showing very similar skills as great apes when dealing with
the physical world.” For example, even a rather subtle emotional
response such as empathy can be tracked in terms of its changes in brain
activity during childhood. These changes, measured by EEG, indicate a
gradual decrease with age in emotional arousal and an increase in cog-
nitive evaluation of the situation (Cheng, Chen, & Decety, 2014). More
generally, there seems to be a network of specific brain areas focused on
the processing of social information that is somewhat independent from
other forms of cognition.
Developing brains are sensitive to both positive and negative social
environments. On the positive side, neuroimaging documents competent
mothering. For example, competent mothering of children at age 12 pre-
dicted brain changes (seen in MRIs) thought to indicate positive develop-
ment at age 16 (Whittle et al., 2014). On the negative side, stresses from
maltreatment (Bruce et al., 2013), low socioeconomic status (Muscatell
et al., 2012), and institutionalized rearing (Mehta et al., 2010) are asso-
ciated with brain functioning in children and adolescents that differs from
that of children reared in more typical environments. Even mild stress-
ors affect brain activity. In one study (Graham, Fisher, & Pfeifer, 2013),
mothers’ reports of higher conflict between parents was associated with
infants’ greater neural responses to very angry speech, compared to neu-
tral speech, across several brain regions known to be involved in emotion
and reactions to stress.
Some neuroscience models have addressed explicitly the continual
interplay of biological and environmental influences and the causes of
diverse developmental pathways. As described in Chapter 2, neurocon-
structivism posits slight initial brain constraints or biases such that, for a
particular task and situation, some neural pathways are more easily acti-
vated or more easily connect to certain outputs. Examples are infants’
biases toward looking at faces or analyzing language sounds. Infants seek
out these stimuli, which further strengthens and specializes these path-
ways. Thus, infants may be slightly biased to look at particular types of
stimuli, but the small biases become further amplified through special-
ized activity. The outcome is specialization of brain pathways, because
the infant does not use the other pathways that initially could have been
used. Slight individual differences in brain structure or function initially
also could cascade into larger differences later that are considered neu-
rodevelopmental disorders.
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Developmental Neuroscience c 255
As for other theoretical issues, neuroscience can address the issue of
quantitative versus qualitative development. Imaging reveals qualitative
changes in the changing organization of neural networks during devel-
opment and quantitative change in the strength of activation of each
neural network. Neuroscience findings also can inform the issue of the
extent to which cognition is general versus domain specific. The increas-
ing specialization of areas of the brain during development suggests that
cognition becomes more domain specific during development.
Another contribution to theorizing is that cognitive neuroscience
research can test some of the claims of theories presented in this book.
For example, the fact that cognitive tasks activate both cognitive-
control and motor areas of the brain (Diamond, 2000) suggests close
connections between action and thought. This could be taken as sup-
port for Piaget’s claim that motor actions play a key role in cognitive
development. Relevant to Piaget’s claims about stages, if engaging in
two tasks believed to tap the same knowledge system in fact activate
the same neural networks, this would suggest that the two cognitive
skills involved are part of the same cognitive structure rather than two
domain- specific ones. Also relevant to Piaget, seeing how different neu-
ral networks interact at various ages can provide clues to age differences
in cognitive organization. Another issue relevant to Piaget is whether
the unexpected competence of infants described in Chapter 2 indicates
the same level of knowledge as that of older children at the age when
Piaget thought they develop that concept. The fact that EEG and NIRS
measures of infants’ face and eye gaze processing, joint attention, and
understanding of human action detect precursors of later networks
for social cognition (Grossmann & Johnson, 2014) could suggest that
social understanding at these two ages is related but not identical.
A final example is that the observed heightened self- consciousness
of adolescents, described by Piaget and Erikson, has been supported
by fMRI measures. When research participants thought that a peer
was actively watching them, adolescents showed higher physiological
arousal compared to other ages, as well as engagement of brain regions
thought to be involved in the processing of socioaffective information
(Somerville et al., 2013).
Applications
The neuroscience approach has led to a number of interesting appli-
cations. An important one is the insights into atypical development due
to brain injury, atypical environments, or neurodevelopmental disorders.
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256 c BIOLOGICAL APPROACHES
This information about brain functioning in such children both clarifies
typical development and suggests interventions for children developing
atypically. For example, 3- and 4- year- old children with autism spectrum
disorder (ASD) showed an atypical pattern of brain activity when view-
ing photos of an unfamiliar woman with a neutral or a fearful expression
(Dawson, Webb, Carver, Panagiotides, & McPartland, 2004). Given that
the ability to accurately identify emotional states in other people is crit-
ical for using emotions to explain behavior, children with ASD clearly
are disadvantaged in this way. One goal is to detect brain patterns during
infancy that predict the later development of ASD so that interventions
can begin early.
Another important application has been to legal issues, an area called
“neurolaw.” Evidence about adolescents’ asynchronous brain develop-
ment, with emotions running ahead of the development of inhibition,
contributed to the Supreme Court decision to end sentences of life
without parole for crimes committed by minors. The reasoning was that
adolescents’ neurobiological immaturity makes them less responsible
for their actions than are adults. Still another application is called “edu-
cational neuroscience.” The idea is to use information about children’s
brain development to design instruction.
Summary
Neuroscience findings and theoretical models have generated a great
deal of excitement in developmental psychology for three reasons.
First, neuroscience provides additional levels of analysis for under-
standing development. This information about the biological processes
involved in behavior has become increasingly important as develop-
mental theorizing has moved more and more to a focus on development
as a changing system, with interacting levels from cells to society (see
Chapter 9). The brain is one important part of this organized, interactive
system. Second, neuroscience has revealed the importance of experi-
ence and learning, as much as the brain, when explaining behavior. In
this way, neuroscience strengthens the long history of developmental
research on the influences of the environment. One sees brain plas-
ticity throughout life in the strengthening or weakening of synapses
and the formation of new neurons and new synapses as the contexts
of development change. Development involves continual interplay
among brain development, behavior, and environmental resources.
Third, neuroscience findings serve as a bridge to clarify the relations
between genes and the environment. As described in the next section,
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Genetics c 257
the brain often is the mediator between the expression of genes into
thinking, feeling, and behavior, and between environmental condi-
tions and the expression of genes. Still, it should be noted that some
developmentalists are concerned that the focus of developmental psy-
chology has shifted so much toward neuroscience perspectives that
the field is out of balance empirically and theoretically as well as in
resources such as grant funding, employment, and university investment
in research.
Genetics
Genetics has had a presence in developmental psychology for decades,
particularly in discussions of the nature– nurture issue— how genetic
predispositions come together with environmental factors to contribute
to behavioral outcomes. However, recently the conversation has shifted.
Historically, behavioral geneticists could ask “How much of the variation
in this trait (e.g., IQ) is due to genetic differences among individuals in
this population and how much is due to environmental differences?”
The question was about sources of individual differences in a group.
Researchers often looked at how the known degree of genetic relat-
edness in the group correlated with similarities in a trait. Thus, they
studied families, twins, and adopted children. For example, studies
have compared adult identical twins, separated early in life, to estimate
the relative contributions of genetic and environmental influences. This
approach continues today and is clarifying some of the nuances of heri-
tability. For example, the siblings of individuals with schizophrenia have
impaired functioning in several areas of cognition compared to normal
control families, even when these siblings do not develop schizophrenia
(Barch, Cohen, & Csernansky, 2014).
A newer approach in developmental psychology draws on molecular
genetics to ask a different question. It asks how the meshing of genes and
environment in an individual causes a trait. What is the causal pathway
from genes to cells to tissues to organs to behaviors, and vice versa? This
question could not have been studied before technologies for assessing
genetic makeup were developed. Geneticists’ drive to map the genome, in
the Human Genome Project, basically completed in 2003, provided tech-
niques to determine the order of DNA building blocks in an individual’s
genetic code (see the beginning of this chapter). Psychologists then used
these techniques to try to map the gene– environment connections
throughout development. That is, they correlated genetic variations with
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258 c BIOLOGICAL APPROACHES
variations in behavior. In part because genetic analyses now are accessible
and cost effective, research in this area has boomed in psychology.
Molecular genetics has generated a great deal of excitement in devel-
opmental psychology because it provides the genetic component for new
theoretical models of the developmental unfolding of brain and behavior
as influenced by genes and the environment together. This contemporary
approach involves Gene X Environment interactions (G X E) and epi-
genetics (when the environment causes chemical changes affecting reg-
ulation of the genes). We now look at each of these.
Models of Gene X Environment Interactions
Mapping the human genome did not lead to the dramatic breakthrough
in understanding physical and mental illness that geneticists expected.
A likely reason is that genes are only part of the equation for human
physiology and behavior. Genes are simply potentials that may or may
not be expressed in particular environments, so in a sense we need to
map the human environment as well as the human genome. G X E inter-
actions show that the environment moderates the association between a
particular gene variant and an outcome. For example, the known associ-
ation between a particular gene variant and depression might be stron-
gest in people who experience stressful major life events. Thus, genes
may or may not be expressed, depending on a child’s developmental
contexts. Similarly, a person’s genotype moderates the effect of an envi-
ronmental factor on outcomes, such as traits, behaviors, mental health,
and cognition. For example, highly stressful life events might be more
likely to lead to depression if a person has a particular pattern of genes.
Thus, due to the contributions of the environment, a given genotype
(genetic makeup) can result in different phenotypes ( outcomes— traits,
behaviors, etc.) in different children, and a given phenotype can reflect
different genotypes in different children.
To understand G X E interactions, it first is necessary to review a
few basic genetic concepts. Humans have 23 pairs of chromosomes in
each cell, and each chromosome is composed of thousands of genes.
Genes are short segments along a long chemical spiraling chain of two
strands of DNA (see Figure 5.2). The basic chemical building blocks of
each gene’s DNA provide an information code (for example, the code
at the beginning of this chapter) for making proteins. These proteins
contribute to the development and regulation of the organism. This
code involves particular sequences of these chemical building blocks. An
allele is one of two or more possible versions of a gene; these are called
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Genetics c 259
genetic polymorphisms—
variants of a particular
DNA sequence. Polymor-
phisms most commonly
involve different versions
of a single base pair (one
of the four pairs of the
genetic code presented
at the beginning of this
chapter) but instead can
involve long stretches
of DNA. A single gene may have many polymorphic regions and poly-
morphisms. An individual has two alleles for a gene pair— one from
each parent. The two alleles in a gene pair can be the same or different
versions, which affects which phenotype (e.g., eye color, blood type) a
person has. This is a main source of genetic variation among individuals
that could affect how much an environmental event or substance (e.g.,
an environmental toxin) affects them.
It is exceedingly complex to study G X E interactions because the
genetic landscape is huge: A person’s genome has 20,000 to 25,000
genes, which sounds like a lot, but is barely more than the number for
the miniscule roundworm, and much less than the 32,000 for an ear of
corn (Schnable et al., 2009). The genome has more than 3 billion bits of
information. Thus, the search for the genes relevant to the behavior or
trait of interest may seem like a search for a needle in a haystack. Still,
the search takes place with the knowledge that the genomes of any two
humans are more than 99 percent the same. Importantly, this one per-
cent of variation can provide valuable clues to the nature– nurture issue.
Genes can be analyzed from a small amount of blood or saliva. One
analytic technique is to examine variations across individuals in a very
small region of a gene that, based on prior research, is a prime suspect
for the outcome of interest. This is called the candidate gene approach.
The initial results were exciting, but subsequently they were not rep-
licated for the most part, perhaps because the gene– outcome link
depends on the environment, as shown in the G X E findings above.
Subsequently, researchers turned to a newer technique, called “Genome
F I G U R E 5 . 2
Chromosome structure, includ-
ing epigenetic changes.
[Patricia Miller]
DNA
Chromosome
Epigenetic modif ication
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260 c BIOLOGICAL APPROACHES
Wide Association Studies” (GWAS), which examines much of the whole
genome of a very large number of individuals (usually thousands) to
detect genetic variations that are correlated with a particular mental
or physical disorder. Particular genetic patterns tend to co- occur with
schizophrenia, autism spectrum disorder, substance- use disorders, and
bipolar disorder (e.g., Horga, Kaur, & Peterson, 2014). Typically the
genetic pattern identified involves numerous genes, because few if any
outcomes of interest to psychologists are due to a single gene. In fact,
mental disorders likely are influenced by thousands of genetic polymor-
phisms (Hindorff et al., 2009). One finding of great surprise to genet-
icists is that about 98 percent of genetic variations are not even in the
coding portions of genes but somehow help regulate genes’ functioning.
Little is known about how these noncoding variants (formerly consid-
ered “junk” DNA) influence outcomes. Another complication to tracking
gene– behavior links is the discovery that what a gene can do can depend
on nearby genes; genes can interact, such that one gene can suppress
another one.
In general, the amount of variation in outcomes associated with
genetic variations from these analyses has been disappointingly small.
Thus, geneticists have moved to larger and larger samples to capture
small correlations between genetic polymorphisms and behavior. Again,
one reason that geneticists have found only small direct effects may be
that the association is large only in particular environments, which
reflects a G X E interaction. That is, the correlation may vary from one
environment to another, for example, under conditions of parental sup-
port versus neglect. Thus, G X E interactions show that mapping the
genome is not enough. At this point, psychologists have studied G X E
interactions for a variety of outcomes (e.g., depression, drug abuse, psy-
chopathology) in a variety of environments (e.g., high stress or trauma,
neglectful parenting, poor nutrition, and low physical activity).
In Chapter 1, the discussion of the issue of how nature and nurture
interact to direct development included examples of G X E interac-
tions. A study was described (Brody et al., 2009) in which improving
parenting skills provided a protective factor for adolescent boys who
had a genetic predisposition for engaging in high- risk behaviors, such
that the predisposition was less likely to be expressed. Thus, good par-
enting is like an insurance policy. If children do happen to be genetically
predisposed to certain disorders that could be expressed under adverse
circumstances, then the effects of good parenting and social supports
may provide a buffer against gene expression and the resulting negative
outcomes. Such findings are exciting to developmental psychologists,
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Genetics c 261
because they show that when children have both high- risk genes and a
high- risk environment it is possible to create an environmental buffer to
genetic tendencies. Complicating the choice of interventions, however,
is the fact that the effects of an experience, such as a psychological inter-
vention, depend partly on a person’s genetic makeup.
The overall model of G X E interactions is that having, or not having,
particular adverse experiences can “turn on” or “turn off ” genes that pre-
dispose children to psychological or health problems later. This model
obviously is of great interest to developmentalists, who want to know
how genes are expressed during development in particular environments,
which may differ from one developmental point to another. To understand
how the environment can be a trigger or a silencer for relevant genes, it
helps to liken a person’s DNA to a large, organized library:
Asking what DNA does is like asking what a book in this library does.
Books sit on a shelf waiting to be read. Once read, the information in
those books can have limitless consequences and can perhaps even lead
to the reading of more books, but that refers to the book’s potential.
Likewise, DNA sits in our cells and waits to be read. The reading or so
called “expression” of DNA can, like the books in our library, have lim-
itless consequences. However, without the active process that triggers
“expression,” this potential may never be realized.
(Champagne, 2009, p. 27)
Just as certain books are blocked and others are easily reached, both
the environment and regions that regulate DNA can block DNA or make
it accessible, thus affecting how easily DNA is expressed. The environ-
ment provides, or does not provide, the trigger. Ineffective parenting,
high stress, or poor nutrition are examples of triggers. In this way, expe-
rience affects the expression of genes. The result is that each cell turns
on only a fraction of its genes. Developmental psychology takes center
stage in this work because turning on particular genes is timed to partic-
ular phases of development, as seen, for example, in puberty changes in
adolescence. Similarly, whether a particular experience is a trigger often
depends on the child’s age and developmental history (for example, poor
prenatal nutrition or lack of cuddling during infancy).
A fuller picture of the pathway between a genetic liability and an out-
come comes from a recent study (Davies et al., 2015) illustrating the
G X E approach. It shows that genetic variation affects the sensitivity of
low- socioeconomic, predominantly minority toddlers to particular expe-
riences, specifically, mothers’ unresponsive caretaking. For children with
a genetic pattern known to put them at risk for poor self- regulation, this
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262 c BIOLOGICAL APPROACHES
poor parenting was linked to an increase in disruptive behaviors two years
later. Children in the sample without that genotype did not show these
disruptive behaviors. Thus, a given environmental variable, unresponsive
mothering, may negatively impact only children with a particular genetic
makeup; some children are more vulnerable than others to adverse family
situations. The likely pathway was that prolonged unresponsive caretaking
triggered the expression of the high- susceptibility genetic variant, which
caused decreased dopamine activity in brain circuits involved in reward
seeking. This in turn led to an uninhibited temperament, with sensation
seeking and risk taking, which escalated into disruptive behaviors.
Epigenetic Models
One groundbreaking and startling finding is that one way that envi-
ronments can affect gene expression (a G X E interaction) is through
epigenetics— the modification of gene activity without actually changing
the gene. These chemical changes to or near the genes affect which genes
are turned on and which are turned off, and this change can continue
into the future. In effect, these chemical tags serve as enhancers and
repressors that reprogram the gene’s activity. It is as if little red or green
flags are attached to certain gene regions (see Figure 5.2). Epigenetic
changes can be caused by poor prenatal nutrition, parental maltreat-
ment, extreme stress, social isolation, and exposure to pollutants,
as well as many other events. Various outcomes have been observed,
including depression, schizophrenia, abnormal responses to stress, and
decreased learning and memory. Every individual has numerous epigen-
etic changes during development.
The actual mechanism of epigenetics sometimes involves attaching
certain chemical compounds to segments of DNA in genes, thereby
affecting access to them and governing the gene’s activity by suppress-
ing or enhancing it. That is, the compound “turns on” or silences the
gene. For example, in one study (Romens, McDonald, Svaren, & Pollak,
2015), high stress from parents’ physical maltreatment of their children
(ages 11 to 14) caused an epigenetic change affecting a gene involved
in stress regulation. The disrupted hormonal system for regulating
stress led to “cascades of downstream changes in biology and behavior”
(p. 303) known to lead to later health and psychological problems. It
often is the combination of genetic risk and environmental risk that
can push children into a maladaptive developmental pathway. What is
particularly important about epigenetics is that it potentially can be a
permanent change that continues to affect development in the future.
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Genetics c 263
Developmental science is at the heart of epigenetics because genes
are expressed during development as experiences accumulate. At any
developmental point, our epigenome (all our epigenetic changes) is
the sum of the environmental signals it has received thus far. Thus, for
example, the epigenetic effects of child maltreatment can accumulate
and only at some point trigger a genetic region. Also, new experiences
later in life can cause new epigenetic changes. Epigenetics is a lifelong
process, and each change in our epigenetic makeup affects how we react
to future environmental events. Also, developmental timing is everything.
A particular environmental event might cause an epigenetic change in
one developmental period but not another. Complicating the picture of
environmental influences on gene activity even further, to some extent
children create their own environments. For example, children with a
genetically predisposed temperament to engage with adults may then
evoke cognitively stimulating experiences from their environments,
which then enriches their environment and affects what epigenetic
changes might occur.
One of the most surprising findings is that epigenetic changes some-
times are passed on to future generations. For instance, maternal abuse
and neglect can cause epigenetic changes resulting in abnormal reactivity
to stress, which continues into the next generation (Champagne et al.,
2006). This finding helps explain the observed cycle of abuse and its nega-
tive effects across generations. The impact of environmental effects on the
next generation seems to contradict classical genetics principles taught in
high school— that experience does not alter genes. However, it is not the
genes themselves that are modified; rather, it is the “cellular memory” of
the altered gene expression profile that somehow is transmitted.
It still is uncertain how abnormal gene regulation conditions are
passed on. It may involve the transmission of the chemically changed
context of the gene that altered its expression; the epigenetic signa-
ture is passed on. Or, the transmission may occur prenatally, affect-
ing the development of the fetus. Suggesting prenatal processes, the
newborns of depressed mothers also have the chemical changes asso-
ciated with this gene expression in the blood of their umbilical cords
(Oberlander et al., 2008).
Finally, an important, and intriguing, index of environmental influ-
ences on the genome is the length of telomeres— the tail- like regions
protecting the ends of chromosomes. Telomeres are thought to be a
molecular clock for biological aging in that eroded (and thus short-
ened) telomeres can indicate that factors such as smoking, obesity, or
chronic stress have caused physiological wear and tear on the body
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264 c BIOLOGICAL APPROACHES
(e.g., the cardiovascular system) and thus physical aging. Short telo-
meres are associated with chronic diseases of aging and early death. In
a longitudinal study, children who experienced two or more forms of
violence— domestic violence, bullying, or physical maltreatment by an
adult— showed significant telomere erosion between ages 5 and 10, even
after controlling for socioeconomic status (Shalev et al., 2013). Similar
effects were shown in young adults, with high levels of stress at age 17
associated with nonsupportive parenting and predicting shorter telomere
length five years later (Brody, Yu, Beach, & Philibert, 2015). Specifically,
chronic activation of the body’s stress response damages the body.
Theoretical Issues
In a sense, epigenetic findings even destroy the dichotomy between
nature and nurture, because nurture changes the regulation of genes.
In light of G X E interactions and epigenetics, perhaps the most accu-
rate way to think about nature and nurture is that humans inherit
resources for development rather than specific gene- based character-
istics (Lickliter & Honeycutt, 2015). The meeting of genetic and envi-
ronmental processes is exceedingly complex— more complex than ever
imagined. An individual is constructed over the lifespan from a dynamic
developmental system consisting of various levels from genes to envi-
ronments, with causality in both directions. Moreover, genetics research
shows the importance of the timing of a particular experience, consis-
tent with ethologists’ notion of sensitive periods. For example, the study
described above on depression was conducted on adolescents because
that is a time when a number of major psychiatric disorders appear, sug-
gesting that adolescence may be a time of particular vulnerability to epi-
genetic changes. The fact that epigenetic effects can be cumulative and
permanent provides an explanation for how adverse early experiences
can cause problems years later.
One important theoretical advance is the differential susceptibil-
ity hypothesis, the theory that some children are especially affected
by environments— both positive and negative ones— whereas other
children are much less affected (Ellis, Boyce, Belsky, Bakermans-
Kranenburg, & Van IJzendoorn, 2011). Some children are like dande-
lions, who seem to be rather impervious to environmental input and
can grow in a variety of environmental circumstances; others are like
orchids, highly reactive and very influenced by both harsh and highly
nurturing environments. This concept may help solve certain mysteries
from research on environmental influences. For example, some children
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Genetics c 265
show remarkable resilience in a childhood of poverty, abuse, and high
stress and manage to stay on a positive developmental pathway. These
children may have genetic polymorphisms making them less susceptible
to environmental influences.
G X E and epigenetics research provide another level of explanation
to the other theories in this book. Each theory identifies particular types
of experience important for development, which potentially could affect
gene expression. For instance, Piaget focused on active interaction with
one’s physical world, Freud and ethologists emphasized early mother-
ing and attachment, Erikson emphasized culture- based socialization,
and Vygotsky thought early language interactions were important. The
genetic approach suggests pathways between these experiential histories
and psychological outcomes, namely, pathways involving turning genes
off or on and perhaps permanently altering the regulation of genes.
Epigenetics research also spotlights the physiological and behavioral
route between the environmental triggering of a gene and the positive
or negative behavioral outcome.
Genetics research also adds to our understanding, in each theory, of
individual differences in children’s responses to events and environments.
Polymorphisms affect the impact of the experiences and environmen-
tal influences emphasized by various theories. For example, different
children may respond differently to disequilibrium (Piaget’s theory) or
guidance in the zone of proximal development (sociocultural theory) or
aggressive models (social learning theory, Chapter 6).
Genetics research points to the need for theories to identify spe-
cific critical aspects of experience. For instance, in a longitudinal study
(Murphy, Slavich, Rohleder, & Miller, 2013), adolescent females at
risk for developing major depression showed more epigenetic markers
for depression at testing sessions only when one specific type of rejec-
tion, “targeted rejection” (intentional rejection of a person), recently
had occurred. This effect was especially strong for females who per-
ceived themselves as high in social status in their peer group. This sug-
gested that targeted rejection set in motion a neurohormonal chain of
events that led to the inflammation of body systems, which is the body’s
protective response to damage or harmful stimuli, including stress.
Chronic inflammation is a change associated with mental and physical
illnesses. These findings suggest new hypotheses about possible different
effects of different kinds of environmental stressors. The study also sug-
gests that perceptions of the environment (accurate or inaccurate), not
just the environments themselves, influence the impact of environments
on susceptibility genes.
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266 c BIOLOGICAL APPROACHES
Cultural developmental theories (Chapter 4) suggest the importance
of attending to human diversity in G X E and epigenetics research.
Human cultures differ in their DNA profiles. It matters who is stud-
ied. Most genetic research has been conducted on people of European
descent, but various genetic polymorphisms occur at different frequen-
cies in different populations. The NIH 1000 Genomes Project is an
international public– private consortium attempting to build a detailed
catalog of the main genetic variations between populations in Europe,
Africa, and East Asia. The goal is to identify the contribution of genetic
variation to illness. A main step is to show which genes indicate the most
variability in their responses to particular aspects of the environment.
However, cultural theories would argue that attending to genetic diver-
sity is only part of the story. Cultural diversity also may contribute to
G X E and epigenetic outcomes. For example, what constitutes a sup-
portive parental environment or what kinds of events are stressful may
show cultural differences.
The focus of genetics research on mental and physical diseases has
prompted developmentalists to construct new models of links between
experience, psychological development, and health. The impact of stress
on health, and on telomere length as an indicator of overall health, for
example, was described earlier. The growing awareness of connections
among genes, the environment, and health can be seen in a current
NIH initiative aimed at understanding effects of different environments
on genes. The Environmental Genome Project identifies “susceptibility
genes,” which have polymorphisms that make individuals particularly
sensitive or insensitive to radiation and natural and human- made chem-
icals, including environmental pollutants.
Some of the current theoretical controversies in genetics are quite
relevant to development. One concerns the extent to which epigene-
tic changes and the resulting bodily changes can be reversed. Another
concerns the fact that much of the genetic variation among people now
appears to come from outside of the coding genes, the basis for the
mapped human genome. Another controversy has to do with the fact
that most of the research thus far has focused on negative outcomes, such
as mental disorders or atypical development. Are the identified genetic
and epigenetic processes the same for normal development, including
positive developments or traits such as language acquisition, prosocial
behavior, and musical talent? Is there a critical difference between typical
environments and very enriched environments?
Several important questions about development likely will be
addressed in future research. Are there sensitive periods for specific
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Genetics c 267
environments measured in G X E interactions? In fact, it has been sug-
gested that researchers should be developing G X E X D (Development)
models (Hyde, 2015). Early childhood and adolescence are good
candidates for sensitive periods because of significant neural, behav-
ioral, and environmental changes at those times. For example, peer
relations (e.g., affiliation and support versus rejection) may be a partic-
ularly strong mediator of gene- brain- behavior links during adolescence.
Another question concerns the range of environmental triggers in chil-
dren’s lives. Much of the genetic- oriented work thus far has looked at
mothering, which, though important, is only one of many important
environmental influences, particularly fathers.
Applications
These genetic and epigenetic breakthroughs have important applications.
Having more information about their children’s genetic makeup, or their
own, and the probability of susceptibility genes being expressed, can help
people make decisions related to physical and mental health (e.g., suscep-
tibility to depression, recommendations about lifestyle, such as exercise).
Eventually, newborn screening involving whole- genome analysis may be
routine. One goal of knowing the genetic composition and environmen-
tal stressors of various racial, ethnic, and socioeconomic groups is to help
tailor interventions to these groups in an attempt to eliminate health
disparities. This is similar to “personalized medicine” in the medical field.
An intervention that reduces stress on children or improves parenting
early on can deter the expression of susceptibility genes into negative
outcomes. Along with these applications, however, come a host of ethical
and legal issues. Do you want to know your genetic makeup, given that
it may alert you to dangers that might never materialize? Would informa-
tion about your child’s genetic makeup affect how you treat him or her?
Should doctors tell patients about a genetic risk for a disorder with no
known preventive treatment, such as early dementia?
Summary
G X E and epigenetic research provides complex new developmental
models of genetic and environmental influences. In fact, such research
has documented the importance of the environment as much as that of
genes. Genes mediate the impact of the environment, and the environ-
ment affects the expression of genes. Sometimes, through epigenetics,
experience even chemically alters gene regulation in ways that are
transmitted to the next generation in some cases. Children differ in their
06_MIL_7898_ch5_211_276.indd 267 1/8/16 5:10 PM
268 c BIOLOGICAL APPROACHES
particular genetic vulnerabilities and even in how sensitive they are to
the environment in general. Environments vary in their degree of sup-
port for positive developmental pathways despite genetic vulnerabilities.
Integrated, Multilevel Biological Theoretical
Perspectives
The various biological approaches in this chapter have developed models
of the pathways between biological processes and behavior, making it
clear that genes, brain, and experience form a complex system in which
each influences, either directly or indirectly, each of the others. This
system is particularly complex because their interactions are develop-
mentally sensitive. For example, a particular environmental event might
cause an epigenetic change during early infancy but not if it occurs
later. Also adding to the complexity is the fact that interactions occur at
multiple levels, from cells to society. The following examples of these
complex models give a flavor of this interrelated system.
Because the brain often is the pathway through which genes are
expressed and thus influence behavior, a new field called developmental
neurogenetics has emerged recently (Hyde, 2015). This approach develops
models in which genetic polymorphisms are associated with particular
neural variability. In other words, the goal is to determine which genetic
polymorphisms predict particular variations in brain neurochemis-
try, architecture, or functioning, which in turn result in variations in
behavior. This approach typically uses the imaging techniques discussed
earlier to assess brain outcomes. An example of a neurogenetic finding
is that a particular genetic variant increases amygdala reactivity during
adolescents’ response to stress (i.e., angry faces) (Battaglia et al., 2012).
Specifically, such a pattern typically indicates a gene (or genes) send-
ing signals to the brain that affect the pathways of neurotransmitters.
Another example is that genetic polymorphisms that affect dopamine
production in certain brain areas are associated with low inhibition of
behavior, for instance, sensation seeking and impulsivity (Caylak, 2012).
One variation of this approach that can advance our understanding
of development is to study these correlations in specific subgroups of
people. For example, one might describe the neural and genetic profiles
of individuals who are resilient despite their developmental history of
harsh, and thus risky, environments (Hyde, 2015).
The developmental aspect of neurogenetics is that the gene- brain-
behavior associations often change as a function of age, not only during
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Integrated, Multi level Biological Theoretical Perspectives c 269
brain development but also throughout the lifespan as individuals engage
in new experiences. A main question is the mechanisms by which these
connections occur. The end result of correlating genetic, neural, and
behavioral variability is a probabilistic model of development. For
example, a model might present the probability of a child developing
depression in a particular environment (e.g., high social support vs.
maltreatment), based on information about the child’s genetic vulnera-
bilities and particular brain structure and functioning. Development is
central because, for example, an initial genetic variant with very small
effects can cascade (see Chapter 1), as one thing leads to another, into
large effects on behavior over time.
Neurogenetics is beginning to be applied to models of the develop-
ment of psychopathology (Hyde, 2015). There are known correlations
between particular brain patterns and particular psychopathologies.
A neurogenetics model would link such correlations to particular
genetic polymorphisms. In other words, the goal is to link genetic vari-
ation to brain variation to behavior variation, including pathological
behaviors. Because brain chemistry and functioning are a phenotype that
is at a level closer to the genotype than are the more distant behaviors
used to classify different kinds of psychopathology, gene- brain links may
be easier to identify than gene- behavior links.
A recent model (Hyde, 2015) expands developmental neurogenetics
by adding measures of environmental variability. Thus, this model adds
G X E interactions to neurogenetics, such that associations of brain
variability with both genetic and environmental variability are included.
Genes, brain, and behavior are all in an environmental context, and the
brain is a mechanism linking G X E interactions to development. For
example, a strong brain reaction to stress might occur with a particular
genetic variant in a child developing in a harsh, stressful environment
but not in a child developing in a more supportive environment.
Another model that nicely ties together the perspectives of this
chapter addresses the relations between the body’s response to stress
and later outcomes. Experiencing chronic violence during childhood,
such as mistreatment by adults, bullying, or domestic violence, often
has adverse effects inside a child’s body that put the child’s physical,
psychological, and cognitive health at risk later, even decades later. The
main mechanism appears to be the stress response, which can lead to the
epigenetic, telomere, and inflammatory changes described earlier. These
changes are associated with increased risk for health problems such as
heart disease, stroke, immune diseases, dementia, and metabolic diseases
(Moffitt et al., 2013). Moreover, altered brain functioning, as seen in
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270 c BIOLOGICAL APPROACHES
neuroimaging, is expressed in behavioral and learning problems, as well
as in depression and anxiety. The hormone cortisol, part of the stress
response, appears to be particularly important (e.g.,Wadsworth, 2015).
Some models of the stress response emphasize environmental conditions
such as poverty and racial discrimination. For instance, preadolescent
African- American preadolescents in the rural South who developed
psychosocial competence despite the developmental risks posed by their
family’s low socioeconomic status, paid a price in harmful physiological
changes in response to the high stress, evident by age 19 (Brody et al.,
2013). Moreover, the negative effects of family instability and maternal
unresponsiveness during the preschool years result in lower cognitive
functioning by age 4 (Suor, Sturge- Apple, Davies, Cicchetti, & Manning,
2015). Finally, maternal prenatal stress can affect development during
infancy and later. Mothers who experience chronic stress during preg-
nancy have newborns with elevated levels of cortisol in their bodies
(Pluess & Belsky, 2011).
Ethology and evolutionary psychology also are part of the study of
this complex system, as reflected for example in new fields, such as
neuroethology and evolutionary cognitive neuroscience. Regarding
connections between genetics and evolution, genetic variation and
plasticity in gene expression (as seen in epigenetics) contribute to
the survival of the species during evolution; when the environment
changes, some genetic polymorphisms may be better adapted than oth-
ers to the new environment. The growing evidence of both plasticity
in gene expression and brain plasticity (in the effects of the environ-
ment and behavior on brain networks) shows that humans are uniquely
equipped to adapt to changing environments. Altered gene regulation
and neural connections can, for instance, help us adapt to harsh social
or physical environments. For example, dangerous and unpredictable
environments tend to lead to a chronic stress response, which is neg-
ative from a health perspective, but by encouraging constant vigilance
may help children survive, adapt, and develop within that environment
(Wadsworth, 2015). In one study, children with stressful childhoods
showed improved detection, learning, and memory on tasks involving
stimuli of importance to them, such as those having to do with dangers
(Frankenhuis & de Weerth, 2013). These systems have evolved and, in
turn, potentially change the course of evolution through, for example,
the transmission of epigenetic changes across generations. In fact, some
of any individual’s inherited epigenetic makeup may have been created
by conditions hundreds of years ago and transmitted through subse-
quent generations.
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Summary c 271
Another way to think about relations between genetics and ethology
is that, given that the environments in which humans develop cause epi-
genetic changes that affect whether a gene is expressed, some genetically
possible behaviors never are expressed and thus cannot enter into the
process of natural selection by increasing or decreasing survival. Thus,
evolution involves not only genetic changes, but also epigenetic changes.
What can we conclude, regarding theory, from this account of neuro-
science and genetics? The predominant contemporary theoretical model
of gene- environment connections is that there is a dynamic interplay at
various levels, including genetic, epigenetic, neuronal, hormonal, emo-
tional, cognitive, behavioral, and environmental levels (e.g., Lickliter &
Honeycutt, 2015). In this developmental system (see also Chapter 9),
each level affects and is affected by each of the other levels: “All adapta-
tions, regardless of when they appear, have their roots in earlier expe-
riences, shaped by the bidirectional interaction between all levels of an
organism and its environment (both macroenvironments, such as the family
and one’s culture, and microenvironments, such as neurotransmitters and
chemicals affecting the functioning of DNA molecules)” (Bjorklund &
Ellis, 2014, p. 247). Note that genes do not hold a privileged controlling
position but are just one component that must interact with other com-
ponents in the system to function. Moreover, the nature of this system
changes from one developmental point to another, and early events can
cascade through later development. We already knew that development
is exceedingly complex; neuroscience and genetics, along with contem-
porary ethological and evolutionary psychology perspectives, are pro-
viding additional mechanisms to explain this complexity.
SUMMARY
The biological terrain of development has many players— ethology,
evolutionary psychology, developmental neuroscience, genetics, epi-
genetics, and many more. Each of these perspectives has made important
contributions to developmental theorizing. Each approach has revealed
both biological and environmental influences on development, and has
proposed models of how they interact. Environmental influences “get
under the skin” and become biologically embedded to impact develop-
ment, as when chronic stress in adverse environments can trigger sus-
ceptibility genes, cause epigenetic changes, and modify brain functioning.
These new findings basically destroy the nature– nurture dichotomy.
Ethology, along with other evolutionary perspectives, is one of zool-
ogy’s main contributions to developmental psychology. Thousands of
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272 c BIOLOGICAL APPROACHES
hours spent observing animals, especially nonhuman primates, have
helped us understand human behavior and its development. Each spe-
cies, including humans, has a set of innate behaviors, specific to that
species. These behaviors have evolved phylogenetically because they have
increased that species’ chances of surviving in its particular environment.
Some of the most important behaviors are social, such as imprinting and
dominance behaviors. Of particular interest are fixed- action patterns
elicited by sign stimuli. Even learned behaviors have a strong genetic
component, because each species has particular learning predispositions
in the form of sensitive periods or general and specific learning abilities.
Ethologists study behaviors by conducting both observations in natural
settings and experimental studies in laboratories.
The ethological point of view has most influenced developmental
psychology by stimulating work on attachment. Very young infants
and adults are pretuned to respond to each other. Current attachment
research examines long- term effects of each pattern of attachment,
adult attachment styles, correlates between parenting quality and infant
attachment, links between attachment quality and an infant’s stress
response, and biological processes involved in developing attachment.
Observation of dominance hierarchies in primates and other animals
has led to similar studies of human peer groups, especially in preschool
settings. Investigators also have asked what cognitive skills might have
evolved in natural settings. With respect to developmental issues, ethol-
ogists see humans as a species that has evolved in order to survive within
a particular environmental niche. Behavior changes both quantitatively
and qualitatively as innate and environmental factors interact during
development. The result is an organism that can operate efficiently within
its environment.
Ethology has several strengths to offer the current field of develop-
mental psychology. With respect to theory, it provides a broad evo-
lutionary perspective on behavior that has encouraged investigators
to look at the function of children’s behaviors. Ethologists advocate
more observational studies of children in natural settings in order to
determine the function of particular behaviors. A final contribution is
the identification of several content areas as particularly important in
development, such as dominance hierarchies, attachment, and cogni-
tion. Ethology has certain weaknesses, however, that limit its usefulness
for developmental psychology. Its theoretical notions, such as sensitive
periods, have not yet reached an explanatory level. With respect to
methodology, the observational method poses many challenges. Finally,
ethologists find it difficult to study certain aspects of development, such
06_MIL_7898_ch5_211_276.indd 272 1/8/16 5:10 PM
as language and abstract thought in older children. Main examples of
contemporary ethological and evolutionary research on development
are attachment, the evolution of human cognition in social groups, and
adaptation during development.
Ethology and evolutionary psychology are a fruitful source of work-
ing hypotheses about what behaviors are important and why they are
acquired. An ethological attitude opens the investigator’s eyes to a broad
context that spans space and time and various levels of analysis. In par-
ticular, ethologically based observations in the early phases of a research
project can give the “big picture” of the behavior that will later be stud-
ied in a controlled laboratory setting.
Neuroscience perspectives have produced models of brain develop-
ment, as cause of and effect of, children engaged in their environments.
Anatomical changes, such as increased myelination, make new learning
possible. An initial overproduction of neurons in early infancy is mod-
ified by experience. Humans have a lifetime of strengthening certain
neural pathways, developing new pathways, and pruning away unused
pathways. An initially highly plastic brain becomes less plastic as spe-
cialization of brain areas and pathways gradually occurs during devel-
opment. Brain areas develop at different rates, resulting in important
asynchronies at certain developmental points, as seen in adolescents’
difficulties controlling their risk- taking behaviors. Finally, brain devel-
opment takes place over the lifespan, subject to constraints from genes,
the environment, and development. Neuroscience has revealed import-
ant mechanisms related to the nature– nurture issue and has provided
evidence for both qualitative and quantitative development. In applica-
tions, neuroscience has improved our understanding of developmental
disorders, such as autism, and has informed the design of educational
programs.
The human genome is an amazingly complex blueprint for develop-
ment. Just as a blueprint may never become a house, a genome may never
be fully translated into behaviors. Genes may be expressed similarly in
most environments, expressed more in some environments than others,
or not expressed at all in certain environments. The two main approaches
are Gene X Environment models and epigenetics. G X E interactions
show that a person’s genotype moderates the effect of an environmental
factor on outcomes, such as traits, behaviors, mental health, and cogni-
tion. For example, highly stressful life events might be more likely to lead
to depression if a person has a particular pattern of genes. Similarly, the
environment moderates the association between a particular gene poly-
morphism and an outcome. Positive, close relationships, especially with
Summary c 273
06_MIL_7898_ch5_211_276.indd 273 1/8/16 5:10 PM
274 c BIOLOGICAL APPROACHES
parents, can buffer the negative effects of certain genes. Epigenetics pro-
vides the molecular mechanism by which G X E interactions affect cell
biology and consequently behavior. Through epigenetics, certain aspects
of the environment affect whether a genetic predisposition is expressed
in behavior, which can result in permanent changes in gene regulation.
Moreover, epigenetic changes can be transmitted to the next generation.
G X E interactions and epigenetics during the course of development
influence degrees of risk for developing a problem, given vulnerable gene
polymorphisms. Bringing together neuroscience and genetics, recent
models have correlated genetic variations and specific patterns of brain
activity. Such information clarifies how the brain is a mediator between
genes and behavior. Variations in environments also should be added to
these models.
Current models of the dynamic interplay among genes, brain, behavior,
and the environment favor a systems approach, to capture the complexity
and co- influences of these components. Development emerges from these
interactions among multiple levels of influence.
SUGGESTED READINGS
The following readings survey evolutionary, including ethological,
research on humans and animals:
Bjorklund, D. F., & Ellis, B. J. (2014). Children, childhood, and devel-
opment in evolutionary perspective. Developmental Review, 34(3),
225–264.
Narvaez, D., Panksepp, J., Schore, A. N., & Gleason, T. R. (Eds.).
(2013). Evolution, early experience and human development: From research
to practice. New York, NY: Oxford University Press.
Lorenz delights us with this account of his life with animals:
Lorenz, K. Z. (1952). King Solomon’s ring. New York: Crowell.
Cognitive developmental neuroscience:
Johnson, M. H., & de Haan, M. (2015). Developmental cognitive neurosci-
ence: An introduction. New York: Wiley- Blackwell. A clear overview of
the field— a good place to start.
Genetics:
NIH has worked with several scientific organizations to create websites
with genetics tutorials for scientists and students in the social sciences.
06_MIL_7898_ch5_211_276.indd 274 1/9/16 12:59 AM
Suggested Readings c 275
As of this writing, the following one with the National Coalition for
Health Profession Education in Genetics is especially useful: http://
www.nchpeg.org/bssr/
Hyde, L. W. (2015). Developmental psychopathology in an era of
molecular genetics and neuroimaging: A developmental neurogenet-
ics approach. Development and Psychopathology, 27, 587–613.
Meaney, M. J. (2010). Epigenetics and the biological definition of
Gene X Environment interactions. Child Development, 81, 41–79. This
article provides background on epigenetics and Gene X Environment
interaction.
06_MIL_7898_ch5_211_276.indd 275 1/8/16 5:10 PM
http://www.nchpeg.org/bssr/
http://www.nchpeg.org/bssr/
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Social Learning Theory
Subjects were tested for the amount of imitative learning. . . . Three measures of
imitation were obtained: Imitation of physical aggression: This category included
acts of striking the Bobo doll with the mallet, sitting on the doll and punching it
in the nose, kicking the doll, and tossing it in the air. Imitative verbal aggression:
Subject repeats the phrases, “Sock him,” “Hit him down,” “Throw him in the air,” or
“Pow.” Imitative nonaggressive verbal responses: Subject repeats, “He keeps coming
back for more,” or “He sure is a tough fella.”
—Bandura, ross, & ross, 1961, p. 33
Dialogue between an interviewer (I) and a mother (M) about her adolescent son:
I: Have you ever encouraged Earl to stand up for himself ?
M: Yes, I’ve taught young Earl, and his Dad has. I feel he should stand up for his
rights, so you can get along in this world.
I: How have you encouraged him?
M: I’ve told him to look after himself and don’t let anybody shove him around or
anything like that, but not to look for trouble. I don’t want him to be a sissy.
I: Have you ever encouraged Earl to use his fists to defend himself ?
M: Oh yes. Oh yes. He knows how to fight.
—Bandura & Walters, 1959, p. 115
These lessons were learned well. One of the boys interviewed mentioned his pride
in his prowess at “stomping”—fighting with his feet: “Like my Dad, he said, ‘If you
know how to fight with your feet, then it’s in your hands, you’ve got it made,’ or
something like that. ‘You never need to be afraid of anybody. ’”
—Bandura & Walters, 1959, p. 122
Se
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rs
to
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C H A P T E R 6
07_MIL_7898_ch6_277_316.indd 277 1/8/16 11:41 AM
278 ▶ SOCIAL LEARNING THEORY
M
ark Twain once remarked, “Training is everything. The peach
was once a bitter almond; cauliflower is nothing but cabbage
with a college education.” This optimistic view of learning
captures learning theorists’ belief that development comes
primarily from experience. Children acquire new behaviors and modify
old behaviors as they encounter their social and physical world. As spe-
cific learning experiences accumulate, children develop, but not in the
stagelike way described by Freud and Piaget. The learning approach is
at the opposite end of the continuum from the biological approaches of
the previous chapter.
It is important to know about learning theories because they brought
scientific respectability to developmental psychology. The approach’s
rigorous research methods made laboratory studies of children possible
in the 1950s and early 1960s, developmental psychology’s formative
years. In this chapter, we see the expansion and transformation of early
learning theory into social learning theory. The focus is on social learning
theory, the most influential learning theory within developmental psy-
chology. The chapter will also present some contemporary approaches
to learning as it is defined today.
Learning theory is the most truly American theory. Most of the
theories in this book arose in Europe and only later influenced North
American psychology. Although early learning studies in Europe can be
found in Russian work on reflexes and conditioning and Ebbinghaus’s
verbal-learning studies in Germany, learning theory blossomed and had
most of its influence on U.S. soil. Learning theory has become part of
our culture and has entered our language as “behaviorism,” “rat psy-
chology,” “behavior modification,” “Skinner box,” and “reinforcement.”
It probably is no accident that learning theory’s emphasis on the role
of the environment fits so well with American egalitarian ideals. If
the environment offers equal opportunity for all, then all humans can
achieve their potential.
In order to understand the assumptions and goals of social learning
theory, we start with its heritage in “classical” learning theory. After that,
sections include a general orientation to social learning theory, examples
of developmental research, and an overview of mechanisms of devel-
opment. Final topics include the theory’s position on developmental
issues, its applications, its strengths and weaknesses, and contemporary
research. The coverage of social learning theory focuses on work stim-
ulated by Albert Bandura, the figure most associated with the theory.
Although Bandura now prefers the term “social cognitive theory,” that
term will not be used because it causes confusion with other areas of
07_MIL_7898_ch6_277_316.indd 278 1/8/16 11:41 AM
History of the Theory ▶ 279
developmental psychology typically labeled as “social cognition.” Also,
the term “social learning theory” still is commonly used by developmen-
tal psychologists when referring to Bandura’s theory.
History of the Theory
Classical learning theory raised many of the issues to which social learn-
ing theory responded. As Henri Bergson (1911, p. 11) noted, “The pres-
ent contains nothing more than the past, and what is found in the effect
was already in the cause.”
Learning Theory
In the early 1900s, psychologists’ attempts to examine systematically
the structure of the mind and the nature of consciousness relied on
introspection—verbalizing one’s own thoughts or feelings. This unsatis-
factory state of affairs led to John Watson’s “declaration of behaviorism”
in 1913. In this strongly worded statement, he asserted that the goal
of psychology should be to predict and control overt behavior, not to
describe and explain conscious states. Just as physical scientists could
observe physical events, psychologists could now point to physical
events (behaviors) as the content of their science and measure them
objectively. Rats press bars, children push buttons, and adults say words.
Learning theorists’ belief in the influence of the environment is
expressed in a famous quote from Watson:
Give me a dozen healthy infants, well-formed, and my own specified
world to bring them up in and I’ll guarantee to take any one at random
and train him to become any type of specialist I might select—doctor,
lawyer, artist, merchant, chief, and yes, even beggar-man and thief,
regardless of his talents, penchants, tendencies, abilities, vocations, and
race of his ancestors.
(1924, p. 104)
Watson did, however, go on to say: “I am going beyond my facts, and I
admit it, but so have the advocates of the contrary and they have been
doing it for many thousands of years.”
Although there are many definitions of learning, a common one is
“a more or less permanent change in behavior which occurs as a result
of practice” (Kimble, 1961, p. 2). Learning theorists’ reductionist strat-
egy for understanding complex behavior is to break it down into simple
units, study the units, and then put the behavior back together again.
07_MIL_7898_ch6_277_316.indd 279 1/8/16 11:41 AM
280 ▶ SOCIAL LEARNING THEORY
The simplest units are associations between a stimulus and a response—
the atoms of psychology. The research strategy, then, is to study sim-
ple associations, then chains of S–R (stimulus–response) associations,
and perhaps even hierarchies of chains, in order to explain complex
behavior. Metaphorically, many simple units of Tinkertoy sticks and
joiners are combined to form a larger structure. During development,
S–R associations can be strengthened, weakened, or chained with other
associations.
Traditionally, learning has been divided into two types: classical con-
ditioning and operant conditioning. Classical conditioning begins with
a reflex—an innate connection between a stimulus and a response.
Examples of reflexes that can be classically conditioned include salivating
when food is placed in the mouth, sucking when a nipple is placed in
an infant’s mouth, and constricting the pupil when a light is shone into
the eye. An unconditioned stimulus (nipple placed in the mouth) elicits
the unconditioned response (sucking). A conditioned stimulus (sight of
the bottle) occurs just before the bottle is given. After repeated pairing
of the bottle and sucking, simply showing a bottle produces sucking.
Sucking has become a conditioned response. More exotic examples are
asthmatic attacks triggered by stimuli such as elevators, children’s choirs,
bicycle races, political speeches, and the national anthem (Dekker &
Groen, 1956).
The most famous case of classical conditioning in children is Watson’s
“Little Albert” experiment. Watson was awarded the grand sum of $100
in 1917 to do this research. He and Rosalie Rayner (Watson & Rayner,
1920) classically conditioned a fear response in 11-month-old Albert.
They placed a white rat in front of the toddler. As he reached for it,
they struck a steel bar behind him with a hammer, producing a noxious,
painful sound. Albert jerked in alarm and cried. After several repeti-
tions of this pairing of the rat and the sound, Albert cried and crawled
away when the rat alone was presented. Albert’s fear was a conditioned
response to the conditioned stimulus, the white rat. The initial reflex was
that the noxious sound (unconditioned stimulus) produced pain (uncon-
ditioned response). The conditioned response generalized to objects
such as a rabbit, a fur coat, and a Santa Claus mask. As it turned out, his
mother removed him from the experiment before Watson had a chance
to decondition him. This study has become controversial in recent years
(Griggs, 2014). In addition to ethical issues, questions have been raised
about Albert’s identity, whether he might have been born with neuro-
logical problems, and whether the conditioning was as successful as is
07_MIL_7898_ch6_277_316.indd 280 1/8/16 11:41 AM
History of the Theory ▶ 281
commonly believed. Over the years, textbook writers have “improved”
the results. In addition, there were methodological problems that muddy
any interpretation of the results.
At a later time, one of Watson’s students, Mary Cover Jones (1924),
found that a naturally acquired fear of animals in a 2-year-old child,
Peter, could be eliminated by extinguishing this fear response, which
presumably was a conditioned response. Peter was seated in a highchair
and given a snack, which produced a positive response. As he ate, a white
rabbit in a cage was brought closer and closer. The conditioned stimulus
(the white rabbit) was not allowed to become powerful enough to evoke
the response of fear by, for example, suddenly being brought too near.
As the stimulus occurred without the related fear response, this associa-
tion was weakened. At the same time, eating, the positive response, was
replacing the negative fear response to the rabbit. The procedure was
quite successful. By the end of the study, Peter was stroking the rabbit
and letting it nibble at his fingers. This treatment obviously requires
a skillful experimenter who does not inadvertently teach the child to
associate eating with fear!
There is an interesting footnote to this research. Peter had to enter a
hospital for treatment of scarlet fever. As Peter was leaving the hospital,
an unfortunate incident occurred. A large dog lunged at him, frightening
him terribly. When Jones then retested Peter, he had reacquired his fear
response to animals and had to be deconditioned again.
This deconditioning technique for overcoming fears contrasts with
Freud’s psychoanalytic study of Little Hans’s fear of horses. Whereas
Freud was concerned with the deep-seated, underlying anxieties, learn-
ing theorists simply try to change the behavior. If Hans would very
gradually approach horses and at the same time establish some posi-
tive response to horses, his conditioned fear response should weaken.
Freud’s view would be that these procedures treat only the symptoms,
not the underlying psychological cause of the problem. If one symptom
is removed, another may appear in its place.
It is difficult to extinguish phobias without intervention because
they are self-perpetuating. By avoiding the feared situation, people
reduce the rising anxiety. Thus, the phobia is reinforced. In addition,
they have no opportunity to extinguish the fear because they do not
allow the feared stimulus to be present. There is an old joke about a man
who is asked why he always holds a banana in his ear. His answer is that
it keeps the lions away. When told there are no lions around, he replies,
“See? It works!”
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282 ▶ SOCIAL LEARNING THEORY
Watson (1924) considered children “lumps of clay” to be shaped by their
environment. He carried his ideas to parents in his child-care manual:
There is a sensible way of treating children. Treat them as though they
were young adults. Dress them, bathe them with care and circumspec-
tion. Let your behavior always be objective and kindly firm. Never hug
and kiss them, never let them sit in your lap. If you must, kiss them once
on the forehead when they say goodnight. Shake hands with them in the
morning. Give them a pat on the head if they have made an extraordinary
good job of a difficult task. Try it out. In a week’s time you will find how
easy it is to be perfectly objective with your child and at the same time
kindly. You will be utterly ashamed of the mawkish, sentimental way you
have been handling it.
(1928, pp. 81–82)
It speaks well for the wisdom and common sense of parents that they did
not adopt his philosophy wholeheartedly. By the 1920s, Watson had left
academia and had become an advertising executive.
The other main kind of learning, operant conditioning, was championed
by B. F. Skinner—one of the most well-known psychologists in history.
Unlike classical conditioning, which begins with a reflex, operant con-
ditioning begins with a behavior that a child spontaneously produces.
Children learn that if they produce a certain behavior, such as smiling
at a parent, they will receive a reinforcement (the delighted parent will
pick them up and play with them). If this sequence occurs a number
of times, smiling can be said to be operantly conditioned as it becomes
more frequent.
The environment changes not only the frequency of behavior by
strengthening and weakening associations but also its form—through
shaping. Pigeons do not naturally play table tennis. However, by begin-
ning with the table-tennis-related behaviors they do have, it is possible
to slowly modify these behaviors into a chain of movements appropriate
to table tennis. The experimenter “ups the ante” (raises the requirement
for obtaining reinforcement) as the behavior gradually comes to approx-
imate the desired behavior. Early in training, moving toward the ball
might be sufficient to receive reinforcement, but later on it may be nec-
essary to make the ball drop onto the opponent’s side in order to receive
reinforcement. Two of Skinner’s students, Keller and Marian Breland,
used shaping to train animals to perform acts for advertising and in their
“IQ Zoo” (Joyce & Baker, 2008). Popgun Pete, a trained chicken, could
pull a string to fire a cannon, and a rabbit could ride a fire engine and
put out a fire. In one exhibit, “Bird Brain,” visitors could play tic-tac-toe
against a chicken, who usually won.
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History of the Theory ▶ 283
Skinner described his first attempt to use shaping on a human:
I soon tried the procedure on a human subject—our 9-month-old
daughter. I was holding her on my lap one evening when I turned on
a table lamp beside the chair. She looked up and smiled, and I decided
to see whether I could use the light as a reinforcer. I waited for a slight
movement of her left hand and turned on the light for a moment. Almost
immediately, she moved her hand again, and again I reinforced. I began to
wait for bigger movements, and within a short time, she was lifting her
arm in a wide arc—“to turn on the light.”
(1980, p. 196)
Thousands of behaviors can be operantly conditioned, ranging
from rats increasingly pressing a bar to children’s diminished drool-
ing (Johnston, Sloane, & Bijou, 1966) to pigeons’ guiding missiles to
their targets in Skinner’s Project Pigeon during World War II. Skinner
(1967) even kept a cumulative record of his writing output, for self-
reinforcement. In a novel, Walden Two (1948), Skinner proposed that
children in his utopian society be raised by behavioral engineers, special-
ists in operant conditioning. Desirable behaviors such as self-control and
independence would be fostered by reinforcement, whereas undesirable
behaviors such as jealousy and poor work habits would be extinguished
by lack of reinforcement.
Skinner’s research goal of defining and controlling the environment
led to the development of certain apparatuses, such as the Skinner box.
This cage-box, with a lever that the animal presses, delivered a food pel-
let to the tray below. Skinner also created a controlled environment for
one of his own infants—a completely enclosed, temperature-controlled,
soundproof “baby tender.” This device has been called a “baby box” and
even an “heir conditioner” (Bradley, 1989). However, it was not, as many
people believed, a Skinner box for conditioning babies.
In the 1960s, laboratory research showed that a wide variety of behav-
iors in infants and children could become more frequent if they were
reinforced. Developmentalists were particularly interested to find that
(a) social reinforcers, such as attention, smiles, and praise from other
people, are especially potent, and (b) the principles of operant condi-
tioning could be applied successfully to undesirable behaviors in natural
settings. So-called behavior modification thus was applied to problematic
behaviors such as temper tantrums, avoidance of social interaction, and,
with autism spectrum disorders, the lack of spoken language. A behav-
ior modifier changes the reinforcement contingencies so that desirable
behavior is reinforced and thereby maintained while undesirable behav-
ior is ignored and thereby weakened. In other words, you try to catch
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284 ▶ SOCIAL LEARNING THEORY
the child doing something right and reinforce it. Harris, Wolf, and Baer
(1967) observed an extremely withdrawn boy who spent 80 percent of
the time at preschool playing alone. Their observations revealed that the
teachers had unintentionally reinforced this behavior by talking to him
and comforting him when he was alone. They ignored the child when he
played with others. The behavior modification program reversed these
contingencies. The teachers attended to the boy when he joined a group
and ignored him when he withdrew. He soon spent 60 percent of his
time playing with other children. Behavior modification thus showed
that a common set of learning principles underlies both normal and
abnormal behavior in children.
As the above account shows, learning studies with children were sim-
ply translations of paradigms used with animals. Children even wandered
through mazes seeking prizes (rather than cheese) at the end (Hicks &
Carr, 1912). It should come as no surprise that children learned faster
than rats but more slowly than college sophomores. The laws of learning
were considered the same in children and other populations. For learning
theorists in the 1950s and 1960s, development involves the accumula-
tion of operantly and classically conditioned responses: “The developing
child may be adequately regarded, in conceptual terms, as a cluster of
interrelated responses interacting with stimuli” (Bijou & Baer, 1961,
p. 15). Learning changes behavior, and thereby causes development.
However, children soon showed that they were unlike rats in many
ways. As learning theorists used slightly more complex tasks in the 1950s
and 1960s, they came to view children as “rats with language.” Children
could label attributes of objects, such as their color or size, and use the
labels to help them learn which attribute always led to reinforcement.
Learning began to look cognitive: Attending to relevant information,
forming hypotheses about the correct answer, and generating strategies
for gathering information increased children’s speed of learning. In fact,
these cognitive skills struck developmentalists as much more important
and interesting than learning per se—the somewhat trivial behavior
of detecting which stimulus was arbitrarily linked to reinforcement in
that particular task. Thus, psychologists began to study language, atten-
tion, memory, and strategies instead. The active, strategic, hypothesis-
forming child seen in learning tasks resembled children described by
Piaget, whose work was beginning to attract attention in the U.S. in
the early 1960s. Furthermore, learning researchers had used abstract,
meaningless stimuli—often colored, geometric shapes—because they
wanted to measure “pure” basic processes of learning, uncontaminated
by previous learning. It is ironic, then, that the most interesting findings
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History of the Theory ▶ 285
from learning research involved children’s use of their previously
acquired cognitive, linguistic, and social abilities as they attempted to
make sense of the simple, meaningless task put before them. The “con-
tamination” was interesting indeed.
Discontent with learning theory came from other quarters as well.
Some of the doubts came from within; hundreds of studies of verbal
learning had not led to a satisfactory account of memory or learning.
In addition, new evidence suggested that biological predispositions
limit or modify the laws of learning. For a given species, some kinds
of learning are easier than others. For example, rats learn to associate
nausea with a certain taste but not with a light or a sound (Garcia &
Koelling, 1966). At the same time, learning theory faced external chal-
lenges. Noam Chomsky’s (1959) attack on B. F. Skinner’s account of
language acquisition was a serious blow because it showed that learning
approaches could not explain the acquisition of a skill as complex as lan-
guage. In addition, alternative conceptions of learning were developing.
Information processing (see Chapter 7), Chomsky’s transformational
grammar, and Piaget’s cognitive theory provided attractive alternative,
more cognitive, explanations of behavior: They characterized learning
as a change in knowledge rather than as a change in the probability of
response. With the entrance of cognitive psychology, psychology began
what Hebb (1960) called its “second American revolution,” the first
being the elimination of any psychology based on introspection.
However, learning theory served a need of the young discipline of
psychology at a critical point in its history. Researchers adopted William
James’s (1892, p. 146) attitude: “I wished, by treating psychology like a
natural science, to help her become one.” Learning theory adopted the
physical sciences as its model, an emphasis that has been called “physics
envy.” Learning theorists asked questions that could be answered and
provided a fruitful methodology for examining those questions, usually
tightly controlled laboratory experiments. In Sheldon White’s words,
learning theories were so influential
because they found for Psychology a reasonable species of psychologi-
cal reality, and because they then laid down a paradigm of cooperative
research procedures which might search that reality with a hope of sig-
nificant findings. . . . one could stop the hair-splitting and throat-clearing
and one could move into intensive scientific development.
(1970, p. 662)
This phase in the history of developmental psychology, from the early
1960s to the early 1970s, was an exciting and fruitful time. A new wave
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286 ▶ SOCIAL LEARNING THEORY
of productive and enthusiastic researchers developed clever experimen-
tal tasks adapted to children. There was confidence that developmental
psychology was progressing. Developmentalists conducted hundreds of
laboratory studies, usually with children easily available—bright, upper-
middle-class children in university towns. (Some 4-year-olds even
greeted experimenters with “What reinforcement do I get this time?”)
Social Learning Theory
Against this backdrop, social learning theorists emerged. They took
learning theory and made it social. Social learning theory was born in
the 1930s at Yale University, perhaps when Clark Hull offered a graduate
seminar on relating learning theory to psychoanalysis. Many of those
attending would become pioneers in social learning theory—O. H.
Mowrer, Neal Miller, John Dollard, Robert Sears, Leonard Doob, and
John Whiting. One of the seminar topics led to the group’s first major
publication, Frustration and Aggression (Dollard, Doob, Miller, Mowrer, &
Sears, 1939), which explored the causes of aggression.
The young group of scholars, trained in learning theory by Hull but
also inspired by Freud, combined these two traditions. In fact, one of
their publications, Personality and Psychotherapy (Dollard & Miller, 1950),
was dedicated to both Freud and Pavlov. Social learning theorists took
interesting and important content from Freudian theory, such as the con-
cepts of dependency, aggression, identification, conscience formation,
and defense mechanisms, but sought explanations for behavior in princi-
ples of stimulus-response learning, which could be observed, rather than
the unconscious, which could not. In Dollard and Miller’s words, “The
ultimate goal is to combine the vitality of psychoanalysis, the rigor of
the natural-science laboratory, and the facts of culture” (1950, p. 3). The
guiding belief of social learning theorists was that personality is learned:
If neurotic behavior is learned, it should be unlearned by some combina-
tion of the same principles by which it is taught. . . . We view the thera-
pist as a kind of teacher and the patient as a learner. In the same way and
by the same principles that bad tennis habits can be corrected by a good
coach, so bad mental and emotional habits can be corrected by a psycho-
therapist. There is this difference, however. Whereas only a few people
want to play tennis, all the world wants a clear, free, efficient mind.
(Dollard & Miller, 1950, pp. 7–8)
Social learning theorists explored much territory in the 1940s and
1950s: imitation, neuroses, cross-cultural influences on personality, iden-
tification, dependency, and child-rearing practices. Their work focused
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History of the Theory ▶ 287
on socialization, the process by which society attempts to teach children
to behave like the ideal adults of that society. As Dollard and Miller
observed, “A system of child training built on the laws of learning might
have the same powerful effect on the neurotic misery of our time as
Pasteur’s work had on infectious diseases” (1950, p. 8). Research exam-
ined correlations between characteristics of parents (for example, high
control and low warmth) or their child-rearing practices (e.g., early
toilet training—Freudianism was still hovering) and the child’s later
personality. In a prototypic study (Sears, Rau, & Alpert, 1965), a child
was placed in a roomful of attractive toys and asked to watch a hamster,
which was in a box with no lid. The experimenter left the room to finish
making the lid for the box. When the temptation to take a closer look
at the toys became too great and the child’s attention left the hamster
for a moment, the hamster silently disappeared through a false floor in
the box. Measures of conscience, specifically guilt, included the length
of time before deviating, the child’s emotional reaction to the deviation,
whether the child confessed, and whether the child accepted blame for
the disappearance.
At first, social learning theorists kept Freud’s focus on drives, whose
reduction is reinforcing. Later, in a major theoretical shift, Miller and
Dollard (1941) turned to imitation as a powerful learning process for
socialization. They proposed that children learn a general tendency
to imitate because various imitative behaviors are reinforced. This
reinforcement of imitation may start very early, as illustrated by this
11-month-old:
Shamini (11 months), noticing great-grandmother snoring with open
mouth, makes a face with jaws open wide but mouth pulled down to
form a small “o” as an imitation of what was an extreme facial gesture.
This causes enormous though slightly embarrassed hilarity in [the] rest
of [the] family. Shamini responds directly to the laughing others, looking
at their faces, laughing, and repeats her “face” with great amusement
several times.
(Reddy, 1991, p. 145)
Social learning theory provided a new perspective on Freud’s import-
ant concept of identification with the same-sex parent. Rather than
“incorporate” the parent and thus acquire a superego, children observe
parents and imitate their behaviors, reflecting their moral values.
Children also control their own behavior by repeating to themselves
their parents’ approving (reinforcement) or disapproving (punishment)
statements. Moreover, adults may praise a boy for being “just like his
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288 ▶ SOCIAL LEARNING THEORY
father.” Children tend to imitate models, such as parents or siblings, who
have been rewarding in the past.
Bandura and Walters (1963) then carried the concept of modeling one
step further by showing that children acquire new behaviors simply by
watching a model who is reinforced. (This cannot have been a stunning
discovery to any parent!) Children who see a hard-working classmate
praised by the teacher learn to try that behavior. And, on the side of
evil, children who get away with a naughty behavior are quickly imitated
as well. Bandura and Walters called this process vicarious reinforcement.
Thus, learning occurs without overt behavior—“no-trial learning,” in
Bandura’s words. This was an important advance over traditional learn-
ing theory, because operant conditioning can gradually produce rela-
tively new behaviors by shaping but cannot explain how complex new
behaviors emerge suddenly after a child watches peers play a new game
or views the antics of superheroes on television.
Bandura and Walters’ imitation theory greatly influenced develop-
mental psychology in the 1960s and early 1970s. It guided most studies
of aggression, sex typing, and resistance to temptation. There was great
interest in discovering which characteristics of models, such as warmth,
power, and similarity to the observer, encouraged imitation. In addition,
the list of social reinforcers was broadened to include peers.
Bandura continued to develop social learning theory and made it even
more cognitive, and thus coined the term social cognitive theory (Bandura,
2012). Social learning theory was able to continue to thrive, despite
the demise of learning theory more generally, because Bandura brought
cognition into social learning theory early on in plausible and interest-
ing ways. He rejected what he called the radical behaviorist “cognitive
bypass operation” (Evans, 1989, p. 83). He was less concerned with the
literal duplication of behavior (imitation) than with observational learning
as a more general process of acquiring information from other people,
books, and electronic media. Observational learning may lead to imita-
tion when there is a model to imitate, but it need not lead to imitation.
After children acquire new behaviors by observing various models,
they can combine and cognitively organize these behaviors to form
more complex behaviors. A girl may become gender typed as female
by observing behaviors of her mother, older sister, female teachers, and
females on television. Learning to play basketball requires integrating a
number of simpler subskills, such as dribbling, guarding, and shooting
baskets. Children sometimes can learn whole complex behaviors all at
once. A young child may learn to play Monopoly after watching peers
play one game.
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General Orientation to the Theory ▶ 289
Because of his groundbreaking work, Bandura is listed as the 20th
century’s fourth most eminent psychologist, right after Skinner, Piaget,
and Freud (Haggbloom et al., 2002). He won several top awards, includ-
ing the American Psychological Association’s Distinguished Scientific
Contribution award “for masterful modeling as researcher, teacher,
and theoretician” (American Psychologist, 1981, p. 27). He was elected
to the National Academy of Sciences, is a Fellow of the American
Academy of Arts and Sciences, and served as president of the American
Psychological Association.
General Orientation to the Theory
The main characteristics of social learning theory are the centrality of
observational learning, a causal model that involves an environment–
person–behavior system, cognitive contributions to learning, and
self-efficacy and agency.
Observational Learning
Both Vygotskian–sociocultural theory and social learning theory empha-
size environmental, nonbiological influences on behavior and the impor-
tance of learning from watching other people in this environment. Both
view development as embedded within pervasive cultural belief systems,
which are acquired by children in part by participating in activities with
other people. However, social learning theorists focus on children as
individuals acquiring competencies and skills, whereas sociocultural the-
ories emphasize children’s culturally saturated social contexts.
Observational learning provides one answer to one of the big myster-
ies of development—how children quickly learn complex new behav-
iors. Observational learning accounts for most new behaviors. Toddlers
learn an average of one to two new behaviors every day simply by
watching and listening to others (Barr & Hayne, 2003). Observational
learning is particularly useful for explaining how novel, complex behav-
iors are acquired during development, which is especially important in
those areas where mistakes are costly or life threatening. There cannot be
much trial-and-error learning in avoiding playing in the street, learning
to drive a car, or conducting brain surgery.
How observational learning occurs can be illustrated by a real-life
example and a laboratory study. One skill acquired by many boys and
girls today is playing soccer. This skill includes a complex set of concep-
tual and perceptual motor skills. It is doubtful that this skill could be
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290 ▶ SOCIAL LEARNING THEORY
taught simply by telling children how to play the game (just try, through
words only, explaining to a child how to do a “header”—deflecting the
ball with one’s head). Children learn from observing models playing—
older children, parents, coaches, and professional soccer players on tele-
vision. These models are particularly likely to be imitated because they
are perceived as having high status, competence, and power (Bandura,
1986; Wood, Kendal, & Flynn, 2013). Books on how to play soccer also
provide symbolic models. These various types of models demonstrate
how to travel with the ball, pass, attempt goals, make corner kicks, and
express elation appropriately after scoring a goal.
To a great extent, children learn the game through what Bandura calls
abstract modeling—abstracting a general rule from observing specific
behaviors. Children gradually extract general concepts of group action
in the game: team defensive strategy, predicting where one’s teammates
will be at a particular moment, and strategies concerning how to play
one’s position.
Children often receive feedback regarding how closely their behavior
matches the model’s. The coach may praise a skillful pass. An attempt to
score that misses the goal gives immediate feedback, and players may
adjust the angle of their kick next time or seek further verbal instruction
or demonstration from others. This reinforcement or nonreinforcement
is a source of information to children concerning their behavior and also
provides an incentive for further participation. Still, reinforcement or
punishment to the model or the child is not necessary for observational
learning to occur: “After the capacity for observational learning has fully
developed, one cannot keep people from learning what they have seen”
(Bandura, 1977, p. 38).
Of the numerous laboratory studies of observational learning, an
excerpt from the famous “Bobo doll” experiment by Bandura, Ross, and
Ross (1961) appears at the beginning of this chapter. Preschool children
saw an aggressive adult model punch a large, inflated Bobo doll and hit
it on the head with a hammer, saying, “Sock him in the nose” and “Pow.”
In a comparison group, the model played nonaggressively with toys, and
a control group had no model. Later, the children played in a room con-
taining a variety of aggressive toys (Bobo doll, dart guns, tetherball with
a face painted on it) and nonaggressive toys (tea set, teddy bears, trucks),
including the toys the adult model had used aggressively. The children
who had observed the aggressive model were more aggressive than the
children who had seen a nonaggressive model or no model. Some of
children’s aggression matched novel behaviors shown by the model, such
as hitting a Bobo doll over the head with a hammer. However, seeing an
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General Orientation to the Theory ▶ 291
aggressive model also seemed to generally disinhibit other aggressive
behaviors, not shown by the model, that the children already had but
typically kept under control. Examples were firing imaginary shots at
objects and saying “Stupid ball” and “Knock over people.” This point is
important because it indicates that seeing even mild aggression might
elicit a great deal of aggression of various kinds.
This study attracted much interest because it suggested that watching
violence on TV or in movies would increase aggression. It was debated,
however, whether the children were expressing “aggression” or simply
playing vigorously in a setting in which doing so seemed to be approved
by adults. Also, they just may have been aroused emotionally and thus
more active.
It is clear that Bandura and Freud give us opposite predictions con-
cerning the effects of watching aggression in other people. Freud would
see such an activity as a way of reducing aggressive tensions, thus less-
ening subsequent aggression. In contrast, Bandura would predict that
viewing aggression, especially if the aggression is not punished, is likely
to cause imitation, thereby increasing aggression. And that is what was
found. Ethology offers yet another perspective on the effect of watching
aggression. Watching who successfully aggresses against whom provides
information for learning the dominance hierarchy of one’s group.
A further result in this study is noteworthy. Although the boys were
physically more aggressive than girls, from other studies we know that
girls learn as much aggression from the model as do boys (e.g., Bandura,
1965). That is, girls can produce the aggressive behaviors when asked
to or rewarded for doing so but typically do not produce as much phys-
ical aggression, perhaps because adults are more likely to prohibit this
behavior in girls than boys. Thus, one must make a distinction between
learning and performance. The finding that children learn and remem-
ber what they observe even if it is not reproduced immediately raises
the concern that viewed violence on television may not have obvious
immediate effects but may be stored in memory for future use.
Researchers have used the basic paradigm of Bandura’s study to show
that observational learning of a variety of behaviors (prosocial behavior,
styles of information processing, conservation of number) is widespread
throughout childhood through a variety of models (filmed, symbolic,
real). Observational learning continues during adolescence. For exam-
ple, adolescents with high exposure to smoking in movies were about
three times as likely to try smoking or become smokers (Heatherton &
Sargent, 2009), even after controlling for a variety of demographic and
personality factors, as well as parenting style.
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292 ▶ SOCIAL LEARNING THEORY
Can social learning explain cultural differences in social behaviors and
personality? Many of the behaviors pervasive within a culture reflect the
fact that children in the culture are exposed to the same or similar mod-
els. For example, cultures vary in teaching about aggression. The Dugum
Dani, a warrior society in the New Guinea highlands, has a training
program that brings boys closer and closer to real warfare (Gardner &
Heider, 1969). War games include skewering the enemy (berry seeds)
on a sharp stick, spearing a hoop tossed by the opposition, battling with
grass “spears,” and watching real battles from a distance. In contrast,
the Polynesians of the Society Islands actively discourage aggression and
rarely provide aggressive models (Levy, 1969). They teach their children
that spirits punish aggression with illness and injury.
Observational learning not only is a process of normal socialization
but also can be a therapy for problem behaviors. For example, observa-
tional learning can help children overcome fears. In one study (Bandura,
1967), preschool children who were afraid of dogs watched a child hap-
pily approach a dog gradually and play with it. After the therapy and even
one month later, most of the previously fearful children would hand-feed
a dog and even climb into a playpen with it. Even just showing the mod-
eling sequence on film also reduced their fears.
Causal Model Includes Environment–Person–
Behavior System
Bandura’s model of learning includes three components: biological and
psychological characteristics of the person (P), the person’s behavior (B),
and the environment (E). In triadic reciprocal causation, these three fac-
tors are highly interdependent, and each factor influences, and is influenced
by, each of the others. Consider a situation in which a girl observes a boy
giving some of his pennies to help poor children. Several characteristics of
the observing child influence whether she will imitate this behavior (P→B).
Is she cognitively and socially developed enough to understand what it
means to be poor? What are her standards of fairness or social justice? Has
she observed her parents contributing to charities in the past? The environ-
mental factors might include the social status of the model, whether the
model was praised after he gave, the salience of the model in that situation,
and other social influences (E→P, E→B). If the girl feels pleased with her-
self after sharing, the behavioral act of sharing affects her psychologically
(B→P). Cognition is important in this process; children symbolically repre-
sent the relationships among the situation, their behavior, and the outcome.
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General Orientation to the Theory ▶ 293
Bandura (1997) describes three types of environments: imposed,
selected, and created. They vary in the child’s active contribution. An
imposed environment is thrust on people. They cannot control its pres-
ence, but they have some control over how they construe it and react
to it. For example, children must attend school, but if they do not like
it at first, they can try to find aspects they like. A selected environment is
the part of the potential environment that people actually experience.
Only the parts of the environment that children select and activate can
affect them. A high school student chooses certain school courses but
not others. A student may take advantage of extracurricular activities
and engage in rewarding leadership experiences or become entangled in
peer pressure to engage in risky behaviors such as heavy drinking. Created
environments are those that children construct through their behavior
(B→E, P→E). Children who choose to watch television a great deal
expose themselves to a set of models that differs from that of children
who usually play with friends instead. Or children may perfect a skill,
such as drawing or ballet dancing, which creates an environment of
social reinforcement in the form of praise from others. In the sharing
situation described above, children who have habitually shared in the
past and thereby elicited warmth and gratitude from others have created
a positive, supportive milieu for themselves. In contrast, aggressive chil-
dren may create a hostile environment for themselves wherever they go,
causing others to react negatively toward them. Thus, children actively
contribute to their own development.
Evidence that children’s behavior can change their social environment
comes from a study by Brunk and Henngeler (1984). Two 10-year-
old child actors exhibited either anxious–withdrawn or aggressively
noncompliant behavior in a setting in which mothers (not their own)
attempted to engage each boy in a game of checkers. The mothers used
more helping and rewards with the anxious–withdrawn child and more
ignoring, commands, and discipline with the aggressively noncompliant
boy. Thus, the boys “created” two different social environments.
One striking example that personal factors lead people to select par-
ticular environments, even where to live, comes from a study in Finland
(Jokela, Elovainio, Kivimäki, & Keltikangas-Järvinen, 2008). Major
temperament traits, such as sociability, emotionality, and activity pre-
dicted migration patterns. Highly sociable people tended to migrate to
urban areas and longer distances; high activity people generally tended
to migrate, and highly emotional people tended to leave home but not
move far away.
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294 ▶ SOCIAL LEARNING THEORY
Cognitive Contributions to Learning
What is Matter? —Never mind.
What is Mind? —No matter.
—Punch, 1855
Figure 6.1 presents Bandura’s (1986) outline of the cognitive processes
underlying observational learning and, to provide a context, the other
component processes involved as well. This model advanced research
on observational learning because it provided a detailed, careful analy-
sis of the specific processes involved in such learning. Because each of
these processes undergoes development, the model provided a map for
studying processes of social development. Children select and process
information, apply general rules or principles, weigh information, and
make a decision—processes described by information-processing theory
(see Chapter 7). Cognitive factors influence what is observed, how that
person or event is perceived, how this new information is organized for
the future, whether the observational learning has a lasting effect, and
what this effect is.
To illustrate these processes, consider a young boy watching a TV
show in which a character beats up another person. Characteristics of
both the model and the boy control the boy’s attention. As summarized
in Figure 6.1, the boy is more likely to attend to the model if the model
is salient (e.g., aggressive) and attractive (e.g., a superhero), if the mod-
el’s behavior is not too complex for the boy’s understanding, if there
are many opportunities to see the model fighting (prevalence), and if
the model’s behavior proved to be effective (functional value). The boy’s
cognitive level, his ability to attend selectively, and his past experiences
influence whether he attends to this particular model. Also, if he has an
optimal level of arousal—not tired, in an alert state—he is more likely
to attend. His attention also may be affected by his expectations about
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07_MIL_7898_ch6_277_316.indd 294 1/8/16 11:41 AM
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07_MIL_7898_ch6_277_316.indd 295 1/8/16 11:41 AM
296 ▶ SOCIAL LEARNING THEORY
rather than another child. What he retains in memory does not have to
be structurally similar to the model’s behavior; it could be a rule, such as
“It’s OK to beat up bad guys.”
The two remaining component processes—production processes and
motivational processes—pertain to the child’s actual performance of the
learned behaviors. When he is pretend-fighting later, he may compare
his behaviors with his mental representation of the model’s behavior and
perhaps modify his behavior (“I have to do a high kick to the chin”). As
for motivation, the boy is more likely to reproduce the fighter’s behav-
ior if the fighter won the fight and the boy thought it looked like fun.
In contrast to Piaget, who examined only the cognitive development
making imitation possible, Bandura is interested also in why a child is
motivated to imitate only certain actions of certain models at certain
times and places.
Abstract modeling, described earlier, is a particularly important
developmental advance. Children can formulate an abstract rule by
pulling out the relevant elements from a number of specific episodes of
observational learning. Abstract modeling is the theory’s main mecha-
nism for explaining language learning. As children observe that the past
tense is usually formed by adding -ed, they abstract this as a general rule
and correctly say “walked” and “talked” and incorrectly say “hitted” and
“doed.” They may even use rules to make very complex incorrect utter-
ances such as “He was disingappeared.”
In contrast to Piaget’s theory, thinking stays near the surface in
Bandura’s theory. That is, children detect regularities in the environ-
ment and generalize them; for example, “I’m usually good at that sort
of game.” These external events are translated into a symbolic form
and combined with other symbolically represented events or used as
information to develop a more general rule; however, the theory does
not specify the construction of broad cognitive structures of the type
described by Piaget. Bandura’s concepts are more like constructed sum-
mary statements about the world.
Self-Efficacy and Agency
“I think I can. I think I can. I think I can.”
—PiPer,The Little Engine That Could, 1989/1930. (quoted in Maddux, 1998)
In recent years, Bandura has emphasized self-efficacy—people’s perception
of their competence in dealing with their environment and exercising
influence over events that affect their lives. A more formal definition
07_MIL_7898_ch6_277_316.indd 296 1/8/16 11:41 AM
General Orientation to the Theory ▶ 297
is “beliefs in one’s capabilities to organize and execute the courses of
action required to produce given attainments” (Bandura, 1997, p. 31).
These courses of action may include behavior, thoughts, and emotions.
Self-efficacy affects all types of behavior—academic, social, and recre-
ational. Children may have the necessary skills for mastering a task, but
if they do not perceive themselves as capable of actually using their skills
effectively, they may fail or, unlike “the little engine that could,” may not
even attempt the task. For example, when given difficult math problems,
children with high math self-efficacy solved more problems, more quickly
rejected strategies that did not work, more willingly reworked failed prob-
lems, and displayed more positive attitudes toward mathematics than did
children with low math self-efficacy (Collins, 1982). This was true even
of children with low math ability. This positive reaction to failure among
highly efficacious children reflects their attributions of their failure to
insufficient effort; they then try harder. In contrast, low-efficacy children
attribute their failure to low ability, an attribution that does not encourage
them to continue trying.
Thus, high self-efficacy is essential for persisting in the face of rejec-
tion. Bandura recounts the many rejections encountered by talented
people who persisted:
James Joyce’s The Dubliners was rejected by 22 publishers. Gertrude Stein
submitted poems to editors for about 20 years before one was finally
accepted. Hollywood initially rejected the incomparable Fred Astaire as
“a balding, skinny actor who can dance a little.” Decca Records turned
down a recording contract with the Beatles with the unprophetic eval-
uation, “We don’t like their sound. Groups of guitars are on their way
out.” . . . Walt Disney’s proposed theme park was rejected by the city of
Anaheim on the grounds that it would only attract riffraff.
(1997, p. 73)
Even infants are developing a sense of personal agency, a sense that
they can cause effects in their environment, which is essential for
self-efficacy. During development, children gradually construct their
self-knowledge about their efficacy in various situations from four main
types of information. The most authentic and direct source of infor-
mation is the success or failure of previous similar attempts. A second
source is the vicarious experience of observing others fail or succeed
on similar tasks. If children perceive themselves as similar to a model
who succeeds, their self-efficacy is enhanced. A third source of infor-
mation is others persuading children into believing they can achieve
their goal. For example, parents praising their child’s efforts at age 14
07_MIL_7898_ch6_277_316.indd 297 1/8/16 11:41 AM
298 ▶ SOCIAL LEARNING THEORY
to 38 months predicts children at age 7 to 8 attributing their success
to hard work, preferring challenging tasks, and generating strategies
for improvement (Gunderson et al., 2013). Finally, information comes
from one’s physiological and affective states: arousal, anxiety, fatigue,
and physical pain. Cognitive development helps children integrate
these four sources of information. Acquiring language, becoming more
socially aware, and learning to tell one’s emotions apart contribute
information as well.
Both parental and child self-efficacy is important for positive develop-
mental outcomes. Parents’ self-efficacy regarding their parenting skills
underlies many of the correlates of parenting quality such as maternal
depression, child temperament, social support, and poverty (Coleman &
Karraker, 1997). Not surprisingly, parents’ feelings of self-efficacy con-
cerning their parenting decrease as their children move from early to
middle adolescence, with its new challenges (Glatz & Buchanan, 2015).
This drop is less if the adolescent and parents have established good
communication. The peer group becomes increasingly important for
self-efficacy. Children with low social self-efficacy “exhibit social with-
drawal, perceive low acceptance by their peers, and have a low sense
of self-worth” (Bandura, 1997, p. 173). Children with high self-efficacy
for aggression are quick to use aggression with their peers to obtain
goals. Schooling, of course, contributes greatly to children’s sense of
intellectual efficacy in various areas. An example of schooling’s effect on
self-efficacy is that children who perceived their classroom environment
as more caring, challenging, and mastery oriented had greater math
self-efficacy, which in turn predicted math performance (Fast et al.,
2010). All of these sources influence children’s resulting self-efficacy,
which affects how resilient they are to adversity and how vulnerable they
are to stress and depression.
Throughout the life span there are changes in which aspects of self-
efficacy are most important. For example, adolescence and young
adulthood bring new challenges to self-efficacy regarding interper-
sonal relationships, physical appearance, and occupational competence.
During middle age, people may reevaluate their lives, doubt their effi-
cacy concerning physical performance, and seek to achieve efficacy in
new areas. A divorce or retooling for a new occupation may be the out-
come. Elderly people may face damaged self-efficacy as a result of per-
ceived memory loss, slowed reactions, and lessened self-esteem because
they no longer hold a job. A self-fulfilling prophecy can occur: If elderly
people are insecure about their efficacy and expect to fail, they may
limit their range of activities and invest little effort in any activity, thus
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General Orientation to the Theory ▶ 299
ensuring their failure. Bandura argues that true declines due to aging can
be offset greatly by real-world knowledge and coping strategies acquired
throughout one’s lifetime.
Self-efficacy is related to the processing of information outlined in
Figure 6.1. Interesting processing biases may be at work. People who
tend to attend to and recall the negative features of their performance
may underestimate their efficacy. Thus, parents and teachers can enhance
children’s self-efficacy by drawing attention to the positive aspects of
their performance and thereby increasing the salience of those aspects.
In fact, the efficacy judgments most conducive to development are slight
overestimations, because these motivate children to try moderately chal-
lenging tasks that could hone their present skills. Parents across cultures
may differ in their response to their child’s success and failure. Chinese
mothers de-emphasize their children’s academic success and emphasize
their academic failure, whereas the opposite is true for American moth-
ers (Ng, Pomerantz, & Lam, 2007).
Collective efficacy is a group’s shared belief in its ability, through collec-
tive action, to produce valued outcomes. For example, high collective
family efficacy is associated with adolescents’ and parents’ satisfaction
with their family life, in part because of the open family communica-
tion and adolescents’ disclosure to parents of their activities outside the
home (Bandura, Caprara, Barbaranelli, Regalila, & Scabini, 2011). As
for a larger group, efficacious schools have characteristics such as strong
academic leadership by administrators, high academic standards and
the belief that students can meet them, and instruction that encourages
students to exercise control over their performance. Bandura believes
that collective political efficacy locally and nationally can bring about
social change that addresses social problems such as ineffective schools,
illiteracy, poor health practices, risky behaviors, unwanted pregnancies,
and the threat of nuclear war. Collective efficacy empowers individuals,
who then increase collective efficacy.
Closely related to self-efficacy is agency. Children are active rather
than passive. If children believe they have the power to produce desired
outcomes (self-efficacy), they are motivated to behave in ways to achieve
these goals (agency) (Bandura, 2006a). For example, a boy wants to buy
a bicycle (sets a goal), plans how he will earn enough money to do so,
and persists at mowing neighbors’ lawns because he keeps thinking
about buying the bicycle. He resists temptation to play with his friends
instead (regulates himself) and when he finds he is proceeding toward
his goal more slowly than he expected, he reflects on whether he in
fact has the necessary motivation to achieve his goal. People reflect on
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300 ▶ SOCIAL LEARNING THEORY
and manage their inner life of emotions and thoughts, as well as their
actions: “[P]eople live in a psychic environment largely of their own
making” (Bandura, 2006a, p. 165).
Examples of Developmental Research: Moral
Judgments and Gender Roles
Two main points of contention between social learning theory and other
theories concern two important developmental acquisitions—moral
judgments and behavior, and gender-role development.
Moral Judgments and Behavior
An important legal question is “At what age can children understand
right from wrong and be responsible for the crimes they commit?”
Different theories offer different perspectives on children’s understand-
ing of morality. For Piaget, changes in moral judgments result from
general cognitive development. Children move from a focus on amount
of damage and degree of punishment to a focus on intentions and exten-
uating circumstances. For Vygotsky, children internalize the moral belief
system of their culture during interaction with adults and peers, such that
moral reasoning varies from culture to culture. For Freud, identification
with parents, especially a parent of the same sex, brings a set of internal-
ized moral standards to children. Social learning theorists emphasize that
children use observed specific behaviors or moral statements to actively
construct general standards of conduct—rules, goals, and expectations
for their own behavior. These standards are especially effective in regulat-
ing behavior because children generalize them to many situations, and use
them even when an external authority is not present. Unlike for Freud,
the parent of the same sex serves as only one of many models from whom
the child learns.
One contribution of social learning theory is to explain why a child’s
moral reasoning or behavior would vary from situation to situation and
from child to child. A child’s previous history of observational learning
and the models in a particular situation influence the child’s behavior. For
example, young boys use moral-judgment rules that are similar in form
and complexity to those of their mothers (Leon, 1984). Also important
are the child’s personal standards, adults’ prohibitions, the expected
punishment or reward, and peer influence. Moral judgments involve a
complex process of considering and weighing various criteria in a given
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Examples of Developmental Research: Moral Judgments and Gender Roles ▶ 301
social situation. Thus, unlike in Piaget’s theory, in some situations a child
makes a judgment based on intentions and in another situation makes a
judgment based on amount of damage.
The tendency of older children to emphasize intentions in moral
judgments reflects their greater exposure to models making such judg-
ments. Also, adults have heightened expectations of older children,
and older children can more easily infer internal states from situational
cues. For example, when disciplining a child, parents are more likely to
explain their reasons for doing so if the child is 8 years old rather than
3 years old. The younger child is not impressed with arguments about
fairness and equality. Similarly, parents’ presentation of legal codes and
societal punishment may be reserved for preadolescents and adolescents.
Thus, children of different ages tend to see models presenting different
sorts of moral judgments.
The main evidence bolstering the social learning account is that chil-
dren’s moral judgments can be altered by a brief social experience in
the laboratory. In a prototypic study, Bandura and McDonald (1963)
first assessed 5- to 11-year-olds’ moral reasoning, based on Piaget’s
stories depicting moral dilemmas. One actor had good intentions but
produced great material damage, whereas the other actor had bad
intentions but produced minimal material damage. First the model
and then the child made judgments about stories. Then the researchers
exposed children to a model whose judgment was opposite that of the
child’s. In a final test for generalization, a different adult in another
room presented new stories that the child judged. As predicted by social
learning theory, the children adopted the model’s moral standards. The
fact that this new moral perspective generalized to new stories in the
third phase suggests that the children abstracted a general rule rather
than imitated specific responses. A control group with no model did
not change. Children maintained these changes for at least a month
(Dorr & Fey, 1974).
Bandura proposed an interesting concept, moral disengagement, which
refers to people justifying their unacceptable behavior. This mental fire-
wall between moral standards and behavior illustrates the important dis-
tinction between moral cognitions and behavior. Moral disengagement
(e.g., blaming the victim, diffusing responsibility away from oneself to
one’s social group) is related to both traditional and cyberbullying in
young adolescents (Robson & Witenberg, 2013). Online social inter-
action may particularly encourage bullying, because features of online
communication, such as not seeing others’ emotional reactions in per-
son, may facilitate aggression (Runions & Bak, 2015).
07_MIL_7898_ch6_277_316.indd 301 1/8/16 11:41 AM
302 ▶ SOCIAL LEARNING THEORY
Gender-Role Development
The development of gender roles is central to much of social develop-
ment. Almost everything we do is gendered, and almost every aspect
of society, from parents to the media, shapes children toward cultural
values concerning gender roles. For social learning theory, the devel-
opmental processes described above also apply to gender-role develop-
ment (Bussey, 2011). Gender development flows from the interaction of
intrapersonal, behavioral, and social influences operating within societal
systems composed of parents, peers, teachers, mass media, and various
social institutions. Gender roles develop through the processes of obser-
vational learning and self-regulation.
Cognitive development also contributes: Infants and toddlers learn
to differentiate between males and females according to their associated
appearance and activities. They learn what their gender is, label them-
selves and others according to gender, and note the styles of behavior of
each gender. By age 3 or 4, or even earlier, children disapprove of boys
feeding, diapering, and comforting dolls and girls playing with trucks.
In fact, in one study (Bussey & Bandura, 1992), when children of this
age were confined to a playroom with only toys gender-typed for the
other gender, they ignored the toys. One boy even flung the doll across
the room and turned his back on it. Some boys tried to transform the
feminine toys into masculine ones, for example, by using an eggbeater as
a gun or a drill. The boys tried to have the “feminine” toys removed. One
boy pointedly told the departing experimenter, “No, I’m finished with
those toys,” even though he had not played with them at all.
During childhood, children continue to form abstractions about
gender based on observations of behaviors and rewards or sanctions.
Childhood provides numerous opportunities to observe gendered behav-
ior because children tend to seek out same-sex playmates and, even
when both sexes are available, to imitate same-gender models more than
other-gender models. Even 3-year-olds copy the preferences of same-sex
(over different-sex) child models for novel food, clothes, toys, and games
(Frazier, Gelman, Kaciroti, Russell, & Lumeng, 2012). They see people
and behaviors repeatedly labeled according to gender and observe that
only certain behaviors are sanctioned for each gender and that opportu-
nities are heavily organized by gender (for example, how far away from
home one can ride one’s bicycle alone, whether wearing jewelry is dis-
couraged). Girls learn that others disapprove of their physical aggression.
Self-efficacy comes into play in many ways, for example, regarding
probable success if one enters male-dominated versus female-dominated
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Mechanisms of Development ▶ 303
occupations. This has been particularly true for fields requiring math
skills; females tend to underestimate their efficacy in this area. For exam-
ple, girls whose teachers do not hold stereotypic biases about gender
develop greater mathematical self-efficacy and valuing of mathematics
(Eccles, 1989), and girls’ perceived self-efficacy in various areas affects
whether they select careers traditionally associated with females (Bandura,
Barbaranelli, Caprara, & Pastorelli, 2001).
Mechanisms of Development
Social learning theorists focus on processes of change (as did Vygotsky)
in contrast to Piaget and Freud, who were more interested in struc-
tural change as children go through the stages. According to Bandura,
development occurs because of three main factors: physical maturation,
experience with the social world, and cognitive development. These
three factors cause developmental changes in all of the processes in
Bandura’s model in Figure 6.1. The first factor, physical maturation, holds
little interest for social learning theorists. Its main relevance is that
young children may not have the physical maturity to reproduce certain
motor patterns they observe. The other two factors are much more
important.
As already discussed, experience with the social world causes develop-
ment as children engage in observational learning and construct general
concepts or rules. As children get older they are exposed to a wider
variety of people, behaviors, and media. Moreover, their social environ-
ment changes simply because society, ranging from their parents to the
legal system, changes its expectations of them. A 4-year-old who cannot
add is not a cause for alarm to adults, but a 7-year-old who cannot add
faces a social environment in school directed toward learning this con-
cept. A teacher provides much more help with reading to a first-grader
than to a third-grader. Older children, by watching the teacher, are
expected to learn complex new skills quickly, with a minimum of verbal
instruction.
The third factor, cognitive development, refers to changes in the cognitive
skills in Figure 6.1. Cognitive processes such as attending, remembering,
integrating pieces of information, and evaluating feedback pull social
development along. The growing ability to translate observations into
symbols and to recombine these symbols makes observational learning
much more flexible and enduring. Older children can model behavior by
reading a description of it or listening to instruction rather than by having
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304 ▶ SOCIAL LEARNING THEORY
to see the behavior. Age differences in cognitive processes can be seen in
what children assimilate while watching a movie. Older children have
much better comprehension and recall of characters, behaviors, motiva-
tions, and outcomes of the behaviors (Newcomb & Collins, 1979). Young
children often do not even make a connection between the model’s
behavior and the consequences of that behavior later on.
Position on Developmental Issues
Human Nature
Learning theories have served as textbook writers’ favorite example of a
theory with a mechanistic view of human behavior. An infant—“a lively
squirming bit of flesh” (Watson, 1928, p. 46)—is material to be fash-
ioned by parents and society. The mechanistic model, however, does not
accurately represent modern social learning theory, in which “people are
self-organizing, proactive, self-reflective, and self-regulating” (Bussey &
Bandura, 1999, p. 691). In triadic reciprocal causation, discussed earlier,
people actively operate on the environment, just as the environment acts
on them. People filter their experience through their current knowledge
and expectations about the world, create their own environment as their
own behavior influences the environment, and generate new behavior
by reorganizing previously learned behaviors. Thus, one can see some
elements of the organismic (e.g., self-organizing) and contextual (e.g.,
contexts matter) worldviews.
There is a basic difference among theorists concerning the role
of interaction. For Piaget and Vygotsky, the interaction or exchange
between a child and the physical (Piaget) or social (Vygotsky) environ-
ment forms a structure that later becomes an internalized cognitive
structure. In contrast, for Bandura the structure of the interchange
between the child and the environment is less important than the new
information acquired or the increased self-efficacy as a result of this
interchange.
One point of comparison among the theorists is the view of humans
as rational or irrational. Both Piaget and Vygotsky emphasized the devel-
opment of rational, logical thought. Although all the theorists consider
logical thinking important, both Freud and Bandura studied illogical,
irrational thought as well, perhaps because of their focus on motivation.
For Bandura, children may think logically or illogically, depending on the
types of models they have encountered in problem-solving situations.
They acquire styles of processing information from other people.
07_MIL_7898_ch6_277_316.indd 304 1/8/16 11:41 AM
Posit ion on Developmental Issues ▶ 305
Qualitative Versus Quantitative Development
Social learning theory views development primarily as a process of quan-
titative change, in which learning accumulates over time. Development
simply involves a multitude of short-term changes. Observational learning
may change somewhat qualitatively when symbolic representation of oth-
ers’ behaviors becomes possible, and when changing from one set of rules
to different ones. However, we do not find either rapid qualitative changes
in movement from one stage to another or massive cognitive reorganiza-
tion. Bandura considers the search for stages counterproductive because
stages draw attention away from individual differences and differences in
the way a given child functions in different environments. Furthermore,
Bandura notes that a failure to learn may be dismissed as a lack of cognitive
readiness, when it actually reflects a poor learning environment. He thinks
that an analysis of which subskills are needed to produce a certain behavior
or knowledge is much more promising than positing stages.
Nature Versus Nurture
A young branch takes on all the bends that one gives it.
—chinese ProverB
Social learning theorists, like sociocultural theorists, emphasize nurture
more than does Freud and much more than does Piaget, the interactionist.
However, social learning theorists do not follow the militant environmen-
talism of traditional learning theory, which viewed the young mind in the
way British empiricist John Locke viewed it: a blank slate on which expe-
rience writes. Rather, biology, for example, species-specific behaviors, can
constrain learning. This was demonstrated dramatically in an attempt to
train raccoons to drop tokens into a slot (Breland & Breland, 1961). The
animals stopped to “wash” the tokens, as if they were food, even though
there was no water around. Bandura’s view of the roles of biology and
children’s active constructors of their experience is captured in his notion
of triadic reciprocal causation. The environment, the person (including
physical maturation), and the person’s behavior are interdependent forces
operating in any event. However, the evolutionary, genetic, and neural
developmental aspects of the person are given little attention.
What Develops
Because what is developed depends greatly on what the environment has
to offer for learning, learning theorists propose few universal behaviors
that would be found in every culture. Whereas Piaget claimed that all
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306 ▶ SOCIAL LEARNING THEORY
physically normal children in the world develop concepts of object
permanence, causality, and conservation, and Freud assumed a universal
concern with sexuality and aggression, social learning theory appears to
be almost content-free (as does Vygotsky’s theory). Investigators have
directed their energy toward process rather than content. One culture
may encourage aggressive behavior, whereas another may discourage
it. Superstitious behavior may be valued and nurtured in one culture,
whereas scientific, analytic thinking may be fostered in another. In other
words, there is no universal endpoint to development. Piaget, in con-
trast, saw development toward a particular way of thinking: formal
operations. And Freud saw mature sexuality and freedom from excessive
anxiety as the goal of development.
Applications
Social learning theory has addressed a variety of social problems involving
children, for example, aggression. Does watching violence on television
and in movies, or playing violent video games make children aggressive?
Are bullies created by watching others effectively use violence and by
successfully bullying other children with no negative consequences?
Why do violent adolescent boys sometimes come from “privileged,”
middle-class families in neighborhoods that support law-abiding behav-
ior? The latter question was examined in a classic study by Bandura and
Walters (1959), illustrated in the excerpt at the start of this chapter.
Although the parents discouraged their sons’ aggression toward them,
they actually encouraged them to use aggression to solve their problems
with their peers and with adults outside the home.
Social learning theory also has been useful for helping dysfunctional
families. Families sometimes unknowingly develop coercive systems
(Patterson, 1980; Smith et al., 2014). During hostile interchanges,
certain behaviors habitually lead to certain other behaviors through a
system of reinforcement. For example, a mother asks her son to clean his
room, the child whines, the mother intensifies her command, the child
resists, and the conflict rapidly escalates. Patterson noted that “rapid
escalation is thought to be an important component in the repertoire
of the trained fighter and well practiced coercive children” (1980, p. 7).
When the behavior of the child becomes unbearably aversive for the
mother, as when the child throws a temper tantrum, the mother gives
up and the child stops his aversive behavior. Each person has ended the
aversive behavior of the other. The mother has increased the chances
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Applications ▶ 307
that the child will act aversively in the future because his resistance was
reinforced by not having to clean his room. Ending the temper tantrum
reinforced the mother, which increases the likelihood that she will give
in on future occasions. This pattern of reinforcement also increases the
likelihood that a rapid escalation of conflict will occur in their future
interactions. More generally, parents in functional and problem families
differ in their discipline skills. In functional families, the parents set up
specific consequences for the child’s misbehavior and consistently apply
them. In contrast, in coercive dysfunctional families, the child learns that
parents may react explosively to misbehavior and make vague punish-
ment threats but will not follow through on these threats.
This negative developmental cascade begins early. Coercive caretaker–
child interactions when children are ages 2 through 5 predict later
teacher-reported oppositional behavior at school age (Smith et al.,
2014). In school, many of the child’s coercive interactions and conduct
problems are directed toward peers, which often leads to rejection by
peers. Thus the child continues to head down a negative developmen-
tal pathway toward later behavioral problems. Families assigned to an
intervention, in contrast, showed declines in child oppositional and
aggressive behavior.
Even the entire family can become a coercive system in which each
family member learns to cope with aversive behavior from others, such as
hitting, teasing, ignoring, verbal abuse, and requests to do work, by coun-
terattacking, which often ends the aversive behavior. A young girl’s teasing
of her older brother leads to his hitting her, which in turn leads to punish-
ment from the parents, which finally may even escalate the boy’s aggression.
Each family member is periodically reinforced for behaving aggressively
and coercively when overpowering another family member through neg-
ative behaviors. After the psychologist makes the problem family aware of
these correlated events, together they try to reduce the amount of aversive
behavior with which the child must cope and try to lower the “payoff ” for
the child’s coercive behaviors. If the child is old enough, the family may
write a contract that includes the child, specifying what behaviors will be
punished by withdrawal of rewards. Thus, they present expectations for
behavior and the consequences of disobeying in a clear and consistent way
that the aggressive child can easily grasp and represent symbolically.
Bandura has applied his theory on an international scale. He has imple-
mented several programs to improve personal and collective self-efficacy
to bring about social change. For example, television and radio programs
focused on increasing self-efficacy have been very effective at increasing
literacy, safe sex to protect against AIDS infection, and the adoption of
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308 ▶ SOCIAL LEARNING THEORY
family-planning methods in several countries in Africa, Asia, and Latin
America. For example, in Mexico, almost one million people took a
course to learn how to read after seeing a drama showing people of
various ages learning to read and consequently improving their lives
(Bandura, 2006b). Other programs have addressed pornography, deter-
rents to crime, encouragement of healthy behaviors, and moral disen-
gagement regarding violence after terrorist attacks.
Evaluation of the Theory
Social learning theory’s strengths are its focus on the situational, social,
and emotional influences on behavior and its testability. As in the chapter
on psychoanalytic theory, the emphasis is on what the theory could
contribute to present and future research and theory building in devel-
opmental psychology. Two weaknesses are an inadequate account of
cognitive development and an inadequate description of development in
natural settings.
Strengths
Focus on Situational Influences on Behavior ▶ As mentioned in
Chapter 2, one challenge to structural theories, such as Piaget’s and
Freud’s, is that a person’s concepts or personality are not expressed
in all situations. Social learning theory’s focus on situational variables
provides a way to explain this domain specificity of knowledge and
behaviors. This analysis of situations is sorely needed in current work
on children’s thinking, remembering, and learning. Looking at charac-
teristics of available models, the child’s previous learning history in that
situation, and available reinforcers may clarify the child’s unevenness
of behavior across situations, or even cultures. Cultures differ in what
concepts parents and teachers emphasize. As mentioned in Chapter 4,
Japanese mothers encourage even very young children to play counting
games. A situational analysis also could contribute to an understanding
of children’s theory of mind. Observing others deceive, manipulate, and
comfort people may contribute to this knowledge.
Cognitive theories generally also ignore motivation. In contrast,
Bandura addresses “hot” cognition (Zajonc, 1980) as well as the “cold”
cognition of other theories. Hot cognition consists of the emotional,
motivational aspect of thinking; cold cognition includes the nature
of thinking but not its emotional aspects. Examples of hot cognition
are children thinking about how to please their parents, experiencing
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Evaluation of the Theory ▶ 309
sadness when they fail at a task, and feeling disappointed in themselves
when they do not meet their own standards of conduct. Motivation
affects whether children apply their knowledge in a particular setting
and thus is important to consider during cognitive assessment.
Another potential contribution is to cultural approaches, which, like
social learning theory, place importance on children learning by watch-
ing the activities of parents, other adults, siblings, and older peers. Social
learning theory can specify the motivational, attentional, and cognitive
processes involved as well as cultural differences in the extent to which
children learn in this way.
Testability ▶ Even those who have attacked learning theories admit
that they are among the most testable theories in psychology. Learning
researchers have defined terms clearly, stated hypotheses precisely, and
kept unobservable, intervening variables to a minimum. Parsimony is
highly valued. It is desirable to have a theory that reminds us that we are
interested in observable behaviors as well as in thinking and attitudes.
Thus, social learning theorists can serve as watchdogs of cognitive psy-
chologists, who sometimes seem to have forgotten about behavior. We
must remember that representations, mental operations, and concepts
of other people ultimately are related to behavior.
Weaknesses
Inadequate Account of Cognitive Development ▶ It is not clear
whether social learning theory is truly a developmental theory. Is devel-
opmental change simply short-term change accumulating over a longer
period of time? Are the processes of social learning the same at all ages?
If development is merely accumulated learning, are there any limits
on how much one can speed up development? A truly developmental
theory should be able to specify, for example, what differences underlie
infants’ ability to copy their mother when she sticks out her tongue and
10-year-olds’ ability to play a new card game after reading the rules.
Adding a clear and specific account of cognitive development would
make the theory more developmental. A child’s cognitive level both
enables and constrains what she can learn through observation. For
example, watching another child share a toy with a friend may be
regarded as an isolated behavior by a 4-year-old but may imply a set
of meanings concerning fairness and reciprocity for an 8-year-old. The
two children differ in what they learn from this observation. As another
example, 48-month-olds were able to sort visually identical objects
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310 ▶ SOCIAL LEARNING THEORY
according to weight after watching an adult do this and could even trans-
fer this observational learning to novel objects, but 36-month-olds could
not (Wang, Meltzoff, & Williamson, 2015). The younger children did
not have the cognitive readiness needed in order to imitate this behavior.
Bandura posited some simple cognitive organization and restruc-
turing during development. He also proposed that as children develop
cognitively, perceptually, and motorically, their observational learn-
ing becomes more efficient and abstract. However, he devoted little
attention to exactly which developing cognitive skills contribute to
observational learning. From a contemporary perspective, several good
candidates to be studied include perspective taking, monitoring reac-
tions to the model’s behavior, considering contexts, evaluating a model’s
testimony, understanding knowledge states, and calibrating multiple
pieces of information or cues (Wood et al., 2013).
Inadequate Description in Natural Settings ▶ A strength of ethology
is its method of observing organisms in their natural settings. In contrast,
from learning theory, we know much more about the variables that can
affect the learning of social behaviors than about what variables actually
operate in the lives of children or what behaviors actually occur at vari-
ous ages. We know how variables operate to produce short-term changes
in the laboratory but less about how they operate in natural environ-
ments. We do not know the ecology in which children learn aggression,
sex typing, or dependency. Similarly, laboratory studies have identified
many processes, such as imitation, abstract modeling, reinforcement,
self-efficacy, and concept formation, that mold gender-role behaviors.
Which processes, in fact, are most important in particular natural settings
at different ages? We need a taxonomy of the various learning situations
in which children typically find themselves in each developmental period.
The theory’s contribution would be much greater if investigators would
examine the models and reinforcement contingencies usually found in
the typical environments of each phase of development. One recent
study (Flynn & Whiten, 2012) shows how research in natural settings
can be informative about observational learning from dominant and
prestigious models. In a preschool setting, children were more likely to
watch another child play with a novel puzzle-box if the observed child
was older, more popular, or more dominant than other children.
Moreover, observational learning and patterns of reinforcement need to
be tied systematically to social–ecological variables, such as both parents
working outside the home, diversity in what constitutes a family, urban-
ization, racial discrimination, and changing gender roles. A complete
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Contemporary Research ▶ 311
account of social learning must also consider demographic variables,
such as socioeconomic level, race, gender, and geographic location. For
instance, we need a description of developmental changes in aggression
that takes into account the type of peer models in the neighborhood that
are seen by children in various subgroups of the population, the type of
day care the child has, and the father’s involvement in child rearing.
Contemporary Research
Social learning theory peaked in its influence on developmental psychol-
ogy in the 1960s and 1970s. Although today it still is included in most
standard accounts of development, relatively few studies with children
are directly stimulated by the theory. The recent work on agency and
self-efficacy, for example, has focused on adolescents and adults. In a
more general sense, however, social learning theory is indirectly respon-
sible for much of the current research on children’s social development:
aggression (Eisner & Malti, 2015), gender development (Hines, 2015),
moral behavior (Killen & Smetana, 2015), peer interaction (Rubin,
Bukowski, & Bowker, 2015), and influences of the media (Calvert,
2015). Work on aggression, for example, has expanded in interest-
ing ways to include bullying, relational aggression (e.g., gossip, social
exclusion), and the genetic and neural foundations of aggression. Today,
important social learning theory concepts such as observational learn-
ing, self-efficacy, and the importance of adults’ and peers’ reactions to
a child’s behavior are simply assumed because of social learning theory.
We now turn to three current active areas of research related to learning
theory: cognitive approaches to learning, imitation, and selective social
learning from others.
Cognitive Approaches to Learning
Developmentalists recently have shown a renewed interest in learning,
in the sense of acquiring new knowledge and skills. Today, learning is
virtually indistinguishable from cognitive change over short periods of
time. Interestingly, many of these more cognitive approaches draw on
the idea from traditional learning theory of the strengthening or weak-
ening of associations. Even infants are adept at detecting regularities in
their environment—which events or stimuli tend to occur together and
may be causally related. These detected regularities are used to form
mental models of the world and neural networks (see Chapter 7). For
example, a toddler hears the word “dog” when a small animal with four
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312 ▶ SOCIAL LEARNING THEORY
legs, a panting tongue, a barking sound, and other characteristics is pres-
ent in various contexts. These features tend to co-occur. Despite some
differences in these specific dogs, they are included in the toddler’s new
concept of dog. These approaches, to be discussed in Chapters 7 and 9,
go by several labels, such as probabilistic models, statistical learning,
computational models, Bayesian networks, and connectionist models.
More generally, a new field—learning sciences—has emerged. This inter-
disciplinary endeavor draws on fields such as cognitive science, machine
learning, computer science, and educational psychology. The goal is to
understand learning processes and to apply them to effective instruction.
Imitation
There is considerable interest in imitation itself—how early it appears,
how it develops, and how it helps development. The ability to imi-
tate is present early on, perhaps even at a few days of age (Meltzoff &
Moore, 1989; Nagy, Pilling, Orvos, & Molnar, 2013). Even as early as
6 months, infants imitated, after 24 hours, what they saw on television,
and did so as often as for live models (Barr, Muentener, & Amaya, 2007).
Anecdotally, parents can attest to their toddler imitating in great detail
their own idiosyncratic mannerisms or the dance moves of a rock star
the toddler has seen on television.
Young children’s imitation presents a paradox. On the one hand,
their imitation often is selective. They extract the important features
of another person’s behavior, infer his intentions, and abstract a rule
that they can see the other person is using (e.g., Williamson, Jaswal, &
Meltzoff, 2010). On the other hand, they sometimes imitate exactly and
even show overimitation—imitating everything the person does, relevant
or not, and even when they know that they are imitating irrelevancies.
A current controversy is over why children do this. It may be that when
a child can easily understand the other person’s behavior she imitates
selectively, but when the behavior is new and complex, and she is not
sure which aspects are important, she may imitate everything and fine-
tune later (Nielsen, Mushin, Tomaselli, & Whiten, 2014). This may be
adaptive in a complex, rich culture with many artifacts that children
have to learn how to use. Or, children may overimitate when they
want to be like the model, or want to demonstrate shared intentions
with the model and communicate affiliation (Over & Carpenter, 2013).
Children also may perceive that sometimes models show cultural con-
ventions or rituals, which should be imitated closely, and sometimes
models are providing opportunities to develop new skills, which permit
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Contemporary Research ▶ 313
some variability in the child’s modeling (Legare, Wen, Herrmann, &
Whitehouse, 2015).
Imitation plays an important role in the evolution of human societies
and in cultural learning during childhood. Chapter 4 described how
culture is transmitted through watching and listening to others and
engaging in the activities observed. Imitation also seems to be a part
of belonging to a social group. People are more likely to imitate others
in their own social groups—their in-groups—than in their out-groups
(Howard, Henderson, Carrazza, & Woodward, 2015). Interestingly,
infants prefer adults who imitate them (Meltzoff, 2007) and show dif-
ferences in brain activity when adults do or do not imitate them (Saby,
Marshall, & Meltzoff, 2012). Children with autism spectrum disorders
imitate less than typically developing children (Vivanti, Trembath, &
Dissanayake, 2014) and even show less “contagious yawning”—yawning
when someone else nearby yawns (Helt, Eigsti, Snyder, & Fein, 2010).
This tendency not to imitate may partially account for their poor social
learning.
One reason for the recent interest in imitation is neuroscientists’ dis-
covery of action mirroring, including a possible underlying mechanism—
the mirror neuron system (Fogassi & Rizzolatti, 2013; Rizzolatti &
Craighero, 2004): When people watch someone else perform an action,
such as reaching for an object, the pattern of brain activity is virtually the
same as when people themselves perform the action. This phenomenon
suggests that performed and observed actions are coded in a common
cognitive and neural network that may enable even infants to imitate
others and understand their intentions and goal-directed behaviors, and
thus learn from them. For example, when 7-month-olds see a failed
behavior, such as an adult’s unsuccessful attempt to reach for an object,
they imitate the intended behavior (successfully reaching for the object)
rather than the failed one (Hamlin, Hallinan, &Woodward, 2008). This
may be a case of “filling in,” during imitation, what one knows based on
one’s prior similar actions. Further evidence that infants apply knowl-
edge about their own actions to those of others comes from studies in
which infants are taught a new goal-directed behavior. Ten-month-old
infants were trained to pull a cane to retrieve a toy. Subsequently, they
could detect the goal-directed nature of another person’s cane-pulling
actions (Sommerville, Hildebrand, & Crane, 2008).
The larger important message of this line of research is that mind
and body are not separated; action and thought are one. The controver-
sies are: Is the neural mirroring system present at birth? How does it
change developmentally? How is it modified by experience? What does
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314 ▶ SOCIAL LEARNING THEORY
this system contribute to the understanding of others’ behavior? Does
this meaning shared between two people also provide a foundation for
language development and communication? Can a poorly functioning
mirror neuron system explain the apparent deficits in imitation in chil-
dren with autism spectrum disorders? Finally, some researchers doubt
that mirror neurons exist in humans.
Selective Social Learning from Others
Children trust, and therefore imitate or accept information from, only
certain people (e.g., Mills, 2013). Preschoolers judge the accuracy and
trustworthiness of people’s information from cues such as speakers’ past
accuracy (e.g., Koenig, Clément, & Harris, 2004) and their perceived
positive or negative intent (e.g., Mascaro & Sperber, 2009). Moreover,
it has been argued (Csibra & Gergely, 2009) that children have an innate
tendency to imitate people who indicate, through cues such as point-
ing, verbal instructions, or eye contact, that they are trying to teach
them something. This research adds to early social learning work on the
characteristics of the model that affect children’s observational learn-
ing by showing that the model’s mental state and previous competence
are important. In this way, children’s cognitive development (ability to
evaluate others’ intent and quality of information) contributes to their
observational learning.
SUMMARY
Social learning theory retains the spirit of the behaviorist movement: the
experimentally rigorous study of basic learning processes. The spotlight,
however, has switched from a hungry rat pressing a bar to a child inter-
acting with other people. Children learn new behaviors by observing
others. Moreover, the effect of environmental influences is cognitively
mediated, as seen in children’s use of language and strategies during
problem solving.
Bandura contributed three key concepts:
1. Observational learning can be much broader than mimicking another per-
son’s behavior. Children can symbolically construct new, complex behav-
iors by listening to another person or watching a movie. Furthermore,
overt behavior is not even necessary in order for learning to occur.
As Bandura summarized the influences of models, they “can serve as
instructors, motivators, inhibitors, disinhibitors, social facilitators, and
emotion arousers” (1989, p. 17).
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Summary ▶ 315
2. Children are self-regulatory. Although reinforcement is not neces-
sary for learning, it is helpful for self-regulation, in part by providing
feedback. Children observe which behaviors lead to reinforcement and
punishment and use these observations as sources of information to
help them abstract rules, evaluate their efficacy, develop standards of
conduct, set goals, and decide in which situations to use the observed
behavior.
3. Triadic reciprocal causation provides a model of behavior change. Three
sources of influence—the person, his behavior, and the environment—
interact and thus influence each other. The most novel features of this
three-pronged model are that children actively select certain environ-
ments, and their behavior even helps shape their environment, which in
turn acts on them.
Children develop five skills that are very important for social learn-
ing: symbolization, vicarious learning, self-regulation, self-efficacy, and
the ability to see the future consequences of present behaviors (Perry,
1989). During development, children become more skilled at the four
component processes of observational learning: attention, retention,
production, and motivation. In particular, the growing ability to use
visual and verbal symbols boosts children’s observational learning. Much
of social development results from the accumulation and integration of
episodes of observational learning. Social learning theory has examined
a wide variety of developmentally important behaviors, such as aggres-
sion, concept formation, language, gender-related behaviors, and moral
development.
Learning theories have become less mechanistic over the years and
increasingly acknowledge biological contributions, though still focus on
nurture. Development mainly is quantitative. Social learning theory has
been applied to interventions for dysfunctional families.
Bandura’s theory is testable. It also is integrative in that it brings
together information processing and socialization processes. Social learn-
ing theory could correct several shortcomings of cognitive approaches,
providing a way to conceptualize why the child’s behavior or demon-
strated knowledge might vary from situation to situation. There are two
needed directions for further developing social learning theory. First,
the interface between cognitive development and observational learning
must be worked out in greater detail before the theory can be consid-
ered a truly developmental theory. Second, the theory could become
much more powerful in predicting and exploring behavior if it acquired
a broader ecological database. The theory has shown us that processes of
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316 ▶ SOCIAL LEARNING THEORY
social learning can guide development; the next step is to discover how
these processes are involved in the environments typically found at var-
ious points in development, in various types of families, and in various
socioeconomic and ethnic niches. Contemporary research has expanded
many topics emphasized by learning theories, including aggression and
environmental influences such as the media. Topics of current interest
include cognitive learning, including applications to instruction; the
development of imitation itself and a mirror neuron system that might
contribute to it; and selective social learning.
SUGGESTED READINGS
Bandura, A. (in press). Moral disengagement: How good people can act inhu-
manly and feel good about it. New York: Worth.
Bandura, A. (2012). Social cognitive theory. In P. A. M. Van Lange, A. W.
Kruglanski, & E. T. Higgins (Eds.). Handbook of theories of social psychol-
ogy (Vol. 1, pp. 349–373). Thousand Oaks, CA: Sage Publications Ltd.
Bandura, A. (2009). Social cognitive theory goes global. The Psychologist,
22(6), 504–506.
Forgatch, M. S., Patterson, G. R., & Gewirtz, A. H. (2013). Looking
forward: The promise of widespread implementation of parent train-
ing programs. Perspectives on Psychological Science, 8(6), 682–694.
Meltzoff, A. N., & Williamson, R. A. (2013). Imitation: Social, cognitive,
and theoretical perspectives. In P. D. Zelazo (Ed.), The Oxford handbook
of developmental psychology. Vol 1: Body and mind. New York, NY: Oxford
University Press.
07_MIL_7898_ch6_277_316.indd 316 1/8/16 11:41 AM
Information- Processing Theory
An experimenter (E) questions a child, Lauren (L), about an addition problem:
E: How much is 6 + 3?
L: (Long pause) Nine.
E: OK, how did you know that?
L: I think I said . . . I think I said . . . oops, um . . . I think he said . . . 8 was 1
and . . . um . . . I mean 7 was 1, 8 was 2, 9 was 3.
E: OK.
L: Six and three are nine.
E: How did you know to do that? Why didn’t you count “1, 2, 3, 4, 5, 6, 7, 8, 9”?
How come you did “6, 7, 8, 9”?
L: Cause then you have to count all those numbers.
E: OK, well how did you know you didn’t have to count all of those numbers?
L: Why didn’t . . . well I don’t have to if I don’t want to.
—Siegler & JenkinS, 1989, p. 66
A part of a connectionist model:
The hidden layer activities, Y⃗ 1(t) and Y⃗ 2(t), resulted from
Y⃗ k(t) = s(V kX⃗k(t) + U k Y⃗ k(t−1)),
where k P{1, 2}, V k and U k are weight matrices and s is the sigmoid:
s(x) = (1 + e−x)−1.
The output, Z⃗ (t), is calculated accordingly:
Z⃗ (t) = s(W 1Y⃗ 1(t) + W 2Y⃗ 2(t)),
with the W k being weight matrices to the output layer.
—Franz & TrieSch, 2010, p. 650
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C H A P T E R 7
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318 ▶ INFORMATION-PROCESSING THEORY
T
his is the information age. With our various electronic devices,
we have constant, fast access to information from friends,
family, work colleagues, and websites around the world. In our
information- heavy world, almost every aspect of play and work
involves decision- making about what information to select, store, and
use. It is not surprising, then, that at least one developmental theory
would use a technology metaphor and focus on how children deal with
information.
In the last five decades, the information- processing approach, on the
wave of the cognitive revolution, spread quietly through the field of cog-
nitive development. It is said that the approach “was never born; it grad-
ually coalesced” (Kendler, 1987, p. 364). Information processing arrived
with little fanfare and, surprisingly, with only moderate clashes with
Piagetian theory. The approach attracted psychologists seeking a more
rigorous experimental approach than Piaget’s and a more cognitive
approach than learning theory. To a great extent, information processing
defines the study of cognitive development as it exists today. However,
as with Piaget’s theory, the influence has so permeated the field that its
presence is almost invisible. Many developmental psychologists who
study memory, mental representation, and problem solving— major
topics of information processing— are not aware that they have accepted
certain assumptions and methods of that approach. They feel they are
simply performing empirical, atheoretical studies of various aspects of
thinking. This chapter makes explicit this implicit agreement about what
thinking involves, what aspects of thought change during development,
what questions are worth asking, and how those questions should be
studied. The information- processing approach continues to change with
the advent of another new technology— neuroimaging. Developmental
cognitive neuroscience is providing another level of explanation of
changes in information processing.
This chapter begins with a brief description of the information-
processing approach and then continues with a historical sketch, a gen-
eral orientation, descriptions of major developmental approaches, and
an account of mechanisms of development. Later sections address the
theory’s position on developmental issues, applications, the theory’s
strengths and weaknesses, and contemporary research.
Information processing is not a single theory but, rather, a frame-
work characterizing a large number of research programs. Information-
processing investigators study the flow of information through the cognitive
system. This flow begins with some input, such as a written passage, a
problem to be solved, or an event, into the human information- processing
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Information- Processing Theory ▶ 319
system. The flow ends with an output, which can be information stored
in long- term memory, motor behavior, speech, or a decision. Mental
operations occur between input and output during real time. For
example, the information may be attended to, transformed into some
type of mental representation, compared with information already in
long- term memory, assigned meaning, and used to formulate a response.
These mental processes are similar in some ways to computer programs
that accept information, perform certain operations on it, and store it.
More generally, both humans and computers manipulate representations
and transform input into output. Both computers and humans are lim-
ited in the amount of information that can be attended to simultaneously
and in the speed with which this information can be processed. The
correspondence is, of course, only partial. The circuitry of a computer
or the design of a computer program is quite unlike the anatomy and
functioning of the brain. However, as we shall see later, the computer
metaphor served as a valuable heuristic for developing the field of infor-
mation processing.
To illustrate this description of the information- processing
approach, consider what happens when a young child first encounters
the Dr. Dolittle story with the pushmi- pullyu, a horselike creature with
a head at each end. The delighted child attends to the picture of the
creature while ignoring other objects on the page and encodes it visu-
ally, as an image, or verbally, as a “ pushmi- pullyu” or “horse with a head
on each end.” He processes this visual or verbal representation further
as he compares it with previously stored information about horses or
fantastic creatures such as unicorns. Furthermore, the child may derive
certain implications about having two heads (“How does it know if it’s
coming or going?”), store the new information in a way that allows him
to recognize pushmi- pullyus on future occasions, and finally laugh, ask
his father to reread the page, or look ahead in the book for more pictures
of the pushmi- pullyu.
Thus, the child transforms information over a period of time.
Information- processing psychologists (who specialize in concepts of
pushmi- pullyus) might ask the following questions: Did the child pro-
cess the input superficially, noting only its physical characteristics, or
deeply, relating it to a system of meaning? How fast did he process the
information? Did he process the pushmi- pullyu’s features simultane-
ously or successively? What limited how much information he could
analyze during the time he could see the picture? Did he use a strat-
egy of rehearsing the label “ pushmi- pullyu,” by saying it several times?
How is the pushmi- pullyu as it is finally stored in long- term memory
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320 ▶ INFORMATION-PROCESSING THEORY
different from the input, the physical stimulus? If the child is shown
another picture of a pushmi- pullyu, how does he retrieve the relevant
information from memory and recognize the picture? If investigators can
answer these questions, they can develop a theoretical model describing
how the child processes information.
As this example illustrates, information- processing psychologists
look at what mental processes children apply to the information and, as
a result, how they transform, manipulate, and use that information. In
other words, they are primarily interested in exactly how the process-
ing system actually operates in real time in a particular situation— how
the system changes external objects or events into a cognitively use-
ful form, perhaps according to certain rules. They examine both how
changes in processing occur during development and the constraints
on these changes. They try to explain “both how children of given ages
have come as far as they have and why they have not gone further”
(Siegler & Alibali, 2005, p. 66). Information processing was attractive
to developmentalists because it presented a set of specific cognitive
processes to guide research on children’s thinking and complemented
Piaget’s structural approach.
Although the pushmi- pullyu example illustrates the “style” of
information- processing psychologists, it masks the diversity of approaches
within the field. There are two main categories of approaches: computa-
tional models (typically computer simulations of children’s thinking) and
empirical studies of various aspects of processing information such as
attention, memory, problem solving, and executive control of cognitive
processes. The latter is much more common in developmental psychol-
ogy, and thus will be the focus of this chapter.
History of the Theory
Once developmentalists entered the domain of experimental psy-
chology en masse in the early 1960s, they felt reverberations from
every significant event in adult experimental psychology. Information
processing was the first major theory of adult cognition to arise since
developmental psychology had become an experimental science. The
cognitive revolution within adult experimental psychology changed the
prevailing view of children’s thinking. The attraction of information-
processing theory for developmentalists can be understood only by
tracing the chain of events within adult experimental psychology that led
from neobehaviorist learning approaches to the information- processing
approach.
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History of the Theory ▶ 321
Two movements in the 1940s through the 1960s transformed adult,
then developmental, experimental psychology. First, as described in
Chapter 6, a crisis of confidence occurred within learning theory,
which led psychologists to seek a more satisfactory approach. For
example, typical research on learning an arbitrary association between
nonsense syllables, for example “ GAV- HIG,” seemed to be of limited
use for our understanding of human thinking. Also, a young linguist
named Noam Chomsky had convincingly argued that learning theory’s
account of language was wrong because it focused on language output
and reinforcement of this output. Chomsky proposed that the essence
of language is a set of underlying abstract rules that generate sentences.
Thus, the important part of language is unobservable and must be
inferred from the relations between language input and output.
The second influential development was the exposure of psychologists
to conceptions of information implicit in new technology. Psychologists
were drawn out of the laboratory to work on improving the human
operation of wartime equipment and weapons during World War II and
the Korean War. They began to think of humans as information trans-
mitters and decision makers when they examined how military person-
nel divided their attention between a plane’s controls and instructions
from a radio, detected blips on a radar screen, and interpreted a plane’s
instrument readings. A human and a machine (plane or weapon) operate
together as a unit. It is desirable that this unit operate efficiently to avoid
unfortunate errors, such as plunging into the ocean.
Another technological influence came from communication engineering
and information theory, which introduced concepts such as “ limited- capacity
channels,” “serial” (successive) and “parallel” (simultaneous) processing,
“coding information” into large units, and “uncertainty” (ambiguous infor-
mation). Thus, psychologists were not only willing to talk about the
mind (in contrast to the behaviorists) but also had a language for doing
so. Later, computer scientists’ work on more sophisticated computers,
robots, and other symbol- manipulating systems suggested to psycholo-
gists that people might also be considered symbol- manipulating systems.
Newell and Simon (1961), in particular, argued convincingly that the
logical capabilities of people could be simulated by appropriate computer
programs. The cognitive revolution in psychology had begun!
The late 1980s and 1990s brought computational models— computer
models of learning and development, as described below. Whereas these
models aimed to mimic the way people actually think, the emerging field
of artificial intelligence tried to develop maximally efficient and intelligent
systems. The latter approach produces robots, computer programs, or
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322 ▶ INFORMATION-PROCESSING THEORY
other devices that can play chess or other games, translate texts, serve
drinks, and keep track of a store’s inventory. These devices often surpass
average mental skills, as anyone who has been humiliated by a computer in
a chess game can attest. For example, even an early computer chess whiz,
“Deep Thought,” beat nearly all of its human opponents (Lindsay, 1991),
and “Deep Blue” even beat the chess expert Garry Kasparov. This work
eventually led to today’s field of developmental robotics, discussed later.
Both information- processing and artificial- intelligence approaches are part
of the contemporary field of cognitive science— an amalgamation of cognitive
psychology, computer science, philosophy, neuroscience, and linguistics.
By the late 1960s, developmental psychologists were beginning to
recognize the potential of information processing for studying children’s
thinking. They were beginning to have doubts about Piaget’s theory, as
described in Chapter 2, and thought that information processing might
offer an attractive alternative. The information- processing approach also
was appealing because it permitted controlled experimental studies, as
had learning theory, but it also supplied a fruitful new methodology,
language, and metaphor for studying the development of thought. In
addition, there already was interest in some of the topics studied by
information- processing psychologists, particularly memory, attention,
and language. There was a sense of excitement about the future of devel-
opmental psychology.
As a result of all of these factors, information processing became a
major force in the field of developmental psychology. Most of the early
information- processing studies were simply direct translations of the
adult research, using children as subjects. For example, researchers gave
children simpler versions of the memory and attention tasks they gave to
adults. Eventually, as happened in learning theory earlier, developmen-
tal research began to go beyond these simple translations and to look
at specifically developmental issues. Numerous studies have examined
children’s information processing in recent decades. In addition, recent
computational modeling approaches have caused another surge of inter-
est in information processing and, because they emphasize learning, have
rejuvenated learning as a topic of study.
General Orientation to the Theory
How do we recognize an “ information- processing cognitive develop-
mental psychologist” when we see one? This species has distinctive
markings that help “psychologist watchers” identify it. The following field
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General Orientation to the Theory ▶ 323
guide describes several characteristics: viewing humans as information-
processing systems, conceptualizing development as self- modification,
conducting task analyses, and using information- processing method-
ology. All of these address two main characteristics of human thought:
“[O]ur thinking is limited in both speed of processing and the amount we
can attend to at any one time, and our thinking is flexible, to get around
these limitations and to adapt cognitively to both internal changes such
as changed plans and external changes such as a new task” (Siegler &
Alibali, 2005, p. 68).
Humans as Information- Processing Systems
There are striking correspondences in how people and computers
manipulate input according to certain rules and store the results of
these operations. We can compare perceiving with “input,” thinking
with a “computer program,” storage capacity with the number of “GB,”
forgetting with hitting the “delete” key, recall with “search,” strategies
with “tools,” and a decision with “output.” The structure of the cogni-
tive system sometimes is called cognitive architecture. An information-
processing psychologist asks, “How are humans programmed to make
sense out of the complex world around them?” and “What would an
information- processing system require in order to exhibit the same
behavior as a child?” (Klahr & Wallace, 1976, p. 5). Information-
processing psychologists make a step- by- step analysis of what a person
does to the information. How this new orientation breaks with the past
is illustrated in its language. For example, “ input– output” connotes a
different sort of thinker than does “ stimulus– response” or “ assimilation–
accommodation.” The input to the information- processing device is
information, which can come in many forms. It might be a word, a
paragraph, a mathematical or logical symbol, a blip on a radar screen, or
a mental image. The device performs certain operations on this informa-
tion, such as comparing it with previously stored information or trans-
forming it into a representation (encoding), for example, by transforming
a written word into a mental image.
The adult mind can efficiently organize millions of pieces of infor-
mation. How is such a remarkable device developed? Information-
processing psychologists view children at various ages or cognitive
levels as being in different knowledge states. They infer each knowledge
state from the relationship between the input and the output. Thus,
each developmental level is characterized by a particular input– output
relationship, and developmental change involves going from one such
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324 ▶ INFORMATION-PROCESSING THEORY
relationship to another. A simple example would be a study in which
two groups of children receive different input— either a set of pictures
or a list of words for those pictures. The researcher would compare the
children’s output— their recall of these items. By looking at the relation-
ship between different inputs ( visual– pictorial or visual– verbal) and their
outputs (types of errors, order in which the objects were recalled, speed
of recall), they would try to infer what mental processes the children in
the two groups applied over time to the input. These processes might
include verbal rehearsal, organizing the objects into categories, or con-
structing visual representations. Developmental changes are apparent in
nearly every phase of processing— from attention through encoding to
recall and decision- making.
Theorists develop specific models of the flow of information through
the human information- processing device. Information processing has
been called the “psychology of boxes and arrows,” because psychologists
construct flow diagrams, sometimes called “models,” such as the one in
Figure 7.1. A model is a theory about the structure, or “blueprint,” of
the mind, as well as how it functions. The information “goes” in and out
of boxes or may be “lost” at any point.
Baddeley’s (2000) influential model, simplified in Figure 7.1, provides
an example. It focuses on the role of working memory, a limited capacity
workspace that actively keeps information alive temporarily so that this
information can be used for thinking and learning. This information may
be new information or may be information called up from the long-
term memory system. The four components of working memory are
a central executive and three limited capacity subsystems— a visuospa-
tial sketchpad, a phonological loop, and an episodic buffer. The central
executive, like a boss, regulates and coordinates the activities of working
memory by allocating resources, manipulating information, and gener-
ally controlling the flow of information. For example, it might inhibit
attention to some compelling but irrelevant feature of the environment
such as a flashing light and direct attention instead to something more
relevant such as words. Like computer software, it directs the activities
of the memory system, keeps track of what is going on in all parts of the
system, and makes sure the entire system is working in harmony. In this
way, the central executive helps humans overcome structural limitations
on how much information can be handled.
The visuospatial sketchpad specializes in processing and retaining visual
and spatial information. The phonological loop processes and retains
speech sounds, much like playing a very short (1–2 second) audio clip
repeatedly. The phonological loop constitutes children’s memory span,
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General Orientation to the Theory ▶ 325
how many numbers or words a child can repeat back. Both the sketch-
pad and the loop decay very rapidly unless something is done to keep
refreshing the material, such as verbally rehearsing a phone number.
The episodic buffer provides a more general type of memory storage and
serves as a temporary interface between the phonological loop and the
visuospatial sketchpad, on the one hand, and long- term memory on the
other hand. It can do this by storing information in a multi- dimensional
code. Children’s central executive accesses the episodic buffer and con-
trols its functions by attending to particular parts of working memory
or to long- term memory. The episodic buffer is particularly important
because it not only forms representations that are both visuospatial and
auditory but also can construct new, more abstract, representations from
these two systems and long- term memory. These new representations
then can be stored in long- term memory. The buffer is called episodic
because, in a sense, it constructs episodes. Episodic memory— memory of
a particular episode such as what happened yesterday— is an important
aspect of long- term memory.
Long- term memory includes not only episodic memory but also other
knowledge about the world— definitions, how to add and subtract, how
to ride a bicycle, and so on. Long- term memory has a large capacity and
retains information indefinitely within a complex mental organization.
During retrieval, information is summoned out of long- term memory
and can be operated on further in working memory. When we watch a
F I G U R E 7 . 1
A flow diagram of the memory system.
[Information from “The episodic buffer: A new component of working memory?” by Alan Baddeley, in Trends in
Cognitive Sciences, 2000, 4, p. 418, and “Development of working memory in childhood” by Nelson Cowan and
Tracy Alloway in The development of infancy and childhood, edited by Mary Courage and Nelson Cowan, 2009,
Hove and New York: Psychology.]
Central
Executive
Episodic
Buffer
Visuospatial
Sketchpad
Phonological
Loop
Long-Term Memory and
Memory-Related Cognition
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326 ▶ INFORMATION-PROCESSING THEORY
movie, for example, working memory analyzes the visual images and
words and integrates this information somewhat, but long- term mem-
ory makes sense of the plot by relating the information to what we
already know about the world.
With respect to development, both description and explanation (see
Chapter 1) questions could be raised about the stages of processing out-
lined in the flow diagram. First, in what way, if any, do the stages of pro-
cessing differ at various ages? Do they differ quantitatively (e.g., more
storage room) or qualitatively (e.g., different processing rules)? Second,
what causes a child to progress from one state to the next? Are changes
in how a child solves a problem due to an increase in the capacity of
working memory, the more efficient retrieval of a relevant rule from
the long- term store, or both? We know that working memory increases
during development and contributes to a variety of important cognitive
skills, such as reading and math (Kroesbergen, van’t Noordende, &
Kolkman, 2014; Nevo & Breznitz, 2013). Some of the most impressive
developmental changes occur in the executive processes, as children gain
better control over their cognitive skills (Best & Miller, 2010). Also, the
phonological loop obviously becomes much more important when lan-
guage develops. As language continues to develop, children can say words
more quickly (Hitch & Towse, 1995), which increases the memory span,
and also learn to rehearse items to keep the information alive in the pho-
nological loop. The developments of working memory and long- term
memory thus are closely linked; each facilitates the development of the
other. Increased memory span makes it possible for long- term memory
to work with more information, and as children develop cognitively and
construct systems of related concepts in long- term memory, the words
they need to keep alive in the phonological loop become increasingly
familiar and thus easier to rehearse and remember.
Development as Self- Modification
A theory cannot be a satisfactory developmental theory unless it includes
processes for bringing about change. In order to simulate development,
including children’s active role in their own development, information-
processing psychologists had to develop models of a system that could
modify itself as a result of experience. For example, as children try out
various strategies and see which one they like best, they begin to use
some increasingly often and others less often. They learn how to select
the most promising routes to solving a problem. If children reject useless
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General Orientation to the Theory ▶ 327
methods and retain helpful ones, they gradually become more efficient
information processors.
An important breakthrough in computational modeling was the
development of self- correcting, self- modifying models that change in
light of their processing history. That is, learning is stored so that new
learning can build on previous learning. A model can ruthlessly reject
procedures that turn out not to be useful, reorganize units already avail-
able, and increase or decrease the number of situations in which a par-
ticular operation will be used. These self- modifications, then, propel the
model from state to state, or from one developmental level to another.
Task Analysis
One hallmark of the information- processing approach is the careful,
almost compulsive, analysis of the experimental or real- life task facing a
child or adult. The investigator asks, “What cognitive skills and capacities
does a child have to have in order to do this task well?” This concern
with the specific features of a particular task follows naturally from
the approach’s focus on the information available in the task setting, the
limits to the person’s processing capacity, the goals of the task, and the
person’s processing skills. The unique goals and demands of each partic-
ular task elicit a different set of processing activities. For example, chil-
dren may verbally rehearse conceptually unrelated objects or categorize
related objects into “kitchen objects” and “ living- room objects” and then
only briefly rehearse them, depending on the task. The task demands
also may lead to different cognitive activities in children of different ages
because of young children’s limitations in information processing. Young
children may understand the goal and know the appropriate rule but
cannot handle all the information in order to apply the rule. Thus the
child’s knowledge is underestimated. For example, a child may be able
to use a balance scale to order blocks according to weight if there are
four blocks but not if there are seven.
Piaget and Vygotsky had little interest in task analysis, but the neo-
Piagetians did. Recall, for example, that they raised the issue of domain-
specific versus domain- general knowledge. Information- processing
investigators tend to propose that a child acquires a set of rules or
strategies that is specific to a particular domain, such as addition. Both
information- process and social learning approaches break down tasks
or behavior into their simple components and then posit ways that chil-
dren learn to integrate these skills into an organized, well- functioning
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328 ▶ INFORMATION-PROCESSING THEORY
system. As mentioned in Chapter 6, Bandura drew on the information-
processing approach to account for the cognitive processing of informa-
tion during observational learning.
Methodology
Information- processing psychologists typically use rigorous experimen-
tal methods to conduct a fine- grained analysis of the time course of
problem solving. The experiments can be microscopic when they involve
very brief events, such as flashing an image briefly and asking a person
to decide whether it is a spatial rotation of an image seen earlier. The
studies often examine such temporal variables as the amount of time, in
milliseconds, the stimulus is exposed, and take temporal measures, such
as reaction time (how long it takes the person to decide whether the
design was rotated). It is assumed that any mental activity takes a certain
amount of time. Thus, it might be assumed that if two tasks are identical
except that one additional cognitive operation is required for one of the
tasks, the difference in the time required to perform the two tasks pro-
vides a measure of the time needed to perform the additional operation.
Long reaction times can also indicate slower processing of information,
for example, in younger children than older, in low- IQ children than in
average- IQ children, and poor readers than good readers. Researchers’
concern with time is not surprising, given their focus on the flow of
information over time.
Another powerful method is the rule- assessment approach based on
error analysis. A task is cleverly designed so that the pattern of cor-
rect and incorrect answers over various types of trials reveals the rule
or rules the child is using to solve the problem. A classic example
is Siegler’s (1978) work with the balance- scale task, described later.
Although Piaget also made considerable use of children’s errors, he
did not analyze them in the elegant, systematic way often found in
information- processing work. Still another assessment is eye- movement
analysis. An eye tracker mounted on a child’s head allows the child to
move around naturally, thus showing what the child looks at, for how
long, and in what order. This information provides clues to processes of
attention and encoding.
Information- processing psychologists, particularly Robert Siegler,
also have adopted the microgenetic method advocated by Vygotsky (see
Chapter 4). In this method, children are given a large number of tri-
als on the same general type of problem (Siegler, 2006). There can
be multiple sessions spread over weeks or months. This design reveals
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General Orientation to the Theory ▶ 329
moment- to- moment changes in a child’s cognitive performance in each
session, for example, changes in which strategies are used. The micro-
genetic method permits investigators to observe change directly, while
it is happening. They can see moments of sudden change, or cognitive
insight—“cognitive moments,” as it were. For instance, children some-
times show “hemming and hawing” behaviors on the trial just before
the one on which they use a new strategy (Siegler & Jenkins, 1989), as
illustrated by the vignette of the child solving an addition problem at the
start of this chapter. A child may suddenly fall silent before giving the
answer, sometimes as long as a minute or more! These odd behaviors
may indicate increased cognitive activity associated with the discovery of
a new strategy. The pattern of change over trials also can reveal whether
children differ in the developmental route they take to the same end
point or their speed of reaching that point. In short, the microgenetic
method brings the magnifying glass in very close to the child’s behavior.
Again, the information- processing approach focuses on specific changes
over small time periods.
Information- processing psychologists also have developed models
that attempt to simulate thinking and development. One type of model
is a flow diagram, described earlier, which visually depicts cognitive
architecture and processing. Computational models, mentioned earlier,
are attempts to write a program or set of computations that is specific
enough, accurate enough, and complete enough to generate, from input,
an output (behavior) similar to that of humans. Thus, they provide a
way to test theories of human thought. The question is: What would an
information- processing system have to be like in order to behave as a
child does? The computer program and the child should make the same
errors and succeed on the same problems. The closer the correspon-
dence, the better the simulation.
Designing a computational model, as described later, can be a long
and arduous task, requiring considerable technical and theoretical skills.
Modelers start by drawing on what is known about a particular behavior,
such as infant reaching, and its neural foundations, and construct a model
as their best guess about the capacity of the cognitive system, the repre-
sentation of information, and the nature of cognitive processes. If mod-
elers have left out some steps in the rules they wrote into the program,
if their instructions are logically inconsistent, or if they have incorrectly
inferred a rule or other representation from the child’s behavior, the
program will give an output that does not correspond to the child’s.
Psychologists then try to correct the program and run it again. Often,
this cycle must be repeated many times. Or, as mentioned above, models
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330 ▶ INFORMATION-PROCESSING THEORY
can learn, and thus modify themselves. This process continues until the
model can take input thought to be similar to the input that children
receive and produce output similar to that of children of several ages.
Major Developmental Approaches
The study of children’s information processing is a diverse, multifaceted
enterprise. The next section offers a sampling of research areas: memory,
rules for problem solving, mathematical understanding, and computa-
tional models. Information- processing psychologists obviously study top-
ics that are somewhat different from those studied by Piaget or Vygotsky.
Memory
Memory is a net; one finds it full of fish when he takes it from the brook; but a dozen
miles of water have run through it without sticking.
—Oliver Wendell hOlmeS
I can’t forget but I don’t remember what.
—leOnard cOhen (SOng, “i can’T FOrgeT”)
Children’s memory is a fascinating phenomenon, in part because it is
fraught with contradictions. On the one hand, it is widely believed that
young children have poor memories. On memory subscales of IQ tests
or on laboratory memory tasks, they perform poorly compared with
adults, and in more natural settings, young children find it difficult to
memorize their phone number and street address. Yet parents or teach-
ers who read stories to preschoolers know that children often memorize
a story word for word after only a few readings. In fact, children become
quite indignant if the reader inadvertently (or because it is past bedtime)
leaves out a word or two.
Children’s memory has been the topic most often studied by
information- processing developmental psychologists and in fact has
been one of the largest research areas in developmental psychology. This
investment of psychologists’ time and energy has paid off handsomely in
knowledge not only about children’s memory but also, as a bonus, about
the development of learning, conceptual development, and self.
Memory involves three main steps. First, children encode informa-
tion, either verbatim or the gist of the event, either the exact words
of a conversation or the essence of its meaning (Brainerd & Reyna,
2014). Next comes the storage of the information, and later, children
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Major Developmental Approaches ▶ 331
retrieve the information. Developmental changes occur in each step, as
the following research examples indicate. Still, even very young infants
appear to be able to encode, store, and retrieve within limits. In one
demonstration of this that draws on operant conditioning in a clever
way, a ribbon connected to a mobile is tied to an infant’s ankle ( Rovee-
Collier & Gerhardstein, 1997). The infant quickly learns, to her delight,
that kicking her feet makes the mobile move. A week later, when she
again is placed in the crib, she sees the mobile and again kicks in anticipa-
tion of the dancing mobile, even though the ribbon is no longer attached
to her ankle. She has remembered what she discovered at the first event.
Two- month- olds remember for as long as two weeks, and older infants
can remember for longer periods and, during the test of recall, require
fewer cues from the original learning situation. This ability to recognize
a situation and retrieve a very simple event is, of course, a very rudi-
mentary sort of memory, and there is much still to develop. In general,
implicit memory, illustrated by this research and by later memory such
as how to ride a bike, matures early and is present in infants. In contrast,
explicit memory, which involves not just recognition but also retrieval of
facts and events, clearly continues to mature for many years.
Although people generally do not remember events from the first
two or three years of their lives, by the preschool years, children clearly
have autobiographical memory— long- term memory for specific events
involving themselves. Autobiographical memory typically is studied by
observing mothers and their children talk about an earlier event, such
as a birthday party or a trip to the zoo. This memory develops not only
because of improved memory per se but also because of the development
of a sense of self (Howe, 2014), which becomes stable around age 2. It
appears that “it’s all about me” at that age because “things that happen
to me” serve to organize events in memory. Subsequent developments
in language, social cognition, and social relationships enrich this basic
self- based organization of memory, and these memories become more
coherent, detailed, and evaluative (Fivush, 2014). From these autobi-
ographical memories, adolescents begin to construct a “life narrative,”
which gives meaning to their lives, shapes their sense of self, and even
affects their thinking about the future.
Children differ in their memories. During the preschool years, some
children’s autobiographical memories are more complex and coherent
than other children’s. These better- formed memories are more likely if
the mother’s reminiscing with the child is complex, elaborate, and eval-
uative, and if she asks open- ended questions rather than questions that
can be answered with a simple yes or no (Fivush, 2014).
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From preschool until adolescence, five main influences on memory
development have been examined— strategies, knowledge, metamem-
ory, capacity, and social- cultural factors. A sixth influence, brain devel-
opment, has been studied more recently and will be discussed in the
contemporary research section.
Strategies c Some memory activities are effortless and seemingly auto-
matic: a baby recognizes her father’s face, a boy relates to his friend the
plot of his favorite television show seen the night before, an adult hums
“White Christmas” while Christmas shopping. The person is not con-
scious of trying to remember and does not make an effort to remember.
These acts of memory “just happen.” There is little change in these types
of memory during development. Simple recognition memory (indicating
that an object or a picture has been seen before) is good even in infants,
as mentioned above. By the end of the preschool years, children recall
coherent, comprehensible stories or past experiences that are of interest
to them. This memory is a by- product of a meaningful activity or event.
When the material to be recalled is not part of a context that is
meaningful to a child and memory itself must become the primary goal,
then there is striking improvement in memory during development.
Remembering phone numbers, a group of unrelated objects, and the
order in which pictures of toys were presented all fall into this category.
Much of the information- processing research on children’s memory
addresses these sorts of remembering.
Children of different ages do different things when they are trying to
remember. Older children know that in order to store unrelated infor-
mation, they must do something special to the material. This “something
special” is a strategy. Defined more formally, strategies are “mentally
effortful, goal- directed processes that are adopted to enhance memory
performance” (Bjorklund, Dukes, & Brown, 2009, p. 145). For example,
if people want to remember what to buy at the store, they could say the
items over and over again to themselves or put the items into categories
such as “dairy products” and “vegetables.” Or they could make up a silly
story about the items (“The carrot swam through the sea of milk on the
back of a tuna . . .”), mark the location of the items on their mental image
of the layout of the supermarket, or, best of all, simply store a list on an
electronic device. These strategies are tools that humans have devised in
their constant struggle to overcome their processing limitations.
An early breakthrough study found that although preschoolers appear
not to be able to use strategies, they actually can produce them if asked
to do so (e.g., to verbally rehearse the items), and these strategies help
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Major Developmental Approaches ▶ 333
their recall (Keeney, Cannizzo, & Flavell, 1967). Thus, young children’s
problem lies in not spontaneously producing the strategy. This production
deficiency was an exciting finding because it showed that young children
have the cognitive ability to use appropriate strategies but simply are
deficient in knowing when, where, and how to use (produce) them
effectively. This was a new way of thinking about young children’s
abilities. Researchers then documented a production deficiency with
many other memory tasks and many types of strategies.
The next big question was “Are there simple strategies of some sort
that preschoolers or even toddlers might produce?” For example, tod-
dlers age 18 to 24 months watched an adult hide a Big Bird stuffed ani-
mal (DeLoache, Cassidy, & Brown, 1985). They were told to remember
Big Bird’s location so that they could find him later. Even though the
experimenter then distracted them with attractive toys for several min-
utes, they frequently stopped playing to talk about Big Bird or his hiding
place (the “Big Bird chair”), look at or point to the hiding place, hover
near it, or try to get Big Bird. These strategy- like behaviors were much
less frequent in control conditions, such as when the adult rather than
the child was to remember the location.
Children continue to acquire and fine- tune their strategies. By the
preteen years, they typically can pick a strategy that fits the particular
task and carry out the strategy spontaneously, quickly, and efficiently.
Certain strategies, however, continue to develop during adolescence. An
example is “elaboration,” or constructing an image out of the materials
to be remembered.
It is impossible to remember everything. Thus, one important strat-
egy for remembering is to select only relevant information. Learning
what not to attend to is as important as learning what to attend to during
encoding. In selective memory studies (for example, Miller, 1990), a
child sits in front of a box with doors, as shown in Figure 7.2. On half of
the doors is a drawing of a cage, which indicates a drawing of an animal
concealed behind the door; on the other doors is a drawing of a house,
indicating a household object behind the door. The researcher tells half
of the children to remember where each animal is located (the other
half of the children are told to remember household objects instead).
During a 30-second study period, the children can open whatever doors
they wish. Typically, preschoolers jump right in and open each door, row
by row. Although their door opening is not random, it also is not stra-
tegic or efficient, for they are wasting their precious working- memory
space viewing irrelevant household objects as well as relevant animals.
In contrast, older children open only the relevant (e.g., animal) doors.
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334 ▶ INFORMATION-PROCESSING THEORY
In an interesting transitional phase, children are partially selective; some
begin by using the selective strategy but then seem unable to sustain it
and lapse back to opening all of the doors.
Children’s use of strategies for remembering has turned out to be
quite complicated. First, children sometimes produce good strategies
that, surprisingly, do not help their recall, or they provide less help for
younger than for older children (Clerc & Miller, 2013; Miller & Seier,
1994). This is called a strategy utilization deficiency. It is puzzling why
children would continue to use a strategy that provides little or no help.
Eventually the strategy helps recall. Second, children often use several
strategies together when trying to remember something, rather than
just one (Coyle & Bjorklund, 1997). Third, they tend to change their
strategies from trial to trial, even dropping a successful strategy in favor
of another one (Siegler, 1996). Fourth, strategy development appears to
benefit from the development of knowledge, metamemory, capacity, and
social interaction, described below.
Recently, longitudinal studies (e.g., Schneider, 2014) have advanced
our theoretical understanding of strategies. Issues include the extent
and stability of individual differences in strategy use and memory, the
gradual or abrupt development of strategies, the developmental trajec-
tories of various types of strategies, developmental changes in how many
different strategies children tend to use on a task, and the prevalence of
strategy utilization deficiencies.
Knowledge c Memory is not a mental process separate from the rest
of cognition. It is intermeshed in a broad system of thought. In fact,
memory has been called “applied cognition” (Flavell, 1971a) because the
cognitive system is simply directed to a particular set of problems,
F I G U R E 7 . 2
Apparatus for Miller’s selective- memory door- opening task.
[Photo supplied by Patricia Miller.]
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Major Developmental Approaches ▶ 335
namely, storage and retrieval. There are three implications for develop-
ment. First, children are more likely to remember material that they
know about and understand, such as a child- oriented movie or familiar
words. Second, children often extract the “gist”—the essence of the
material— and construct “fuzzy” memory representations rather than
memorize a story or paragraph verbatim (Brainerd & Reyna, 2014).
Third, during development as children become “ world- wise” and
acquire a growing store of knowledge about objects, events, and people
in the world, their recall improves.
Numerous studies show that knowledge helps recall (Haden, 2014).
When children become experts in a particular domain, they demon-
strate good memory in that domain. In a classic study, children who
were skilled chess players had better recall of the locations of chess
pieces on a chessboard, positioned as if in the middle of a game, than did
adults who knew less about chess (Chi, 1978). Thus, children’s greater
knowledge in a particular domain can outweigh adults’ other cognitive
advantages. Knowing about chess permits child experts to “chunk” the
chess pieces into significant units (for example, an attack), whereas nov-
ices must memorize individual pieces and locations by rote. Similarly, on
other kinds of memory tasks, learning about categories of items permits
children to use the strategy of chunking items to be learned into catego-
ries such as clothing, transportation items, and food.
Another influential study showing that knowledge facilitates mem-
ory involved a 4- year- old who was obsessed with dinosaur lore (Chi &
Koeske, 1983). He knew the names of 40 different dinosaurs, under-
stood the differences between a pachycephalosaur and a rhamphorhyn-
cus, and persuaded his patient mother to spend an average of three hours
a week reading his dinosaur books to him. The boy could remember
more of his better- known (to him) than his lesser- known dinosaurs. An
analysis of what dinosaurs and traits were highly associated showed that
the better- known dinosaurs had many links to other dinosaurs and were
better organized according to their characteristics.
Although knowledge often helps recall, it also can make it less
accurate. As Barbara Kingsolver noted in Animal Dreams, “Memory is
a complicated thing, a relative to truth, but not its twin.” As children
increase their store of knowledge, they tend to make inferences that
go beyond the information given. Hebb (1949) likened this feature of
remembering to the way a paleontologist reconstructs a prehistoric
creature. Similar to the way a paleontologist generates a complete
dinosaur from lone fragments and his general knowledge about the
anatomy of dinosaurs, a person reconstructs an event by filling in among
remembered fragments. Sometimes greater knowledge leads to poorer
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336 ▶ INFORMATION-PROCESSING THEORY
recall. For instance, increasing age is associated not only with increased
later recognition of items that actually were seen but also of items that
are conceptually related to these items (Brainerd & Reyna, 2014). An
example would be falsely recognizing “sleep” when only words such as
“bed,” “rest,” “awake,” and “tired” had been presented. Older children
with more categorical knowledge spontaneously make a reasonable
inference from the information they have been given.
Children’s social knowledge, such as social beliefs, attitudes, and expec-
tations, also affects memory. For example, school- age children with the
most stereotyped views of gender- appropriate behavior recalled more
pictures of traditional (for example, female secretary) than nontra-
ditional (for example, male secretary) activities (Signorella & Liben,
1984). In addition, they sometimes even reconstructed the pictures, for
example, recalling that a secretary was female when in fact the person
was a male. Racial stereotypes have a similar biasing effect on European-
American children’s recall of the personal characteristics of African-
American and European- American children in stories (Bigler & Liben,
1993). Children had trouble accurately recalling the characteristics that
ran counter to their racial stereotypes. Thus, memory does not simply
copy the world. Children actively “construct” a memory from inferences
based on their knowledge. In short, “creative memory” is a by- product
of cognitive development.
One cognitive change in knowledge that affects memory is the devel-
opment of scripts— generalized, coherent mental representations of a
series of events that occur in a consistent temporal order in everyday life
(Nelson, 1986, 1996). These scripts describe “what’s supposed to hap-
pen” in certain situations, and they lead children to expect that certain
events will occur in a particular order. If this order is violated, children
may become confused. For example, a 2- year- old who once was given
a bath before dinner, rather than after, became very upset because she
thought she would not be fed that evening (Hudson, 1990). Scripts also
allow children to understand and remember events. Even young chil-
dren develop scripts for familiar situations, such as eating at a fast- food
hamburger restaurant:
I walk in there and I, I, I ask my daddy and then the daddy ask the lady
and the lady gets it. One small coke, one cheeseburger. . . . They want
to eat here so they don’t need a tray. Then we go find a table. I eat it all
up. All. And throw the . . . paper . . . the cheeseburgers in the garbage
can. . . . Goodbye. Goodbye. Jump in the car. . . . Vroom! Vroom!
Goodbye.
(Nelson, 1978, p. 260)
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Major Developmental Approaches ▶ 337
The foundation for scripts may start when babies remember the
temporal order of simple events. For example, they can later repeat a
sequence of events such as putting a ball into a cup, inverting a smaller
cup on top of the larger one, and shaking the cups (Lukowski & Bauer,
2014). Scripts involve the social world of people and events and seem to
correspond to the way children represent complex events of their day- to-
day lives. Notably, scripts both help and hinder memory. They help a child
“fill in” details when recalling an event. However, scripts also hinder the
recall of one specific event because, for example, the various trips to the
restaurant blend together into the script and the child recalls what usually
happens at restaurants rather than what happened on one particular visit.
A final observation about the relationship between knowledge and
recall is that since children’s interests and knowledge differ from those
of adults, their most salient memories may differ from those of adults.
One 5- year- old, when asked if he remembered the place he had moved
from two years earlier, answered: “I remember lots about Michigan.
I remember you left a piece of cheese at the back of the refrigerator and
it got green stuff all over it.”
Metamemory c
“The horror of that moment,” the King went on, “I shall never, never forget!” “You will,
though,” the Queen said, “if you don’t make a memorandum of it.”
—leWiS carrOll
The production deficiency studies mentioned earlier showed that chil-
dren’s difficulties with strategies lay in knowing where, when, and how
to produce them. This led to studies of this sort of knowledge about
memory. Metamemory is knowledge about memory and is a special case
of metacognition, which is knowledge about any aspect of human thought.
Taking notes while listening to a lecture, underlining key points in a
textbook on developmental theories, writing a shopping list before
leaving for the supermarket, leaving one’s completed homework by the
front door the night before school, and mentally walking through the
previous day in order to recall where a jacket might have been left all
reflect metamemory. During development, we acquire an understanding
that sometimes it is necessary to make an extra effort or do something
special in order to remember and that certain factors facilitate or hinder
memory. These factors can include person, task, or strategy variables
(Flavell & Wellman, 1977). Examples are knowing that there are limits
to how much can be remembered (person variable), that recognition
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338 ▶ INFORMATION-PROCESSING THEORY
is easier than recall (task variable), and that verbal rehearsal aids recall
(strategy variable). Thus, children become amateur psychologists.
Preschoolers have limited knowledge about memory. For instance,
they claim superhuman memory abilities, such as when they predict
that they can remember 10 items even though they can remember
only three or four (Flavell, Friedrichs, & Hoyt, 1970). In a classic
study, Kreutzer, Leonard, and Flavell (1975) asked children whether
it mattered if, after being told a phone number, they made the call
immediately or got a drink of water first. Approximately 40 percent
of the kindergartners but more than 75 percent of the fifth- graders
thought it would be better to phone first. Presumably, children become
increasingly aware that short- term memory fades rapidly. This study also
provides an example of increasing knowledge about strategies. When
given a retrieval problem in which a boy is trying to remember at which
Christmas he received his dog, nearly half of the kindergartners were
unable to suggest a way to recall the correct Christmas but all of the
fifth- graders could. They thought of aids such as taking a mental trip
back to each Christmas and recalling the gifts received or trying to recall
other things that happened when the dog was received in the hope that
doing so would cue their recall.
Children’s thinking about strategies can become rather complex, as
the following exchange with a third- grader demonstrates:
Say the number is 633-8854. Then what I’d do is— say that my number
is 633, so I won’t have to remember that, really. And then I would think,
now I’ve got to remember 88. Now I’m 8 years old, so I can remember,
say, my age two times. And then I say how old my brother is, and how old
he was last year. And that’s how I’d usually remember that phone number.
(Is that how you would most often remember a phone number?) Well,
usually I write it down.
(Kreutzer et al., 1975, p. 11)
Children not only learn about the nature of memory and the variables
that affect it but also learn to monitor their memory performance and
the strategies they use to help it. For example, they notice whether
a strategy is helping recall and decide whether to switch to another
strategy or add a second one. The development of metamemory also
is important for distinguishing between one’s true and false memories,
such as real versus imagined events, and between stronger and weaker
memories (Ghetti, Lyons, Lazzarin, & Cornoldi, 2008). Dramatic
changes in metamemory through childhood or later demonstrate that
teaching children to use strategies effectively must include a metacogni-
tive component as well as just teaching them new strategies.
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An important theoretical question is whether metamemory actually
helps memory, for example, by knowing that strategies help and actually
producing strategies. The results are not consistent, but several longitu-
dinal studies (Grammer, Purtell, Coffman, & Ornstein, 2011; Schneider,
2014) suggest that the two are related. Earlier metamemory was linked
to the later use of strategies, and links among metamemory, strategy use,
and recall became stronger with age. Moreover, in a study of children
drawn from grades K to 4, metamemory not only was associated with
greater use of strategies but also affected how much these strategies
helped recall (DeMarie, Miller, Ferron, & Cunningham, 2004).
Capacity c A main constraint on children’s memory is their limited
processing capacity. For example, with increasing age, children can
repeat back, in order, a longer string of numbers (e.g., 3281734). Or,
regarding working memory, more manipulation of this information
becomes possible, for example, repeating these numbers in reverse. This
capacity view connotes a container metaphor in which children have
small boxes in their heads and adults have larger boxes (Schneider &
Weinert, 1989) or a weight- lifter metaphor in which older children have
greater “raw mental muscle power” (Flavell, Miller, & Miller, 2002).
A commonsense explanation of improved capacity would be that the
brain matures physically. Although that is one contributor, the full story
is more complicated. When cognitive skills are practiced, they become
more automatic and thus less capacity- demanding. For example, as
children become more skilled readers, they can recognize words more
quickly; they process the information faster. The faster children can pro-
cess information, the more information they can deal with at any one
time. Thus, after practice, a given amount of capacity goes much further.
Also, increased knowledge probably helps children use what they have
more efficiently because new information can be packaged into preexist-
ing categories and structures. Consequently, some of the developmental
increase in capacity reflects children’s improved efficiency in using a
constant amount of capacity.
Improved capacity has important consequences, such as facilitating
children’s use of strategies, which are effortful. The high effort of strat-
egies when they are first acquired may account for young children’s
utilization deficiencies, described earlier, in which children produce a
good strategy but it does not help their recall at first. After producing an
effortful strategy, young children have less remaining capacity to devote
to memorizing per se than do older children for whom the strategy itself
requires less effort (Miller & Seier, 1994).
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Social– cultural Context c Children talk to other people about the
past— what happened a moment ago, yesterday, or months ago. Here is
one such exchange, in which a mother (M) and her 5- year- old child (C)
are recalling a visit to a natural history museum:
M: What other kinds of dinosaurs were in there?
C: Uh, Tyrannosaurus rex.
M: . . . and they made ’em move, didn’t they? Didn’t they move?
C: No.
M: They did too move (laughing).
C: No he did not. It did not have his skin on.
M: Oh that’s right, one of them was just bones.
C: That was Tyrannosaurus rex.
M: Tyrannosaurus rex was just his bones. Okay.
(nelSOn & FivuSh, 2004, p. 502)
As discussed in the earlier chapter on cultural approaches, memory
is socially embedded. Social factors influence memory, as when par-
ents and teachers scaffold children’s attempts to remember. Moreover,
remembering is put to social uses, as in this example. Recalling shared
experiences strengthens relationships and connects children to their
families and communities.
Culture also shapes the content of memory: “We are what we
remember, and in turn, what we remember is determined by who we
are” (Wang, 2014, p. 606). European- American children’s memories
are more elaborate and self- focused than those of Asian children (Wang,
2014). Also, European- American children often spontaneously offer
new information about the event, while Asian children are more pas-
sive, mainly responding to their mothers’ questions. Like their mothers,
European- American children engage in self- expression, often talking
about their personal opinions, preferences, and interests. In contrast,
Asian children are more likely to talk about other people, rules, and
discipline. European- American mothers also elaborate more about
emotions in these conversations than do Asian mothers (Fivush, 2009).
These differences reflect cultural differences in beliefs about the
importance of the self, autonomy, and individual mental states versus
relatedness and collectivism. Given the close ties between develop-
ment of self and autobiographical memory in early development, this
cultural difference may contribute to cultural differences in the age
of one’s earliest memories. For example, Canadian children aged 8,
11, and 14 had an earlier age of first memory, and produced more
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Major Developmental Approaches ▶ 341
early memories overall, than did Chinese children (Peterson, Wang, &
Hou, 2009).
Perhaps the most compelling evidence of this cultural construction
of self comes from studies of bilingual children who were interviewed
in either Chinese or English (Wang, Shao, & Li, 2010). The results mir-
rored those above. Children interviewed in English talked more about
their personal experiences and their own roles and perspectives, and
indicated higher agreement with Western- independent values, than did
children interviewed in Chinese.
Information processing is social not only in terms of the importance
of social influences but also in terms of processing social information.
Research on social information processing shows that cognitive beliefs
and expectations can bias how children process information— what
they attend to in their social environments, the intentions they attri-
bute to others, what information they recall, and how they respond
to others’ behaviors. For example, highly aggressive boys tend to
interpret an ambiguous event, such as being hit by a ball on the
playground, as intentional, whereas less aggressive boys do not. An
intervention begun in elementary school decreased adolescent antiso-
cial behavior by changing children’s processing of social information
(Dodge, Godwin, et al., 2013). Specifically, the intervention reduced
the bias to attribute hostile intentions to others, increased children’s
generation of competent responses to social problems, and devalued
aggression. Early family experiences can contribute to processing
biases. For example, children who have been neglected and physically
abused tend to attribute hostility to others and respond with aggression
(Keil & Price, 2009). The information that children store about their
previous social interactions biases their current information processing
and behavior.
Mathematical Understanding
Researchers recently have had great interest in how children use informa-
tion about numbers to construct an understanding of mathematics. The
earlier theoretical push was Piaget’s seminal work on this topic. The prac-
tical push is awareness of how poorly U.S. children perform on mathe-
matics tests compared to other modern nations and the concern that it
might be because of the way math is taught in school. We cannot design
effective math instruction until we have a detailed picture of children’s
understanding of math at each age, and of the developmental mechanisms
for moving from earlier understanding to later understanding. Work on
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mathematical understanding from an information- processing perspective
is represented below by Robert Siegler’s work— first on strategies for
addition and more recently on developmental changes in the understand-
ing of magnitude.
Children use strategies not only for remembering, as described
above, but also for other sorts of cognitive work, including mathematical
thinking. Siegler (e.g., 2006) used the microgenetic method described
earlier to study how children develop new addition strategies over
several problems and sessions and select from their toolbox of current
strategies. In the slice of laboratory life at the start of this chapter, a
young girl is trying to solve an addition problem. She worked on a large
set of addition problems, and Siegler observed her pattern of errors
and correct answers, recorded her strategies, and asked her about her
strategies. He found that at any age a child uses a variety of strategies to
solve addition problems. To solve 4 + 3, a child might put up four fin-
gers on one hand and three fingers on the other hand and then count all
the fingers. Or she might put up her fingers and recognize their number
without counting. Or she might start with the larger of the two numbers
and count on from that point (4, 5, 6, 7).
In this experiment and others, children show the following interesting
behaviors: At any age, a child typically uses several different strategies
from one problem to the next on the same sorts of problems or even
the same problem a short time later. Children often use six strate-
gies or more on a set of addition problems (Siegler & Jenkins, 1989).
Sometimes the variation is quite sensible: On easy problems with small
numbers, children use the simple recognition strategy because they can
easily detect the number of fingers or even just give a correct answer
that they have memorized. On other problems that are easy because one
number is small, such as 8 + 2, they can use the strategy of counting up
from 8. On harder problems, they may have to use the harder strategy of
counting all of the fingers. This seems smart. They are using a fast, low-
effort strategy on easy problems, where it is likely to be accurate, and
slower, more effortful strategies on harder problems to insure a correct
answer. Over time they increase their use of the most efficient strategies,
decrease their use of the less efficient strategies, and discover new strate-
gies. However, children sometimes seem to act in irrational or surprising
ways. They may construct a new strategy right after using an existing
one successfully. They may successfully use a new, more efficient strategy
but then abandon it for a while and go back to an earlier strategy. Still,
these seemingly inefficient temporary rejections of successful strategies
are useful, because they help children keep old strategies available while
discovering new ones.
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Major Developmental Approaches ▶ 343
Although children sometimes are taught strategies or learn them
by watching others, they at times invent a new strategy by themselves
during the course of problem solving. Some children show a great deal
of insight into their discovery. Others do not and, during question-
ing, even claim, for example, not to have counted at all, even though
videotapes clearly showed that they had used a new counting strategy
(Siegler & Jenkins, 1989). In fact, children’s new strategies often seem
to stay unconscious for a while. Siegler and Stern (1998) found that
almost 90 percent of their second- graders discovered a new strategy but
could not yet report it.
Thus, the contemporary view of children’s strategies emphasizes
variability more than consistency, and, on a single problem, multiple-
strategy use more than single- strategy use. Strategy variability seems
to be the rule rather than the exception during development. That is,
Siegler sees all of development as a transition period; children are always
thinking in multiple ways, rather than in just one. This going back and
forth among various strategies appears in areas as diverse as motor
behaviors in infants (Adolph & Robinson, 2015), conceptual under-
standing in school- age children ( Karmiloff- Smith, 1992), and scientific
reasoning in adolescents and adults (Schauble, 1996).
More recently, Siegler’s work has turned to children’s understanding
of numerical magnitudes (e.g., Siegler & Lortie- Forgues, 2014). Much
of his research focuses on fractions, one of the most difficult concepts
for elementary school- aged children to master; even some adults have
trouble with this concept. In Siegler’s view, the keys to number devel-
opment are understanding numerical magnitude and broadening the
range and types of numbers whose magnitudes are well understood.
First, children need to be able to encode and represent numbers accu-
rately. For example, if shown an array of 20 or so black dots and white
dots, can they judge whether there are more black dots or white dots?
Even 6- month- old infants can do this well if there are twice as many black
dots as white dots, but even some adults struggle if the ratio is 11 to 10.
Infants’ estimations are based on nonsymbolic representations of number
(e.g., perception of which category has more). This early ability is of inter-
est because it predicts children’s symbolic (“1, 2, 3 . . .”) mathematical
understanding years later. Thus, nonsymbolic representations of number
might be the foundation for understanding at least small symbolic number
sets, which then leads to later more conceptual math understanding.
This translation from nonsymbolic to symbolic number is surprisingly
slow. For example, when 3- and 4- year- olds who can count to 10 are
asked to pick up N objects, some children can give the correct number of
objects for only the number 1; others for only the numbers 1 and 2; others
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344 ▶ INFORMATION-PROCESSING THEORY
only the numbers 1, 2, and 3; and others only the numbers 1, 2, 3, and
4 (Le Corre, Van de Walle, Brannon, & Carey, 2006). Thus, several years
after they showed understanding of relative magnitude, they still have
trouble with symbolic numbers, even with small numbers. Later, even
after they understand the magnitudes of numbers 1 to 10, they continue
to have trouble understanding the magnitudes of even larger numbers.
Also, when they place the numbers 1 to 10 on a physical number line,
they place small numbers, such as 2 and 3, much farther apart than
they do large numbers (e.g., 7 and 8), indicating an incomplete under-
standing of number. This pattern of very slow transfer from small to
large numbers repeats itself in each successive new numerical concept
throughout childhood. And again, understanding number magnitude in
early elementary school predicts later understanding of more complex
math concepts, such as fractions in middle school (Bailey, Siegler, &
Geary, 2014), suggesting that understanding number magnitude is cen-
tral to the development of mathematical understanding.
In this line of research, consistent with the information- processing
approach, careful attention is given to the specifics of the task (e.g.,
number of items) and the systematic manipulation of task characteristics
(i.e., varying the ratio). Also, the amount of time it takes to solve the
magnitude problem is taken to indicate the difficulty of the task, and
microgenetic change in strategy informs developmental theory. Finally,
Siegler finds interesting, illuminating developmental patterns in chil-
dren’s variability of performance in similar versions of a task.
Rules for Problem Solving
Another main line of information- processing research involves detecting
which rule a child uses on a problem- solving task (Siegler, 1978). Consider
a task (see Figure 7.3) in which children have to predict which side of a
F I G U R E 7 . 3
Example of a trial on Siegler’s balance- scale task.
[Information from Developmental Differences in Rule Learning: A Microgenetic Analysis by Robert S. Siegler
and Zhe Chen published in Cognitive Psychology, Volume 36, Issue 3, (1998). Republished with permission
of Elsevier; permission conveyed through Copyright Clearance Center, Inc.]
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Major Developmental Approaches ▶ 345
balance scale (like a seesaw or a teeter- totter) will go down. The relevant
information is the number of weights (all of equal weight) on each arm of
the scale and how far they are from the middle of the scale. On each arm
of the scale are four equally spaced pegs on which weights can be placed.
The arms are locked into place until after the child predicts which side, if
either, will go down. A young child, for example, might use a simple rule
“If the weights on each side of the scale are unequal, then the side with
more weight will go down,” thus ignoring the weights’ distance from the
center of the scale. With increasing age, children consider more and more
information until they develop a rule that assesses the exact contribution
of both number of weights and distance by multiplying the number of
weights on each peg by that peg’s ordinal distance from the fulcrum. (The
ordinal position can be used because the pegs are an equal distance apart.
The fourth peg from the midpoint is four times as far away as the first
one.) By comparing the outcome of this computation for the two sides,
children can predict which side will go down.
Using an elegant design, Siegler systematically varied the number of
weights and their distance in a series of problems. Each rule would lead to
a characteristic pattern of correct and incorrect predictions over the series
of problems. This study is an example of the rule- assessment approach
based on error analysis described in the section on methods. Consider,
for example, a “ conflict– weight problem,” in which there is more weight
on one side but the weights are more distant on the other side. The con-
figuration is such that the side with more weights goes down. Children
using the rule based on number of weight would be correct because they
consider only the number of weights. Children using a more advanced rule
that considers both number of weights and distance from the fulcrum,
however, are correct only part of the time because they simply guess.
They know that both distance and number of weights are important but
cannot determine the exact contribution of each. Children using the most
advanced rule are always correct because they can calculate the contribu-
tion of both variables. Notice that the children’s errors are as informative
as their correct answers. Similar analyses have assessed age differences in
rule use on many other tasks as well, including conservation, projection of
shadows, probability, speed, and mathematical calculations.
What children bring to this task— their age, initial rule, and initial
encoding of the task— affects what they can learn during the task.
In one study (Siegler & Chen, 1998), 83 percent of the 4- year- olds
failed to encode the distance of the weights from the fulcrum and thus
were unable to learn that this feature might be related to the problem.
Although they saw 12 problems on which the weights were equal and the
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346 ▶ INFORMATION-PROCESSING THEORY
side with weights farther from the fulcrum went down, and each time
they were asked “Why do you think that side went down?” they never
seemed to notice the dimension of distance.
The way that information- processing psychologists study the balance–
scale task contrasts with Piaget’s approach to the same task. Although
both were interested in how children reached their answer, Piaget used
the task to diagnose whether children have underlying mental opera-
tions. Siegler, in contrast, inferred what specific rules the child used for
the task at each step en route to developing an understanding of bal-
ancing weights. He thus identified partial knowledge and made a more
detailed analysis of the relation between the child’s actions and, because
he had done a task analysis, the stimulus characteristics of the task— the
number of objects and their distance from the fulcrum. He also could
see the process of learning because he used a microgenetic design.
Computational Modeling
In the general information- processing approach described thus far, the
computer serves as a loose metaphor to help researchers think about
the processes a person uses to represent, store, and solve problems
about words, pictures, objects, or events. These researchers adopt the
informal, but not the formal, language of computer science. They talk
about “information,” “capacity,” and “rules” but do not translate cognitive
processes into a formal computer language in a computer program.
At most they might develop flow diagrams of the flow of information
through the cognitive architecture (see Figure 7.1). The computation
modeling approach, in contrast, might try to design a computer model
with a system of rules or cognitive processes that generate these input-
output relations. These models not only generate behaviors similar to
those of children of various ages but also include learning mechanisms
that lead to changes, thus simulating developmental changes. Two kinds
of computational models are described next— production systems and
the more recent connectionist models.
Production Systems c Production systems models of development
usually involve a set of rules, expressed in symbolic representations.
These rules generate behavior on complex problem- solving tasks, which
can be compared with what children actually do on these tasks. An influ-
ential production system (Klahr & Siegler, 1978) modeled children’s
rules on the balance scale described above. An example of a symbolic
representational rule is “If X is present, then do Y.” These models were
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Major Developmental Approaches ▶ 347
called production systems, because the rules specified the conditions
(the “if ”) that produce each behavior (the “then”). A rule might be “If
the weights on each side of the scale are unequal, then the side with more
weight will go down,” and the child picks the side with more weights.
This production system models not only the behavior of children of
different ages but also learning during a session. Over trials on the task,
feedback on applying the if- then rule(s) leads to more advanced rules.
Thus, learning involves acquiring, and sometimes changing, production
rules. Sometimes rules conflict, as when one predicts on the basis of
number of weights and one on the basis of distance from the fulcrum,
and lead to different decisions. This conflict may lead to a new, more
complex rule. This production system model successfully predicted
children’s decisions and described movement from one kind of rule to
another one, thus modeling development.
There are numerous types of computational models today. Rather
than focus on children’s use of rules during problem solving, they
address the question “How do children somehow turn a vast amount
of sensory stimulation, much of it ambiguous or irrelevant (“noise”),
into something meaningful?” Children manage to form categories and
abstract representations, detect cause and effect, and predict events.
Next is a description of the most common type of computational model
today— connectionist models.
Connectionist Models c Connectionist models, also called neural network
models, involve a network of nodes and connections between these nodes,
analogous to brain networks of neu-
rons and synapses (see Figure 7.4
for a very simple model). In fact,
these models are constructed so as
to be consistent with what is known
about brain structure, function, and
development. The current interest
in cognitive neuroscience may be
one reason for the attractiveness
of connectionist models. This net-
work of artificial neurons forms the
underlying microstructure of basic
cognitive processes. In contrast to
production systems models, which
involve symbolic language- like
representations of rules and the
Output units
Input units
Hidden units
F I G U R E 7 . 4
A simple connectionist model.
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348 ▶ INFORMATION-PROCESSING THEORY
manipulation of symbols, connectionist models represent the likelihood
of activation of each connection. Another difference is that connection-
ist models involve parallel distributed processing, in which a large amount
of input is analyzed simultaneously, in contrast to the serial, sequential
processing of production systems. Thus, connectionist models depict
thinking as a pattern of activation in neural- like networks. If Descartes
had been a connectionist, he would have declared, “I have a pattern of
activation in a neural- like network, therefore I am.”
More specifically, each neuron- like information processing unit
has a numerical value, usually the probability that it will be acti-
vated. Connectionist models posit several layers or levels of units (see
Figure 7.4). The input provided by the modeler might include, for
instance, a series of words or pictures, to represent children’s expe-
rience. For example, there are some extensive databases of young
children’s language environments that facilitate creating the input for
connectionist models of language learning. At the input level, processing
units encode the input provided by the modeler and sometimes signals
from other networks. At the next level, so- called hidden systems, or
internal representations, use information from the input level to com-
pute more complex relations. A final complex level produces output
such as decisions, words, or thoughts. The model might represent learn-
ing a new word by adjusting weights between units; the child’s saying
a word would be represented by the activation of an output unit that
stands for that word. The modeler tries to bring the neural network to a
state in which it can take a given input and produce the same output as
a child. Designers have developed models with a variety of architectures
(see Yermolayeva & Rakison, 2014). Recent models are much more
complex than the one in Figure 7.4, with more levels, more sets of hid-
den units, and even subnetworks.
Not surprisingly, in connectionist models the connections are all-
important. Each unit is connected to units in different layers and some-
times in the same layer as well. Each unit can excite or inhibit other units.
As in the brain, the strength of any given connection depends on the
frequency of “firings” between the two elements of the connection. That
is, with experience, certain units are consistently fired and thus become
highly associated (heavily weighted), while other units do not. A helpful
analogy is a traffic map showing the most heavily traveled routes in red.
In a connectionist model, as in the brain, a unit fires if the total amount
of activation it receives from other units exceeds a certain threshold.
In this connectionist world, a piece of knowledge does not reside in
a single place in the system. Rather, knowledge is a distributed pattern
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Major Developmental Approaches ▶ 349
of activation over many connections. It is a pattern of connections
with various weights. And any one unit may take part in representing
many different pieces of knowledge if it is part of several patterns
of activation. Each network of activation overlaps heavily with other
distributed patterns of activation. The goal is to show that different
distributions of connections— patterns of connectivity— correspond to
different knowledge levels in children of different ages. These models
capture the complexity of the cognitive system (and of the brain, as well)
because the activation in any unit or system of units is affected by the
activity of other units or systems of units.
A model is constructed in the following way: Based on empirical
data with children, the modeler sets the starting weights of connections,
the pattern of the connections among units, unit activation or inhibition,
and the mathematical function for how each unit’s total input is trans-
formed into an output. The modeler also sets several rules that govern
the flow of activation from input to output. For example, an integra-
tion rule calculates the total input each unit receives from other units
due to the outputs of those units and the weights on the connections.
Because some units activate other units and some units inhibit other
units, this rule usually involves calculating the weighted sums of the
excitatory and the inhibitory inputs. After all these parameters are set,
the modeler provides carefully selected input. Based on the rules, input
activates certain units and each of these units passes on its output to cer-
tain other units with whom it connects. In complex models, this may con-
tinue for several levels. As a result, the pattern of weights changes, which
constitutes learning. In this way, the model produces short- term change,
and short- term change can add up to long- term change. In short, the
model takes input and mathematically generates a set of data (outputs).
Note that learning, or cognitive development, occurs when the pat-
tern of connections changes or the relative strength of the connections
changes after each set of inputs. That is, the model may respond to feed-
back as to whether the output was accurate or inaccurate. If the match
is poor, the model or the model- maker may adjust the strengths of the
various connections in a way that would minimize error on later trials. In
some models, new units are added as a result of experience. The system
typically learns by example (actually, a large number of examples). For
instance, if a model is learning names of objects, an object (the input)
may activate a unit representing a word. If that word is incorrect, the
model may be informed which word should have been activated and the
weights of the connections are changed so that it is more likely that next
time the correct word will be activated.
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350 ▶ INFORMATION-PROCESSING THEORY
Let us now consider two simple connectionist models. One model
(Gureckis & Love, 2004) simulates infants’ category learning about
types of imaginary animals. The input to the model was a series of
imaginary animals that differed in terms of three attributes: type of
body (giraffe, cow, elephant), feet (webbed, club, and hoofed), and tail
(fluffy, feathered, and horse). Each item for the model consisted of a
set of three attributes, such as giraffe, feathered tail, and webbed feet,
that corresponded to a drawing of this animal that had been shown to
infants. A series of these three- attribute lists made up the input (expe-
rience). The lists were constructed so that the attributes were perfectly
correlated. For instance, a giraffe always had a feathered tail and webbed
feet; a cow always had a fluffy tail and club feet. Over trials, the model
looked for correlations ( co- occurrences) among the attributes (e.g.,
giraffes always have feathered tails) to form several clusters of animals,
with similar looking animals in each cluster. The weights of various con-
nections were changed accordingly. After this learning, when a novel
animal was presented, the cluster that was activated the most formed the
output— the (hopefully) correct category for the animal.
Another example is a model that describes how German children
learn which of the six forms of the German definite article “the” go with
which nouns (MacWhinney, Leinbach, Taraban, & McDonald, 1989).
The appropriate article in German is determined by the noun’s gender
(masculine, feminine, neuter), number (singular or plural), and role in
the sentence (for example, subject, direct object). The input level con-
sisted of 35 units that analyzed these features of nouns. Two levels of hid-
den units consisted of units formed by combinations of the input- level
features, such as the gender and number of the noun, and six output
units represent the six possible German articles.
Much like the experience of very young German children who are
surrounded by spoken German, the input to this connectionist model
was repeated experience with a set of common German nouns and
their correct article. This experience led to changes in the strengths
of connections between particular articles and particular nouns in the
model. Some pathways fired many times and became stronger because
of the frequency with which a particular article occurs with particular
nouns in German. Some pathways never or rarely fired and remained
weak because certain articles never or rarely occur with certain nouns.
With more experience, the model became more accurate as correla-
tions between nodes began to approximate correlations between par-
ticular articles and nouns in the real world of German language. In
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Major Developmental Approaches ▶ 351
this process, the model compared its answer with the correct answer;
a match strengthened the rule, whereas a mismatch did not. Once
the model constructed a set of rules for which articles go with which
sorts of nouns in which contexts, it was tested with unfamiliar nouns.
The model was fairly successful at choosing the correct article, much
like children generalize the associations or rules of language they have
acquired. Other evidence that the model was a good simulation of
language development is that during learning, the model made some
of the same sorts of errors that young German children do, such as
overusing the article that is used most often in German. And the same
article– noun combinations that are most difficult for children were also
the most difficult for the model. Thus, this connectionist model is a self-
modifying system that is consistent with what is known about language
development.
Although both production and connectionist models can simu-
late change and thus serve as examples of the self- modifying systems
described earlier, this is especially true of connectionist models,
which focus on cognitive change. After the model builder specifies
the architecture of the network and learning algorithms and provides
a series of inputs, the model itself does the rest of the work of learn-
ing. A strength of self- modifying computational models is that they
can identify and test theories about mechanisms of development. To
simulate longer- term development, model builders sometimes change
the parameters of the model in ways known to occur in development,
such as changes in neural processing or changes in experiences (input)
(Yermolayeva & Rakison, 2014). For example, they might introduce an
increased working- memory capacity into the model or provide more
pictures or more time per picture in the input to simulate the greater
capacity and experience of older children. The beauty of these complex
models is that they can show how introducing this small change into the
model can eventually lead to a significant change in the system. In fact,
some kinds of abnormal cognitive functioning may be caused by a very
small initial atypical variation at the perceptual level of functioning that
gets magnified in its effects as one thing leads to another over time and
experience. For example, in one model, a small initial disturbance in
processing phonemes plus exposure to 40,000 sentences led to specific
language impairment (SLI)—deficits in syntactical (grammatical) pro-
cessing (Joanisse & Seidenberg, 2003).
Connectionist models have contributed to theory building not only
by simulating children’s development but also by providing a new
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352 ▶ INFORMATION-PROCESSING THEORY
theoretical perspective on some of the mysteries of development. One
example is toddler’s language spurt (McMurray, Horst, & Samuelson,
2012), often attributed to a qualitative change in cognition or the brain,
specific to language. In contrast, this spurt can be explained by con-
nectionist general principles of learning described above, such as slow
associative learning, parallel learning, and competition among networks.
A connectionist model also provided a new explanation of Piaget’s
observation that babies continue to reach for an object in location A,
where it was first hidden and they had found it, even after they have seen
the object moved and hidden in location B. Piaget attributed this error to
the lack of an appropriate sensorimotor scheme. In contrast, Munakata’s
(1998) connectionist model predicted a U- shaped trajectory based on the
strength of the tendency to reach to location A, with less reaching to A
with very low or very high weighting. When the weights for that bias are
weak, in young infants, there should be no reaching for A; as the weights
increased, the activation of the A location eventually could persist over a
delay (i.e., after the object is hidden in B), thus creating the error of reach-
ing for A. Then, when the weights for reaching for B are strong enough,
the infant should no longer have the A bias. Thus, the model provided an
alternative explanation— a memory- based developmental mechanism—
for the A bias. It also led researchers to study infants younger than those in
previous research, infants who have not yet developed the A bias.
Another reason for the excitement about connectionist models is that
they have the advantage of requiring researchers to have very precise
hypotheses about relevant experience and cognitive processes. These
models also have contributed to developmental psychology by providing
an alternative view of what is developed— subsymbolic weighted sets of
relatedness rather than symbolic rules. These models are complementary
to “good old fashioned cognitive psychology” (Oakes, Newcombe, &
Plumert, 2009) because they can examine mechanisms that cannot fea-
sibly be studied with behavioral methods (Schlesinger & McMurray,
2012). For example, they can introduce deprivation or cause atypical
development, which cannot be done with children. Finally, connection-
ism is considered a unifying theory, because it should be possible to use
it to study all kinds of knowledge and behavior. However, one negative is
that connectionist models may be quite complex and technical, and thus
not easily used by nonspecialists.
Connectionists have constructed developmental models on numerous
topics, such as language learning, motor behavior, causal reasoning, read-
ing, and categorization (see Yermolayeva & Rakison, 2014, for descrip-
tions). In addition, known developmental changes in brain functioning
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Mechanisms of Development ▶ 353
have been modeled. For example, in one model, after the learning phase
(presentation of input) was completed, the connections that had low
weights were eliminated (Mayor & Plunkett, 2010). This simulates the
synaptic pruning during development described in Chapter 5.
Mechanisms of Development
One novel source of change is variability in behavior. The puzzling obser-
vation that children keep changing their strategies rather than staying
with a successful one led to a model to try to depict this variability.
In Siegler’s influential overlapping- waves model: “A wave, like children’s
thinking, never stands still” (Siegler, 1996, p. 239). As applied to strategy
development, in Figure 7.5 each wave represents a different strategy.
The strategies, like waves, overlap in that a child continues to use an old
strategy even after a new strategy begins to develop. Many strategies look
like waves because they gradually gather strength, peak, and then crash as
Strategy 3
Strategy 1
Strategy 2
Strategy 4
Strategy 5
Age
Pe
rc
en
t o
f u
se
F I G U R E 7 . 5
Siegler’s overlapping- waves model of cognitive development.
[Siegler. Children’s Thinking, in Figure “Siegler’s Overlapping Waves of Cognitive Development,” Copyright ©
1998, Prentice- Hall, Inc. Reproduced by permission of Pearson Education, Inc., p. 98.]
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354 ▶ INFORMATION-PROCESSING THEORY
the child discontinues them. We saw in an earlier section that at any age
children have several strategies that they could use to solve a problem. In
the figure, a child discovers new strategies (3, 4, and 5) and adds them to
his repertoire. Some waves never become the most prominent one but
still influence the other waves. The wave model of constant change and
variability contrasts with the staircase- like stage models, like Piaget’s, that
depicts development as a series of levels, with brief periods of transition
between levels.
Why would children show such variability, especially when it seems to
be counterproductive, as when they drop a successful strategy? Siegler
draws an analogy to biological evolution. As in evolution, change comes
about through variation, competition, and selection. Various strategies
compete for dominance. Through experience, a child learns that some
strategies are more adaptive (useful, accurate, or efficient) than others
and thus retains (“selects”) these in the long run. Thus, a process of com-
petition among skills or ideas, in this case, strategies, leads to “survival
of the fittest.” Moreover, it is adaptive to have multiple strategies because
if one strategy fails to solve a problem, the child can go to “plan B.”
Variability in approaches to a problem also is adaptive because it seems
to set the stage for children’s ability to profit from new experiences or
training. That is, children who show variability seem to be more ready to
change their thinking. They may be open to mechanisms of development
that move along their thinking. Siegler has used this evolutionary model
of cognitive change to account for changes in a variety of areas, such as
arithmetic, reading, problem solving, and spelling. Psychologists’ past
tendency to consider variability a nuisance rather than a phenomenon
of interest may have directed attention away from behaviors that could
provide important clues to developmental change.
Information- processing theorists have identified at least four specific
mechanisms of development: automatization, encoding, generalization,
and strategy construction. In automatization, processing that used to
require conscious awareness becomes more and more automatic. For
example, when children count five fingers on one hand many times when
learning to count, they eventually can automatically say “five” when hold-
ing up one hand with all fingers extended. This releases space in working
memory for other cognitive activities, such as constructing a new strategy.
Changes in encoding features of the environment can encourage a child
to notice, and thus use, different information, as when a child learns to
check whether the problem has one large digit (5) and one small one (2),
which leads to efficient use of the strategy of counting “5, 6, 7.” When
information contradicts a person’s beliefs, children and even adults can
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Posit ion on Developmental Issues ▶ 355
have trouble “seeing,” and encoding, what is in front of their very eyes. In
one study (Kaiser, McCloskey, & Proffitt, 1986), participants watched a
ball released by an electric toy train fall in a curve forward and down to
the floor. Most school- age children and many adults encoded the event
as the ball falling straight down. Even later, when confronted with the
actual curved trajectory of the ball, many still had trouble accepting,
and encoding, this information that violated their beliefs. Recall also
that some children encoded only number of weights on the balance- scale
task. Teaching children what information to encode (both distance from
the scale’s center and number of weights) enables them to learn from
feedback regarding their predictions on the balance scale and subse-
quently to adopt new rules for problem solving (Siegler, 1978).
A third mechanism of change, generalization, operates when a child
applies, for example, an adding strategy to new problems with a similar
structure. Finally, strategy construction occurs when a child has an insight
into the problem and tries a new approach. These four mechanisms work
together to bring about cognitive change. General cognitive develop-
mental changes, such as increased knowledge and organization of this
knowledge, can facilitate the work of these mechanisms.
Researchers have studied change mechanisms with the microgenetic
method, which provides a fine- grained description of change that some-
times suggests the cause of the change. Some also study change with self-
modifying connectionist models. As a result of input, the model changes
the relative strengths of various connections in the system, as described
earlier. Change in the overall pattern of associations of various strengths
constitutes learning. If the hypothesized change mechanism in the model
is correct, it should modify itself and generate a description of change
that mimics children’s change over time. Although this change is over a
short period of time, developmental changes over longer periods of time
may involve similar principles.
Position on Developmental Issues
Human Nature
In an update of Newton’s view that humans are like machines, humans
are now said to resemble computer programs (or laptops, for children?).
In this mechanistic view, input is followed by a series of events and finally
output. A connectionist model passively waits for input. Flow diagrams
seem to portray static structures nudged into activity by intruding
arrows. And, robots aside, computers and flow diagrams typically do not
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356 ▶ INFORMATION-PROCESSING THEORY
move themselves, call a friend, or select a good book to read. Despite
these mechanistic features, in many ways the information- processing
approach is organismic in its emphasis on dynamic organization, of both
children’s cognitive system and models; change in both children and
models involves active reorganization. Both modify themselves. Children
actively interpret new experiences, apply rules and strategies, search for
further information in the environment, or even “construct” information
as they make inferences based on the input and on previous knowledge.
Children become more active cognitively with increasing age as they
develop metamemory to enhance their memory by rehearsing, making
written reminders, and relating new information to old. Similarly, self-
modifying connectionist systems extract patterns from input, develop
hypotheses, use input to test these hypotheses, and perhaps create new
subnetworks or layers of units and connections. In flow models, executive
control processes oversee and actively coordinate the memory system.
Qualitative Versus Quantitative Development
Information- processing theories allow for both qualitative and quanti-
tative development. They do not have the strongly qualitative, stagelike
development found in Piagetian and psychoanalytic theory. However,
they do have some types of qualitative change: the emergence of new
strategies for storage or retrieval, rules for problem solving, changing
patterns of activation of nodes and connections, and modes of represen-
tation (for example, verbal representation after language is developed).
Quantitative development appears in increases in the number of items
remembered, in the amount of information in the knowledge base, in
the number of strategies in one’s repertoire, and in the strength of asso-
ciations in connectionist systems. There often is interplay between quan-
titative development and qualitative development, as when children’s
experience with weighing items leads to a new rule about balance scales,
which then becomes more efficiently and consistently applied to a variety
of situations. Or, in connectionist systems, a quantitative strengthening
of connections can lead to crossing over a threshold, which produces a
new behavior that looks qualitatively different from previous behaviors.
Nature Versus Nurture
Nature and nurture interact to produce change. The environment contin-
ually brings input to the cognitive system, but neurological development
increases the efficiency of the transmission of neuronal impulses. Also,
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Applications ▶ 357
the tendency toward economical, nonredundant, efficient processing
may be innate (Klahr & Wallace, 1976), and the processing system may
be pretuned to process certain types of stimuli, such as linguistic input.
In connectionist models, learning occurs within the constraints of the
developing brain: “New structures can emerge at the interface between
‘nature’ (the initial architecture of the system) and ‘nurture’ (the input
to which that system is exposed)” (Bates & Elman, 1992, p. 15).
What Develops
Stated most generally, cognitive processing develops. It becomes more
efficient and organized in its operation and acquires more and more
content as the child explores the world. More specifically, children
acquire strategies, rules, scripts, patterns of connections, and a broader
knowledge base. Another way to describe what develops is: “knowing”
(development of knowledge about the world), “knowing about knowing”
(metacognition), and “knowing how to know” (development of strate-
gies) (Brown, 1975).
Applications
As mentioned in Chapter 6, cognitive science has generated a new
learning sciences approach that draws on cognitive science theories and
concepts about knowledge and learning to design effective instruc-
tion. Information- processing concepts such as adequate working
memory, chunking into categories, transfer to related tasks, and
problem- solving strategies inform instructional design. Task analysis is
critical— breaking reading and mathematics down into their compo-
nent parts and identifying the cognitive skills necessary in each phase
of processing. One poor reader might have problems in the initial
phase— encoding— whereas another poor reader might have trouble
integrating the meaning of consecutive sentences, which would call
for different kinds of instruction. Working memory has emerged as an
especially important factor. Having poor working memory is associated
with problematic classroom behaviors such as inattention, distractibility,
and failure to keep track of what one is doing (Alloway, Gathercole,
Kirkwood, & Elliott, 2009). Moreover, a large- scale longitudinal study
of children from age 3 through early adulthood showed that working-
memory capacity predicts how well children do in reading and spelling
(Schneider & Bullock, 2009).
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358 ▶ INFORMATION-PROCESSING THEORY
Teachers can help children acquire memory strategies. First- and
second- graders whose teachers were told to use memory- relevant
language, such as strategy suggestions and metacognitive information,
showed more knowledge about strategies and more advanced strat-
egy use on a memory task (Grammer, Coffman, & Ornstein, 2013).
In another intervention, focused on “learning how to learn,” teachers
emphasized choosing a good strategy, self- testing, and planning (e.g.,
Hacker, Dunlosky, & Graesser, 1998).
Mathematics and science instruction have been of particular interest.
In mathematics, one intervention, based on Siegler’s research on math
understanding described earlier, used board games with a numerical
theme with low- income preschoolers to improve their math perfor-
mance (Siegler & Ramani, 2009). This population is known to be at
risk for falling behind in math understanding. In scientific thinking,
children and even adults have great difficulty separating hypotheses from
evidence. One critical thinking skill is to know how to design uncon-
founded experiments by changing only one variable while keeping the
values of all other factors the same, in order to determine whether
that variable caused the experimental outcome. Researchers have devel-
oped successful instruction for this concept and documented the impor-
tance of teacher guidance over simply learning on one’s own (Matlen &
Klahr, 2012).
Memory research, using longitudinal studies, has been extended to
children at risk. For example, infants born prematurely sometimes show
long- term memory deficits (Rose, Feldman, & Jankowski, 2014). In a
developmental cascade, premature birth affects less complex abilities
such as speed and attention, which then affect more complex abilities
such as memory, which in turn affect general cognitive ability. Also,
experiencing prenatal metabolic disturbances due to iron deficiency
associated with diabetic mothers alters memory circuitry and impairs
memory performance through infancy and early childhood (Riggins &
Nelson, 2014).
A final important application of memory research is to children’s
eyewitness testimony in general, but particularly for their own abuse,
a situation where they often are the only witnesses. There are several
issues: How accurate is young children’s testimony in general? Does
the highly emotional, traumatic nature of abuse affect children’s recall
of trauma- related information? How valid are “recovered memories”—
older children’s or adults’ memories of apparently forgotten abuse
during early childhood? How suggestible are young children when sub-
jected to repeated questioning by parents, false information provided
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Applications ▶ 359
after the event, or cross- examination in a legal setting? Researchers
study children’s eyewitness testimony in two main ways. One is to create
a live or videotaped event that reproduces some elements of the abuse
situation in an ethical way. Children might recall a highly stressful event
they saw or events during a Simon Says game in which the child and the
experimenter touch parts of each other’s bodies (White, Leichtman, &
Ceci, 1997). A second approach is to study naturally occurring, mildly
traumatic, but nonabusive, experiences, such as going to the dentist or
receiving urethral catheterization.
Although there is considerable debate about the answers to the
above questions, a wealth of information is emerging (Goodman, Ogle,
McWilliams, Narr, & Paz- Alonso, 2014; Howe & Knott, 2015): Although
younger children usually do not recall as well as older ones, their errors
usually are errors of omission rather than of providing false informa-
tion. Also, in general, older children are less suggestible than younger
ones. However, an exception may be that, with increasing age, chil-
dren are more likely to incorrectly think they experienced something
if it makes sense, that is, if it fits into the “gist” of what they encoded.
An example mentioned in the earlier section on knowledge effects on
memory, is falsely recognizing “sleep” when only words such as “bed,”
“rest,” “awake,” and “tired” were presented (Brainerd & Reyna, 2014).
With respect to recall for abuse specifically, most child abuse victims
have particularly good recall of stressful events. A major contribution
of developmentalists has been to develop standard protocols for inter-
viewing children to elicit accurate testimony (Goodman et al., 2014).
Features typically include building rapport with the child, assessing the
child’s developmental level, discussing the distinction between truth
and lies, and explaining interview rules (e.g., acceptable to say “I don’t
know”) before questioning. Then questioning proceeds from free recall
and open- ended to more specific questions, to avoid leading the witness.
Interestingly, there is reason to doubt that anatomically detailed dolls
and other props improve young children’s recall accuracy (Salmon, Pipe,
Malloy, & Mackay, 2012).
In addition to these general findings, there is evidence of variability
among children in the accuracy of their recall for negative events. For
example, the type of attachment matters (Chae et al., 2014). Among
children with parents high in avoidance (see Chapter 5), higher levels of
distress when receiving an inoculation predicted less accurate recall of
that event. In contrast, the combination of low parental avoidance– high
stress predicted more accurate recall. Also, preschoolers with more pos-
itive representations of their parents had more accurate recall. Avoidant
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360 ▶ INFORMATION-PROCESSING THEORY
parents may not in the past have discussed distressing events with their
children or prepared them for coming negative events, resulting in their
children’s poorly represented and processed memories for such events.
Thus, socioemotional factors contribute to recall of distressing events.
The constant use of electronic devices in daily life has raised con-
cerns about multitasking, given children’s limited processing capacity,
immature attention system, and poorly developed executive function-
ing. Crossing an intersection while engaged with an electronic device
and studying while listening to music raise questions about children’s
safety and learning. The research indicates that multitasking usually
compromises information processing and learning (Courage, Bakhtiar,
Fitzpatrick, Kenny, & Brandeau, 2015). However, these negative effects
may be avoided by creating certain conditions: giving the child control
over the task requirement, making learning platforms developmentally
appropriate, and permitting practice.
Evaluation of the Theory
The information- processing approach changed the way developmen-
talists thought about children’s thinking and greatly influenced almost
every area of cognitive developmental research. In this section, the focus
is on its strengths and weaknesses as a developmental theory. The theory’s
strengths lie in its ability to express the complexity of thought, its pre-
cise analysis of performance and change, and its rigorous methodology.
Its weaknesses include the shortcomings of models and metaphors,
problems with addressing certain developmental issues, and a neglect of
the context of behavior.
Strengths
Ability to Express the Complexity of Thought c The information-
processing approach, like Piagetian theory, addresses complex thinking.
It tries to specify a variety of cognitive processes, ranging from the
simple detection of a stimulus to the development of complex rules,
strategies, and concepts. Furthermore, it attempts to characterize how
perception, attention, memory, language, and abstract mental opera-
tions are interrelated. The approach posits an intricate organization of
thought in which control processes direct and supervise. For example,
children learn to handle large amounts of information by “chunking” it
or by relating it to what they already know. Connectionist systems show
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Evaluation of the Theory ▶ 361
that a few simple principles of learning (e.g., associations between units,
weighting of connections, competition between networks) can account
for the detection of complex patterns in the environment and the emer-
gence (sometimes unexpectedly) of complex concepts in children.
Precise Analysis of Performance and Change c Perhaps the great-
est strength of information- processing theories is their specificity. They
carefully specify the input and children’s cognitive architecture. They
then make specific predictions about a child’s behavior from moment to
moment, on the basis of a fine- grained analysis of the task, the current
state of the child’s cognitive system, and microgenetic changes over
numerous trials. Connectionist models are particularly specific because
they must identify all assumptions and relevant parameters, decide on
calculations for the processing nodes to use, and look at exact changes in
strength of particular associations. Psychologists are forced to clear up
any muddled theoretical thinking.
The Piagetian and information- processing approaches have much in
common. Both attempt to explain how more advanced concepts grow
out of earlier, simpler ones— specifically, how a child’s current cognitive
system both constrains and permits the emergence of new knowledge.
However, information- processing investigators attempt to be more
explicit about how children use their cognitive skills in a given situation.
This is a theory of performance, which, as mentioned in Chapter 2, is
weakly developed in Piaget’s theory. Information- processing theories
describe how attention, memory, strategies, representational processes,
and logical operations “connect” with tasks. For example, if the task
requires that a child decide whether objects on a balance scale will bal-
ance, the information- processing approach would specify how the child
selects certain information about the objects (for example, number, dis-
tance from the fulcrum), encodes it, and applies rules from long- term
memory. Piaget’s décalages (asynchronies in applying a concept to dif-
ferent but related tasks or content areas) become less mysterious when
investigators analyze the information- processing demands of each task.
Some tasks make greater demands on working memory than do other
tasks. More generally, the information- processing approach emphasizes,
more than does Piaget, processing limitations, strategies for overcoming
these limitations, domain- specific knowledge about the task at hand, and
specific behaviors involved in the process of change on a particular task.
Rigorous Methodology c Related to the theory’s specificity is that
hypotheses generated by the theory are testable— a trait shared with
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362 ▶ INFORMATION-PROCESSING THEORY
social learning theory, less so with Piaget’s or Vygotsky’s theory,
and much less so with psychoanalytic theory. Information- processing
researchers use stringent and precise experimental methods. As one
psychologist commented, “Many of us have become methodological
behaviorists in order to become good cognitive psychologists” (Mandler,
1979, p. 281). Laboratory research on basic processing often makes
precise measurements of processing time. For developmental research,
error analysis and microgenetic designs have proved to be particularly
powerful assessment procedures. By cleverly designing different types
of problems, researchers have discovered that young children are using
simpler, less complete rules, procedures, or strategies than are older
children.
Weaknesses
The preceding short section on strengths is followed by a longer sec-
tion on weaknesses. This imbalance does not reflect an abundance of
weaknesses in the theory. Rather, most of the strengths were mentioned
earlier in the chapter, whereas weaknesses have been neglected and must
now draw our attention.
Shortcomings of Models and Metaphors c A basic problem with flow
diagrams and computational models is that these models may adequately
describe what the relation between input and output could be, but not
necessarily what it is. Similarly, it is possible for different models to
predict performance equally well. This is one limitation to the generally
good testability mentioned earlier. Thus, it can be difficult to judge the
psychological validity of a model.
One problem specific to computational models is that constructing
these simulations is a time- consuming, technical, often tedious task.
Consequently, the majority of researchers studying cognitive develop-
ment do not use this method. Part of the problem is that in order to be
complete and to run successfully, the modeler must be careful not to
exclude relevant information. An example of this problem is a college
campus computer dating program that contained much information
about students’ interests and attitudes (Kendler, 1987). The results
were not considered successful by a brother and sister who were paired
together! No one thought to instruct the computer that siblings should
not be paired.
Another problem with computer models is that they often are highly
specific, precise models of very limited, specific behaviors. Because
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Evaluation of the Theory ▶ 363
they must consider all relevant variables, it is difficult to develop more
general models that can run successfully. Still, connectionist models are
becoming increasingly successful at self-modifications that eventually
lead to more general models.
The metaphors of information processing have been useful. Viewing
thinking as bearing some similarities to computer processing and
the brain has provided a productive new perspective on thinking and
development. However, like all metaphors, information- processing
metaphors can be a dangerous tool. As George Eliot, in Middlemarch,
cautioned: “We all of us, grave or light, get our thoughts entangled in
metaphors, and act fatally on the strength of them.” One example is
that metaphors, and even the more formal models, usually have excess
meaning that was not intended. For instance, flow diagrams may make
us erroneously think of memory as passive, sequential, and unrelated
to other cognitive processes or to emotions. In addition, adopting a
particular model may seriously limit our thinking. Once psychologists
began to express memory as a series of discrete steps (boxes in a flow
diagram), it took several years before a less dichotomous, more gradual,
levels- of- processing approach, or parallel processing models, could be
seriously proposed. Thus, it must be kept in mind that a model is similar
only in certain ways to the phenomenon to which it is applied.
Metaphors also can constrain our thinking in that they may overly
encourage us to think about cognition in terms of spatial representa-
tions. Memory metaphors usually are spatial, implying that we “search”
our mental space for objects stored in physical space (Roediger,
1979). There almost seems to be a “homunculus” (little man) who
rifles through the files of memory until he finds that necessary paper.
In these files or in semantic networks, concepts are stored at differ-
ent “distances” from each other. Examples of cognitive metaphors
in Roediger’s list include a workbench, a pushdown stack (of clean
plates in a restaurant), an acid bath, a dictionary, and a subway map.
In a spoof of memory models, Hintzman (1974) likened memory to
a “cow’s belly.” Information (like food) is transferred from the “ short-
term stomach” to the “ long- term stomach.” In this way, we “ruminate”
over ideas and “digest” information.
The technology of the times suggests certain metaphors, beginning
with Plato’s likening memory to the impression of a seal on a wax
tablet, which in his time was a method of storing information. Later
metaphors were the gramophone, switchboard, tape recorder, com-
puter, and holograph. Today’s computer metaphor may evolve as devices
become more mobile, social, and varied. Will the Internet become a
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364 ▶ INFORMATION-PROCESSING THEORY
metaphor for thinking? What metaphor will a post- Internet technology
bring? A computer metaphor may eventually seem as naive as Plato’s
wax tablet.
Problems with Addressing Certain Developmental Issues c The
information- processing approach has advanced our understanding of
adult cognitive systems. How successfully has it contributed to devel-
opmental theory? The approach rates high marks for its careful, refined
descriptions of the processing system at various ages or cognitive levels.
Its focus on change offers great potential for identifying mechanisms of
development, which may be the central question about development.
What are the main developmental issues still to be resolved?
One issue concerns developmental continuity. Recently, great strides
have been made in studying information processing in infants and tod-
dlers, especially working memory and the analysis of linguistic input.
What is less clear is how these early competencies are related to the
much later, more verbal and complex ones. Connectionist approaches
offer mechanisms of change for this continuity in the short term and
hopefully will be able to address longer- term changes eventually. Part
of the issue is the longstanding question of whether short- term change
involves the same mechanisms as long- term change. Does the short-
term changing of weights of various connections also characterize the
change from age 2 to 7? Can the qualitative change that sometimes
emerges from these changing weights explain larger, more general
qualitative changes? Does children’s change from being “universal nov-
ices” (Brown & De Loache, 1978) to experts in an increasing number of
domains parallel long- term cognitive change? For example, when older
children learn, they bring more to the table due to their considerable
experience and understanding than do younger children. This difference
suggests that older children’s learning may be more likely to involve
drawing on previous knowledge, rearranging old knowledge, or simply
generalizing to a new domain. That is, the readiness to learn may look
somewhat different in a 2- year- old than a 7- year- old. Connectionist
models may be more successful at addressing these developmental issues
for some kinds of cognitive activities, such as detecting regularities in
language, than others, such as metacognition and social cognition.
Neglect of the Context of Behavior c Information- processing the-
ory generally has neglected the context of behavior, such as goals,
emotions, and affordances of the physical and social environment. As
one critic commented, “Ask not what’s inside your head, but what
your head is inside of ” (Mace, 1977). Another one noted that what a
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Contemporary Research ▶ 365
reader would conclude about the mind after reading a 904-page book
surveying cognitive science is “Minds talk a lot . . . they move a lit-
tle, they see a little, but they don’t feel much else” (Anderson, 1991,
p. 287). Information processing has focused on the processing mech-
anisms the person brings to a task or setting and on the task parame-
ters more than on the interplay between the demands or possibilities
of the larger setting and the needs, goals, and abilities of the person.
However, researchers recently have made some progress in addressing
how cognition is embodied in motor behaviors, as described in the sec-
tion on contemporary research. Some research on the social context
of cognition was described in the section on memory, and work on the
intertwining of emotion and memory is described in the applications
section. Also, the possibility of cultural differences in basic cognitive
processing was explored in Chapter 4 in work on cultural differences
in attentional processes. For example, Mexican- heritage children in the
United States more often simultaneously attend to multiple ongoing
events than European- American children, who tend to alternate their
attention among events (e.g., Correa- Chávez, Rogoff, & Mejía Arauz,
2005). Thus, even basic attention processes are culturally formed; when
a culture values children’s attending simultaneously to multiple events
in the community around them, cultural practices guide children in
that direction. Differing contexts related to the socioeconomic status of
families contribute to basic information processing as well. For exam-
ple, young adults who grew up in poverty have poor working memory,
which appears to be mediated by the high chronic stress experienced in
growing up in such an environment (Evans & Schamberg, 2009). The
observed accumulative wear and tear on the body was caused by phys-
iological responses to stress. Finally, the social context affects the sort
of learning described in connectionist models. Parents influence which
parts of the environment become input into infants’ processing systems.
Parents direct infants’ attention to certain objects and events through
shared attention, label certain objects but not others, and give certain
types of toys to young children.
Contemporary Research
Some contemporary research was described throughout this chapter.
Thus, this section will focus on several areas that recently have become
quite active— executive function, cognitive neuroscience, embodied
cognition, Bayesian models, statistical learning, and developmental
robotics.
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366 ▶ INFORMATION-PROCESSING THEORY
Executive Function
One topic of great current interest is executive function— cognitive con-
trol activities that help children adapt to novel tasks. Executive control
is related to the central executive in the Baddeley model described
earlier. The core executive functions are thought to be inhibition of
impulsive behaviors or decisions, working memory, and cognitive
shifting from one framework (e.g., sort by color) to another (sort by
shape) (Miyake et al., 2000). An example of inhibition is a task in which
children must say “day” when shown a moon and “night” when they see
a sun (Montgomery & Koeltzow, 2010). Like an orchestra conduc-
tor, executive function coordinates a child’s cognitive activities. These
skills are very important for effective information processing because
they insure focused attention on relevant information, avoidance of
distractions, planning, strategies, and cognitive flexibility during prob-
lem solving. The prefrontal cortex, the anterior area of the cortex, is
heavily involved in executive functioning, and is thought to synchronize
neuronal activity widely distributed in the brain. An example of the
importance of executive functions is that they are related to school
readiness and predict how well children achieve academically (Best,
Miller, & Naglieri, 2011; Blair, & Raver, 2015). They also appear to be
particularly disrupted in children with autism spectrum disorders or
ADHD. Moreover, executive function seems to serve as a protective fac-
tor for homeless children: Homeless children with high executive function
experience greater academic success (Masten et al., 2012). Executive
function also is related to social- cognitive developments, such as the-
ory of mind and social competence (Razza & Blair, 2009). Remarkably,
children with better inhibitory control had better physical and mental
health and better earnings and were more law abiding 30 years later
(Moffitt et al., 2011).
Recent research has identified a number of factors that contribute
to executive function. For example, competent parenting (sensitivity
and responsiveness) predicts later higher executive function (Blair,
Cybele, & Raver, 2014), as do good peer relationships (Holmes, Kim-
Spoon, & Deater- Deckard, 2015). Somewhat troubling is the fact
that television decreases executive function as well. Watching 10 to
20 minutes of televised fantastical events depleted executive function
in young children, when compared to playing or watching other kinds
of shows (Lillard, Drell, Richey, Boguszewski, & Smith, 2015). There
is recent interest in the possible benefits, for executive functioning,
of mindfulness— focusing on in- the- moment thoughts and feelings in
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Contemporary Research ▶ 367
a calm and nonjudgmental way. For example, a social and emotional
learning program involving mindfulness and caring for others, designed
for elementary school students, enhanced cognitive control ( Schonert-
Reichl et al., 2015). (It also reduced stress, promoted well- being and
prosocial behaviors, and produced positive school outcomes.)
Developmental Cognitive Neuroscience
The great interest in developmental cognitive neuroscience research
described in Chapter 5 includes information processing. Brain develop-
ment creates new possibilities for processing, for example, when myelin-
ation (insulation of neural impulses) during infancy increases working
memory, and later maturation of the prefrontal cortex facilitates the
control of attention. Although initial biases direct infants toward certain
information to process, such as social information including language,
for the most part, brain plasticity makes it possible for infants to ana-
lyze information in the particular environments in which they dwell.
Experience strengthens certain neural pathways and weakens others.
This in turn affects infants’ subsequent processing of information.
A main question is “What sort of brain architecture and functioning
supports each kind of information processing— simultaneous or succes-
sive processing, detecting patterns of co- occurrence of environmental
features, encoding features in order to construct rules, or generating
a script or ‘theory’ of the world to be tested?” For memory, the ques-
tion is “how the roughly 1500 grams (3 ½ pounds) of tissue that sits in
the bony case atop our shoulders manages to vividly re- create— and
even allows us to re- live— events and experiences from the past” (Bauer,
2009, p. 115).
Recent neuroimaging research provides biological support for many
of the findings in information processing (e.g., Johnson & DeHaan,
2015; Stiles, Brown, Haist, & Jernigan, 2015). During development,
brain regions become increasingly specialized for processing particular
kinds of information, though brain networks link activity over multiple
regions of the brain. In fact, one theory is that large- scale patterns of
brain organization during development emerge from neural activity
linking regions of the brain (Johnson, 2011). Significant progress has
been made in understanding brain contributions to memory develop-
ment. When children create a new memory, there is a physical change in
the brain. Neural synaptic connections are altered and thus patterns of
activation change. Different types of memory are controlled by different
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neural structures and networks. For example, the development of epi-
sodic memory during childhood corresponds closely to the development
of certain parts of the hippocampus, located under the cerebral cortex
(DeMaster, Pathman, Lee, & Ghetti, 2014). The hippocampus plays an
important role in consolidating memories into long- term memory by
binding details of an event into a mental representation that integrates
these features.
Neuroscience research not only provides another level of explanation
of known information- processing development but also contributes
to theory building by suggesting new hypotheses. For example, neural
activity linking regions controlling higher- level cognition with regions
central to motor behavior, emotions, and the processing of social infor-
mation supports theorizing about embodied cognition (see below) and
the intimate role of emotions and social interaction in development (e.g.,
Grossmann & Johnson, 2014). Both of these areas have been slighted in
previous information- processing research. For example, developmental
social cognitive science is exploring topics such as infants’ processing of
faces, brain activity during infant– parent shared attention, and the auto-
matic brain processes that occur when we are happy, angry, or empathic.
Brain development related to the effects of emotion on memory involves
different brain circuitry at different ages (Carver, 2014). Subcortical
areas develop relatively early, during infancy, and increase arousal, which
facilitates fast responses to emotions. The prefrontal cortex develops
quite late— during adolescence— and contributes to cognitive strategies
of emotion regulation.
Embodied Cognition
Another trend has been many years in the making. The critique
that information- processing approaches ignore the context led to
the embodied cognition approach in adult cognition (e.g., Glenberg,
Witt, & Metcalfe, 2013), and this approach has spread to developmental
psychology. Cognition is more than the manipulation of abstract sym-
bols. Rather, cognition is grounded in action; we process information
in order to do something. The brain is in an active, moving body that is
trying to navigate the physical and social environment. Although Piaget
emphasized motoric contributions to infant development, it played little
role after that, except as a way to explore the environment. Today, a vari-
ety of lines of research have converged on the conclusion that cognition
controls actions, and interactions of the body and brain affect cognition.
Here is a sampling: Measures of neural activation in sensorimotor areas
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Contemporary Research ▶ 369
of the cortex showed that 9- month- old infants recruit their motor sys-
tem when a situation suggests an impending action (Southgate & Begus,
2013). The crawling ability of 9- month- olds predicted their ability to
mentally rotate an object (Schwarzer, Freitag, Buckel, & Lofruthe, 2013).
A 14-year longitudinal study found that infants’ motor- exploratory com-
petence set in motion a developmental cascade that affected various levels
of intellectual function that in turn contributed to academic achievement
in adolescence (Bornstein, Hahn, & Suwalsky, 2013). The mirror neu-
ron system discussed in Chapter 5 showed that watching others’ actions
activates appropriate regions of the brain. Children given conservation
training with gestures (even with no objects present!) as well as verbal
instruction improved their understanding more than did verbal instruc-
tion alone (Ping & Goldin- Meadow, 2008). A main implication is that
cognitive developmental research and theorizing should be focused on
how a new cognitive skill contributes to the generation of action, and
how action facilitates cognitive development.
Bayesian Computational Models
Work on computational models continues. Connectionist models have
become increasingly complex in recent years— adding more layers,
more sets of hidden units, a working memory (activity in one layer in
the model feeds back into itself or into a different layer), repeating loops
and mini- networks within the larger network, mechanisms for learn-
ing sequences (e.g., predicting what word is likely to come next) and
emerging new hidden units over time (Schlesinger & McMurray, 2012).
The increasingly complex, interactive, and self- regulating nature of con-
nectionist models has led to integrations with dynamic systems theory,
which is discussed in Chapter 9.
Recently, Bayesian models have been applied to development.
Developmentalists are interested in these models because they address
two important questions: How do children make inferences about
objects, events, and causality in a world where there is too little usable
information because much of it is ambiguous (as when two contig-
uous events may or may not have a causal relationship)? How can
preexisting beliefs and knowledge, known to influence thinking, be
modeled such that their influence is represented in everyday thinking,
and how are beliefs and knowledge updated as a result of experience?
One approach to these questions is to think of children’s inferences as
probabilistic, given the uncertainty of the meaning of many or most
situations. Specifically, Bayesian probabilistic inference is used, or at
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least approximated. Bayesian models take the connectionist approach of
explaining behavior in terms of probabilistically weighted information.
Like other computational approaches, they force modelers to be specific
about their assumptions, about information in the setting, and about
children’s prior and present relevant information.
From a Bayesian perspective, what typically happens when young
children try to understand their experiences is that they learn from
examples, generalizing from these examples. For instance, they see
various cats and, through inference, generalize to a category— cat—
to which they learn to assign a word—“cat.” As they encounter new
examples, they sometimes are sure that it fits the category (it is defi-
nitely a cat), sometimes are sure it does not (it definitely is not a cat; it
probably is a dog), and sometimes are not sure (a cat with no tail— a
baby lion?). This uncertainty is especially likely in young children who
are just beginning to form categories. The idea of Bayesian models is to
represent, in a model, this uncertainty, past beliefs, and some learning
mechanism that explains how children’s categories gradually become
more like those of adults.
Basically, the assumption is that children form representations of
the probability of their hypotheses being correct: “I kind of think this
is a cat (70% probability), but it might be a baby lion (20%) or some
other animal (10%).” Children set these probabilities (unconsciously,
of course) of each hypothesis based on the category of cat they already
had and the information provided in the current encounter (Does it
meow? Does it have a long tail?). Stated differently, a child has a certain
amount of belief to allocate to her various hypotheses about what the
creature is. Experience with each new creature just moves around this
allocation. As one hypothesis is strengthened, the others are weakened.
After learning, based on an exemplar of a cat with a short tail, the child’s
prevailing belief may be that cats usually have long tails but can have
short tails. Another example, from adults, is the way physicians infer a
diagnosis. They may have an initial diagnosis (hypothesis) based on a set
of symptoms, but additional tests bring new information, leading the
physician to shift the probability of each of the several possible diag-
noses. A hypothesis about the illness that initially had a low probability
could, given enough evidence, become the hypothesis with the highest
probability. What both the child and the physician are trying to do is
figure out the underlying causal structure— the essence of a cat or the
disease— that generates the data that they use to make an inference.
Similarly, children infer from a person’s behavior the probable men-
tal state causing the behavior, or infer from a person’s spoken language
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Contemporary Research ▶ 371
to the underlying generative language system, and so on. In all these
examples, given the data observed and the learner’s prior knowledge,
the learner infers which construct, or causal model, is most likely to
have generated the data. In this way, as a result of experience, chil-
dren change their beliefs. In experiments, a researcher might first
assess children’s prior beliefs, then present them with a carefully spec-
ified set of data, and then examine which hypotheses they endorse.
Bayesian models have been developed and tested for various topics,
such as language acquisition, perception, concept formation, and motor
behavior.
From these examples, it is clear that one reason Bayesian models are
attractive is that they seem to describe the uncertainty and messiness of
everyday learning. The approach also provides a particularly useful way
to think about how young children develop and fine tune their concepts
and causal understanding. Moreover, children learn surprisingly quickly.
For example, young children somehow pick up new words and their
underlying concept after only a few examples. For instance, in a child’s
first encounter with a new word/concept, such as “sushi,” the referent
is ambiguous. It could refer to any food in a Japanese restaurant, all
circular food, all food that includes rice, just the seaweed wrapping, or
even the chopsticks. If three people at the child’s table are having three
different kinds of “sushi,” and two people are having something else, with
a different label, the probability of the child’s concept of sushi being
basically correct becomes very high and the probabilities of her other
hypotheses become very low.
Another reason why the Bayesian approach is attractive is that it can
incorporate what a child brings to the setting— innate or learned con-
straints on selecting one hypothesis over another. For example, children
have several biases for learning words, such as applying new words to
whole objects rather than to parts (e.g., Markman,1990). Thus, the nov-
ice sushi eater above would tend to assume that the word “sushi” refers
to the whole piece of sushi, rather than just the seaweed wrapping or
just the rice. Still another reason for the attractiveness of Bayesian mod-
els is that they have contributed to developmental theory by offering
an alternative mechanism of development— shifting probabilities of the
likelihood of children’s hypotheses about the world.
The Bayesian approach, and the phenomena it explains, is much more
complicated than can be communicated here. The many technicalities
of constructing Bayesian models are beyond the scope of this chapter
(see Perfors, Tenenbaum, Griffiths, & Xu, 2011, for a tutorial, and
Gopnik & Wellman, 2012, for applications).
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372 ▶ INFORMATION-PROCESSING THEORY
Bayesian models were inspired in part by empirical work showing
that children can engage in statistical learning. They can detect complex
statistical patterns and use them to make causal inferences, and thus
could think in ways depicted by Bayesian models. As a very simple
example, children automatically process the probability of two items
or events occurring together in the input. For example, infants have
surprisingly sophisticated language- learning mechanisms for attending
to and remembering frequencies of co- occurrence in sounds in language
input that may account for their early, rapid acquisition of language. That
is, they quickly learn the likelihood of particular syllable sequences—
which sounds tend to occur together. In one study (Pelucchi, Hay, &
Saffran, 2009), for example, English- learning 8- month- olds could track
the probabilities of these co- occurrences of sounds in fluent infant-
directed Italian speech. In this way, infants learn to extract words from a
continuous stream of sound. Children have plenty of data to draw on in
detecting these patterns. They hear approximately 17,000 words a day
(Risley & Hart, 1995).
Young children not only detect correlations among data and extract
reoccurring patterns, but they also infer abstractions, such as rules of
grammar. For example, after children encounter “a boy” and “a girl”
many times but never “a boys” and “a girls,” they infer a rule about how
to form singular and plural nouns. A convincing demonstration that
detecting the statistical regularities of language is a powerful mechanism
of language learning comes from a line of research showing that infants
can learn an artificial language based on knowledge of the statistical reg-
ularities of the language (e.g., Saffran & Thiessen, 2007). Young children
also draw on statistical learning to construct abstract causal structures.
An example is that, from observing patterns of probability among events
and noting the effect of their actions on a machine, they can determine
what they have to do to make a machine play music (e.g., Fernbach,
Macris, & Sobel, 2012).
In a striking demonstration that even infants have expectations about
probabilities (and perhaps are even sensitive to sampling patterns), Xu
and Garcia (2008) showed 8- month- old infants a box of white and red
Ping- Pong balls, in an 80:20 proportion. Then the experimenter took
some balls from the box. Infants looked longer when a sample of mostly
red balls was taken from a box of mostly white balls (an improbable
though not impossible event) than when a sample of mostly white balls
was removed. This suggests that infants are even sensitive to sampling
patterns.
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Contemporary Research ▶ 373
Statistical- learning approaches have directed researchers’ attention
to the nature of the information to which children are exposed, for
example, language input. In one study, an analysis of the words in books
parents commonly read to children showed that this language input had
more variation than that of parents’ conversations with their children
(Montag, Jones, & Smith, 2015). This is important because variety in
language input facilitates language development.
Bayesian and statistical learning approaches show that children possess
powerful learning skills that help them go well beyond the information
given. These approaches are particularly promising for suggesting how
automatic processing in infants could partially account for their seem-
ingly precocious cognitive skills described in the chapter on Piaget, as
well as their ability to acquire language early and quickly.
Developmental Robotics
A final topic of current interest is developmental robotics— the design of
autonomous machines that acquire cognitive and behavioral skills through
experience (Cangelosi & Schlesinger, 2015). The idea is to develop
flexible and adaptive robotic intelligence. The initial architecture, plus
exploration of the world and interacting with other people, propels the
robot toward greater complexity. The focus of developmental robot-
ics on broad skills contrasts with earlier artificial intelligence systems,
which were specialized for a particular task, such as chess. These earlier
systems had most of the knowledge they needed built in, so they under-
went little or no learning. Today, robots are being designed with devel-
opmental principles and findings in mind. The approach is similar
to computational modeling, except that the product is an embodied
learner, in three- dimensional form, that interacts with the environ-
ment, rather than a more abstract learner in a computerized simulation.
This modeling can be a tool to test developmental theories or provide
insights about development, especially mechanisms of development,
including how motor behavior shapes learning and development, and
vice versa. Robots, though programmed by a computer, can take many
forms: humanoid, wheeled cart or vacuum cleaner, a machine arm, or
even doglike or insectlike shapes (Cangelosi & Schlesinger, 2015). For
example, iCub approximates the size and shape of a 3- year- old child
(Parmigiani et al., 2012). One line of research even involves language
learning between two robots— a tutor and a learner (Spranger, 2015).
An interesting application has been to develop social- assistive robots for
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374 ▶ INFORMATION-PROCESSING THEORY
children with autism spectrum disorders or Down syndrome, or hospi-
talized children (Cangelosi & Schlesinger, 2015).
Thus, contemporary research from an information- processing per-
spective continues to address longstanding topics such as memory and
problem solving, but with new energy from executive function research.
In addition, research is expanding into a variety of new and exciting
areas.
SUMMARY
The information- processing approach studies how human information
detection and manipulation systems work. Investigators take the com-
puter program as a model— either as a metaphoric heuristic device or
as a way of simulating and testing their views concerning the nature of
human thought. Children change developmentally in how they attend
to, represent, store, weight, and combine information in order to reach
their goals despite their limited processing capacity. These changes
occur at various points in the system, for example, in working mem-
ory and long- term memory in some models. Much of development
occurs via self- modification, as children formulate rules of decision-
making and modify them as a result of feedback, or detect regularities
of co- occurrence in the environment. Investigators often begin by per-
forming a task analysis. They then either formulate a computer program
simulating how children learn, solve a problem, or store information, or
test the efficiency of the child’s processing by conducting experiments.
Humans are limited in how much information they can process at a
given time and in how fast they can process this information. Much of
development involves learning how to overcome these limitations by
acquiring strategies and developing executive functions. Research on
memory, the most studied area of information- processing development,
shows that much of memory development is caused by the acquisition
of strategies, the growing store of domain- specific knowledge, increased
metamemory, greater functional capacity, and social- cultural influences.
There are many levels of influence on memory development. Brain
development, practice, exploration, and culture all play some role.
The discovery and selection of various strategies alters the process-
ing of information. There is turning out to be more variability, and less
consistency, in children’s strategies and performance than once thought.
Social influences appear to be quite important. Children develop a
series of rules for problem solving and acquire new information that
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Suggested Readings ▶ 375
can be expressed in production systems simulations. Connectionist
models propose simple principles of learning through the strengthening
and weakening of associations in a network. These transparent, precise
accounts of development test hypotheses about developmental change
and sometimes produce unexpected new findings and new hypotheses.
Mechanisms of development such as encoding, generalization, strat-
egy construction, automaticity, and brain maturation cause more
efficient processing. Information- processing theorists view humans as
active, organized, self- modifying systems. Development involves both
quantitative and qualitative change and both genetic and environmental
influences. The essence of development is an increasingly efficient sys-
tem for controlling the flow of information.
The theory has been applied mainly to educational settings and to
issues concerning the reliability of young children’s eyewitness testi-
mony. The strengths of the theory are its ability to express the complex-
ity of thought, its precise analysis of performance and change, and its
rigorous methodology. Weaknesses involve certain shortcomings of the
models and metaphors, problems with addressing certain developmental
issues, and a neglect of the context of behavior. Contemporary research
areas include executive functions, developmental cognitive neurosci-
ence, embodied cognition, Bayesian computational models (including
statistical learning), and developmental robotics.
SUGGESTED READINGS
Bauer, P. J., & Fivush, R. (Eds.). (2014). The Wiley handbook on the devel-
opment of children’s memory. West Sussex, UK: Wiley- Blackwell. This
two- volume set covers numerous aspects of memory development.
Brown, D. A., & Lamb, M. E. (2015). Can children be useful witnesses?
It depends how they are questioned. Child Development Perspectives, 9(4),
250–255.
Cangelosi, A., & Schlesinger, M. (2015). Developmental robotics: From
babies to robots. Cambridge, MA: MIT Press.
Yermolayeva, Y., & Rakison, D. H. (2014). Connectionist modeling
of developmental changes in infancy: Approaches, challenges, and
contributions. Psychological Bulletin, 140(1), 224–255. This article pro-
vides further detail on connectionist models of development.
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Gibson’s Ecological Theory of
Perceptual Development
We tested 36 infants ranging in age from 6 months to 14 months on the visual
cliff. Each child was placed upon the center board, and his mother called him to
her from the cliff side and the shallow side successively. All of the 27 infants who
moved off the board crawled out on the shallow side at least once; only three of
them crept off the brink onto the glass suspended above the pattern on the floor.
Many of the infants crawled away from the mother when she called to them from
the cliff side; others cried when she stood there, because they could not come to her
without crossing an apparent chasm. The experiment thus demonstrated that most
human infants can discriminate depth as soon as they can crawl.
—Gibson & Walk, 1960, p. 64
On uphill trials [on slopes in a laboratory] infants often attempted hills where
they were likely to fall, despite falling on previous trials and in previous sessions.
Crawlers usually struggled at the base of impossibly steep slopes for the entire
duration of the trial, sometimes getting partway up, then sliding back down. After
lengthy frustrated attempts, they tried equally hard moments later at the next
impossibly steep slope. Walkers usually adopted a similar strategy, getting a run-
ning headstart on two feet and flinging themselves at impossibly steep inclines.
Sometimes persistence paid off and infants eventually reached the summit.
—adolph & EpplEr, 1999, p. 40
Se
rg
ey
N
iv
en
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te
rs
to
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C H A P T E R 8
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378 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
C
hildhood is a time of perceptual discovery. Children look at and
explore the wondrous objects, events, and surfaces in the envi-
ronment occupied by the human species and thus learn what
they can do in the world. They perceive faces to smile at, hills
to climb, approaching objects to avoid, words to respond to, seashells
to play with, and flowers to sniff. Although such discovery is exciting
in itself, it also permits adaptation to this environment. Children are
information “hunters and gatherers,” trying to survive in an information-
heavy world. Eleanor Gibson’s focus on the importance of perception
for adaptation is a companion piece to the account of ethology and
evolution in Chapter 5. Gibson took on a question largely ignored by
other theorists we have met: How do we learn about our world through
perception? Surely this is a basic task of development. Gibson’s answer
to this question is that, by moving around, children detect information
that specifies objects, events, and layouts in the world that they can use
for their daily activities. They “perceive what is going on around them
so as to make good use of what the world offers” (Gibson, 1997, p. 42).
The organization of this chapter is as follows: First is a biographi-
cal sketch, followed by a general orientation to the theory, and then
a description of infant perceptual learning. A section on mechanisms
of development is followed by the theory’s position on developmen-
tal issues, applications of the theory, an evaluation, and contemporary
research.
Biographical Sketch
Eleanor J. Gibson’s (1910–2002) studies in psychology began when she
was a student at Smith College. There she met and married a young
faculty member, James Gibson, who also was to become an eminent
psychologist. After earning her master’s degree with a thesis on learn-
ing, she became an instructor at Smith and attended the Gestaltist
Kurt Koffka’s lectures regularly. Gibson moved on to Yale, hoping to
study animal behavior; instead she ended up studying people. At Yale,
she obtained a Ph.D. under Clark Hull, the eminent learning theorist.
Gibson, however, did not feel intellectually comfortable in the stimulus–
response learning climate of Yale. Her husband’s relocation for military
service during World War II temporarily interrupted her career. When
the Gibsons went to Cornell University, Eleanor became an unpaid
research associate for 16 years (due to nepotism rules). The Gibsons
spent their careers developing an ecological approach to perception—
the relation of an organism to its surroundings.
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General Orientation to the Theory c 379
Gibson’s early work in the 1950s and 1960s developed the new fields
of perceptual learning and perceptual development. At Cornell she
studied goats and sheep at the “Behavior Farm.” One study, on maternal–
infant bonding in goats, was never completed because the baby goats’
caretaker gave away some of them (Caudle, 2003). Gibson then stud-
ied babies’ depth perception on “visual cliffs” and children in reading-
related situations in the laboratory. She became a professor at Cornell in
1966. Her book Principles of Perceptual Learning and Development (1969),
which won the Century psychology prize, was hailed as one of the most
influential books on development at that time (Hartup & Yonas, 1971).
Her theory provided an alternative to learning theory and Piagetian
approaches. Years after her “retirement,” she continued to contribute to
the field through her research and writing (e.g., Gibson & Pick, 2000).
She received many top research awards from the main professional orga-
nizations and was awarded the National Medal of Science— the nation’s
highest scientific honor. She also was elected to the National Academy of
Sciences, the American Academy of Arts and Sciences, and the National
Academy of Education.
General Orientation to the Theory
Gibson’s theory concerns perception, broadly defined. The developmen-
tal mystery she wanted to solve is how infants and children learn to per-
ceive and make use of objects, events, and surfaces given the complex,
constantly changing array of stimulation in which they are immersed.
She asked four questions: What do infants and children perceive? How
do they pick up this information? What actions or interactions take
place? What are the consequences for knowledge? (Gibson & Pick,
2000) This section examines characteristics of the theory that show how
Gibson addressed these questions: the ecological approach, the notion
that information for perception is specified in stimulation, the active
nature of human perceivers, and ecological methods.
Ecological Approach: Affordances
Like ethologists’ focus on the functions of behaviors, Gibson wanted to
find out the uses of perception in our daily lives. People need to perceive
objects, spatial layouts such as floors or the ground, and temporal events
such as approaching objects in order to adapt to the world: to walk
around in it, find things in it, play in it, and even survive in it. These stim-
uli are complex relational units, not simple sensations of light or sound.
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380 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
Unlike most theories of perception, Gibson’s theory stressed what per-
ceivers do in natural environments. Gibson’s research and theorizing
centered on affordances. Affordances are what an environment offers or
provides for an organism; they are opportunities for action. Humans’
environments “afford” surfaces of support for walking or crawling,
objects for grasping, passageways allowing movement, and barriers pre-
venting movement. Even the social environment offers affordances, for
example, a smiling or angry face affords positive or negative interactions.
Thus, the person and the environment fit together to form a whole, with
a meshing of the person’s activities and the environment’s affordances.
The utility of a property of the environment depends on the capacities
of the organism. If an infant cannot yet walk, a solid surface does not
afford “walking on.” Affordances thus involve a relationship between the
organism and its surroundings. Gibson claimed that these affordances
are perceived directly: “We do not perceive stimuli or retinal images or
sensations or even just things; what we perceive are things that we can
eat, or write with, or sit down on, or talk to” (1982, p. 60).
As children acquire new motor skills during development, they
discover new affordances. Once infants can sit up, this sets in motion
a cascade of advances: Sitters do more visual– manual exploring while
looking at objects than do nonsitters, which then leads to improved 3-D
perception of objects (Soska, Adolph, & Johnson, 2010). When children
learn to walk, they learn to perceive whether a surface affords solid
support for walking. They look at, feel, and pat an unfamiliar surface
to get information about how solid and stable it is. This affordance is
irrelevant for, and unknown to, a younger infant. In one experiment
illustrating this point (Gibson et al., 1987), infants were placed on a
walkway raised 4 feet from the floor. Their smiling mothers stood 6 feet
away at the other end of the walkway. The walkway for one condition
was a rigid surface (strong plywood covered with a patterned fabric),
which affords locomotion for both crawling and walking. In the other
condition, the walkway was a patterned fabric on a water bed, which
affords crawling but not walking. The infants who could walk looked at
and felt the ambiguous water bed surface more than the rigid surface
before they either walked on the rigid surface or crawled onto the water
bed. Because they already had experience with walking on rigid surfaces,
they knew that such surfaces afford walking, but they were not sure
about the water bed surface. The infants who could only crawl showed
little, if any, differentiation of the two surfaces; they readily moved onto
both of them because both were perceived as affording crawling. Thus,
infants’ locomotion abilities affect what surfaces they perceive to be safe
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General Orientation to the Theory c 381
for crossing. There is a fit between what the environment provides and
the child’s actions, goals, and abilities.
Infants’ bodies are constantly increasing in size and in the distribu-
tion of weight and, thus, in their biomechanics. Indeed, babies grow
by as much as 1.8 centimeters in length per day (Lampl, 1993). Babies
show flexible learning as they constantly adapt their changing bodies in
an environment with changing affordances— new action possibilities:
“Whereas a robot can be programmed to assume a particular body
and environment, babies cannot because yesterday’s body or environ-
ment may no longer hold true today” (Adolph & Robinson, 2015).
Fast- growing adolescents and pregnant women face a similar situation.
Women in the late months of pregnancy constantly update their percep-
tion of affordances, given their enlarging body, and thus can accurately
judge whether they can go through passageways that they could formerly
(Franchak & Adolph, 2014). Note that in learning about affordances,
infants and adults learn about themselves— their own bodies— as well.
Humans have evolved species- specific ways of perceiving the world
and learning perceptually. Children’s evolutionary heritage provides the
perceptual equipment to perceive— or learn to perceive— the affor-
dances of the particular objects, events, and spatial layouts that charac-
terize human settings. We also have hands to detect whether a perceived
object can be grasped and manipulated. Similarly, bats are pretuned to
use acoustic information (interpreting feedback from sounds) to help
them navigate in dark caves. The environment affords food, mates, and
places to hide from predators. By exploring and playing, children learn
the affordances of objects, events, and surfaces.
The fact that experience creates new affordances explains individual
differences in the ability to use potential affordances: “A three- inch- wide
beam affords performing backflips for a gymnast, but the affordance is
not realizable by others; rock climbers learn to use certain terrains for
support that do not appear to others to provide a surface of support”
(Gibson & Pick, 2000, p. 17).
Information Is Specified in Stimulation
To begin to understand Gibson’s answer to her first question, about
what is perceived, one must understand her conception of the role of
stimulation in perception. Her description of the active, self- motivated
child exploring the stimulus world at first seems quite similar to Piaget’s
view of children. The theorists part, however, in their conceptions of
how children “know” the world through activity. Piagetian children
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382 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
“construct” their knowledge by forming mental schemes based on
their motor behaviors with objects. Because perception produces static
images, it must be corrected by operational knowledge. Similarly, other
cognitive and perceptual approaches see perception as an act of enrich-
ing, with knowledge, a sparse, ambiguous, uninformative retinal image.
For instance, information- processing approaches describe processes that
add meaning to the stimulus by relating it to memories and knowledge
in the long- term store. They refer to going beyond the information given
by making inferences based on knowledge of the world.
In contrast, Gibson believed that stimulation is a rich source of infor-
mation that specifies objects, events, and surfaces. The developmental
issue, then, is how children learn to extract more and more information
from that stimulation. As children perceive, they differentiate informa-
tion, rather than add to it. Her claim that complex information, includ-
ing structure, is inherent in stimulation is controversial. It is important,
therefore, that we consider this claim carefully.
When we move, the visual stimulation around us appears to be in
motion as well, though typically we do not notice that movement. What
we have to do is extract patterns, or structure, in the flux of moving
stimulation that specifies events, places, and objects. If children can
extract this information, they perceive events, places, and objects and
understand how the affordances fit with their abilities. They do not per-
ceive a single, discrete “stimulus,” such as an object: “There is no shutter
on the retina, no such thing as a static image” (1988, p. 5). In other
words, stimulation is a field of available information about affordances
to be differentiated, and perception is a process of information pickup
that happens over time.
Stimulation carries many levels of information. At the simplest and
most concrete level, a child tells objects apart by one or several distinc-
tive features— critical features that can be used to discriminate between
objects. Suppose a boy moves near an ocean and for the first time in his
life encounters hundreds of shells. He begins a collection and attempts
to identify the shells with the help of a field guide with photographs.
Although he is perceptually capable of telling all of the shells apart if he
places them side by side, he actually notices only a few distinctive fea-
tures at first, perhaps only salient differences in color, shape, and size.
Only after much playing with the shells and comparing them with each
other and with the pictures in the book does he realize that the stimulus
class “shells” has a particular set of distinctive features that allows him
to determine the appropriate label for each shell. Although size is a
salient feature, it seldom is important for differentiating types of shells.
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General Orientation to the Theory c 383
In contrast, slight differences in the shape of the crown at one end of
the shell or subtle differences in the colored pattern on the shell are
quite important. Although this information was in the light stimulating
the boy’s eyes from the start, he did not really notice it or abstract it
as a defining feature until he had more perceptual experience with the
shells.
As another example, imagine that a practical joker mixed up the con-
tainer labels on the entire stock of ice cream in a 48-flavor ice cream
store. An efficient way to tell the flavors apart and group together iden-
tical flavors would be to pick out the minimal set of distinctive features
that distinguish the types of ice cream. The set might include the follow-
ing: color, nuts versus no nuts, sherbet versus nonsherbet, flavor ( fruit-
based, chocolate- based, or other), and smooth versus textured. Faces are
another group of objects that can be differentiated by distinctive features.
Cartoonists take advantage of striking facial characteristics by exaggerating
them in caricatures. A toothy grin or large nose can bring instant recog-
nition. Gibson showed that attending to the distinctive features of letters
is part of the process of learning to read (Gibson, Gibson, Pick, & Osser,
1962). Orientation (M versus W) and curved versus straight (D versus O)
are distinctive features, whereas size and color are not.
A second level of information in an optic array involves invariants—
relations that remain constant over change. Children extract what is
permanent about objects despite changes in their appearance as the
objects move toward or away from them. It is clearly more economical
to perceive a single, constant mother of a particular size and shape than
a succession of different mothers that expand and shrink as their distance
changes. In one study (Gibson, Owsley, & Johnston, 1978), Gibson
asked whether 5- month- olds could extract the invariant property of
rigidity (lack of malleability) when an apparently rigid object underwent
various kinds of movements. Babies saw a round, disklike piece of foam
rubber move in three ways, for example, rotation in the frontal plane,
rotation around the vertical axis, and movement toward or away from
them. They watched these rigid movements in succession until they
habituated, that is, stopped looking at the object. Then they saw, in suc-
cession, a fourth rigid motion, perhaps rotation around the horizontal
axis, and then a nonrigid, elastic motion (an experimenter continually
squeezed and released the spongy disk). The infants showed little interest
in the new rigid motion but much interest in the nonrigid motion. This
attention to the novel property of nonrigidity indicates that the infants
had extracted the invariant property of rigidity from the stimulus flux of
the earlier three movements.
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384 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
Children can extract a third, larger unit— perceptual structure. For
example, we abstract a melody from a succession of notes. We recognize
this melody as the same melody even if it is transposed to a different
key or played at a different tempo or on a saxophone instead of a piano.
When we hear a new orchestral work, we have a relatively undifferenti-
ated perception of the work after the first hearing. Only after listening
to the work several times are we able to extract melodies and their
transformations and grasp the overall structure of the piece. For most
people raised in the West, this task is more difficult with Eastern music
or modern compositions using the 12-tone scale, which are less familiar,
than with the first hearing of yet another Haydn symphony. In this musi-
cal example, stimulation has remained the same throughout the repeated
hearing. What has changed is what information we have extracted. The
pattern is there in stimulation, but we may not have perceived it at first.
Our perception became both more specific, as we became aware of subtle
musical qualities, and more abstract, as we perceived musical patterns.
Thus, Gibson noted that her theory might be called a “seek and ye shall
find” theory (1977, p. 157). Our perception improves not by filling in
the raw auditory stimulus by adding words or applying schemes, not by
cognitively gluing together the notes, but by listening to the music and
directing our attention.
Humans as Active Perceivers
Perception does not just happen to a passive perceiver, like a patron waiting for the
server to arrive with a meal. Instead, we do things to make perception happen; we
sample and select from a buffet of potential information. Perception does not occur
only in the brain; it is a whole body activity.
—adolph & robinson, 2015, p. 131
No parent would be surprised by the claim that children seem to be
constantly in motion. Parents might, however, be surprised by the claim
that this motion is essential to perceptual development, even in infancy.
Children are active organisms that explore in order to learn about the
world. They actively extract affordances and use them to discover new
affordances. For example, children may perceive the affordances of var-
ious types of balls by kicking them, rolling them, and trying to bounce
them. Then, by using them in a game for which they are suited, children
discover new affordances, such as passing the ball to teammates.
During development, children gain control over their bodies and
expand their exploratory potential. They work hard to use each new
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General Orientation to the Theory c 385
postural achievement to attend in new ways. Young infants struggle to
hold their head and shoulders upright when carried so that they can
look about. Later, trying to sit without support while attending to and
slapping at a toy requires constant work to maintain balance. Still later,
infants just learning to stand suddenly fall to a sitting position when they
let go of a chair to attend to and pick up a block on the seat. Children
gain more control over their attention, and it becomes more efficient.
They can, for example, more efficiently compare two objects by looking
systematically back and forth between them.
Humans, as a species, are inherently motivated to explore and learn
about their world. There are, however, goals and needs specific to each
task or situation. A girl putting together a puzzle attends to shape and color
because these attributes are information she needs to achieve her goal of
completing the puzzle. A baby learning to walk must be very attentive
to the position of her body in space and the distance between furniture.
Young soccer players seek a different sort of information. They continu-
ally search for and track the ball, perceive the spatial relationship between
other players and the ball, and use feedback concerning their attempts to
kick the ball (falling down, kicking erratically, and so on). Adult mountain
climbers are more attentive to where they place each step than are people
taking a leisurely walk (Gibson & Rader, 1979). In these examples, there
is a relationship— ideally, a match— between the person’s goals and the
information actively extracted from the environment.
Methodology
Although Gibson’s research, as well as other research stimulated by her
theory, followed the experimental procedures of other areas of develop-
mental psychology, it was unusual in one way. It tried to retain ecological
validity in the experimental setting. This does not mean that Gibsonians
necessarily observe perceptual activities in their natural settings. It does
mean that they attempt to simulate (mimic important features of) the
stimulation, tasks, and goals of the child’s natural environment in the
experimental setting: Multimodal stimulation (for example, faces that
move and make sounds and objects that can be touched), various kinds of
environmental supports for locomotion (for example, solid or nonsolid
surfaces), and opportunities for obtaining feedback from exploratory
activities (and thus detecting contingencies). This shows the close con-
nection between theory and methods— both stress the ecology.
Early on, Gibson had puzzled over why a newborn goat, when placed
on a small, high stand to get it out of the way while its twin was being
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386 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
delivered, knew to stand motionless on this high surface (Caudle, 2003).
In a clever experiment to test infants’ depth perception, Gibson, along
with Walk (1960), constructed a “visual cliff ” to simulate a cliff or drop-
off in the real world. Gibson also was inspired to create this miniature
Grand Canyon after visiting the real Grand Canyon with her young
children and pondering, with some concern, their ability to perceive
it as a drop- off. The visual cliff is a table with a glass top that looks like
a solid surface on one- half of the table; on the other half of the table,
the floor is visible through the glass. Thus, the apparatus displays infor-
mation specifying a drop- off. Some of the results were described at the
beginning of this chapter. Infants who can crawl stay on the “cliff ” half,
refusing to crawl onto the half of the glass that hangs over the appar-
ent “thin air.” The visual- cliff experiments demonstrated that crawling
infants perceive depth at an edge at least as early as 6 or 7 months. Later
research using heart rate indicated that even younger infants differenti-
ate the cliff and noncliff sides (Campos, Langer, & Krowitz, 1970). One
method to examine the role of experience is to train perceptual- motor
behavior to see whether performance on the cliff improves. In one such
study (Dahl et al., 2013), pre- crawling infants received several weeks of
experience sitting in a motored cart and controlling its movements with
a joy stick. They then showed earlier cliff avoidance than infants with no
cart practice.
More recently, Adolph has developed ecologically based variations of
the visual cliff that are adjustable, to permit various degrees of cliffs, gaps
to reach over, and slopes (see Figure 8.1 for an example, the excerpt at
the start of this chapter, and Adolph & Robinson, 2015, for a review).
After testing novice and experienced independent sitters, crawlers, and
walkers, Adolph concluded that whether babies are willing to enter
onto risky surfaces depends on whether they have yet grasped the affor-
dances of the mode of mobility they choose. That is, infants do not have
a general fear or wariness of heights. Rather, affordances are driving the
behavior; experience in each new mode of mobility is needed to learn
about affordances for that mode.
Recent technological advances, especially head- mounted eye trackers,
have made it possible to determine what infants and children actually look
at as they move around naturally. By using this device, it was possible to
learn, for example, that crawling and walking infants have very different
views of the world, mainly the floor versus other people near and far
(Kretch, Franchak, & Adolph, 2014). Eye trackers also provide detailed
descriptions of visual exploration of objects. For instance, when viewing
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What Infants Learn About c 387
images of animals, 4- month- olds with experience with pets tended to
look at the most informative part of animals— their heads— compared
to infants with no pet experience (Hurley & Oakes, 2015).
What Infants Learn About
Locomotion is one of infants’ greatest achievements. Infants conquer grav-
ity, propel themselves through space, and stay balanced despite encounter-
ing novel and variable surfaces. As infants move from crawling to standing
to cruising to walking to running (mostly running, it seems to parents),
and learn to control these postures, they learn to use information about
objects, events, and layouts to exploit their affordances. We look at some
important developments during infancy in three areas: communication,
interaction with objects, and locomotion in the spatial layout.
Communication
The ecology of the human infant includes other people. Even before
babies utter their first word or manipulate objects, they begin learning
to participate in the social world. Newborns recognize, and prefer,
their mother’s voice and face, recognize the overall pattern of people’s
speech, and discriminate between a foreign language and their own.
Young babies learn the affordances of other people’s facial expressions,
gestures, vocalizations, and actions and learn to respond to them. For
example, they can detect the emotional states of other people— an
angry facial expression affords bad events, a happy one affords positive
events. Babies thus come to anticipate the behaviors of others and to
respond to them. Primitive nonlinguistic “conversations” are possible,
for infants learn about turn taking and see themselves as able to control
their interactions with others. Babies learn that they are agents with
particular physical abilities and intentions. Eventually, babies and their
parents engage in joint visual attention as they look at and talk about
an object or event together. All of this is a perfect context for learning
about language and social relationships. The following studies give a fla-
vor of how perception relates to communication.
Infants detect correspondences between faces and voices. For example,
9- month- olds looked longer at a female face when it was accompanied
by a female singing voice than when it was accompanied by a male sing-
ing voice (Hillairet de Boisferon et al., 2015). In another experiment,
using a videotape of a face in the dark with small lights attached, Soken
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388 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
and Pick (1992) showed 7- month- olds patterns of moving lights speci-
fying happy or angry faces. When infants heard a soundtrack of a happy
or angry woman, they looked at the appropriate face, even though they
could see no details of the face. As a final example, infants use infor-
mation from their mothers’ faces to avoid dangerous situations when
perceptual information is inadequate. When trying to decide whether to
walk down a slope that they are not sure is safe, 18- month- olds follow
their mothers’ encouraging or discouraging words, gestures, and facial
expressions ( Tamis- LeMonda et al., 2008). However, perception trumps
maternal wisdom: They ignore encouraging advice to walk down risky
slopes and discouraging advice to avoid safe slopes.
Interaction with Objects
Infants make use of whatever motor abilities they currently have to
explore their environment. Even very young infants, by moving their
head and eyes, can scan the visual layout and discover rudimentary prop-
erties of objects and layouts. Later, they can reach for and manipulate
objects, thus learning about the properties of objects and their affor-
dances. Consider, for example, a baby lying in her crib and gazing at her
stuffed bear on a nearby shelf. She sees a single, solid, three- dimensional
object separate from the shelf and from the other toys on the shelf.
When her mother bends over the crib and occludes some of the bear,
the baby does not think that her mother has bisected the bear. If the bear
falls off the shelf, she expects that all parts will fall together but that the
shelf and wall will not also fall. If the bear falls toward her, she does not
think that it is becoming larger or that it is changing shape as its angle
changes. And, finally, she knows that the falling bear may make contact
with her face and most certainly will afford cuddling and chewing.
Infants’ early perception of the separateness of objects was demon-
strated in the following study (Needham & Baillargeon, 1998): Babies
at 4½ months of age saw either a cylinder or a tall blue box for several
seconds. Then they saw both objects next to each other and watched as a
hand appeared and pulled the cylinder. In one case, the hand pulled the
cylinder away from the box, and in the other case, the cylinder drew the
box with it. Babies looked longer when the objects moved together, an
outcome that in infant research is taken to mean that the babies were
surprised at this improbable event. The inference is that they had per-
ceived the objects as separate. Remarkably, the results were the same
when a 24-hour delay separated the presentation of one object and both
objects. This outcome indicates that a very brief visual experience with
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What Infants Learn About c 389
a single object served to segregate it from an adjacent object, even at a
later time. This experiment also serves as an example of the clever meth-
ods that have been constructed to assess early competencies. Similar
experiments document infants’ perception of number, solidity, size and
shape constancy, substance, and texture.
One startling perceptual skill concerns babies’ detection of the unity
of objects and events. For example, 4- month- old infants perceive a long
stick protruding on either side of a rectangular object as a single, unbro-
ken, partially occluded stick, rather than two short sticks separated by
an object, which is literally what they see. However, they perceive this
unity only if they see the stick move back and forth or in depth rather
than remain stationary (Kellman & Spelke, 1983). Thus, as Gibson pro-
posed, action— of the object, the infant, or both— is essential for accu-
rate perception. One of the most striking demonstrations of perceived
object unity is the perception of a living object in motion. Fox and
McDaniel (1982) presented a biological- motion light pattern— a video-
tape of 10 lights mounted on the joints of the arms, legs, and hips of a
figure running in the dark. Another display included the same number
of lights, but their movement was random. Infants ages 4 and 6 months
tended to look at the running pattern, which indicates both their ability
to differentiate an object in biological motion from a random array and
their preference for viewing a pattern of moving lights organized into a
unitary object.
Different kinds of objects have different kinds of motion paths. Babies
use this motion cue to differentiate animate and inanimate objects. In
one study (Baker, Pettigrew, & Poulin- Dubois, 2014), babies first were
habituated to two events on a computer screen. One event was a dog
jumping over a barrier— an appropriate pattern of non- linear motion
for an animate object, such as a dog, but not for an inanimate object. The
other event was a car (an inanimate object) hitting and rebounding off
the barrier— linear movement appropriate for both animate and non-
animate objects. Subsequently, infants looked longer when a different
inanimate object, a bus, jumped over the barrier like the dog had (a sur-
prising motion pattern for an inanimate object) rather than rebounded
like the car. Infants did not show this differential looking when a differ-
ent animate object, a cat, jumped over the barrier or hit and rebounded
off the barrier, because animate objects can follow either motion path.
Thus, by 10 months of age, babies connect certain categories of objects
with certain types of movement.
Babies show multimodal object perception. Specifically, they extract
the properties of various modalities, such as visual and tactual properties,
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390 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
that go together. For example, infants can tactually recognize an object
that they had previously only seen (Streri & Pecheux, 1986). Moreover,
even newborns look at a speaker whose mouth movements match the
specific sounds they hear rather than the speaker making other sounds
(Aldridge, Braga, Walton, & Bower, 1999).
Finally, infants are even sensitive to the sight– sound correspondences
of musical events by 7 to 9 months (Pick, Gross, Heinrichs, Love, &
Palmer, 1994). Infants heard a soundtrack in synchrony with two displays
but specific to only one of the instruments. They appropriately looked at,
for example, the musician playing a cello rather than a clarinet and the
one playing a trumpet rather than a flute. Thus, experience with various
instruments apparently is not necessary for detecting sound– sight cor-
respondences and for differentiating instruments from different families.
Locomotion in the Spatial Layout
As infants learn to roll, creep, crawl, and walk their way around their
environments, their attention expands to larger arrays. As J. J. Gibson
commented, “The surface is where most of the action is” (1979, p. 127).
Infants’ perceptions of the layout guides their locomotion around obsta-
cles, through openings, and onto safe, solid surfaces. A toddler crossing
a room needs a great deal of affordance information in order to crawl
under a table, over rather than around a blanket on the floor, and around
rather than over the dog. She constantly has to make decisions. Objects’
affordance of being carried seems to fascinate toddlers, who often
delight in carrying objects from one place to another. Gibson (1988)
noted that this affordance apparently takes a while to be learned com-
pletely, for toddlers sometimes try to carry a toy or piece of furniture
almost as large as themselves.
Children must constantly tailor their locomotion both to the prop-
erties of the terrain and to their own developing abilities. In order to
crawl or walk, infants need to find surfaces that afford crawling or walk-
ing. Infants’ ability to extract affordances for crawling or walking were
shown in studies of the visual cliff and other risky surfaces, such as steep
slopes, described earlier.
When infants first acquire a new locomotion skill, they seem obliv-
ious to its limitations. An example is Adolph’s (1997) longitudinal
study of infants encountering upward and downward slopes of various
steepness— angles ranging from 0 to 36 degrees (see Figure 8.1). Infants
had to decide whether they had the capability to climb or descend in
this potentially (though not really) dangerous situation to reach a parent
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What Infants Learn About c 391
at the receiving end offering a Cheerio. At first, crawlers showed little
caution and often just plunged ahead, even on the steepest slopes, and
had to be rescued again and again (see the excerpt at the beginning of
this chapter). Over weeks, as the infants’ crawling expertise increased,
their judgments of affordances improved. The infants tried out a variety
of strategies. They sometimes tried various means of traversal down
the slope by testing different sliding positions while still on the starting
platform. They sat and hung their legs over the slope or changed into a
backing position and looked over their shoulders down the slope. The
babies eventually crawled on the safe slopes and refused to crawl on the
riskier ones. Interestingly, later when they began to walk, they again
judged poorly, but they again improved with experience. Thus, with
each new postural advance, the infants had to relearn information about
affordances relevant to their new ability. The better perceivers more
effectively explored the slopes by looking, feeling, and trying out various
positions, such as backing down or sliding. The fact that a control group
without repeated experience with the slopes in the experiment exhib-
ited the same pattern shows that specific learning on those particular
F I G U R E 8 . 1
Adolph’s walkway with adjustable slope used to test infants’ judgments of whether to
descend slopes that vary in steepness. The experimenter followed alongside to ensure the
infants’ safety.
[“Learning in the Development of Infant Locomotion,” by Karen Adolph, in Monographs of the Society for
Research in Child Development, 1997, 62(3, Serial No. 251). Adapted by permission of the Society for Research
in Child Development.]
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392 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
slopes was not important. Rather, practice in maintaining posture and
noticing consequences during daily activities transferred to the labora-
tory situation.
Subsequent experiments also showed that experience with an earlier-
developing skill does not transfer automatically to a later- developing
one. For example, in a group of 12- month- olds, experienced crawlers
refused to crawl over risky drop- offs, but novice walkers stepped repeat-
edly into the drop- off (Kretch & Adolph, 2013). (Human “spotters”
make sure that the infants do not actually fall.) Experienced walkers
(18- month- olds), who now know the affordances of walking, would not
step off (though did figure out other ways to get down into the lower
surface). Thus, perceptual learning is surprisingly specific to a particular
postural control system.
Social- cultural factors can influence the development of locomotion.
For example, several cultures in Africa, the Caribbean, and India try to
promote infant locomotion by strengthening infants’ legs and improving
their upright balance with massage and special standing and stepping exer-
cises (Adolph, Karasik, & Tamis- LeMonda, 2010). In the United States,
when parents are asked to adjust a ramp to create the steepest slopes they
will allow their infants to crawl down independently, fathers are more
likely than mothers to provide challenges for their toddlers by letting them
try slopes beyond their ability (Ishak, Tamis- LeMonda, & Adolph, 2007).
Mechanisms of Development
The sections thus far have described a number of processes for bringing
about development. Efficient exploratory activities lead to the economi-
cal extraction of information specifying affordances. For a 7- month- old,
“fingering explores texture, hand- to- hand transfer and rotation explore
shape, and squeezing and banging explore substance” (Gibson & Pick,
2000, p. 150). Children move their eyes to the television, turn their
head toward the sound of a distant call, move their hands over sap drip-
ping down a tree, sniff when dinner is being prepared, and cautiously
roll a brussels sprout over their tongue. Consequently, children detect
features, relations, and higher- order structure that specify affordances
of objects, events, and layouts. Children also filter out irrelevant infor-
mation, as in the “ cocktail- party phenomenon” (or “ birthday- party
phenomenon” in children), in which all background noise is filtered out
in order to hear a single voice. Maturation permits new postures and
motor skills that lead to new affordances.
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Posit ion on Developmental Issues c 393
Position on Developmental Issues
Human Nature
Gibson’s view of human nature is much like Piaget’s. In these organismic
views, people are inherently motivated creatures who actively explore
and try to extract sense from their world. Ideally, this is an organized
and efficient process in which the child’s needs and goals mesh with the
nature of the environment. In Gibson’s and Piaget’s views, the child has a
tremendous capacity to learn from experience and adapt to the environ-
ment. Both theorists describe complex organisms that are sensitive to
the complex structure of the environment. The theorists differ, however,
in the source of this structure. Gibson believed that in stimulation there
is structure, which specifies the information available to be perceived.
The child learns to detect this structure and the affordances of settings.
In contrast, Piaget believed that to a great extent the nature of the inter-
action between the child and the world constructs the structure.
Qualitative Versus Quantitative Development
Just as perception in adults can gradually improve with practice, so
perception in children gradually improves as a result of experience.
Perceptual development is not stagelike and thus not mainly qualitative.
There may, however, be specific qualitative changes in the exploratory
strategies children use. For example, children’s systematic visual com-
parison of two objects may replace their earlier random looking at the
two objects. Qualitative change also occurs when the emergence of
crawling or walking causes the reorganization of the motor system and
a change in the set of affordances for that new skill.
Nature Versus Nurture
Gibson was interested primarily in describing and explaining how chil-
dren learn from experience and what they learn, especially affordances.
However, she thought that nurture and nature are inseparable. They do
not just interact; they fit together. What information children extract
from the environment depends on their evolved species- specific genetic
endowment in addition to their maturational level, immediate goals,
and unique set of learning experiences. Babies are innately equipped to
find out what the world is like and what it lets them do. Their growing
control over their bodies and their awareness of their bodies in space is a
big part of the story of perceptual learning and development.
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394 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
What Develops
Gibson identified four hallmarks of human behavior: agency, prospec-
tivity, the search for order in the world, and flexibility (Gibson & Pick,
2000). Agency is “the self in control, the quality of intentionality in behav-
ior” (p. 160). Even infants learn that their actions have effects on the
environment and that they can control their own behavior. Prospectivity
pertains to intentional, anticipatory, planful, future- oriented behaviors.
For example, infants open and then begin to close their hand when
reaching for an object, in preparation for grasping it. Based on perceived
affordances in the setting, children reach, anticipate outcomes, and
perceive where they are going in a room. The search for order involves
children’s tendencies to see order, regularity, and pattern and thus
make sense of the world. Earlier sections described invariants, higher-
order structure in stimulation, and economy of selecting information.
Finally, regarding flexibility, “perception adjusts to new situations and to
changing bodily conditions such as growth, improved motor skill, or a
sprained ankle” (Gibson & Pick, 2000, p. 169). Infants face the challenge
of a changing body in a variable world.
Applications
Gibson’s work on reading showed that perceptual learning about letters,
correspondences between letters and sounds, and the structure of sen-
tences is essential for learning to read. In addition, her theory suggests
that preschool teachers can provide interesting and varied objects and
surfaces and let young children learn perceptually by exploring that
world. Perceptual learning also is essential for children’s safety and
health. Being able to judge the slipperiness of surfaces and the lack of
support offered by a rickety bridge railing are essential for avoiding seri-
ous accidents. Studies of affordances can inform bicycle safety programs
for children. One study looked at how children on bicycles try to judge
gaps between cars when entering an intersection with continuous cross
traffic (Plumert & Kerney, 2014).
Evaluation of the Theory
Gibson’s theory is the most well- known theory of perceptual devel-
opment. It has inspired a great deal of creative research, especially
regarding infants’ early perceptual and motor competencies. The eval-
uation will focus on the potential of Gibson’s theory to guide not only
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Evaluation of the Theory c 395
perceptual research but also developmental research more generally and
to tie perception to other areas of development. The strengths of the
theory are its focus on the ecological context of perception and its put-
ting the body back into developmental psychology. The main weakness
is the unclear account of cognition.
Strengths
Focus on the Ecological Context of Perception c As Gibson com-
mented, “Only a few hardy perception psychologists still study percep-
tion of the real world rather than small displays on computer screens”
(1991, p. 607). Gibson asked how perception serves us in our daily lives
in a world of complex patterns, objects, and events rather than points
of light or brief, static stimuli. In James Gibson’s words, she worked on
“perception outdoors under the sky instead of perception of points in a
darkroom” (1979, p. xii). The perception of the affordances of natural
units is essential for adapting to the environment. This ecological ori-
entation has relevance for the current state of cognitive developmental
research. Like ethological theory, Gibson’s theory could enrich the
information- processing approach, for example, by directing it toward
(1) larger, more complex properties of the environment to be pro-
cessed, (2) events rather than static stimuli, and (3) affordances.
First, Gibson criticized the tendency of information- processing
researchers to break down the world into objects and properties of
objects such as color and shape. In Gibson’s words, “Such a concep-
tion requires them to invent ‘processing mechanisms’ to put the world
together” (1977, p. 156). In contrast, Gibsonians showed that even
young infants can detect structures, such as melodies, and complex and
meaningful properties of the world, such as pliability and traversability.
Second, information- processing approaches should take seriously
Gibson’s concern with the processing of events that occur over time:
a rapidly approaching object, a ball rolling across the floor, one object
striking another, liquid being poured out of a glass. This change in focus
would broaden our understanding of processing based on the typically
studied static stimuli, such as pictures, letters, objects, and written
words. Most real- life events involve the movement of one or several
objects or people— a complex set of information. Some of the social
information processing work does address more complex events, such
as a negative social interaction.
A third implication is that information- processing work should give
more attention to functions: How do children gather, and process,
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396 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
information about the functions of artifacts and natural objects and events
in the environment? What do they offer for humans? In fact, Gibson
suggested that affordances provide a natural organization for knowledge,
for example, a category of “things you can walk on.” Learning about the
affordances of events, objects, and surfaces may be a first step toward a
conceptual understanding of them.
Putting the Body Back into Developmental Psychology c Gibson
did not leave the child wrapped in thought (Pick, 1992): Children are
doing something in order to achieve some goal in a setting. Thus, she
was ahead of her time in her focus on the fit between the body and
what the setting offers— what might be called “embodied perception”
( Cañal- Bruland & van der Kamp, 2015). Embodied cognition, the influ-
ence of the body on cognition (see Chapter 7), may draw on embod-
ied perception— information from affordances learned while moving
around, exploring surroundings, and achieving some goal. When we
seek information about affordances, we do so because of our physi-
cal and psychological needs for moving toward resources, expressing
ourselves, interacting with others, obtaining objects to work on, and
so on. We explore to obtain information for a particular purpose. If
the goal is a social one, knowing the possibilities for action provided
by other people may contribute to the understanding of their mental
states, which impacts social interaction. If the goal is nonsocial, such as
determining the number of objects, knowing the separability and unity
of an object may contribute to an understanding of how to count. Our
affordance- gathering actions in a particular setting may pave the way
for a more abstract understanding of how to make our way around that
setting. In these ways, Gibsonian perceptual development can contribute
to an embodied cognitive development.
As another example of how Gibson’s focus on the role of the body
in perceptual development can inform work on other areas of develop-
ment, consider work on the development of the self. Gibson’s emphasis
on what children do contrasts with most theories’ focus on what chil-
dren know or what they are like. For example, developmentalists speak
of a “ self- concept,” which connotes a static something that the child
has, whereas Gibson speaks of self in terms of “agency,” which connotes
doing and action. Babies become aware of themselves as one object
among many and can link proprioceptive information from their own
body to a visual image of their body. Remarkably, Bahrick and Watson
(1985) found that 5- month- olds could discriminate between a live
video display of their own currently moving legs and that of another
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Contemporary Research c 397
identically dressed infant or their own legs videotaped at another time.
In the latter two displays, proprioceptive and visual information were
not synchronized. Moreover, infants can even tell when the video has
reversed their right and left legs! (Morgan & Rochat, 1997). Work on
the development of self would be enriched by a consideration of one’s
body, and what it can do, as well as one’s psychological characteristics.
Weaknesses
A weakness of Gibson’s theory is her unclear account of cognition.
Contemporary psychologists tend to make a distinction between per-
ception and cognition and then address how they interact. Gibson
probably was correct that this distinction is misguided; it is artificial to
try to separate the two. Still, her placement of many abilities that most
psychologists would label as cognitive under the rubric of perception is
puzzling to many in the field. The basic problem is that Gibson proposed
a theory of the direct perception of the environment but then included
some behaviors that seem to many psychologists to involve indirect,
interpretive cognition. For instance, Gibson’s examples of perceptual
learning included inferring emotions from a parent’s face, reading maps,
interpreting X- ray and aerial photographs, and identifying material
under a microscope. Others included detecting means– end relations,
perceiving causality, learning that events in the world can be contingent
on one’s own actions, and perceiving conservation as an invariance over
time and over an event sequence (Gibson, 1969, pp. 8–9, 388), which
sound very Piagetian. Furthermore, children are said to perceive affor-
dances such as swinging (on swings), warmth and light for reading (from
a fire), and hiding (behind a screen). These examples seem to involve
inference, categorization, and interpretation. In short, the distinction
between perception and cognition is blurred.
Contemporary Research
Research on one topic of current interest, infant perceptual learning,
was described in the section on that topic. The other main contem-
porary Gibsonian- inspired research examines infants’ perceptually
guided motor behaviors, asking intriguing questions such as “Why are
toddlers who are able to climb up a slope or stairs unable (or unwill-
ing) to climb back down?” and “Why does it take weeks of experience
with a new motor skill such as crawling or walking before it can guide
behavior adaptively?” “Why does an experienced crawler’s awareness
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398 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
of affordances of surfaces not transfer to beginning to walk on those
surfaces?” It may be that some perceptual learning is specific (e.g., steep
slopes are dangerous to crawl on) and some is general and can be consid-
ered “learning to learn” as when infants “acquire the ability to generate
relevant information about novel locomotor problems and their poten-
tial solutions” (Adolph, 2008, p. 214). When novice walkers encounter
a slope, a shag carpet, or a wobbly railing for the first time, they have
to generate information to begin a process of specific learning about
the relation between their walking ability and the nature of the layout.
There are plenty of opportunities to learn: Twelve- to 19- month- olds
average 2,368 steps per hour— the length of 7.7 American football fields
(Adolph et al., 2012). Infants are amazingly clever at figuring out solu-
tions. For example, when encountering a wobbly rubber bridge handrail
that collapsed to the floor when leaned on, some infants crossed safely
by leaning backward as if wind surfing or mountain climbing (Berger,
Adolph, & Lobo, 2005).
Another developmental puzzle of current interest is why infants give
up an efficient motor behavior that they have mastered, and whose
affordances they know, in order to take on a new motor behavior at
which they are novices (Adolph & Tamis- LeMonda, 2014). In particular,
as soon as children take their first step, they abandon crawling, which
served them well for getting around efficiently and safely, in order to go
through months of wobbling and falling. In fact, new walkers have about
32 falls per hour (Adolph et al., 2012). At this point, it is better to be
a skilled crawler than a bumbling walker. Eventually there will be ben-
efits of walking— faster mobility, a richer visual input, better access to
distant objects, and new ways of interacting with other people— though
new walkers do not know that yet. Even when new walkers were placed
at the top of a steep slope into the crawling position that allowed them
to slide safely down such a slope before, about half of them stood up,
tried to walk, and fell (Adolph, 1997). So why do they persist? There
may be several reasons (Adolph & Tamis- LeMonda, 2014): Even with
falling, new walkers can go faster than experienced crawlers, and even
experienced crawlers actually fall quite a bit— an average of 17 falls per
hour (Adolph et al., 2012). Given that novice walkers walk more than
experienced crawlers crawl, overall, even poor walking may be more
beneficial than excellent crawling. Plus, even poor walkers can see more,
especially distant objects that provide more opportunities for play, and
can carry objects to their mothers to try to get their attention.
Finally, neuroimaging is identifying some of the brain correlates of
infant perceptual learning. For example, infants’ brain organization for
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Summary c 399
identifying objects is both similar to, and different from, that of adults
(Wilcox & Biondi, 2015). We now know some of the age- related changes
in patterns of neural activation associated with shape and speed infor-
mation about objects during the first year of life (Wilcox, Hawkins, &
Hirshkowitz, & Boas, 2014). Thus, as infants develop sitting, then crawl-
ing, then walking, it may be possible to identify, with neuroimaging, how
each advance affects infants’ perception of shape and speed. Another line
of research related to Gibson’s theory is that it is known that many tasks
activate both cognitive- control and motor areas of the brain (Diamond,
2000), reflecting close connections between action and thought.
SUMMARY
Gibson asked four questions: What is learned? How is this information
picked up? What actions (or interactions) take place? What are the
consequences for knowledge? Her answers are the following: Children
learn to perceive affordances, namely, what it is that the events, objects,
and layout in the environment offer that relates to the infant and can be
controlled by the infant. An object’s affordance is what can be perceived.
This relation is a fit between children and their environments. Children
extract, from stimulation, information that specifies these places,
objects, and events and their affordances for actions. They learn to per-
ceive distinctive features, invariants, and patterns in events, objects, and
layouts. As they learn what is invariant in objects and events, children
learn about themselves as objects that move about this world of vari-
ants and invariants. Infants also learn to participate in a communicative
event. Importantly, children learn the consequences of their attempts to
use affordances— successful exploration and play versus falling or not
reaching a toy.
The ecological context of this learning is important because children
learn to perceive information that helps them adapt to this environment.
In each setting, children’s goals— whether playing or reading or climb-
ing over a fence— guide their pickup of information. In general, the fit
between the goal and perception improves during development. As a
result of active exploration, infants learn about communication, interac-
tion with objects, and locomotion in spatial layouts.
Regarding developmental issues, Gibson viewed humans as active,
self- motivated creatures who develop primarily quantitatively but also
sometimes qualitatively. Nature and nurture intertwine to produce an
efficient, adaptive perceptual system. The strengths of the theory are
its focus on the ecological context of perception and its inclusion of
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400 c GIBSON’S ECOLOGICAL THEORY OF PERCEPTUAL DEVELOPMENT
the body in motion during cognition. An area of the theory needing
further development concerns the nature of cognitive aspects of percep-
tual learning. Contemporary Gibsonian- inspired research is addressing
puzzling aspects of infants’ motor development, so important for their
learning about the affordances of their world.
SUGGESTED READINGS
The best sources for Gibson’s theory are her own publications:
Gibson, E. J., & Pick, A. D. (2000). An ecological approach to perceptual
learning and development. New York: Oxford University Press. This is
the most up- to- date, comprehensive account of her theory.
Gibson, E. J. (2002). Perceiving the affordances: A portrait of two psycholo-
gists. Mahwah, NJ: Lawrence Erlbaum. This inspiring autobiography
shows the obstacles that women scientists had to overcome in the 20th
century.
An interview with Gibson can be found on the website of the Society for
Research in Child Development.
The following article puts Gibson’s career into a historical perspective
and identifies her main contributions:
Pick, H. L., Jr. (1992). Eleanor J. Gibson: Learning to perceive and
perceiving to learn. Developmental Psychology, 28, 787–794.
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Theories Today: Themes and
Perspectives
An experimenter shows a 5- year- old a candy box with pictures of candy on it and
asks her what she thinks is in it. “Candy,” she replies. She then gets to look inside
and discovers to her surprise that it actually contains pencils. What would another
child who had not yet looked inside think was in it, the experimenter next asks.
“Candy,” says the child, amused at the deception. The experimenter then tries the
same procedure with a 3- year- old. The response to the first question is the expected
“candy,” but the response to the second is an astonishing and unamused “pencils.”
More surprising yet, the younger child also claims, in response to further question-
ing, that he himself had initially thought that pencils would be in the box— and
had even said there were.
—Flavell & Miller, 1998, p. 851
The preferred states of infants’ motor systems in nonreaching movements— their
individual intrinsic dynamics— profoundly influenced the nature of the transi-
tion to reaching. . . . Two infants, Gabriel and Nathan, had large and vigorous
movements; the other two were quieter and generated fewer and slower, less force-
ful movements. The task for all the babies was the same: To get their hands in the
vicinities of the desired objects. But they had different problems to solve to do this:
Gabriel and Nathan had to damp down their forceful movements to gain control;
Hannah and Justin had to produce more muscle force to extend their arms forward
in space and hold them stiffly against gravity.
—Thelen & SMiTh, 2006, p. 295
Se
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C H A P T E R 9
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402 c THEORIES TODAY: THEMES AND PERSPECTIVES
D
evelopmental theories, like the children they describe, are
always in motion, always changing. Each chapter in this book on
the “big” approaches also described some of their contemporary
relatives that are currently stimulating research, for example,
connectionism and modern attachment theories. The sections on con-
temporary research showed how each theory is alive and well, in some
form, today. Where are we now in our theorizing about development?
This chapter begins with a description of the principles from the various
theories that are so generally accepted that they form the foundation
for developmental theorizing and research today. Next is an overview
of theories emphasized or deemphasized today. Then the main section
provides an account of four themes that currently are driving theorizing
and research. In the context of these themes, several prevailing theories
are presented.
Generally Accepted Theoretical Principles
One sign that developmental theorizing has advanced over the years
is that several theoretical ideas from the various theories in this book
are so compelling and supported by research that they are merely
assumed today and form part of the current foundation for research
and theorizing. First, children are active, not passive. They contribute
to their own development by selecting certain contexts and interpret-
ing new experiences in light of their current knowledge and history of
social experiences (constructivism). Second, understanding development
involves description and explanation from multiple perspectives, from
cells to society. Thus, studying development is an interdisciplinary
enterprise. The various levels are dynamically intertwined, in constant
two- way interaction, such that changes in each level impacts other
changing levels as well. Third, there is an underlying continuity to
development. Each point in development involves a quantitative or
qualitative change, based on a child’s previous developmental history,
that sets in motion a cascade of short- term and long- term changes.
Fourth, it is assumed that a main goal of developmental work is to
identify developmental processes that drive development. These pro-
cesses flow from the inseparable activities of nature and nurture. These
four assumptions may not be reflected in every new theory and study,
but they form the bigger picture of the enterprise of developmental
science.
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Themes Driving Theorizing and Research Today c 403
Overview of Theorizing Today
Let us keep making theories. We may eventually get the right one.
—eleanor J. GibSon (2003, p. 295)
No one theory currently dominates the field. Several have waned in influ-
ence, in that research today rarely explicitly tests them— Freud, Erikson,
classical Piagetian theory, Vygotsky, social learning, and Gibson. However,
all have contributed major theoretical ideas that have been assimilated into
the field, as described above, such that their impact is almost invisible.
Certain theories currently are influential for specific topics, such as con-
nectionism for language and brain development, information processing
for memory development, Bowlby for attachment, evolutionary theory
for genetic and brain influences, dynamic systems theory (see below) for
motor and language development, and Piagetian- inspired theory theory and
core knowledge theory (see below) for conceptual development. Although
Vygotsky’s theory has little explicit presence today, it is very much pres-
ent in the considerable interest in the cultural contexts of development.
Today, for the most part, instead of building grand theories, developmen-
talists seem to be constructing small, focused theories that are energizing
research in specific areas, such as attachment or theory of mind. An excep-
tion is dynamic- systems theory, a very broad theory described below. In
terms of salient topics and approaches, the ones that seem most on the rise
currently are genetics (especially epigenetics, Gene X Environment inter-
action), neuroscience, computational models (especially connectionist and
Bayesian models), executive function, and dynamic systems. Most of these
focus on the two- way interplay between nature and nurture, and between
quantitative and qualitative changes. Most were boosted by technological
advances— in computer technology, neuroimaging or genetic analyses.
Themes Driving Theorizing and Research Today
Four themes, or questions, seem to capture the current excitement in
research and theorizing and highlight the main debates about devel-
opment: How general are developmental changes? How can complex,
dynamic change be captured theoretically? How can theories best depict
long- term development? How can theories best depict universal and
diverse aspects of development? In the context of these questions,
several theoretical approaches will be described: theory theory, core
knowledge, and dynamic systems.
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404 c THEORIES TODAY: THEMES AND PERSPECTIVES
1. How general are developmental changes?
As mentioned in the chapter on Piaget, others’ research cast doubt on
his view that the cognitive structure of a particular stage is reflected in
most or all domains. Specifically, children often do not seem to have
concepts characteristic of a particular stage that they apply consistently
across tasks. And cognitive changes do not seem to change the whole
cognitive system. Instead, children seem to have a coherent understand-
ing specific to a particular domain and, for the most part, construct this
understanding from experience with that particular domain. For exam-
ple, mathematical knowledge comes from experience with counting,
measuring, and so on. Today, the prevailing approach to understanding
conceptual knowledge seems to focus on domain- specific knowledge.
The debate centers on how best to characterize this understanding as
well as the role of innate factors. Below are the two main positions
in this debate: the theory theory and core knowledge. The former is
constructivist— in the Piagetian spirit— and the latter emphasizes innate
predispositions toward the early acquisition of certain concepts.
The Theory Theory c Suppose a child is told the following story, which
the experimenter acts out with dolls (Wimmer & Perner, 1983): A boy
puts some chocolate in a blue cupboard and goes out to play. In his
absence, his mother moves the chocolate into a green cupboard. After
the boy returns for his chocolate, the children are asked where the boy
will look for it. Three- year- olds immediately say “the green cupboard,”
where the chocolate actually is, even though the boy in the story could
not possibly know that the chocolate was moved. In contrast, the 4- and
5- year- olds usually say “the blue cupboard,” because, unlike the 3- year-
olds, they have a theory of mind in which people act on the basis of their
beliefs, even when the beliefs are false. This surprising and compelling
demonstration of 3- year- olds’ belief system, and its relatively rapid
change over the next year or two, became the basic paradigm for theory-
of- mind research. One could say that the 3- year- old and the older child
have different theories of mind— different underlying principles about
mental states and their connections to behavior and the physical world.
The first excerpt at the start of this chapter describes another popular
assessment of understanding of false beliefs. Theory of mind, a main
topic within the theory theory, is one of the most active research areas
in developmental psychology today (Wellman, 2014).
The theory theory proposes that children, and perhaps even infants,
have the capacity to construct intuitive, folk, everyday, naïve “theories”
that attempt to explain a particular domain. For example, children have
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Themes Driving Theorizing and Research Today c 405
theories of biology, physics, and mind. Evidence of these domains being
somewhat independent includes a child’s uneven knowledge across these
domains as well as cognitive deficits specific to one domain in children
with disorders believed to be biologically based. An example is the
poor understanding of certain aspects of mind in children with autism-
spectrum disorders. These theories are called “foundational” in that they
address particularly important aspects of daily life, such as the properties
of physical objects, and are influential for shaping and constraining other
concepts during development.
According to the theory theory, children’s thinking progresses much
as does scientific discovery and hypothesis testing. Children are little
scientists who test their theories. Children are born with a tendency to
form naïve, or folk, theories, which help them make sense of the world.
Such a theory is an organized representation about a particular domain.
These theories entail unobservable causal relationships that underlie
observable phenomena. A simple example, from theory of mind, is the
knowledge that desires lead to intentions; a child might understand that
another child wants to find her new game and thus intends to look for it.
Or, in the cupboard example, 4- and 5- year- olds think that beliefs lead
to the behavior of looking for an object in a particular place, even when
the belief is false. The claim is that young children and perhaps even
infants construct causal theories of mind rather than isolated pieces of
knowledge about mind. These theories are somewhat abstract, coherent,
and internally consistent, much like Piaget’s cognitive structures but on
a much smaller scale. Children use these causal- explanatory theories to
interpret the world, predict future events, and explain previous events.
Although children test their theories, theories are somewhat resistant
to change. Children initially tend to try to ignore disconfirming evidence
or perhaps patch up the theory. An implication for education is that
children (and even adults) resist giving up their theories, for example,
their belief that the world is flat, based on their everyday experience,
even when teachers provide evidence that the world is round. Getting
children to give up an old theory is as important as providing them with
a new theory. The following is an example of a child’s resistance when
told that flowers turn toward the sun, which contradicted the child’s
current belief (Opfer & Siegler, 2004, p. 325):
Child: But they can’t turn theirselves! . . . Remember, they can’t turn
theirselves?
Experimenter: But they can.
C: [shrugs]
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406 c THEORIES TODAY: THEMES AND PERSPECTIVES
E: Why would the yellow flowers turn . . . ?
C: They couldn’t! They can’t turn theirselves.
E: Sure they can.
C: [quietly] They can? [more loudly] Not if the wind blows it.
E: Well, there is no wind.
C: Then how can it turn over? Only a person can turn over, like this
[moves arm as flowers were depicted as doing]—or, the wind can
blow it over [moves arm to illustrate wind blowing flowers to face
the sun].
As counterevidence continues to build, children adjust their theories.
Consider a 9- month- old baby who has a simple theory of action
(Gopnik & Meltzoff, 1997). He believes that he can influence people’s
actions by communication (e.g., screeching loudly at a restaurant) and
can influence objects’ actions by making physical contact with them.
This theory about the role of force on physical objects works fairly well
much of the time in a 9- month- old’s world. However, counterevidence
arises when he tries to put a block into a bottle with a narrow neck. He
repeatedly but unsuccessfully tries to force it into the bottle but even-
tually must reconsider his theory, and by 18 months he has a new and
better theory that acknowledges that brute force does not always work
with physical objects. The new theory in turn has a new set of interpre-
tations, predictions, and explanations that he will test.
The new theory may be a revision of the old theory, as in the above
example of physical force. Or the new theory may be quite different
from, and incompatible with, the old theory. An example of a new the-
ory is the change from a flat- world to a round- world theory. This radical
theory change constitutes a cognitive revolution, similar to the scientific
revolution in changing from Newtonian to Einsteinian physics in the
history of science.
Experience (evidence and counterevidence) contributes to the spe-
cific theory children construct. Consequently, they have different theo-
ries for different domains, and a child’s theories may evolve at different
rates in different domains. Not only would a 6- year- old’s theory of
biology be very different from her theory of mind, but also one theory
could be more advanced than the other.
Many sorts of evidence support the claim that children develop a the-
ory of mind. Infants seem to have some inkling of mental states such
as people’s intentions; then, during the preschool years, children move
from a focus on desires to a focus on true and false beliefs. That is, young
preschoolers predict and explain others’ behavior in terms of people’s
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Themes Driving Theorizing and Research Today c 407
desires— what people want to do— and older preschoolers also consider
what people believe about reality. As an example of the latter, 4- and
5- year- olds understand that John looked around the neighborhood for
his puppy because he thought it had gotten lost and he wanted to find it,
even though it actually was asleep under the bed. Another theory- of-
mind ability is knowing that people can have mental states that differ
from their behavior, as when someone is sad but smiles so that others
cannot detect the sadness.
Regarding a theory of physics, recent demonstrations of young infants’
considerable knowledge about properties of objects, such as their per-
manence and continuity, and correlations between objects’ sights and
sounds were described in the chapters on Piaget’s and Gibson’s theories.
Also, the information- processing chapter reported adults’ and children’s
adherence to their theory that objects fall straight down even though
they saw evidence to the contrary when watching an object dropped
from a moving toy train. An example of young children’s changing
theory of biology is their awareness of some, but not all, properties
that distinguish living from nonliving entities (as in the above flower
example). They are puzzled by plants, for example, because plants grow,
like animals, but have only passive movement, unlike animals. Other evi-
dence is that young children seem to have some notion of the “essence”
of an animal, because they can ignore physical similarity or dissimilarity
and detect underlying essences. For example, they consider a realistic-
looking mechanical monkey to be more like a hammer than like a real
monkey (Carey, 1985). However, some essences are harder for young
children to maintain. This was demonstrated when children were told
a story about a scientist who operated on a horse to make it look like a
zebra (Keil, 1989). The scientist added stripes to the horse, cut off its
mane, taught it to live in Africa, and so on. Is it still a horse? Young chil-
dren had trouble continuing to think of it as a horse, but older children
did not.
Some developmentalists question whether infants and young children
have knowledge that is abstract, coherent, and consistent enough to be
called a “theory.” Preschoolers’ understanding of mind, for example, may
involve a more concrete and limited body of knowledge acquired from
interaction with family and peers and from their knowledge of their
own desires and intentions. In response, theory- theory theorists have
identified the defining qualities of a theory theory (Wellman & Gelman,
1998): First, the theory theory proposes that children divide the world
into fundamentally different sorts of “things”—for example, thoughts
versus solid physical objects. Second, children understand that each
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408 c THEORIES TODAY: THEMES AND PERSPECTIVES
domain involves fundamentally different sorts of causes— for example,
in the physical domain, one object collides with another object, causing
it to move, but desires and intentions cause human behavior. Third, chil-
dren refer to distinctive underlying constructs in their understandings—
for example, the mind consists of mental representations, but solid
objects are composed of physical substances. Fourth, concepts form a
larger system. Desires are connected to intentions to perform certain
actions, as when a desire for candy leads to the intention of obtaining
some, which leads to a trip to the store. In other words, if children have
a theory, they should honor distinctions among domains as to the sort
of entities they are and use distinctive causal principles when reasoning
about various domains. They also should construct theories such that
each domain is represented by a distinct set of unobservable and inter-
connected causal notions. The debate between theory theory and other
approaches continues today.
It is clear that the theory theory looks somewhat Piagetian in its
claims that knowledge is organized, that children construct new knowl-
edge, that current knowledge constrains what sort of change can occur,
and that a period of instability accompanies change. However, the
approach differs from Piaget’s in that it tends to consider each theory
to be domain specific and relatively separate from the others. Also, the-
ories appear much earlier than Piaget thought, and most theory change
is more modest than the dramatic changes from one Piagetian stage to
another.
Recent theory- of- mind research has focused on several issues: Is
infants’ apparent understanding of others’ mental states (e.g., predicting
a person’s intention, knowing what a parent is looking at or pointing
to) actually a theory? How does it differ from the later, more advanced
understanding of intentionality? What factors contribute to theory- of-
mind development? Executive function and parents’ input have been of
particular interest. Do children in all cultures follow the same devel-
opmental sequence of acquiring various aspects of theory of mind?
There seem to be both similarities and differences. How does theory of
mind develop further after the preschool years? What specific aspects
of theory of mind are compromised in children with autism- spectrum
disorders? What brain networks support theory- of- mind understanding?
For example, the brain regions activated when children and adults think
about other people’s thoughts becomes more specific to people’s mental
states rather than their appearance or social relationships, with increas-
ing age (Gweon, Dodell- Feder, Bedny, & Saxe, 2012). How is theory
of mind related to social interactions (Brink, Lane, & Wellman, 2015)?
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Themes Driving Theorizing and Research Today c 409
How is theory of mind related to other areas of social cognition, such as
obligations, norms, and morality?
A recent theoretical advance is to integrate theory theory with the
Bayesian models of statistical learning described in the information-
processing chapter (Gopnik & Wellman, 2012). Specifically, a main learn-
ing mechanism for changing one’s theory of mind may be to infer causal
structure by drawing on statistical information about regularities in social
behavior. During development, children sometimes adjust the probabil-
ities of several possible hypotheses rather than reject one and move to
the next one.
Some developmentalists think that the theory theory does not provide
a satisfactory explanation of young infants’ precocious understanding of
the world. They think that it is necessary to assign a significant innate
component to explain such abilities. We now turn to this account.
Core Knowledge c Core knowledge theories (e.g., Spelke, Bernier, &
Skerry, 2013) propose domain- specific knowledge, as does the theory the-
ory. However, core knowledge theories posit that humans have evolved a
largely innate set of cognitive skeletal principles— a skeletal explanatory
system— that facilitates early, rapid learning in certain domains. This
small set of systems is the starting state of human cognition. It requires
minimal environmental input to be activated and then constrains how
knowledge develops as a result of experience. Various theorists suggest
somewhat different sets of domains. One influential theory proposes
five somewhat separate, but integrated, core knowledge systems (Spelke
et al., 2013): objects (and their motions), agents (and their goal- directed
actions), number (and their arithmetic operations), places (that one can
navigate to in the spatial layout), and geometrical forms. Each system
has a different set of principles, for example, cohesion (objects move
as connected wholes), contact (objects interact only when they touch),
and continuity (objects move on open paths) (Spelke & Kinzler, 2007).
Infants use these principles to perceive object boundaries, represent
objects out of view, and predict the movements of objects. Thus, the
principles guide representation and reasoning in the domains. Learning
in these core knowledge areas proceeds much more quickly than learn-
ing in other domains because the core principles guide learning. That is,
there is an innate push toward certain kinds of information processing,
which accounts for surprisingly early knowledge in some domains.
Evidence for this early core knowledge is found in earlier chapters that
presented evidence of surprisingly advanced understanding in newborns
and young infants. Young infants expect that objects are whole, even
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410 c THEORIES TODAY: THEMES AND PERSPECTIVES
when the whole object cannot be seen, and that one solid object cannot
pass through another one. They also differentiate arrays with different
numbers of objects and expect longer arrays to have more objects
(Huang & Spelke, 2015). Early on, infants recognize familiar faces and
categorize faces according to sex, age, and race. Infants are predisposed
to imitate others, especially others perceived as like them; to share men-
tal states such as attention and information; to infer others’ goals; and
to evaluate others’ helpful or nonhelpful behaviors (Spelke et al., 2013).
Moreover, in studies of infants’ responses to animated stimuli, infants
seem to expect that members of a social group will act in similar ways—
engage in similar actions and make similar choices (Powell & Spelke,
2013). This inference is specific to social stimuli; they do not show these
expectations when the same cues are depicted with inanimate figures.
Thus, there is an early, rudimentary, domain- specific understanding of
social relationships. Infants also differentiate human patterns of move-
ment (a pattern of moving lights indicating a person running) from ran-
dom motion. Regarding the geometry core system, 2- year- olds can use
abstract two- dimensional maps to locate objects in three- dimensional
layouts, drawing on both distance and angle information ( Winkler-
Rhoades, Carey, & Spelke, 2013). As an example of core biological
knowledge, 8- month- old infants expect animals to have insides (Setoh,
Wu, Baillargeon, & Gelman, 2013). They consider it a violation when
a self- propelled, agentive object turns out to be hollow. These five core
systems have been found in other cultures and nonhuman primates as
well, thus suggesting an evolved conceptual system (Spelke et al., 2013).
They exist even in people with little or no formal education and with
primitive symbol systems.
These core knowledge systems serve as the foundation for the devel-
opment of later, more abstract and flexible understanding about these
domains. An example is early intuitive preverbal reasoning about
approximate numbers and later formal verbal reasoning about numbers
(Piazza, 2010). Another example is early use of maps (e.g., distance
and angle information) for navigation and later formal understanding of
geometry (Huang & Spelke, 2015). Neural networks supporting core
knowledge can be considered a “neurocognitive start- up tool” for the
eventual transformation of core knowledge, as a result of experience and
maturation, into more abstract concepts (Piazza, 2010). The principles
of a core knowledge domain guide and constrain this development.
The theory- theory and core- knowledge approaches are similar in their
focus on early domain- specific knowledge systems and developmental
modifications of these knowledge systems. They differ in that the theory
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Themes Driving Theorizing and Research Today c 411
theory assigns less innate influence, focuses less on infants’ apparent pre-
cocious knowledge about the physical and social world, and places more
importance on theory construction and testing, even during infancy.
They both address what constrains human cognitive development,
though their answers are different— innate biases (core knowledge) or
constructed theories (theory theory).
It should be noted that not all developmentalists who think that
children’s knowledge is domain specific are theory theorists or core
knowledge theorists. An example of other domain- specific approaches
is moral domain theory, which focuses on how moral reasoning is dis-
tinct from other domains such as reasoning about social conventions
(e.g., Helwig & Turiel, 2011). Other examples are certain computa-
tional approaches and the neo- Piagetians, especially Kurt Fischer and
information- processing approaches focused on knowledge acquisition or
problem solving in, for instance, math. In one theory not discussed in this
book, Howard Gardner (2011) proposed domain- specific intelligences
in several domains, such as linguistic, spatial, logical- mathematical,
musical, bodily kinesthetic, intrapersonal (understanding the self ), and
interpersonal (understanding others). Although some of these forms
of intelligence are assessed on IQ tests, some, particularly musical and
kinesthetic intelligence, are not. In Gardner’s view, professional musi-
cians and dancers, first- rate quarterbacks, plumbers, and car mechanics
display high intelligence of nontraditional sorts.
There also are nativist domain- specific approaches other than core
knowledge. Modularity approaches argue that the mind consists of a
loosely connected set of specialized, encapsulated, innate modules, struc-
tures, or constraints shaped by evolution to perform a particular function
(Fodor, 1983). Modules are preprogrammed to respond to specific sorts
of information, and the number of modules potentially can be large. A
module requires little experience in order to be triggered. For example,
simply being exposed to language may be sufficient for normal language
development; instruction is not necessary. Experience is thought to have
little effect other than to provide content that fits into the innate struc-
ture; counterevidence cannot overturn the modules. Thus, infant minds
in many ways are not that different from adult minds; the modules just
have to be expressed.
Finally, although domain- specific approaches characterize much of the
theorizing and research today, there also is great interest in identifying
specific domain- general mechanisms that contribute to the construction
of domain- specific knowledge. Executive functions, especially working
memory, are a prime example, as seen in research on the contributions
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412 c THEORIES TODAY: THEMES AND PERSPECTIVES
of executive function to the development of theory of mind (Devine &
Hughes, 2014). One current goal of theorizing is to integrate domain-
specific and domain- general knowledge.
2. How can complex, dynamic change
be captured theoretically?
Each theory in this text has added complexity to the picture of devel-
opment, often by adding another level of analysis or showing the intri-
cate connections among areas of development or among biological and
environmental contributions. Moreover, the body in motion in Gibson’s
theory and embodied cognition (described in Chapter 7) add the notion
of a developing child as a body in action. All of this has converged to
create great interest in dynamic- systems theory because it captures this
complexity, connections, and action, and provides a broad and coherent
account of development.
Dynamic- Systems Theory c Dynamic- systems theory addresses changes
over time in complex, self- organizing, holistic systems. One self-
organizing system from an earlier chapter is Piaget’s cognitive structures
that reorganize themselves in order to maintain equilibrium. Dynamic-
systems theory comes from work on complex systems in physics and
mathematics, but it fits into models of biology and the organismic tra-
dition in developmental psychology. In dynamic systems’ “ big- picture”
view, one can understand development only by considering “the multi-
ple, mutual, and continuous interaction of all the levels of the developing
system, from the molecular to the cultural” and “nested processes that
unfold over many time scales from milliseconds to years” (Thelen &
Smith, 2006, p. 258). The moving body and the brain are closely con-
nected; thus cognition is embodied. There are two- way interactions
among the brain, body, and environment. This inclusiveness makes it the
broadest, most encompassing developmental theory and may provide
a way to integrate other developmental theories into an overarching
developmental theory.
In a dynamic system, a person’s behavior depends on all the forces at
work in the current moment. The irreducible unit is the organism- in-
context. In this way, the approach resembles sociocultural developing-
person- in- context approaches and Gibson’s theory. A simple example is
a person’s choice of dinner restaurant, which depends on the interaction
of elements such as what kind of food he had for lunch, how hungry he
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Themes Driving Theorizing and Research Today c 413
is, what preferences are expressed by his dinner companions, and what
kind of restaurants are located nearby. Another simple example, which
shows the interdependence of brain, body, and the physical world, is that
babies walk quite differently when they are wearing a diaper, especially
a bulky cloth diaper, than when they are naked (Cole, Lingeman, &
Adolph, 2012). These different forms of walking are due to system- wide
changes: A diaper causes spreading of the legs, which makes the infant’s
gait less mature and leads to more missteps and falls.
A mountain stream serves as a good metaphor for a dynamic system
(Thelen & Smith, 2006). At various points down the mountain, the
stream is expressed as a fast stream, a small trickle, a waterfall, or a still
pool, depending on many factors, such as the rate of flow of the water
downstream, the terrain, and weather conditions. Most of the time, this
pattern is about the same. After a heavy rain or a drought, however, the
configuration of the water changes, though in predictable ways. To under-
stand the current dynamic state of the stream and how it self- organizes,
we must consider many time frames, from the ancient geological history
of the mountain to the recent rainstorm. We also must consider many lev-
els of “cause,” from the terrain of the mountain and gravity to water mole-
cules. The same is true of changes in human dynamic systems. Developing
children show patterns, self- organization, and interconnected changes on
many levels, ranging from culture to molecules.
To explain a person’s behavior, rather than focus on abilities or traits
that a person “has,” the theory focuses on the assembling or re- creating
of a behavior on the spot. That is, a behavior emerges from the pattern of
all the variables operating at a particular moment. Any behavior is “softly
assembled” in the moment from the interaction of multiple subsystems
for the specific task at hand; the behavior is not set in stone and can vary
on future occasions or even disappear for a while. For example, it can
be difficult to say when an infant “can walk,” because walking appears in
some situations but not others, and the quality of the walking varies from
situation to situation (the diaper example above). Given the overall state
of the system in its current setting, a certain behavior comes together.
Dynamic- systems theory asks, “Where do new behaviors come from?”
New complex forms or skills emerge from interactions of the parts of
a complex system— from the relations among the parts and the self-
organizing nature of living organisms. New behaviors can be said to “fall
out” of the current status of the system in its present context, just as a
new stream falls out of an existing stream after a heavy rain. This concept
of emergence of new forms is found in biological systems theories in the
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414 c THEORIES TODAY: THEMES AND PERSPECTIVES
development of an embryo from one cell through various more complex
organizations or the emergence of a new organ or limb during prenatal
development through a predictable set of configurations.
One example of the emergence of a new ability is that babies who do
not have the motor skill to perform some desired action try to create a
behavior that works. In trying to assemble a new motor behavior on the
spot, such as trying to obtain a toy out of reach or walking on a water
bed for the first time, infants draw on the motor skills they already have.
First they try out several different behaviors in an attempt to find one
that works. Then, after seeing which behaviors work, or appear promis-
ing, they put together and fine- tune a new behavior, such as pulling on
the cloth on which the desired toy rests. Thus, both the nature of the
task and the child’s current motor skills and motivations determine what
develops in a particular situation at a particular time. “Individual speed
‘personalities’” (Thelen & Smith, 2006) also play a role, as seen in the
second excerpt at the start of this chapter. A more cognitive example
of emergence, in older children, is the creation of a new strategy in
response to information specifying the task in its physical environment.
That is, given children’s current strategies and skills, the nature of
the task materials, and their goals, they assemble a new strategy. This
theoretical account provides a new perspective on strategy variability
(described in the information- processing chapter). A child might suc-
cessfully use a new, good addition strategy on one addition problem but
drop it moments later for an older strategy, if the dynamic situation (i.e.,
all active current forces) has shifted slightly.
Consider a classic dynamic- systems experiment: As mentioned in
the ethology/biology chapter, newborns have a stepping reflex. They
appear to walk, much like a toddler does, when supported in an upright
position with their feet touching the floor. The fact that this reflex dis-
appears around two months of age traditionally has been interpreted
as showing that maturing higher brain functions begin to inhibit lower-
level reflex behaviors. However, the dynamic- systems approach suggests
another explanation (Thelen, Fisher, & Ridley- Johnson, 1984). The fact
that babies older than 2 months continue to show this “walking” pattern
when lying on their backs argues against the traditional inhibition expla-
nation. Thelen and her colleagues proposed instead that as babies gain
weight over their first few months, their legs become too heavy to lift
when they are upright. Their evidence was that these older babies, who
apparently had lost the walking reflex on the usual measures, suddenly
began showing it again when held in a waist- high tank of water that made
their legs less heavy. Thus, an infant’s behavior depends both on what the
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Themes Driving Theorizing and Research Today c 415
infant can do and the affordances of the immediate setting. If you change
one element in the dynamic system, you change the interaction of the
parts. Recently, the disappearance of the walking reflex has become a
mystery again, because another change in the setting— lifting a baby
into the air— causes babies who had lost the walking reflex to once again
show the walking pattern ( Barbu- Roth et al., 2015). This observation
casts doubt on the hypothesis that the weight of the legs is the critical
variable.
An important notion in the theory is that of an attractor state— a pre-
ferred state in which the system tends to reside. Stated differently, it is
a child’s preferred behavior within the set of possible behaviors of the
current state of the system. Although behaviors vary, the organism tends
to return to this preferred state of relative stability. A 4- year- old tends to
walk in a particular way, at a particular speed, but the form of walking
changes somewhat when walking very fast or when walking in water or
on a rocking boat or a water bed. An 8- year- old tends to use a partic-
ular addition strategy but uses others if the numbers get so large or so
small that other strategies work better or a less effortful strategy can be
used. In large time frames, even stages such as Piaget’s can be consid-
ered attractor states with periods of instability between them. Indeed,
in dynamic- systems theory, the system organizes and reorganizes over
time to form a series of dynamically stable attractor states. This notion
of an attractor state is useful for capturing both the consistency and
variability of children’s behavior. Proposing an attractor state “banishes
forever the vocabulary of programs, structures, modules, and schemas
and supplants these constructs with concepts of complexity, stability,
and change. Stability defines the collective states of the system, assessed
by its resistance to change” (Thelen & Smith, 2006, p. 274).
One reason why dynamic- systems theory is attractive is that it makes
intriguing predictions about development based on several subtle prin-
ciples of change. One principle is that a small initial difference or effect
can have reverberations that culminate in large, dramatic differences or
effects later. This idea is expressed in developmental cascades, discussed
in earlier chapters: An early event or development sets in motion a series
of far- reaching effects over a number of years. One implication is that
a researcher may need to look for causes of a new behavior not only in
recent events but also in much earlier events. A related prediction is that
a small change causes changes throughout the system. Thus, dynamic-
systems researchers might look for effects of instruction on tasks other
than the ones on which they trained a child. Another principle is that
quantitative change can lead to qualitative change as a skill gradually
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416 c THEORIES TODAY: THEMES AND PERSPECTIVES
changes until it passes a critical threshold and then seems to emerge as
a qualitatively different skill. For example, infants’ muscles gradually
become stronger to the point that they can— apparently suddenly— sit
without support.
It is clear that dynamic- systems and connectionist approaches have
much in common, and in fact have been combined fruitfully (Samuelson,
Jenkins, & Spencer, 2015). They both emphasize the importance of what
is in the initial state and the entire matrix of connections, and show how
small initial differences in that initial state result in large changes later.
Both also see gradual quantitative change eventually causing a system-
wide change and the emergence of a new, qualitatively different new
behavior. The brain, on which connectionism is modeled, is a dynamic
system in which a change in one part impacts the whole brain system,
and there is continual interaction during development among genes,
brain, cognition, behavior, and environment.
Given the above principles, it is obvious that methods for studying
dynamic systems must examine moment- to- moment changes over time.
This characteristic is shared with information- processing approaches.
Microgenetic methods (Chapters 4 and 7) and longitudinal designs are
the best methods for looking at change. By looking at behavior over
a period of time, researchers can identify the preferred state. They
also can identify the point of most rapid and significant change when
the system is self- organizing to a new developmental level. At this
unstable point, a system reveals itself, especially its processes of change.
One technique for measuring the dynamic pattern of locomotion and its
change is to dress babies in black bodysuits with reflective markers (like
baby bikers) at their joints. As the babies learn to move across a surface
by creeping, crawling, or scooting, a computer reads the reflections to
determine the speed, direction, and pattern of the movements over time
(Freedland & Bertenthal,1994). By looking at how each behavior flows
from previous behaviors and from the current environment, such as the
surface on which the baby crawls, it is possible to hypothesize what vari-
ables (for example, body weight, body proportion, perceptual ability)
are controlling behavior. Finally, the experimenter tests this hypothesis
experimentally; an example is the earlier experiment in which babies
walked in water.
Another attraction of the dynamic- systems approach is its inclusion
of many aspects of development and many levels of analysis. In prin-
ciple, one could study any sort of content from a dynamic- systems
perspective, a characteristic that distinguishes it from most of the other
theories in this book. The approach shares with Piagetian theory a
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Themes Driving Theorizing and Research Today c 417
desire to describe the overall organization of behavior and dynamic
equilibration. Most of the theories in this book tend to break complex
systems into simpler, cause- and- effect relations, thereby limiting their
scope. However, the inclusiveness of dynamic- systems theory makes it
difficult to conduct research from this perspective. It is difficult to iden-
tify and examine all potential causes of a behavior and their complex
interactions.
The main topic studied thus far is infants’ motor behaviors, such as
walking, reaching, and searching for hidden objects, because such
behaviors are easily observed and measured. However, the approach also
has been applied to more cognitive topics, such as object permanence,
naming hierarchical categories, and inferring intent (Samuelson et al.,
2015), and to social development topics such as play (Steenbeek & van
Geert, 2008), emotion regulation (Lewis & Cook, 2007), personality
development (Nowak, Vallacher, & Zochowski, 2005), interpersonal
communication (Fogel & Garvey, 2007), and even social deviance
(Caprara, Dodge, Pastorelli, & Zelli, 2007). For example, the Caprara
et al. study showed that a behavior that initially is only slightly devi-
ant from the norm can cascade over time into serious aggression. A
number of variables in the system (child variables, social environ-
mental variables) determine both whether the initial slight deviance
does escalate and whether the serious aggression can be brought back
to its attractor state. Dynamic systems theory has even been applied
to worldwide problems such as violence, poverty, and family crises
(Fogel, King, & Shanker, 2008), and extensions to other topics appear
regularly.
Dynamic- systems theory is one version of a larger metatheoretical
approach called relational- developmental- systems theory (Overton & Molenaar,
2015). This larger approach includes the characteristics of dynamic-
systems theory, but in particular it breaks down dichotomies in favor of
a holistic synthesis of, for example, nature and nurture, and qualitative
and quantitative changes, and an understanding of their relations. The
approach also focuses on the relations ( two- way influence) between indi-
viduals and their contexts. The individual and context are fused within
the entire relational- developmental system. These relations change
throughout a person’s lifespan and are embedded in a particular time
and place in history. The approach is aligned closely with contextualism
(discussed in Chapter 4), embodied cognition (discussed in Chapter 7),
and optimal lifespan development.
These first two contemporary themes— breadth of change and dynamic
change— are the focus of several identifiable theories, as described above.
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418 c THEORIES TODAY: THEMES AND PERSPECTIVES
In contrast, the last two themes have no current overarching theory.
Rather, the themes characterize the focus of numerous lines of research
from which major theories may eventually evolve.
3. How can theories best depict long- term development?
Developmental research now has identified, and provided informa-
tion about, so many influences on development that it now is possible
to look at the effects of multiple causes of development over childhood
or even longer stretches of the lifespan. The increased availability of
huge sets of data, including longitudinal data, with hundreds or thou-
sands of individuals provides opportunities to look at many variables.
Moreover, advances in the power of computers for calculations and in
statistical models of causal relations among variables over time have
made it possible to develop predictive models of complex, long- term
development. For example, statistical models can identify the direction
of causes, including two- way interactions. They also can detect moder-
ating variables, such as effective parenting, that can serve as a buffer to
dampen the effects of child risk factors, such as premature birth or a
difficult temperament. In addition, these models can test for mediating
variables, such that variable A does not affect a child outcome directly
but does have an effect through variable B. For example, a difficult tem-
perament may elicit angry, ineffective parental reactions, which increase
the child’s aggression. Temperament does not cause aggression directly
but has an effect through parenting variables.
To provide a sense of work that examines long- term changes, devel-
opmental cascades, and diverse developmental pathways, we turn to
work by Nancy Eisenberg and her colleagues. One study was multi-
method, multi- informant, large (N = 474) and longitudinal— ages
5–10 at time one, 11–17 at time two, and 12–18 at time three (Wang,
Chassin, Eisenberg, & Spinrad, 2015). An aspect of temperament— low
effortful control (poor self- regulation)—predicted high aggression
later. Having both low effortful control and low impulsivity predicted
more depression later or co- occurring aggression and depression. The
effect of effortful control on later aggression or co- occurring aggres-
sion and depression varied, depending on the child’s age and degree
of impulsivity. For instance, for older adolescents, lower effortful
control predicted more symptoms only for children with average or
high impulsivity. This study illustrates the use of statistical models that
capture the complex relations among multiple variables, the detection
of multiple pathways to depression versus aggression or depression plus
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Posit ion on Developmental Issues c 419
aggression, and the identification of age and impulsivity as moderators
of the relation between effortful control and later problems. In other
words, children who start out at risk because of poor effortful control
likely will follow different developmental pathways, depending on their
impulsivity. The study also was typical in that it was not generated by a
broad, salient theory, though it was related to a theory specific to the
effects of temperament. Complex, predictive models such as this one
are clarifying the developmental processes involved in both typical and
atypical development.
4. How can theories best depict universal and diverse
aspects of development?
The chapter on Vygotsky and sociocultural approaches stated that work
from these approaches broadened developmental psychology by stim-
ulating theoretical and empirical work on cultural differences between
countries and within a country, as well as on cultural processes involved
in all aspects of development. A main thrust of current research is to
continue this work on diversity and integrate it with what aspects of
development seem to be universal. No overarching theory of culture
or diversity predominates, but the research has a common purpose— to
develop theories of human development based on multiple races, ethnic-
ities, social classes, genders, and other differences. Of particular interest
is how these factors might lead to different developmental pathways.
Numerous studies in the Vygotsky/sociocultural chapter provide exam-
ples of this large enterprise.
Position on Developmental Issues
Regarding worldview, the theory theory and, especially, the dynamic-
systems approaches are organismic because they emphasize self- organizing
systems. Both approaches include both quantitative and qualitative
change and emphasize interactions between nature and nurture. In con-
trast, core knowledge theory emphasizes the innate origins of thinking.
In many ways, dynamic- systems theory breaks down the dichotomies of
nature– nurture and qualitative– quantitative because all of these work
together to bring about change. Finally, the “what” of development
includes new theories, the modification of skeletal core knowledge, and
new attractor states (such as new knowledge or abilities). More than any
other theory in this book, dynamic- systems theory focuses on change, on
processes of development.
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420 c THEORIES TODAY: THEMES AND PERSPECTIVES
SUMMARY
Developmental theories develop. Four themes guide current develop-
ment work: How general are developmental changes? How can com-
plex, dynamic change be captured theoretically? How can theories best
depict long- term development? How can theories best depict universal
and diverse aspects of development? Regarding the first theme, theory
theory and core knowledge theories propose that children develop
coherent, causal- explanatory, domain- specific concepts and that devel-
opment involves changes in these concepts in light of feedback from
testing these theories. Core knowledge theories posit innate skeletal
knowledge in several domains; this core knowledge constrains and
guides further conceptual development. Regarding the second theme,
dynamic- systems theory is a broad theory that tries to encompass all rel-
evant factors operating at a particular developmental moment. This the-
ory focuses on change and on two- way interactions within and between
multiple levels and on the emergence of new knowledge and skills as
children construct behaviors on the spot.
SUGGESTED READINGS
Spelke, E. S., Bernier, E. P., & Skerry, A. E. (2013). Core social cog-
nition. In M. R. Banaji & S. A. Gelman (Eds.), Navigating the social
world: What infants, children, and other species can teach us (pp. 11–16).
New York: Oxford University Press.
Spencer, J. P., Perone, S., & Buss, A. T. (2011). Twenty years and going
strong: A dynamic systems revolution in motor and cognitive devel-
opment. Child Development Perspectives, 5(4), 260–266.
Wellman, H. W. (2014). Making minds: How theory of mind develops.
New York: Oxford University Press.
10_MIL_7898_ch9_401_420.indd 420 1/9/16 1:18 AM
Reflections
The beginnings and endings of all human undertakings are untidy, the building
of a house, the writing of a novel, the demolition of a bridge, and, eminently, the
finish of a voyage.
—John Galsworthy
Se
rg
ey
N
iv
en
s/
Sh
ut
te
rs
to
ck
C H A P T E R 1 0
11_MIL_7898_ch10_421_434.indd 421 1/7/16 12:04 PM
422 c REFLECTIONS
A
lthough it is tempting to tidy up the assortment of theories pre-
sented here by offering an orderly set of conclusions, that aim is
not realistic. Developmental psychology is a huge, multifaceted
discipline that has produced a diverse group of theories. Some
theories are bold and speculative, while others are cautious and precise;
some are large scale and rambling, while others are modest and sys-
tematic. Furthermore, they ask different questions about development.
Consequently, they address different levels of reality, ranging from a
gene to an action to a child- in- social context. Any attempt to integrate
all the theories would be foolish at best and misleading at worst.
This chapter, then, offers several “untidy” thoughts that linger after
this survey of theories. The first section summarizes the theories’ posi-
tions on the four developmental issues that were raised in each chapter.
In the second section, we revisit the issue of mechanisms of develop-
ment, discussed in each chapter. In the third section, we view the history
of developmental theory from two points of view. In the final section,
critical psychology provides another perspective on developmental
theorizing.
Developmental Issues Revisited
Human Nature
The distinctions among organismic, mechanistic, and contextualist
worldviews served as a useful heuristic for understanding and compar-
ing developmental theories, though some theories do not fall neatly
into one category. The organismic worldview depicts children as active
agents who engage with their social and nonsocial environments and
contribute to their own development. Most contemporary versions of
the theories have at least some element of this. Children actively assim-
ilate, accommodate, and equilibrate (Piaget); strengthen ego processes
(Freud); construct a sense of identity (Erikson); and acquire cultural
tools that help them co- construct knowledge and skills with other
people (Vygotsky/sociocultural). In addition, children actively develop
self- regulatory mechanisms and seek out particular environments (social
learning); develop a set of strategies, rules, and procedures for problem
solving (information processing); and search and actively adapt to their
environment (ethology/evolution). Children also explore environments
for their affordances (Gibson), construct and test out intuitive theories
(theory theory), use their core knowledge to construct more abstract
understanding, and self- organize to produce new behaviors (dynamic
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Developmental Issues Revisited c 423
systems). Active self- regulation, in particular, is important for social
learning theory, Vygotsky, Piaget, Bowlby, information processing (exec-
utive control processes), and dynamic systems. Some of the theories
also include passive, mechanistic biological- or environmental- based
processes. Examples include the push from biological drives (Freud,
Erikson, ethology), the expression of innate core knowledge systems
(core knowledge), the registering of co- occurring events (some ver-
sions of connectionism and neuroscience), reinforcement contingen-
cies (learning theory), and reflexes and the response to sign stimuli
( ethology).
Mechanistic and organismic approaches also differ in their focus on
antecedent causes of behaviors or inherent causes within a whole struc-
ture. Antecedent mechanistic causes are involved in stimulus– response
associations (learning theory), fixed action patterns (ethology), and
input– output procedures (information processing). Inherent causes are
illustrated by cognitive structures with a tendency toward equilibration
(Piaget); theories (theory theory); the organization of the id, ego, and
superego (Freud); a pattern of distributed activation (some connec-
tionist self- regulating models); intrinsic motivation (Gibson); control
systems of behavior (Bowlby’s ethological theory); dialectical systems
(sociocultural); and the self- organizing tendencies of a system (dynamic
systems).
Overall, Piagetian and dynamic- systems theories are the most clearly
organismic theories, whereas traditional learning theory is the most
clearly mechanistic. Later, social learning theories, especially Bandura’s,
added some organismic, self- regulatory features to learning theory.
Finally, the contextual worldview is most clearly seen in Vygotskian-
sociocultural theories and dynamic systems theory and least seen in
social learning theory and information processing. However, almost
every contemporary theory is at least beginning to conceptualize the
ways in which developing children are embedded in contexts.
In addition to differences in the theories’ worldviews, there are
striking differences in the theories’ overall views of humans as develop-
ing into rational, efficient “scientists” or into socioemotional cognitive
beings that develop intuitive concepts and “hot” cognition ( emotion-
laden cognition) and seek the meaning of events in their lives. Piagetian,
information- processing, and, for the most part, core knowledge and
theory- theory theorists have emphasized the rational; Freud and Erikson
emphasized how motives and needs affect thinking. The other theories
are more neutral on this issue or have addressed both kinds of thinking.
For example, in social learning theory and cultural approaches, the
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424 c REFLECTIONS
models that children observe may demonstrate either logical or irratio-
nal thinking. Genetics and neuroscience approaches can focus on either
rational or emotional thoughts and behaviors. Ethologists, evolutionary
psychologists, Gibsonians, and core knowledge theorists emphasize the
adaptation required for survival or optimal functioning in the particu-
lar environment. Rational, scientific thought is most adaptive for some
settings, whereas sensitivity to interpersonal relationships and emotions
may be more adaptive in other settings.
Our theorists’ views of human nature are not a trivial matter because
they influence their theorizing. As the biographies of the theorists illus-
trated, theorists’ worldviews are influenced by their backgrounds and
cultures. This is not necessarily a negative because it has led to new
theories that offer novel perspectives on development. Examples are
Piaget’s biological background (adaptation of organisms), Freud’s med-
ical background (sexual drives and psychopathology), and Vygotsky’s
political– historical context (improving minds through activity, work,
and cultural tools).
Qualitative Versus Quantitative Development
The contemporary view is that dichotomies, such as qualitative versus
quantitative and nature versus nurture, are obsolete ways of thinking.
Both of these involve intertwined processes that cannot be separated in
a developing organism. Still, thinking of the theories’ emphases on qual-
itative or quantitative change as falling along a dimension is a useful way
to compare and contrast them. All the theorists see a number of ways
in which development increases quantitatively— in amount, frequency,
or degree. With increasing age, children strengthen and generalize their
cognitive skills (Piaget), increase their ego strength (Freud and Erikson),
and develop their skills gradually as they move through the zone of
proximal development (Vygotsky). They also imitate more accurately
(social learning theory), process information more efficiently (informa-
tion processing), and increase or decrease the strength of certain neural
pathways and develop more specialized brain regions (neuroscience and
connectionism). In addition, children detect more affordances (Gibson),
refine their theories (theory theory), and use core knowledge to develop
abstract concepts (core knowledge).
Although all the theories posit at least minor qualitative change, only
dynamic systems and the stage theorists— Piaget, Freud, and Erikson—
make qualitative change a central part of their theories. In the other
theories, the most common qualitative change is a smaller- scale change,
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Developmental Issues Revisited c 425
such as a new strategy of learning or problem solving (information pro-
cessing) or theory change within a particular domain (theory theory).
Dynamic- systems and connectionist approaches address how quantita-
tive change, once it crosses a certain threshold, can lead to a qualitative
reorganization of a whole system. A major current question is how
best to conceptualize the relations between qualitative and quantitative
change during development. Thus, the current focus is on process rather
than dichotomies.
Nature Versus Nurture
All the theorists agree that development emerges from a complex con-
figuration of innate and experiential influences. However, they vary in
what they choose to study. Ethology, evolutionary psychology, neurosci-
ence, genetics, and core knowledge approaches have focused research on
nature. Still, their research findings often show the effects of nurture—
in attachment, changes in brain organization as a result of experience,
epigenetics, and the learning guided by core knowledge systems. Social
learning and Vygotskian- sociocultural theories most clearly empha-
size nurture, though they acknowledge the contributions of nature.
Piagetian, Eriksonian, and theory- theory approaches most clearly are
interactionist. Piaget, for example, depicted development as an inter-
action of two innate factors (physical maturation and equilibration) and
two types of experience (social and physical). Erikson also stressed both
biological and social changes, showing that as drives change, they mesh
(or conflict) with social institutions. Some of the other theories do not
focus on this issue but imply interactionism. In information process-
ing, for example, brain development obviously increases the potential
efficiency of the information- processing system, and problem- solving
experience leads children to adopt new strategies when they receive
feedback during attempts at problem solving. Gibson’s theory posits
the evolution of perceptual learning abilities that permit adaptation to
the environment. Connectionist models vary in how much starting- state
architecture the modeler includes.
What Develops
The diverse answers to “What develops?” suggest that development can
be understood only by looking at various levels of analysis, from cells to
society. What develops is how each level is organized within itself and
how each level interacts with each other level. An organism, with its
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426 c REFLECTIONS
genetic, physiological, psychological, and behavioral aspects, is part of a
system that includes the environment, with its physical, interpersonal,
and cultural aspects. Each level of analysis contributes to our under-
standing of behavior and has its own set of principles. Behavior can never
be reduced to any single level, such as the neurological, and no level
is more important than the others. Only a theory with multiple levels
of analysis is likely to describe the complex interweaving of innate and
environmental forces during development. No theory has accomplished
this, though dynamic systems theory has at least offered a general outline
of what such a theory might involve.
Some theories aim for a very broad account of development, whereas
others focus more narrowly. The stage and dynamic- systems theorists
look at stage- or state- defining characteristics and therefore operate at
a very general level. In their view, the most important developments
are cognitive structures (Piaget), personality structures (Freud and
Erikson), or continually self- organizing systems (dynamic systems).
Other theorists focus on more specific acquisitions, often limited to cer-
tain situations or types of stimulation: rules (information processing and
social learning theory), the perception of affordances (Gibson), adaptive
behaviors (ethology), intuitive theories (theory theory), and culturally
constructed skills (sociocultural). With respect to content, the theories
range from stressing social behaviors and personality (Freud, Erikson,
social learning theory) to thinking (Piaget, information processing,
Vygotsky, theory theory, core knowledge) to perception (Gibson). The
sociocultural, dynamic- systems, ethological, genetic, and neuroscience
approaches study a variety of behaviors.
Moving Toward Mechanisms of Development
The introductory chapter stated that a developmental theory must
describe development within one domain and the relationship among
simultaneously developing domains and that it must explain the course
of development that has been described. Then a section of each chap-
ter examined that theory’s contributions to our understanding of what
moves development along. Among the mechanisms offered were assim-
ilation, accommodation, and the equilibration process (Piaget); biologi-
cal drives, identification, and ego strengthening (Freud); internalization
and dialectical processes (Vygotsky); biological maturation and fixed-
action patterns (ethology); gene expression (genetics); brain maturation
and experience, reorganization of neural networks, and strengthening
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Moving Toward Mechanisms of Development c 427
and weakening neural pathways (neuroscience); and observational
learning (social learning theory). Other mechanisms are automatization,
increased working memory, and acquisition of strategies (information
processing); changing weights of a distributed pattern of activation (con-
nectionism); statistical learning (Bayesian theory); perceptual learning
(Gibson); theory change (theory theory); and self- organization and reg-
ulation (dynamic systems; some connectionist models).
A common weakness of developmental theories is that they lack an
adequate account of specific mechanisms of development. For example,
Piaget, Freud, and Erikson have given us a rich description of devel-
opment, but their mechanisms of development— equilibration and the
invariant functions for Piaget, drives for the psychoanalysts— are vague.
We cannot easily observe and study these mechanisms. In contrast, social
learning, information processing, ethological, Gibsonian, sociocultural
theories, and dynamic- systems theories emphasize processes of change
but are weaker at describing what develops. Even these process theories,
however, could be improved with more specificity. What we need are
precise accounts of moment- to- moment, real- time activities. The field
has made some progress in this regard in recent years. The microgenetic
method is a step in the right direction. Connectionist, Bayesian, and sta-
tistical learning approaches, in particular, are providing precise models
of change, including the mechanisms involved. The models depicting
two- way connections among genes, brain, and behavior (and maybe con-
texts), described in Chapter 5, are promising as well. The challenge will
be to integrate all of these mechanisms into a larger dynamic system.
The next decade likely will be an exciting time for theorists focused on
mechanisms of change.
One task for any proposed mechanism of development is to tie together
different versions of a similar skill across the lifespan. For example,
mechanisms move an infant’s understanding that a person is intention-
ally reaching for an object to a preschooler’s fuller understanding of
intentions to an adult’s mature understanding. Another task is to address
the two roles of developmental mechanisms. The first role is to facilitate
the acquisition of new skills. Many dynamic systems and connectionist
models are focused on explaining how a new skill emerges. The second
role of processes is to make these skills readily accessible for daily use.
Research suggests that much of development involves children’s learning
to use the skills they have already acquired. Children can think in words
long before they spontaneously verbally rehearse a list of items to be
remembered. Young children have a rudimentary understanding of num-
ber but are easily diverted from using this understanding by distracting
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428 c REFLECTIONS
stimuli or a large amount of information to process. Adolescents use
formal operations in some content areas but not others. Information
processing approaches have identified attention, working memory, and
retrieval as particularly important for accessing knowledge and skills.
Historical Progress of Developmental Theories
It often seems to me that’s all detective work is, wiping out your false starts and
beginning again. Yes, it is very true, that. And it is just what some people will not do.
They conceive a certain theory, and everything has to fit into that theory. If one little
fact will not fit it, they throw it aside. But it is always the facts that will not fit in that
are significant.
—aGatha Christie, Death on the Nile
A succession of developmental theories has waxed and waned in influ-
ence. Are we left with a sense of scientific progress? Has each successive
theory been better than the one before it? The traditional view of scien-
tific progress, also the commonsense view, sees the history of a discipline
as a cumulative enterprise. Each new discovery or theory builds on pre-
vious work and is a refinement of it in the search for truth. Each theory
stands until empirical observations cast doubt on its validity.
Clearly, there is continuity and a sense of theory development
between Freud and Erikson within the psychoanalytic tradition or
between classical learning theory and social learning theory within
learning theory. Over a longer period of time, however, the historical
progression of theories in this volume does not seem to follow this
pattern. One is struck more with discontinuity than with continuity
in moving from Freud to learning theory to Piaget to information pro-
cessing to dynamic systems. Each theory challenged a previous one and
proposed an attractive alternative conception of development more than
it refined the earlier theory. Often a new theory is accepted because it
corrects the excesses of an established theory, as when developmental-
ists were attracted to sociocultural approaches because they address the
social context of thinking, which is relatively ignored by information
processing approaches. Similarly, the theory- theory and core knowledge
approaches offer a plausible account for the counterevidence regarding
Piaget’s theory, specifically, early competencies and domain- specific
knowledge. A switch of allegiance occurs despite the fact that newer
theories are less well worked out than the abandoned theories. The his-
tory of developmental psychology suggests that when a theory cannot
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Historical Progress of Developmental Theories c 429
be modified satisfactorily, the stage is set for change. A discipline seems
to have a particular need at some point in history and embraces a new
theory that promises a more satisfactory view of that discipline.
Such discontinuities from one theory to another become understand-
able if one looks at Thomas Kuhn’s (1970) account of the growth of scien-
tific knowledge. Kuhn provided an alternative to the traditional account
of each theory building on previous ones in a linear fashion. Instead, he
saw successive theories as supplanting previous theories. He posited the
following historical sequence within any scientific discipline: First is a
“preparadigmatic phase,” in which no one theory or generally agreed-
upon way of studying the discipline’s subject matter has emerged. There
is debate over fundamental issues within the discipline. Next comes a
period of “normal science,” in which one paradigm dominates the field
or at least an important subarea of the field. A paradigm is a generally
accepted set of assumptions as to what should be studied, what questions
should be asked, how these questions can be studied, and how the results
should be conceptualized. For example, the information processing
approach emerged from a general agreement among developmental psy-
chologists to study the flow of information through a processing system
that resembles the operations of a computer and, furthermore, to ask
how that information is stored, not how it is strengthened as a result of
reinforcement. An investigator using this paradigm therefore is likely to
measure reaction time, types of errors, or number of items correct but
probably will not ask about reinforcement schedules. Thus, a paradigm
serves as a working model of how to do science.
A paradigm is both an intellectual framework and a sociological phe-
nomenon. Examples of this intellectual framework are the organismic,
mechanistic, and contextualist worldviews. One holding a mechanis-
tic worldview, for instance, would be more likely to develop a theory
that posits external mechanical rather than internal cognitive causes of
behavior. Also, the general- orientation section of each chapter in this
book roughly defines the paradigmatic characteristics of each theory.
With respect to the sociological aspect of paradigms, Kuhn pointed to
a “community” of scholars who share certain assumptions or ground
rules. The scholars can make rapid progress during the period of normal
science because, instead of questioning the assumptions of the approach,
they can concentrate their efforts on gathering data and solving prob-
lems identified by the paradigm. It is a time for “ mopping- up operations”
(Kuhn, 1970) to tidy up the paradigm. Scientists maintain the paradigm
by training students to carry on the tradition. The students absorb the
conventions for solving problems in the field and thereby “step into the
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430 c REFLECTIONS
circle” of that paradigm. An old paradigm never dies immediately; it just
fades away as students trained in the new paradigm enter the field and
believers in the old paradigm are ignored and left behind.
The change from one paradigm to another follows a typical pattern.
At some point, a crisis arises. Phenomena may be discovered that cannot
be explained by the current paradigm and consequently cause a crisis of
confidence in the paradigm. Examples from developmental psychology
might be the failure of learning theory to explain language development,
young children’s belief in nonconservation, and incorrect answers on
theory- of- mind tasks (specifically, not understanding false beliefs). If a
more promising alternative paradigm appears on the scene, it may win
the allegiance of the field and begin its own phase of normal science.
Thus, after a first paradigm emerges in a discipline, there is a continual
back- and- forth movement between normal science (a time of stability)
and scientific revolution (a time of change). The history of a science is
cyclic more than continuous, according to Kuhn.
Obvious examples of scientific revolutions are Darwinian theory,
Einstein’s theory of relativity, and the Copernican revolution, which
brought the view that the sun rather than earth is the center of the
universe. Each of these paradigms brought a gestalt- like shift in the way
scientists looked at facts.
It is interesting that whether a new theory, set of findings, or method
influences the field and eventually becomes a paradigm depends on
many factors that have nothing to do with the work itself. A good case
in point is the fact that Binet, the IQ pioneer, conducted experiments
on conservation and other concepts of number before Piaget was even
born. In fact, Binet published over 200 books and papers on topics such
as children’s memory and cognitive styles that had nothing to do with IQ
testing. Yet this work was, and still is, ignored for various historical and
sociological reasons (Siegler, 1992; Wesley, 1989).
Psychologists disagree about the value of Kuhn’s model for the social
sciences and about where to locate psychology in this history- of- science
model. Is psychology in a preparadigmatic phase, or has it entered the
cycle of paradigms and scientific revolutions? There has never been a
paradigm that was accepted by the entire field of psychology or even
developmental psychology. Today, psychologists still question basic
issues about development, such as whether newborns have any innate
knowledge, for example, skeletal core knowledge systems. However,
a paradigm can be restricted to a subarea within the field. From this
perspective, there are several candidates for paradigms in developmental
psychology. In fact, each of the theories described in this book has won
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Crit ical Psychology: Are Theories of Development Gendered? c 431
over a group of scholars who have accepted the assumptions and gone
about the business of solving problems defined by these assumptions.
One example is the Piagetian group in Geneva. A group of investiga-
tors accepted Piaget’s intellectual framework and proceeded as though
they were working out the details of this framework. Piaget’s theory
never quite reached this status among American researchers in cogni-
tive development. Other paradigmatic communities can be identified
for computer- simulation, particularly connectionist, approaches at
several U.S. universities, for ethology in Germany, learning in the early
1960s, and dynamic systems and the theory theory in parts of the United
States and Europe.
Regardless of whether future generations will look back on today
as a time of preparadigmatic or paradigmatic science, Kuhn’s view of
science as both continuous (during normal science) and discontinuous
(during scientific revolution) seems to have some validity in the history
of theories of developmental psychology. Both continuity and disconti-
nuity are apparent in information processing, for example. It built on
the precision and analytic posture of learning theory but won followers
in part because of dissatisfaction within the ranks of learning research-
ers, rather than simply because it produced a better version of learning
theory. An example of attempts to patch up a faltering paradigm can be
seen when learning theory posited verbal mediation (associations involv-
ing verbal labels), generalized rules, and complex hierarchies of mental
associations to try to incorporate some of the alternative explanations
offered by cognitive theories. The observable stimuli and responses went
underground, and mental S– R chains, expectations, concepts, and rules
entered the vocabulary of learning theory. However, this did not halt the
declining influence of the theory, because emerging cognitive theories
provided a more plausible explanation of anomalies that had appeared in
learning experiments.
Critical Psychology: Are Theories
of Development Gendered?
A final perspective on the various theories in this book comes from crit-
ical psychology (e.g., Parker, 2015), which critiques mainstream psychol-
ogy from a variety of perspectives. In general, it shows how the discipline
of psychology and the theories it produces are products of the culture
in which they arose and, thus, may entail biases. It questions the tradi-
tional view that the evaluation of facts is totally objective, that “there is
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432 c REFLECTIONS
only one established dogma in science— that scientists do not blindly
accept established dogma” (Brush, 1976, p. 68). Thus, critical psychol-
ogy uncovers culture- based assumptions of psychological research and
theory regarding the self, behavior, society, and development. The aim is
to produce better science and theorizing.
One influential aspect of culture, for example, is its conception of
masculine and feminine gender roles. Feminist theories have critiqued
and transformed a wide range of disciplines across the sciences and
humanities (e.g., Tong, 2013). For example, in the field of history, add-
ing the activities of women to what is studied changed models of history
from a focus on wars, generals, and rulers to the inclusion of everyday
family and community life, and social reforms. In recent years, devel-
opmentalists have drawn on feminist theories to critique, and provide
alternative perspectives on, developmental psychology (Burman, 2008a,
2008b; Miller & Scholnick, 2000; Scholnick & Miller, 2007).
Parallel to the change from cross- cultural psychology to cultural psy-
chology described in Chapter 4, work on gender is changing somewhat
from the gender- differences approach that has characterized the field of
psychology to a gender- psychology, or feminist- psychology, approach.
In the latter view, gender is not just another individual difference— an
independent variable that causes differences in thinking and behavior.
Rather, like culture (and in fact a main aspect of culture), gender per-
vades all human situations and is an inextricable part of any event. Also,
like cultural beliefs, beliefs about gender are so pervasive and deeply
ingrained that they are often invisible to people within a culture. Finally,
models of behavior and development arising mainly from one culture
or gender may not be universal or appropriate for understanding all
behaviors.
Developmentalists and feminist scholars ask some of the same
questions— about the process of acquiring knowledge, the effects of
social institutions on people, the effects of experience on one’s perspec-
tive, and the construction of social categories (Miller, 2006). There are a
number of feminist theories, such as liberal (positivist), socialist, African
American/ethnic, essentialist, existentialist, psychoanalytic, radical,
postmodern, and postcolonial theories (Rosser & Miller, 2000). Each
offers a framework through which to explore various central issues in
developmental psychology. However, despite their differences, these
feminist theories have certain commonalities. In particular, they focus on
the notion of connections rather than separation, distance, and dichot-
omy (see examples below). That is, development is as much a process
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Crit ical Psychology: Are Theories of Development Gendered? c 433
of developing relationships with others and developing an understand-
ing of the complex connections in the social and physical world as it
is a process of establishing autonomy, mastery, competition, supposed
objectivity, and analysis of reality into objects and properties. Moreover,
feminist approaches focus on the cultural, institutionalized organization
of social relations according to gender, race, class, and ethnicity (and
therefore differences in power). There is no universal child; rather there
are individual children of a particular race, ethnicity, gender, nationality,
and social class who develop in a culture that has beliefs about all these
identities that influence children’s development. A satisfactory account
of development must start with this diversity rather than bring it in after
“normal” or “typical” development is addressed.
The following are several examples of attempts, inspired by feminist
theories, to provide a broader conception of development (Miller &
Scholnick, 2000). Metaphors can have implicit cultural assump-
tions. Metaphors may depict development as a process of argument
(conflict), survival of the fittest (competition), an arrow (directionality
to development), and building or, in contrast, from a feminist perspec-
tive, a process of friendship (scaffolding), conversation (collaboration),
apprenticeship, and narrative (sense making) (Scholnick, 2000). In other
words, one could view a developing child as a solitary, distanced, sci-
entific thinker who develops concepts of isolated objects in the world,
focuses on mastery of his environment, and competes with others for
resources. In contrast, one could view development as analogous to
collaboration and the search for meaning.
Another example of uncovering implicit gender biases in research
and theorizing is the study of aggression, which can be physical, as
it typically has been studied, or relational, as is the case with gossip
(Crick & Rose, 2000). Moreover, thinking can be linear, distanced from
the object of study, and reductionist, or it can be contextual– relational,
situated, reciprocal, dialogical, connected, co- constructed, experien-
tially based, and diverse (Miller, 2000). Developmentalists have raised
other issues, such as these: Who has the authority to author an autobi-
ographical memory; whose voice and memory counts? (Fivush, 2000)
Does the world as viewed from the margins (in minority, low- power
positions) look different from the world as viewed from the center (of
power)? How do children’s essentialist concepts of gender and develop-
mentalists’ essentialist concepts of children impact development and its
study? (Gelman & Taylor, 2000) Feminist approaches clearly have close
ties to the sociocultural theories within developmental psychology. The
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434 c REFLECTIONS
inclusion of feminist theories in developmental psychology is part of a
larger movement toward a broader, more diverse, multicultural vision
of people and their development.
Conclusions
As Beilin commented, “History makes every theory look deficient in
some way” (1985, p. 9). Because no one theory satisfactorily explains
development, it is critical that developmentalists be able to draw on
the content, methods, and theoretical concepts of many theories. Each
theory has something important to say; no theory alone is sufficient.
A knowledge of the developmental theories in this volume can serve as a
heuristic for developmental researchers and professionals working with
children. Shifting from theory to theory provides a flexible perspective
on children’s behavior.
Suggesting the value of using theories flexibly does not mean, how-
ever, that there is no place for developmentalists who operate within a
single theory. There is value to pushing a single theory to its limits. As
Kuhn noted in his discussion of paradigms, sometimes rapid progress is
most likely when investigators do not question the assumptions of their
field. Finding out where a theory breaks down can be very informa-
tive. As the English logician Augustus De Morgan commented, “Wrong
hypotheses rightly worked from have produced more useful results than
unguided observation.” Given the current level of knowledge in devel-
opmental psychology, we need both eclectics and true believers.
“Where shall I begin?” asked the White Rabbit.
“Begin at the beginning,” the King said gravely, “and go on till you come
to the end: then stop.”
—Lewis Carroll (Alice in Wonderland)
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NAME INDEX
Note: Page numbers in italic represent figures and tables.
467
Abrams, S., 120
Adler, A., 98, 99
Adolph, K. E., 19, 343, 377, 380,
381, 384, 386, 390, 391, 392,
398, 413
Ainsworth, M. D., 226, 228
Akst, H., 227
Alderson-Day, B., 173
Aldridge, M. A., 390
Alibali, M. W., 318, 323
Allen, J. P., 10
Alloway, T. P., 357
Alpert, R., 287
Amaya, G., 312
American Psychologist, 289
Anderson, J., 365
Arnett, J. J., 148
Arseth, A. K., 149
Averill, J. R., 12
Baddeley, A. D., 324, 366
Baer, D. M., 284
Bahrick, L. E., 396
Bailey, D. H., 344
Baillargeon, R., 76, 388, 410
Bak, M., 301
Bakeman, R., 195
Baker, D. B., 282
Baker, R. K., 389
Bakermans-Kranenburg, M. J., 264
Bakhtiar, A., 360
Baldwin, J. M., 1
Balle-Jensen, L., 194
Banaji, M. R., 75
Bandura, A., 190, 277, 278–279,
288–300, 295, 301, 302, 303,
304, 305, 306, 307–308, 310,
314, 315, 328, 423
Barbaranelli, C., 299, 303
Barbu-Roth, M., 415
Barch, D. M., 257
Bardi, L., 228
Barnett, D., 229
Barr, R., 289, 312
Barry, O., 176
Basalla, G., 245
Bates, E. A., 357
Battaglia, M., 268
Bauer, P. J., 337, 367
Baumrind, D., 202
Beach, S. R. H., 21, 264
Beaulieu, D. A., 229
Bedny, M., 408
Beebe, M., 182
Begus, K., 369
Beilin, H., 73, 81, 434
Belsky, J., 219, 264, 270
Bendicsen, H. K., 132
Berger, S. E., 398
Bergman, A., 115
Bergson, H., 279
Berland, J. C., 165
Bernier, E. P., 77, 409
Bertenthal, B. I., 416
Best, J. R., 170, 326, 366
Bhaskar, R., 154
Bialystok, E., 201
Bidell, T. R., 86, 87
Bigler, R. S., 336
Bijou, S. W., 283, 284
Binet, A., 27, 156, 430
Biondi, M., 399
Bjorklund, D. F., 218, 233, 239,
245, 246, 271, 332, 334
Blair, C., 366
Blätter, F., 13
Blehar, M .C., 228
Blizinsky, K. D., 178
Bloom, P., 91, 313
Blumenthal, T. D., 252
Blurton-Jones, N., 230
Boas, D. A., 399
Boguszewski, K., 366
Boldt, B. R., 202
Bornstein, M. H., 195, 242, 369
Borst, G., 92
Bovet, M., 73
Bower, T. G. R., 77, 390
Bowers, E. P., 191
Bowker, J. C., 311
Bowlby, J., 99, 115, 129, 211,
214, 224–227, 234, 236, 241,
403, 423
Bowman, C. R., 56
Boyce, W. T., 264
Bradley, B. S., 283
Braga, E. S., 390
Brainerd, C. J., 330, 335, 336, 359
Brandeau, K., 360
Brannon, E. M., 90, 344
Breland, K., 282, 305
Breland, M., 282, 305
Bremner, J. G., 77, 91
Bretherton, I., 130
Breuer, J., 97
Breznitz, Z., 326
Bringuier, J., 59
Brink, K. A., 408
Brody, G. H., 21, 260, 264, 270
Bronfenbrenner, U., 185, 189, 190,
191, 209, 238
Brown, A. L., 158, 174, 333,
357, 364
Brown, R. D., 332
Brown, T. T., 250, 367
Bruce, J., 254
Brückner, G. H., 217
Bruner, J. S., 134
Brunk, M. A., 293
Brush, S. G., 432
Bryant, P. E., 73, 78
Buchanan, C. M., 298
Buckel, R., 369
Budak, D., 192
Bugental, D. B., 229, 245, 246
Bukowski, W. M., 311
Bullock, M., 357
Burman, E., 432
Burnham, J. C., 98
Bussey, K., 302
Butler, S., 218
Cacioppo, J. T., 248
Cacioppo, S., 248
Cairns, R. B., 215
Caldara, R., 251
Call, J., 239, 243
Calvert, S. L., 311
Campbell, C., 130
Campione, J. C., 174
Campos, J. J., 386
13_MIL_7898_bm_name_index_467_476.indd 467 1/19/16 11:20 AM
468 c NAME INDEX
Cañal-Bruland, R., 394
Cangelosi, A., 373, 374
Cannizzo, S. R., 333
Caprara, G. V., 299, 303, 417
Carello, C., 222
Carey, S., 344, 407
Carey, S. C., 410
Carpendale, J. I. M., 80
Carpenter, M., 244, 312
Carr, H. A., 284
Carraher, D. W., 198
Carraher, T. N., 198
Carrazza, C., 313
Carroll, L., 154, 337, 434
Carver, L. J., 256, 368
Case, R., 74, 83–85, 85, 94
Casey, B. J., 253
Cassidy, D. J., 333
Cassidy, J., 129, 228, 230, 236,
242, 243
Cassirer, E., 15
Caudill, W., 194
Caudle, F. M., 379, 386
Caylak, E., 268
Ceci, S. J., 359
Cernoch, J. M., 228
Chae, Y., 359
Champagne, F. A., 261, 263
Charcot, J., 97
Charlesworth, W. R., 232, 238, 241
Chassin, L., 418
Chavajay, P., 192, 193
Chen, C., 254
Chen, E., 202
Chen, X., 198, 200
Chen, Y., 21
Chen, Z., 344, 345
Cheng, Y., 254
Cheon, B. K., 178
Chi, M. T. H., 335
Chiao, J. Y., 178
Child, I., 99
Childs, C. P., 199
Child Trends Data Bank, 200
Cho, G. E., 199
Chodorow, N., 129
Chomsky, N., 67, 285, 321
Christie, A., 428
Church, R. B., 92
Cicchettii, D., 238, 270
Cillessen, A. H. N., 230
Clément, F., 314
Clerc, J., 334
Coffman, J. L., 339, 358
Cohen, L., 330
Cohen, R., 257
Cole, M., 155, 158, 175, 195
Cole, W. G., 412
Coleman, P. K., 298
Collins, J. L., 297
Collins, W. A., 246, 304
Cook, L. C., 417
Cookston, J. T., 201
Cooper, C. R., 193
Copernicus, N., 430
Cornoldi, C., 338
Corpuz, R., 229
Correa-Chávez, M., 196, 365
Cosmides, L., 215, 232, 233
Cote, L. R., 195
Courage, M. L., 360
Coyle, T. R., 334
Craighero, L., 313
Crane, C. C., 313
Crick, N. R., 433
Crosnoe, R., 202
Cross, D. R., 184
Csernansky, J. G., 257
Csibra, G., 230, 314
Cunningham, W., 339
Cybele, R. C., 366
Daele, L. van den, 32
Dahl, A., 386
Darwin, C., 17, 98, 213, 218, 227,
232, 430
Davidson, D. H., 195
Davidson, P., 82
Davies, P. T., 231, 261, 270
Da Vinci, L., 101
Davis, B., 227
Dawson, G., 256
Deater-Deckard, K., 366
Decety, J., 254
Dede, C., 192
Dekker, E., 280
DeLoache, J. S., 221, 333, 364
DeMarie, D., 339
De Marsico, M., 180
DeMaster, D., 368
De Morgan, Augustus, 434
Descartes, R., 19, 348
Devine, R. T., 412
De Vries, P., 101
Dexter, A., 192
Diamond, A., 92, 255, 399
Dissanayake, C., 313
Dodell-Feber, D., 408
Dodge, K. A., 341, 417
Doestoevsky, F., 173
Dollard, J., 286, 287
Doob, L., 286
Dornbusch, S. M., 202
Dorr, D., 301
Dowling, A. S., 120
Doyle, A. C., 11
Drake, S. G., 171
Drell, M. B., 366
Dugmore, N., 123
Duh, C. J., 205
Dukes, C., 332
Dunlosky, J., 358
Dunn, J., 175
Ebbinghaus, H., 278
Ebstein, R. P., 243
Eccles, J., 303
Eddington, A., 1
Edelman, G. M., 251
Edelman, M. S., 239
Eibl-Eibesfeldt, I., 217, 222, 223,
224
Eigsti, I., 313
Einstein, A., 28, 29, 36, 53, 58, 68,
145, 430
Eisenberg, N., 418
Eisner, M. P., 311
Ejesi, K., 201
Elder, G. H., Jr., 188, 190
Eliot, G., 19, 363
Eliot, T. S., 141
Elkind, D., 94
Elliott, J., 357
Ellis, B. J., 218, 233, 239, 245,
246, 264, 271
Elman, J. L., 357
Elovainio, M., 293
Engels, F., 156
Ensor, R., 177
Eppler, M., 377
13_MIL_7898_bm_name_index_467_476.indd 468 1/19/16 11:20 AM
NAME INDEX c 469
Erikson, E. H., 2, 21, 23, 95, 96, 99,
132–149, 151–152, 154, 220,
255, 265, 403, 422, 423, 424,
425, 426, 427, 428
Erlich, N., 221
Eron, L. D., 13
Escalona, S., 99
Esposito, G., 242
Euclid, 68
Evans, G. W., 365
Evans, R. I., 28, 137, 138, 139, 288
Fast, L. A., 298
Federal Interagency Forum on Child
and Family Statistics, 184
Fein, D. A., 313
Feldman, J. F., 358
Feldman, R., 242
Fernbach, P. M., 372
Fernyhough, C., 173
Ferrara, R. A., 174
Ferron, J., 339
Fey, S., 301
Fireman, G., 81
Fischer, K. W., 74, 85–88, 94, 154,
411
Fisher, D. M., 414
Fisher, P. A., 254
Fisher, S., 127
Fitzpatrick, C., 360
Fivush, R., 203, 331, 340, 433
Flavell, J. H., 52, 68, 71, 72, 79,
89, 333, 334, 337, 338, 339,
401
Fliess, W., 97
Flynn, E. G., 290, 310
Fodor, J. A., 411
Fogassi, L., 313
Fogel, A., 417
Fonagy, P., 130
Fox, N. A., 236
Fox, R., 389
Fraleigh, M. J., 202
Fraley, R. C., 131
Franchak, J. M., 381, 386
Frankenhuis, W. E., 219, 270
Franz, A., 317
Frazier, B. N., 302
Frederick II, 240
Freedland, R. L., 416
Freitag, C., 369
Freud, A., 99, 103, 133, 138,
220
Freud, S., 2, 4, 5, 10, 21, 23, 33,
95, 96–129, 130, 131, 132,
133, 134, 137, 139, 141, 144,
145, 146, 147, 148, 150–151,
152, 154, 156, 163, 220, 231,
239, 241, 265, 278, 281, 286,
287, 289, 291, 300, 303, 304,
305, 306, 308, 403, 422, 423,
424, 426, 427, 428
Freund, L. S., 164
Frias, M. T., 229
Friedrichs, A. G., 338
Frisch, Karl von, 214
Froimson, J., 241
Fuligni, A. J., 149, 150, 202
Fung, H., 202
Gabbard, G. O., 129
Gallistel, C. R., 77, 78
Galsworthy, J., 421
Garcia, C., 199
Garcia, J., 285
Garcia, V., 372
Garcia Coll, C., 201
Gardner, H., 411
Gardner, R., 292
Gardner, W. P., 167
Garvey, A., 417
Gathercole, S. E., 357
Gatzke-Kopp, L. M., 238
Gauvain, M., 162, 165, 167, 182,
199
Gay, J., 175
Gazzaley, A., 132
Gazzola, V., 245
Gearhart, M., 186
Geary, D. C., 233, 344
Geert, P. van, 417
Geisel, T. S. (Dr. Seuss), 137
Gelderen, L. van, 198
Geldhof, G. J., 191, 230
Gelman, R., 73, 77, 78, 410
Gelman, S. A., 75, 302, 407, 433
Gergely, G., 314
Gerhardstein, P., 331
Gesell, A., 9
Ghetti, S., 338, 368
Gibson, E. J., 21, 23, 24, 74, 188,
237, 377, 378–397, 399, 403,
407, 412, 422, 423, 424, 425,
426, 427
Gibson, J. J., 378, 383, 390, 395
Gill, M. M., 132
Gill-Alvarez, F., 19
Gillath, O., 242
Glatz, T., 298
Glenberg, A. M., 368
Glick, J. A., 175
Gluck, S., 205
Gobbo, C., 82
Godwin, C. A., 132
Godwin, J., 341
Goethe, J. W. von, 96
Golding, C., 179
Goldin-Meadow, S., 92, 369
Goldsmith, D., 194
Goldstein, W., 194
Göncü, A., 158
Gonzales, M., 198
Gonzales, N., 150
Goodman, G., 359
Gopnik, A., 76, 371, 406, 408
Gordon, I., 242
Gordon, W., 65
Gorky, M., 139
Gottlieb, G., 215
Gould, S. J., 227
Graesser, A. C., 358
Graham, A. M., 254
Grammer, J. K., 339, 358
Greenberg, R. P., 127
Greenfield, P. M., 170, 198, 199,
200
Greenwald, A. B., 247
Griffin, A. M., 221
Griffiths, T. L., 371
Griggs, R. A., 280
Griskevicius, V., 246
Groen, J., 280
Gross, D., 390
Grossman, T., 254, 255, 368
Guan, S. A., 170
Guberman, S. R., 186
Gunderson, E. A., 298
Gureckis, T. M., 350
Gutbir, T., 243
Gweon, H., 408
13_MIL_7898_bm_name_index_467_476.indd 469 1/19/16 11:20 AM
470 c NAME INDEX
Haan, M. de, 248, 250, 367
Hacker, D. J., 358
Haden, C. A., 335
Haggbloom, S. J., 289
Hahn, C., 369
Haist, F., 250, 367
Haldane, J. B. S., 212
Hall, C. S., 100, 102, 106, 114,
121, 122, 151
Hall, G. S., 98
Hallinan, E. V., 90
Haltigan, J. D., 131
Hamlin, J. K., 90, 91, 313
Harkness, S., 176
Harris, F. R., 284
Harris, P. L., 75, 314
Hart, B., 372
Hartmann, H., 99, 132
Hartup, W. W., 379
Hawkins, L. B., 399
Hawley, P. H., 230, 234
Hay, J. F., 372
Hayes, C., 243
Hayes, M., 198
Hayne, C., 289
Haynes, O. M., 195
Heatherton, T. F., 291
Hebb, D. O., 20, 285, 335
Hegel, G. W. F., 157
Heider, K. G., 292
Heine, S., 184
Heinrichs, M., 390
Helt, M. S., 313
Helwig, C. C., 411
Hencke, R. W., 86
Henderson, A. M., 313
Henggeler, S. W., 293
Henrich, J., 184
Hentges, R. F., 238
Herrmann, E., 243
Herrmann, P. A., 313
Hess, E. H., 216
Hessel, E., 10
Hickmann, M., 153
Hicks, V. C., 284
Hildebrand, E. A., 313
Hill, P. L., 148
Hillairet de Boisferon, A., 387
Hinde, R. A., 230
Hindorff, L. A., 260
Hines, M., 311
Hintzman, D. L., 363
Hirshkowitz, A., 399
Hitch, G. J., 326
Hitler, A., 138
Hobbes, T., 17
Hogan, J. D., 67
Holmes, C. J., 366
Holmes, O. W., 58, 330
Honeycutt, H., 264, 271
Hopkins, J. R., 133, 147
Horga, G., 260
Horney, K., 99, 129
Horst, J. S., 352
Hoss, R. A., 221
Hou, Y., 341
Houdé, O., 92
Howard, L. H., 313
Howe, M. L., 331, 359
Hoyt, J. D., 338
Huang, Y., 410
Hudson, J. A., 159, 336
Huggenberger, H. J., 252
Hughes, C., 177, 412
Hull, C., 286, 378
Hume, D., 14
Hurley, K. B., 387
Hutchins, E., 159
Hutchinson, G. E., 212
Hyde, L. W., 267, 268, 269
Iaccino, W. J., 67
IJzendoorn, M. H. van, 229, 264
Influs, M., 243
Inhelder, B., 28, 29, 55,
73, 74
Ishak, S., 392
Islam, T., 242
James, W., 15, 285
Jankowski, J. J., 358
Jantz, T. K., 132
Jaswal, V. K., 312
Jenkins, E., 317, 329, 342, 343
Jenkins, G. W., 416
Jennings, J. A., 188
Jensen, P. S., 240
Jernigan, T. L., 250, 367
Joanisse, M. F., 351
Johann, M., 242
Johnson, M. H., 250, 253, 255,
367, 368
Johnson, S. P., 77, 380
Johnson-Laird, P. N., 125
Johnston, J., 383
Johnston, M. K., 283
Jokela, M., 293
Jones, E., 96, 98, 100
Jones, J. D., 236, 243
Jones, M. C., 281
Jones, M. N., 373
Jong, P. F. de, 198
Joyce, J., 297
Joyce, N., 282
Juang, L. P., 201
Jung, C., 98, 99
Kaciroti, N., 302
Kaiser, M. K., 355
Kaminski, J., 239, 243
Kamp, J. van der, 394
Karasik, L. B., 392
Karmiloff-Smith, A., 92, 249, 343
Karraker, K. H., 298
Karremans, J., 230
Kasparov, G., 322
Kaur, T., 260
Kearins, J. M., 171
Kearney, J. K., 394
Keating, D. P., 91
Keeney, T. J., 333
Keil, F. C., 407
Keil, V., 341
Kellman, P. J., 389
Keltikangas-Järvinen, L., 293
Kendal, R. L., 290
Kendler, H. H., 318, 362
Kenny, S., 360
Keysers, C., 245
Kierkegaard, S., 152
Killen, M., 311
Kimble, G. A., 279
Kim-Spoon, J., 366
King, B. J., 417
King, M., 243
King, R. A., 120
Kingsolver, B., 335
Kinzler, K. D., 409
Kirkwood, H., 357
Kitayama, S., 154
13_MIL_7898_bm_name_index_467_476.indd 470 1/19/16 11:20 AM
NAME INDEX c 471
Kivimäki, M., 293
Klahr, D., 323, 346, 357, 358
Klein, G. S., 132
Klein, M., 99, 132
Klopfer, P. H., 220
Kluger, J., 132
Knott, L. M., 359
Koch, B. J., 132
Koelling, R. A., 285
Koeltzow, T. E., 366
Koenig, M. A., 75, 314
Koenig, O., 222
Koeske, R. D., 335
Koffka, K., 378
Kohlberg, L., 75
Kolkman, M. E., 326
Krafft, C. E., 249
Kretch, K. S., 386, 392
Kreutzer, M. A., 338
Krieger, S. C., 132
Kris, E., 99
Kroesbergen, E. H., 326
Kroger, J., 149
Krowitz, A., 386
Kruger, A. C., 186
Kuhl, P. K., 22
Kuhn, D., 71, 181, 193
Kuhn, T., 429, 430, 431, 434
Kuo, S. I., 246
Laible, D., 241
Lam, S., 299
Lambercier, M., 28
Lampl, M., 381
Lane, J. D., 408
Langer, A., 386
Langlois, J. H., 221
Lansu, T. A. M., 230
Lazzarin, F., 338
Le Corre, M., 344
Lee, J. K., 368
Lee, S., 198
Legare, C. H., 313
Leibniz, G. W., 14–15
Leichtman, M. D., 359
Leiderman, P. H., 202
Leinbach, J., 350
Leon, M., 300
Leonard, C., 338
Leontiev, A. N., 156
Lerner, J. V., 191
Lerner, R. M., 191
Levy, R. I., 292
Lewis, M. C., 417
Li, Y. J., 341
Liben, L. S., 56, 91, 336
Libertus, M. E., 90
Lickliter, R., 264, 271
Lillard, A. S., 366
Lin, S., 202
Lindsay, R. K., 322
Lindzey, G., 122, 151
Lingeman, J. M., 413
Linzarini, A., 92
Lipp, O. V., 221
Lobo, S. A., 398
LoBue, V., 221
Locke, J., 14, 19, 305
Lofruthe, A., 369
Looft, W. R., 71
López, A., 196
Lorenz, K. Z., 211, 214, 216, 219,
220, 221, 227, 234
Lortie-Forgues, H., 343
Lourenco, O., 68, 70, 77
Love, B. C., 350
Love, M., 390
Lukowski, A. F., 337
Lumeng, J. C., 302
Luria, A. R., 155, 156, 162,
173, 186
Lyons, K. E., 338
Mace, W. M., 364
Machado, A., 68, 70, 77
Mackay, K., 359
MacNeill, L. A., 231
Macris, D. M., 372
MacWhinney, B. J., 350
Maddux, J. E., 296
Mahajan, N., 91, 313
Mahalingam, R., 150
Mahler, M. S., 115, 228
Main, M., 228
Malloy, A., 359
Malti, T., 311
Manago, A. M., 170, 199
Mandler, G., 362
Manning, L. G., 270
Marcia, J. E., 149
Marini, Z., 82
Markman, E. M., 371
Marks, A., 201
Markus, H. R., 154
Marshall, P. J., 313
Martin, M. J., 231, 238
Martinussen, M., 149
Marx, K., 98, 156
Mascaro, O., 230, 314
Mascolo, M. F., 82, 87
Mash, C., 242
Masten, A. S., 366
Matlen, B. J., 358
Maurice-Naville, D., 80
Maynard, A. M., 199, 200
Mayor, J., 353
McCain, G., 12
McCloskey, M., 355
McDaniel, C., 389
McDonald, F. J., 301
McDonald, J., 262, 350
McGrew, W. C., 230
McLean, K. C., 149
McMurray, B., 352, 369
McPartland, J., 256
McWilliams, K., 359
Mead, G. H., 15
Mehta, M. A., 254
Mejía-Arauz, R., 192, 196, 206,
365
Meltzoff, A. N., 225, 310, 312,
313, 406
Mendelson, T., 228
Metcalfe, J., 368
Michaels, C. F., 222
Mikulincer, M., 229
Miller, A., 143
Miller, G. E., 265
Miller, N. E., 286, 287
Miller, P. H., 6, 74, 169, 205, 247,
259, 326, 333, 334, 334, 339,
366, 401, 432, 433
Miller, P. J., 199, 202
Miller, S. A., 77, 339
Miller, W. N. E., 286
Mills, C. M., 314
Mitchell, L., 148
Miyake, A., 366
Moffitt, T. E., 269, 366
Molenaar, P. C. M., 417
13_MIL_7898_bm_name_index_467_476.indd 471 1/19/16 11:20 AM
472 c NAME INDEX
Molloy, L. E., 10
Molnar, P., 312
Montag, J. L., 373
Montagu, A., 213
Montangero, J., 80
Montero, I., 173
Montessori, M., 17
Montgomery, D. E., 366
Moore, M. K., 225, 312
Morelli, G. A., 194
Morgan, R., 397
Morra, S., 82
Morris, P. A., 189, 191
Morsella, E., 132
Mowrer, O. H., 286
Mrazek, A. J., 178
Muentener, P., 312
Müller, U., 80, 91
Munakata, Y., 352
Munholland, K. A., 130
Munroe, R. L., 182, 199
Murphy, M. L. M., 265
Murray, F. B., 75
Murry, V. M., 21
Muscatell, K., 254
Mushin, I., 312
Naglieri, J., 366
Nagy, E., 312
Najafi, B., 192, 206
Narr, R. K., 359
National Center for Education
Statistics, 198
Needham, A., 388
Nelson, C. A., 358
Nelson, C. A., III, 236
Nelson, K., 203, 336, 340
Neubauer, P. B., 120
Neville, H. J., 251
Nevo, E., 326
Newcomb, A. F., 304
Newcombe, N. S., 352
Newell, A., 321
Newport, E. L., 247
Newton, H. P., 138
Newton, I., 12, 355, 406
Ng, F., 299
Nielson, M., 312
Nietzsche, F., 104
Norenzayan, A., 184
Nowak, A., 417
Nunes, T., 78
Oakes, L. M., 352, 387
Oberlander, T. F., 263
Ogle, C. M., 359
Okamoto, Y., 85
Omark, D. R., 239
Opfer, J. E., 405
Oppenheim, D., 194
Ornstein, P. A., 339, 358
Ortigo, K. M., 129
Orvos, H., 312
Osser, H., 383
Oudekerk, B. A., 10
Over, H., 244, 312
Overton, W. F., 14, 417
Owsley, C. J., 383
Paik, J. H., 198, 205
Palmer, C., 390
Palombo, J., 132
Panagiotides, H., 256
Panchanathan, K., 219
Papert, S., 26
Paris, S. G., 184
Parke, R. D., 115
Parker, I., 431
Parmiggiani, A., 373
Pasteur, L., 287
Pastorelli, C., 303, 417
Pathman, T., 368
Patterson, G. R., 306
Pavlov, I., 286
Paz-Alonso, P. M., 359
Peace, M. A., 181
Pecheux, M., 390
Peeke, H. V. S., 228
Pelucchi, B., 372
Pepper, S. C., 14, 15–16
Perez, S. M., 162, 165,
167
Perfors, A., 371
Perner, J., 404
Perry, D. G., 315
Peterson, B. S., 260
Peterson, C., 89, 341
Pettigrew, T. L., 389
Pfeifer, J. H., 254
Philibert, R. A., 21, 264
Piaget, J., 2, 3–4, 5, 7, 8, 9, 10,
11, 13, 18, 21, 23, 24, 25,
26–83, 85, 86, 87, 88, 89–94,
96, 99, 100, 102, 109, 112,
120, 122, 125, 137, 145, 148,
154, 155, 156, 157, 159, 163,
168, 169, 172, 173, 177, 179,
188, 203, 219, 220, 235, 237,
239, 247, 255, 265, 278, 284,
285, 289, 296, 300, 301, 303,
304, 305, 306, 308, 318, 320,
322, 327, 328, 330, 341, 346,
352, 361, 362, 368, 373, 381,
393, 404, 405, 407, 408, 412,
415, 422, 423, 424, 425, 426,
427, 428, 430, 431
Piaget, V., 35
Piazza, M., 410
Pick, A. D., 379, 381, 383, 388,
390, 392, 394, 396
Pick, H. L., 388, 396
Pietromonaco, P. R., 242
Pilling, K., 312
Pine, F., 115
Ping, R. M., 369
Pipe, M., 359
Plato, 363–364
Plötner, M., 244
Pluess, M., 219, 270
Plumert, J. M., 352, 394
Plunkett, K., 353
Poincaré, J. H., 12
Pollak, S. C., 131
Pollak, S. D., 262
Pomeranatz, E. M., 299
Pornpattananangkul, N., 178
Porter, R. H., 228
Poulin-Dubois, D., 389
Powell, L., 410
Powers, A., 253
Powers, S. I., 242
Pratkanis, A. R., 247
Price, J. M., 341
Price-Williams, D. R., 65
Profet, M., 240
Proffitt, D. R., 355
Purtell, K. M., 339
Rader, N., 385
Rakison, D. H., 348, 351, 352
13_MIL_7898_bm_name_index_467_476.indd 472 1/19/16 11:20 AM
NAME INDEX c 473
Ramani, G. B., 358
Ramirez, M, III, 65
Ramsey, J. L., 221
Rank, O., 99
Rapaport, D., 99, 132
Rapport, S., 213
Ratner, H. H., 186
Rau, L., 287
Raver, C. C., 366
Rayner, R., 280
Razza, R. A., 366
Reddy, V., 287
Reese, H. W., 14, 16
Regalila, C., 299
Regolin, L., 228
Reyher, J., 128
Reyna, V. F., 330, 335, 336, 359
Rhodes, M., 244
Rholes, W. S., 242
Rice, K., 129
Richey, E. M., 366
Ridley-Johnson, R., 414
Riegel, K., 16
Riggins, T., 358
Risley, R. R., 372
Ritter, P. L., 202
Rivas-Drake, D., 150
Rivera, N., 199
Rizzolatti, G., 313
Roberts, D. F., 202
Robinson, S. R., 19, 343, 381,
384, 386
Robson, C., 301
Robson, K. S., 227
Rochat, P., 76, 397
Roediger, H. L., 363
Rogoff, B., 158, 163, 165, 166,
167, 169, 170, 171, 180,
183, 185, 192, 194, 196, 206,
208, 365
Rohleder, N., 265
Roisman, G. I., 131
Romens, S. E., 262
Ronai, Z., 242
Rose, A. J., 433
Rose, S. A., 358
Rosenberger, N., 148
Ross, D., 277, 290
Ross, S. A., 277, 290
Rosser, S. V., 432
Rousseau, J. J., 17
Rousselet, G. A., 251
Rovee-Collier, C. K., 331
Rubenstein, A. J., 221
Rubin, K. H., 311
Ruffman, T., 73
Runions, K. C., 301
Russell, J., 76
Russell, J. W., 302
Russell, M. J., 228
Ruvalcaba, O., 196
Sabbagh, M. A., 75
Saby, J. N., 313
Saffran, J. R., 372
Sagi, A., 229
Sagi-Schwartz, A., 229
Salmon, K., 359
Sameroff, A. J., 230
Samuelson, L. K., 352, 416, 417
Sandel, T. L., 199
Sargent, J. D., 291
Saxe, G. B., 186, 197
Saxe, R., 408
Scabini, E., 299
Scarr, S., 6
Schachinger, H., 252
Schamberg, M. A., 365
Schauble, L., 343
Scheper-Hughes, N., 179
Schlein, S. P., 146
Schlesinger, M., 352, 369, 373,
374
Schliemann, A. D., 198
Schnable, P. S., 259
Schneider, W., 334, 339, 357
Scholnick, E. K., 432, 433
Schonert-Reichl, K. A., 367
Schore, A. N., 131
Schwarzer, G., 369
Scribner, S., 155
Sears, R. R., 286, 287
Segal, E. M., 12
Seidenberg, M. S., 351
Seier, W. L., 247, 339
Setoh, P., 410
Seuss. See Geisel, T. S. (Dr. Seuss)
Shackman, J. E., 131
Shahaeian, A., 89
Shakespeare, W., 18, 155, 212
Shalev, I., 264
Shanahan, M. J., 188
Shanker, S. G., 417
Shao, Y., 341
Shapley, H., 213
Sharp, D. W., 175, 413
Shaver, P. R., 228, 229, 230, 236,
243
Shaw, G. B., 139
Sheese, R., 82
Sherman, L. J., 129
Shweder, R. A., 184, 194
Siegal, M., 76
Siegler, R. S., 71, 198, 317, 320,
323, 328, 329, 334, 342, 343,
344, 344, 345, 346, 353, 353,
354, 355, 358, 405, 430
Signorella, M. L., 336
Simion, F., 228
Simon, H. A., 321
Simon, T., 27
Simpson, J. A., 242, 246
Sinclair, H., 73
Skerry, A. E., 77, 409
Skinner, B. F., 282, 283, 285, 289
Slater, A. M., 77
Slaughter, V., 89, 221
Slavich, G. M., 265
Sloane, H. N., 283
Sloutsky, V., 90
Smetana, J. G., 311
Smith, E. D., 366
Smith, J. D., 306
Smith, L., 80
Smith, L. B., 373, 401, 412, 413,
414, 415
Snyder, P. J., 313
Sobel, D. M., 372
Soken, N., 387
Solomon, J., 228
Somerville, L. H., 254
Sommerville, J. A., 313
Soska, K. C., 380
Southgate, V., 369
Sowell, E. R., 92
Spangler, G., 242
Spelke, E. S., 77, 389, 409, 410
Spencer, J. P., 416
Sperber, D., 233, 314
Spiker, C. C., 18
13_MIL_7898_bm_name_index_467_476.indd 473 1/19/16 11:20 AM
474 c NAME INDEX
Spinrad, T. L., 418
Spitz, R. A., 99, 115
Spock, B., 139
Spranger, E., 17
Spranger, M., 373
Stalin, J., 157
Starr, A., 90
Steele, H., 130
Steele, M., 130
Steenbeck, H., 417
Stein, G., 297
Steinberg, L., 253
Sterbini, A. S., 180
Stern, D. N., 115
Stern, E., 343
Stevenson, H. W., 198
Stigler, J. W., 197, 198
Stiles, J., 250, 367
Stipek, D., 247
Strachey, J., 105
Streri, A., 390
Sturge-Apple, M. L., 270
Sullivan, H. S., 99
Sung, S., 246
Suomi, S. J., 230
Suor, C. M., 270
Suor, J. J., 270
Super, C. M., 176
Suter, S. E., 252
Suwalsky, J. T. D., 195, 369
Svaren, J., 262
Svoboda, C. P., 71
Syed, M., 148, 149, 201
Szeminska, A., 28
Tamis-LeMonda, C. S., 388, 392,
398
Taraban, R., 350
Taylor, A. M., 240
Taylor, M. G., 433
Telzer, E. H., 150
Temperini, M., 180
Tenenbaum, J. B., 371
Tharp, R. G., 182
Thayer, G. H., 217
Thelen, E., 401, 412, 413, 414,
415
Thiessen, D., 233
Thiessen, E. D., 372
Thioux, M., 245
Thompson, R. A., 240, 241
Thorndike, E. L., 222
Tinbergen, N., 214, 217, 236
Tobin, J. J., 195
Tolman, E. C., 7
Tomaselli, K., 312
Tomasello, M., 186, 239, 243, 244,
245, 253
Tong, R. P., 432
Tooby, J., 215, 232, 233
Toulmin, S., 158
Towse, J., 326
Trembath, D., 313
Triesch, J., 317
Tsai, K., 150
Tuddenham, R. D., 29
Tulviste, P., 168
Turiano, N. A., 148
Turiel, E., 411
Twain, M., 106, 278
Valenzi, S., 242
Vallacher, R. R., 417
Valsiner, J., 158
van der Kamp, J. See Kamp, J.
van der
Van de Vijver, 175
Van de Walle, G., 344
van IJzendoorn, M. H. See
IJzendoorn, M. H. van
van’t Noordende, J. E., 326
Vivanti, G., 313
Vizioli, L., 251
Voltaire, 71
Vondra, J. I., 229
Vuyk, R., 80
Vygotsky, L. S., 2, 9, 21, 23, 24, 86,
153–188, 192, 198, 204–205,
207–209, 231, 232, 239, 265,
300, 303, 304, 306, 327, 328,
330, 362, 403, 419, 422, 423,
424, 426
Waddington, C. H., 217
Wadsworth, M. E., 270
Walk, R. D., 377, 386
Wall, S., 228
Wallace, A., 213
Wallace, J. G., 323, 357
Wallbank, T. W., 240
Walters, R. H., 277, 288,
306
Walton, G. E., 390
Wang, F. L., 418
Wang, Q., 340, 341
Wang, S.–H., 199
Wang, Z., 310
Warneken, F., 244
Wason, P. C., 125
Wass, R., 179
Waters, E., 228
Watson, J. B., 279, 280, 282,
304
Watson, J. S., 396
Webb, S. J., 256
Weerth, C. de, 270
Weinert, F. E., 339
Weinstein, H., 194
Weintraub, R. A., 5
Wellman, H. M., 89, 337, 371,
407, 408
Wellman, H. W., 404
Wen, N. J., 313
Wertsch, J. V., 45, 153, 155, 156,
158, 176
Wesley, F., 430
Westen, D., 129
White, B. L., 9
White, R. W., 132
White, S., 182
White, S. H., 15, 285
White, T. L., 359
Whitehouse, H., 313
Whiten, A., 310, 312
Whiting, J., 99, 286
Whittle, S., 254
Wilcox, T., 399
Williamson, R. A., 310, 312
Wilson, A., 243
Wilson, E. O., 212, 214
Wimmer, H., 404
Winkler-Rhoades, N., 410
Winnicott, D. W., 115
Winsler, A., 173
Witenberg, R. T., 301
Witt, J. K., 368
Wober, M., 176
Wohlwill, J. F., 71
Wolf, M. M., 284
Wood, L. A., 290, 310
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NAME INDEX c 475
Woodward, A. L., 90, 313
Wright, H., 213
Wu, D., 410
Wu, D. Y. H., 195
Wynn, K., 91, 313
Xu, F., 371, 372
Yermolayeva, R., 348, 351, 352
Yonas, A., 379
Young, J. W., 19
Yu, T., 264
Zajonc, R. B., 306
Zaman, W., 203
Zeanah, C. H., 236
Zeitlin, M., 176
Zelli, A., 417
Zeng, R., 199, 200
Zhang, X., 192, 196
Zimmerman, P., 242
Zochowski, M., 417
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Abilities. See also Competencies
assessing, 175–176, 249
concrete operations, 48 (See also
Concrete operational period)
ego and, 102 (See also Ego)
emergence of, 414
of infants, 22, 81–82, 90–91,
224–225, 233, 244, 251,
369 (See also Locomotion,
of infants)
mathematical, 197, 297 (See
also Mathematical
understanding)
overestimation of, 198
skill development, 10, 18, 22,
86, 163
underestimation of, 76–78
verbal, 74, 173, 186
Abnormal behavior
behavior modification and, 284
environment and, 222
Erikson’s study of, 146
normal–abnormal continuum,
110–111
origins of, 108–109
Abstract modeling, 290, 296. See
also Modeling
Abstract vs. concrete thought,
168, 181
Accommodation. See also
Equilibration
defined, 58
in information processing, 323
Piagetian view of, 58–62, 72,
120, 219, 235, 422, 426
Acculturation, 201
Action mirroring, 313
Activation
of attachment, 226, 227,
228–230
of brain and neural networks,
245, 255, 348, 367,
368–369, 399
in connectionist models, 348–
349, 352, 356, 423, 427
of evolved behavior, 235
of stress responses, 264
Adaptation
aggression and, 231
biological approach to, 13, 31,
62, 63
cognitive, 58–60, 233
during development, 245–248
to environment, 31, 33, 34, 69,
226, 237, 378, 395, 422,
424, 425
ethology and, 13, 22, 218,
219, 235
genetics and, 215, 271
intelligence and, 31
optimal, 237
to social/cultural change, 200,
221
Adaptive behavior, 199, 426
Affordances, 379–381, 396,
397, 422, 424, 426
Agency
in Gibson’s theory, 394, 396
in social learning theory, 299–300
Aggression
culture and, 231, 292, 306
as destructive instinct, 100,
111, 234
displaced, 125, 239
gender and, 302, 433
imitation and, 288, 291
information processing and, 341
instigators of, 6, 13, 131, 219,
246, 291, 298, 301, 417,
418
natural settings and, 310–311
relational, 311
social learning theory and, 277,
286, 306–307
study of, 13, 127, 230–231, 237,
290–291, 418–419, 433
superego and, 105
Alice’s Adventures in Wonderland
(Carroll), 154
Altruistic behavior, 214
Anal stage (in Freud’s theory), 109,
114, 116–117, 122, 220
“Analysis of a Phobia in a Five-
Year-Old Boy” (Freud), 119
Animal Dreams (Kingsolver), 335
Anxiety
arousing, 103–104, 113, 116,
281
coping with, 109, 113, 130, 140,
298
defined, 121
effect on ego, 102–103,
117–118
Freud’s study of, 10, 100
stage regression and, 33, 114
stress and, 219, 270
Appropriation, 169, 177, 185
Artificial intelligence, 321–322, 373
Assessment
of abilities, 175–176, 249
of attachment, 229
of development, 65, 91, 362, 404
dynamic, 174, 179–180, 183
in education, 66
in information-processing theory,
328, 345, 362
motivation and, 309
nonverbal, 77
Assimilation. See also Equilibration
defined, 58
in information processing, 323
Piagetian view of, 58–62, 67, 72,
120, 219, 235, 422, 426
Associations. See also Free
association; Stimulus–
response model
in connectionist models, 7, 356
environmental effects, 20
in language, 321, 351
learning and, 355, 361, 423, 431
in social learning, 280, 282, 311
Attachment
activation of, 226, 227, 228–230
applications of, 123, 236
Bowlby’s theory of, 99, 129,
224–227
infant–caretaker, 99, 114–116,
123, 129–131, 214,
224–232
research in, 236, 241–243
significance of, 130, 183
SUBJECT INDEX
Note: Page numbers in italic represent figures or tables.
477
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478 c SUBJECT INDEX
Attractor state, 415, 417, 419
Autobiographical memory, 331. See
also Memory
Automatization, 354, 427
Autonomy vs. shame and doubt (in
Erikson’s theory), 135, 136,
137, 140–141
Avoidant attachment, 229. See also
Attachment
Baby box, 283
Babyishness, 227, 227
Baddeley’s memory model,
324, 366
Balance-scale task, 344, 344–345
Basic trust vs. basic mistrust (in
Erikson’s theory), 136,
139–140
Bayesian networks (models), 312,
369–373, 403, 409, 427
Behaviorism, 67, 278, 279. See
also Learning theory
Behavior modification, 278, 283, 284.
See also Learning theory
Bioecological theory. See
Bronfenbrenner’s
bioecological theory
Biological approach (in Piaget’s
theory), 31
Biological energy (in Freud’s theory),
100, 101, 423
Biology vs. culture. See Nature vs.
nurture
Bowel training, 140, 141. See also
Toilet training
Brain. See also Neuroscience
anatomy of, 233, 249–250, 399
behavior and, 22, 92, 132, 236,
245, 414
connectionist models of (See
Connectionist models)
development of, 250–256, 367,
368, 424, 425
emotion processing in, 131
(See also Emotions)
evolution of, 232, 248
genetics and, 21, 178, 253,
257–258, 267, 268–269
id/ego/superego as regions of,
105–106
imaging of, 131, 212, 242,
248–249, 268, 398–399
(See also Neuroimaging)
maturation of, 22, 64, 83, 88,
91–92, 339, 426
patterns of activity in, 313,
366, 369
plasticity of (See Plasticity)
research on, 248, 253, 408
Bronfenbrenner’s bioecological
theory, 188–192
Candidate gene approach, 259.
See also Genetics
Capitalistic view of human nature.
See Human nature
Caretakers, infant–caretaker
attachment, 224–232
Case’s neo-Piagetian theory,
83–85, 85
Cathexis, 114, 118
Causation, triadic reciprocal, 292,
304, 305, 315
Central conceptual structures, 84
Central executive, 324, 325. See
also Executive function
Centration, 46
Change. See also Qualitative vs.
quantitative development
in children over time, 8, 9,
80–81
dialectical, 157, 176–177
phylogenetic vs. ontogenetic, 218
social change and culture,
198–200
structural, 33, 65, 82, 250, 303
Childhood and Society (Erickson),
133
Child-in-activity-in-culture concept
of Vygotsky, 158–163,
168, 179
Child’s Conception of Physical
Causality, The (Piaget), 28
Child’s Conception of the World
(Piaget), 28
Chunking, 335, 357, 360
Civilization and Its Discontents
(Freud), 98
Classical conditioning, 280, 282,
284. See also Conditioning
Classical learning theory, 278, 279,
428. See also Learning
theory
Class inclusion, 49, 50, 51, 63, 64,
89, 188
Clinical methods, 34, 65, 79
Cognition. See also Metacognition
brain development and,
252–253
central role of, 66–68
culture and, 160
embodied, 368–369, 396
hot vs. cold, 308–309, 423
human evolution of, 243–245
perception and, 397
physical maturation and, 22
social cognition, 47–48, 125,
365 (See also Intelligence;
Social cognition)
Cognitive adaptation, 58–60, 233.
See also Adaptation
Cognitive architecture, 323, 329,
346, 361
Cognitive capacity, 66, 84–85.
See also Memory
Cognitive development. See also
Learning
in information-processing theory,
318, 349
in Piaget’s theory, 62–65, 89,
91–92
in social learning theory,
303–304, 309–310
in Vygotsky’s theory, 174, 183
Cognitive equilibration, 60–61. See
also Equilibration
Cognitive growth, 31
Cognitive immaturity, 247
Cognitive neuroscience. See
Neuroscience
Cognitive organization, 57–58, 245.
See also Structuralism
Cognitive psychology, 214–215,
285, 352. See also
Cognitive science
Cognitive rehearsal, 294
Cognitive science, 132, 312,
322, 357, 365. See also
Information-processing
theory
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SUBJECT INDEX c 479
Cognitive-structural theory. See
Piaget’s cognitive-structural
theory
Collaborative learning, 179,
180–181, 187, 190, 239
Collaborative problem solving, 166,
192–193, 244
Collective efficacy, 299
Collectivism, 199–200, 204, 340
Commitment, 149
Communication, 387–388, 417.
See also Language; Speech
Compensation, 49, 60, 73, 101
Competencies. See also Abilities
assessing, 389, 428
culture and, 140
peer collaborations, 192
research on, 78
secure attachment and, 229
social learning and, 289
zone of proximal development, 163
Computational models. See also
Bayesian networks (models);
Connectionist models;
Production systems
applications of, 403
defined, 320
development of, 329
purpose of, 321, 322
robotics compared with, 373
self-correction in, 327, 351
shortcomings with, 362–363
types of, 346–347
Computer processing, 319, 321,
363–364. See also
Information-processing
theory
Concrete operational period, 36,
48–51, 54, 55, 73
Conditioning, 278. See also
Classical conditioning;
Operant conditioning
Conflicts
in collaborative problem
solving, 192
dominance hierarchy and, 231
in Erikson’s theory, 147
in families, 201
internal, 121
reinforcement and, 73, 307
Conjunction, 53
Connectionist models. See also
Neural networks
application of, 312, 360–361,
364, 403
complexity of, 369
described, 347, 347–353
developmental issues with,
422–425, 427
distributed activation
(See Activation)
dynamic systems vs., 416
as a neural network, 7, 347–348
social context and, 365
Conscience, 105, 110, 118,
141–142, 287. See also
Superego
Conscious behavior, 105, 107,
108, 132
Conservation
age differences and, 345
culture and, 165
development of, 188, 291,
306, 430
perceptual learning and, 397
Piagetian view of, 48, 60, 68,
70–71, 73–76, 89, 92
training in, 369
Construction of Reality in the Child
(Piaget), 43
Contextualism. See also Developing-
person-in-context
distinguishing among worldviews,
422, 423, 429
in Erikson’s theory, 145
human nature and, 177, 234, 304
origin of, 188
purpose of, 15–16, 417
qualitative and quantitative
change in, 18
Contextual metaphors, 16
Control systems, 225–226, 234,
423
Conversations, culture and,
202–203
Coordination
of assimilation and accommoda-
tion, 60
in children, 87–88
eye–hand, 65
in infants, 81–82
of secondary schemes, 39–40
Core knowledge theory
conceptual development, 403
described, 409–412, 428
developmental issues in, 419,
422, 423, 424, 425, 426
Created environment, 293
Crisis vs. commitment, 149
Critical periods, 21, 219
Critical psychology, 431–432
Cross-cultural psychology, 162, 432
Cross-cultural research, 187,
194–198
Cultural apprenticeships, 166
Cultural neuroscience, 178. See
also Neuroscience
Cultural psychology. See also
Vygotsky’s sociocultural
theory
origins of, 2, 162, 432
trends in, 205–207
Cultural transmission, 244
Culture
aggression and, 231, 292, 306
beliefs and practices in, 196, 308
biology vs. (See Nature vs.
nurture)
competencies and, 140
contexts of, 190
dynamic skills and, 87
effects of schooling, 175, 194,
196–198, 200
imitation and, 140, 221, 313
infant sleeping arrangements
and, 194
influence of, 432
information processing and,
194–196, 365
learning and, 221
memory and, 340–341
narratives and conversations,
202–203
peer collaboration and, 192–193
physical ecology and, 161
psychosocial dimensions of,
134–135
research across, 194–198
role of, 145, 146, 160–161
social change and, 198–200
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480 c SUBJECT INDEX
Culture (continued )
social-cultural factors in
locomotion, 392
social experience and, 64–65
study of, 6, 175–176, 207 (See
also Vygotsky’s socio-
cultural theory)
theory of mind and, 89
tools of, 170–171, 422
Darwinian algorithms, 233
Death of a Salesman (Miller), 143
Décalages, 70, 361
Deconditioning, 280, 281. See also
Conditioning
Defense mechanisms, 103–105,
109, 123
Depression
in adolescence, 201, 264, 265
altered brain functioning and,
269–270
disturbed relationships and, 130
Freud and, 111
genetics and, 258, 262, 267, 269
maternal, 298
pathways to, 418–419
Despair. See Integrity vs. despair (in
Erikson’s theory)
Destructive instinct, 100, 111, 234
Developing-person-in-context,
188–191
Development, mechanisms of
in Erikson’s theory, 136,
144–145, 147, 426, 427
in ethology, 234, 426, 427
in Freud’s theory, 120–122,
426, 427
in Gibson’s theory, 392, 427
in information-processing theory,
353–355, 427
in Piaget’s theory, 57–62, 426,
427
review of, 426–428
in social learning theory, 303–
304, 426, 427
in Vygotsky’s theory, 176–177,
426, 427
Developmental cascade, 10, 269,
307, 358, 369, 402, 415,
418
Developmental continuity, 364, 402
Developmental issues. See also
specific issues
in connectionist models,
422–425, 427
in core knowledge theory, 419,
422, 423, 424, 425, 426
in Erikson’s theory, 21, 145
in ethology, 21, 234–235
in Freud’s theory, 21, 122–123
in Gibson’s theory, 21, 393–394
in information-processing theory,
21, 355–357
in Piaget’s theory, 21, 62–65
in social learning theory, 21,
304–306
in Vygotsky’s theory, 21, 177–179
Developmental neurogenetics,
268–269
Developmental neuroscience. See
Neuroscience
Developmental Psychology of Jean
Piaget, The (Flavell), 68
Developmental range, 86
Developmental robotics. See Robotics
Developmental social cognitive
science, 368. See also
Cognitive science
Developmental theories. See also
specific theories and
studies
chronology of, 23
introduction to, 2, 402
value of, 11–13
Dialectical change (process), 157,
176–177, 178, 423, 426.
See also Change
Differential susceptibility
hypothesis, 264
Discrimination
in learning, 37, 67, 165
racial, 270, 310
Disequilibrium, 60, 61, 65, 120,
177, 265
Disorganized attachment, 228
Displaced aggression. See
Aggression
Displacement, 43
Distinctive features of information,
382–383
Diversity
cultural, 158, 178, 199, 206,
266, 419
of development, 183–184
genetic, 266
racial/ethnic, 6
social–cultural aspects of, 310
Domain-specific knowledge. See
Knowledge
Dominance hierarchy, 230–231
Don Quixote (Cervantes), 96
“Dostoevsky and Parricide”
(Freud), 98
Dream analysis, 34–35, 97, 102,
111, 112, 126, 127
Drive energy, 100
Dynamic assessment, 174,
179–180, 183. See also
Assessment
Dynamic equilibration, 10, 417. See
also Equilibration
Dynamic skills, 86–87. See also
Skills
Dynamic structuralism, 86
Dynamic-systems theory
behavior and, 413–414, 422–
423, 425, 426
development and, 427
Fischer’s views on, 87
origins of, 2, 403
overview of, 412–418, 419
progress in, 428
Dysfunctional families, 306–307.
See also Families
Early experiences, 21, 108, 124,
131, 194, 220, 264
Early Growth of Logic in the Child,
The (Piaget), 78
Ecological-systems theory. See
Bronfenbrenner’s bioeco-
logical theory
Ecological theory of perceptual
development. See Gibson’s
ecological theory of percep-
tual development
Education. See also Instruction;
Learning
collaborative problem solving, 193
goal of, 17
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SUBJECT INDEX c 481
implications for, 405
informal vs. formal, 199, 200,
410
Vygotsky and, 156, 157
Educational neuroscience, 256. See
also Neuroscience
Ego. See also Id; Superego
defense mechanisms, 108, 123
defined, 101
development of, 119
function of, 102–105, 132
id and superego vs., 111, 121
organization of, 423
satisfying, 117
strengthening, 422, 426
structural relationships, 105,
105–106, 122
Egocentric speech, 45, 172. See
also Speech
Egocentrism, 45–46, 47, 53–54,
247
Ego ideal, 105
Embodied cognition, 368–369,
396, 412, 417. See also
Cognition
Embodied perception, 396–397
Emerging adulthood, 148–149
Emotions
behavior and, 164–165, 183, 256
cognition and, 75, 124–125
inferring, 397
personality and, 122
processing of, 131, 242, 249,
299–300, 368
understanding, 205, 297, 340,
424
Enactive rehearsal, 294
Encoding, process of, 323,
354–355, 357
Environment
adapting to (See Adaptation)
affordances in, 380
being in equilibrium with, 60,
61, 64
effect on development, 20–21,
32, 60, 80, 92, 145, 154,
229, 246, 256, 422
epistemology and, 30–31
ethology and, 13, 22, 219, 230,
235
genetic connections with,
263–264, 271
heredity vs., 20, 235, 263–264
(See also Genetics; Nature
vs. nurture)
hostile (harsh), 185, 219, 242,
268, 293
individualism’s effects on, 199
interacting with, 36, 163, 341
learning theory and, 278, 279, 298
macro vs. micro, 271
natural, 221, 222, 241, 310–311,
380, 385
perception of, 397
physical, 9, 61, 64–65, 154, 216,
233, 252, 364, 368, 414
social–cultural, 86, 109, 303
(See also Vygotsky’s socio-
cultural theory)
stimulation from, 251–252
stress in, 189
thought and, 31, 51, 86, 103
triadic reciprocal causation, 292
types of, 293
Environment–person–behavior sys-
tem, 292–293
Epigenetics, 135, 144, 258, 259,
262–264, 270, 403. See
also Genetics
Episodic buffer, 325
Epistemology. See Genetic episte-
mology
Equilibration. See also Cognitive
equilibration; Dynamic
equilibration
cognitive, 60–61
Freudian view of, 120, 144
as a functional invariant, 57
observable behavior and, 4
Piagetian view of, 7, 31, 61, 64,
65, 73, 80–81, 83, 177,
422, 423, 425, 426, 427
Erikson’s psychosocial theory
applications of, 146
biographical sketch of Erikson,
133
contemporary research, 148–150
development issues, position on,
21, 145
emphasis on identity, 137–138
mechanisms of development in,
136, 144–145, 147, 426,
427
methodology of, 138–139
orientation to, 133–139
psychosocial stages in, 134–137
stages in, 139–144
strengths of, 146–147
weaknesses of, 147
Erogenous zones, 113, 116. See
also Anal stage (in Freud’s
theory); Oral stage (in
Freud’s theory)
Eros, 100
Ethnography, 175
Ethograms, 222, 223
Ethology
aggression, study of, 230, 231,
237, 291
applications of, 236
attachment (See Attachment)
defined, 13, 212
developmental issues, position on,
21, 234–235
evolutionary perspective of,
218–219, 270
genetics and, 270–271 (See also
Genetics)
importance of, 236–239
introduction to, 212
learning predispositions in,
219–221
limitations of, 239–241
mechanisms of development in,
234, 426, 427
methodology, 221–224,
238–239
orientation to, 215–224
origins of, 2, 23, 24, 213–215
peer interactions, 230–232
problem solving, 232–233
research in, 241–248
species-specific innate behavior,
215–217
strengths of, 236–239
weakness of, 239–241
Evolutionary psychology, 214–215,
232, 233, 270
Evolutionary theory, 2, 218
Executive control structures, 83, 423
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482 c SUBJECT INDEX
Executive function, 366–367, 408,
411
Executive processing space, 83
Exosystem, 189, 190
Experience. See Early experiences
External vs. internal dialogue, 168,
187
Eye–hand coordination, 65. See also
Coordination
Eye tracking, 386–387
Eyewitness testimony, 358–359
Facts, 4, 11–12
Families. See also Immigrant
families
attachment theory and, 236
child rearing in, 202
collective efficacy in, 299
conflicts in, 201
culture of, 160–161, 202–203,
205, 206, 340
dysfunctional, 306–307
genetic influence on, 21, 257
influence on behavior, 147, 270,
306–307
interactions in, 189, 194, 407
nontraditional, 6
obligations of, 148–149, 150,
201
social relationships in, 50, 64–65,
175, 196, 199
structure of, 190
Fear. See also Anxiety
of animals, 119–120, 221,
280–281
Darwin’s observations on, 213
of death, 108, 144
Erikson’s study of, 140, 143
facial expressions of, 225, 256
Freud’s study of, 117, 127
of height, 386
overcoming, 292
Feminist theories, 6, 432–434
Fischer’s neo-Piagetian theory,
85–88
Fixation, 104, 114
Fixed action patterns. See also Sign
stimuli
abnormal behavior and, 222
complexity of, 216–217
development of, 423, 426
evolutionary nature of, 218, 226,
233
in infants, 216, 225
qualitative and quantitative
change, 234–235
studies of, 223–224
Flow diagrams, 324, 325, 329, 346,
355, 362, 363
Foreclosure person, 149
Forever Panting (De Vries), 101
Formal operational period, 36,
51–55
Free association, 104, 111–112,
126. See also Associations
Freud’s psychoanalytic theory
applications of, 123–124
biographical sketch of Freud,
96–99
biologically based drives, 10
case study (“Little Hans”), 119–
120, 123, 281
contemporary research, 129–132
developmental issues, position on,
21, 122–123
dynamic approach to, 100–101
introduction to, 96
mechanisms of development in,
120–122, 426, 427
methodology of, 111–113
normal–abnormal continuum in,
110–111
orientation to, 99–113
origins of, 4, 23, 24
progress in, 428
stage approach to, 108–110,
113–120
strengths of, 124–126
structural approach to, 101–106
topographic approach to,
106–108
weaknesses of, 126–129
Frustration and Aggression (Dollard,
Doob, Miller, Mowrer, &
Sears), 286
Function, 46
Functional causes of behavior, 237,
240
Functional invariants, 57, 58, 60, 72
Future of an Illusion, The (Freud), 98
Gandhi’s Truth (Erikson), 139
Gender
aggression and, 302, 433
behavior and, 232, 288, 310,
336
biases in research, 433–434
culture and, 6, 179, 203, 205
identity and, 149
relationships and, 129
role of, 129, 133, 179, 302–303,
432
stereotypes of, 336
Generalization, 355
Generativity vs. stagnation and
self-absorption (in
Erikson’s theory), 136,
143–144
Genetic epistemology, 29–31, 43,
62, 69, 79
Genetic polymorphisms, 259, 265,
268, 269
Genetics. See also Epigenetics
adaptation and, 215, 271
applications of, 267
behavior and, 218, 257, 262
brain development and activity
(See Brain)
depression and, 258, 262, 267,
269
ethology and, 270–271
gene X environment interac-
tions, 21, 258–262, 265,
266–267, 269, 403
genotypes vs. phenotypes, 258,
259
introduction to, 257–258
nature vs. nurture, 21, 21,
425
new technology in, 212
research in, 257–258
social behavior and, 214
theoretical issues in, 264–267,
424, 426
Genital stage (in Freud’s theory),
109, 110, 119, 122
Genomes, study of, 259–260
Gibson’s ecological theory of
perceptual development
affordances, 379–381, 396, 397,
422, 424, 426
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SUBJECT INDEX c 483
applications of, 394
biographical sketch of Gibson,
378–379
contemporary research, 397–399
developmental issues, position on,
21, 393–394
ecological perspectives of,
379–381, 395–396
human perception, 384–385
infant learning, 387–392
information processing and,
395–396
introduction to, 378
mechanisms of development in,
392, 427
methodology in, 385–387
orientation to, 379–387
origins of, 23, 24
stimulation, 381–384
strengths of, 395–397
weaknesses of, 397
Guided participation, 166
Guilt. See Initiative vs. guilt (in
Erikson’s theory)
Hallucinatory wish fulfillment. See
Primary-process thought
Hamlet (Shakespeare), 155
Heredity vs. environment, 20, 145,
235. See also Nature vs.
nurture
History-of-science, 428–431
Horizontal décalages. See Décalages
Human nature
capitalistic view of, 16–17
in Erikson’s theory, 145, 423
in ethology, 234, 422
in Freud’s theory, 122, 422,
423, 424
in Gibson’s theory, 393, 422, 423
in information-processing theory,
355–356, 422, 423
introduction to, 14–17
mechanistic view of, 14, 15, 17,
72–74, 422, 423, 429
mercantilistic view of, 17, 18,
122
organismic view of, 14–15,
17–18, 122, 304, 419,
422, 423, 429
in Piaget’s theory, 62, 422,
423, 424
review of, 422–424
in social learning theory, 177–
178, 304, 422, 423–424
in Vygotsky’s theory, 177–178,
422, 423, 424
Hypnosis, 97, 108, 127, 128
Hypotheses
accuracy of, 370–371, 415
defined, 4
experimenting with, 53
formulating, 15, 52, 233, 238,
265, 284, 356, 368
importance of, 352, 434
testing, 15, 30, 55, 71, 127–128,
361–362, 405, 416
Hypothetical constructs, 3–4, 12
Hypothetico-deductive thought, 52
Hysteria, 97, 128
Id. See also Ego; Superego
defined, 101
ego and superego vs., 111
function of, 101–102
organization of, 423
satisfying, 118
structural relationships, 105,
105–106
the unconscious, 107
Identity, 46, 137–138, 149, 422
Identity-achieved person, 149
Identity and repudiation vs. iden-
tity diffusion (in Erikson’s
theory), 136, 137,
142–143
Identity crisis, 138
Identity-diffused person, 149
Identity diffusion, 143
Identity: Youth and Crisis (Erikson),
133
Imaging (brain), 131, 212, 242,
248–249, 255, 268,
398–399. See also
Neuroimaging
Imitation
aggression and, 288, 291
of behavior, 127, 186–187,
188, 231, 287–288, 302,
312–314
culture and, 140, 221, 313
by infants, 90, 225, 410
learning and, 83, 186, 277
mental representations and, 42
motivation and, 296
neural networks and, 313, 424
origins of, 44
reinforcement and, 67, 287
Immaturity, 247, 256, 360
Immediate causes of behavior,
237
Immigrant families, 200–202
Implicit memory, 132. See also
Memory
Imposed environment, 293. See
also Environment
Imprinting, 219–220, 225, 272
Individualism, 199–200
Industry vs. inferiority (in Erikson’s
theory), 136, 142
Infant–caretaker attachment,
224–232. See also
Attachment
Information processing
cognitive contributions to, 294
continuity vs. discontinuity in,
364, 407, 428, 431
function of, 422
by infants, 194–195, 251,
364–367, 372
multitasking and, 360
organizing information, 11–12
social, 341
systems for, 323–324
Information-processing theory
applications of, 357–360
attachment and, 226
cognitive development and, 125
compared with perceptual
learning, 382
computational modeling in,
346–353
contemporary research,
365–374
development as self-modification
in, 326–327
development issues, position on,
21, 355–357
history of, 320–322
introduction to, 318–320
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Information-processing theory
(continued )
mathematical understanding in,
341–344
mechanisms of development in,
353–355, 427
memory and, 330–337
metamemory and, 337–341
methodology in, 328–330,
361–362
orientation to, 322–330
origins of, 2, 23, 24
problem solving, rules for,
344–346
progress in, 428, 429
strengths of, 360–362
task analysis in, 327–328
weaknesses of, 362–365
Initiative vs. guilt (in Erikson’s
theory), 136, 141–142
Innate behavior. See Fixed action
patterns
Innate vs. acquired. See Nature vs.
nurture
Inner speech, 169, 172. See also
Speech
Insecure attachment, 131, 229,
240, 242. See also
Attachment
Insecure–avoidant babies, 228
Insecure–resistant babies, 228
Instruction. See also Education
applications of, 357
change and, 92
cultural practices, 160, 161,
165–166, 186, 221
problem-based learning, 181
readiness for (See Readiness)
scaffolding and, 86
in scientific thought, 53
zone of proximal development
and, 179, 180
Integrity vs. despair (in Erikson’s
theory), 136, 144
Intellectual functioning, 169–174
Intelligence
artificial, 321–322, 373
environment and, 31
evolution of, 213
information processing and, 328
intelligence-testing approach
to, 232
social cognition and, 176
tests of, 27, 411
Intelligent behavior, 58
Interactions, with objects, 388–390,
407, 409, 425
Intermental vs. intramental, 167–
169, 172, 177
Internal conflicts, 121. See also
Conflicts
Internal working models, 129–130,
225
Interpretation of Dreams, The
(Freud), 97
Intersubjectivity, 166–167, 177,
183, 186, 187, 204
Intimacy and solidarity vs. isolation (in
Erikson’s theory), 136, 143
Intrinsic motivation, 62, 423. See
also Motivation
Introspection, 126, 279, 285
Invariant functions, 63, 427
Invariants in information, 383
Irrational thought, 125, 304. See
also Thought
Isolation. See Intimacy and solidarity
vs. isolation (in Erikson’s
theory)
Judgment and Reasoning in the
Child (Piaget), 28
Knowledge
connectionist models and,
348–349
core (See Core knowledge theory)
domain-specific, 409–410, 428
Piaget’s view of, 30–31
role of, in memory, 334–337
Language. See also Communication
behaviorism and, 278
bilingualism, 201
computational approaches to,
369–373
development of, 11, 22, 171,
173, 186, 247, 285, 298
discriminating phonemes, 251
impairment in, 351
importance of, 171, 245
learning, 220–221, 251, 296, 321
pragmatics of, 174
social uses of, 203
thought and, 9, 44–45
Language and Thought of the Child,
The (Piaget), 28
Latency period (in Freud’s theory),
109, 118–119
Learning. See also Education
alternate conceptions of, 285
by children, 65–66, 142, 289–
290, 370–371, 380
cognitive contributions to, 294–
296, 311–312
collaborative, 179, 180–181,
187, 190, 239
connectionist models and, 349
importance of, 217
by infants, 220–221, 387–392,
397–399
maturation vs. (See Nature vs.
nurture)
observational, 288, 289–292,
295, 303, 305, 310, 311,
427
perceptual (See Gibson’s ecolog-
ical theory of perceptual
development)
predispositions to, 219–221, 235
readiness for, 180, 183, 220,
242, 364, 366
self-efficacy and agency,
296–300
social learning and personality,
286, 292
specific and general skills,
220–221
statistical, 312, 372
theories of (See specific theories
of learning)
Learning sciences, 312
Learning theory. See also Social
learning theory
academic psychology and, 67
discontent with, 285, 321
failures in, 430
history of, 279–286
modification of, 67
nature vs. nurture, 305
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origins of, 2, 23, 278
reinforcement in (See
Reinforcement)
Libido, 100, 101, 104, 113, 115
“Little Albert” experiment, 280
“Little Hans.” See “Analysis of a
Phobia in a Five-Year-Old
Boy” (Freud)
Locomotion
cognition and, 243
of infants, 188, 380–381, 385–
387, 390–392, 391, 413
patterns in, 416
Logicomathematical systems/
structures, 32, 49, 53, 64,
65, 71, 81
Long-term memory. See Memory
Macroenvironments, 271. See also
Environment
Macrosystem, 190
Mathematical understanding. See
also Logicomathematical
systems/structures
in children, 66, 297, 341–344,
404
in connectionist models, 349
culture and, 196–198
gender and, 303
in information-processing theory,
341–344, 357
research in, 358
Maturation vs. learning. See Nature
vs. nurture
Mechanisms of development. See
Development,
mechanisms of
Mechanistic view of human nature.
See Human nature
Memory. See also Information
processing; Working
memory
autobiographical, 331
capacity of, 9, 74, 82–83, 247,
324, 325–326, 339, 357
development of, 9, 10, 18–19,
330–332, 338, 356,
359–360
distortions in, 126
flow diagram of, 325
implicit, 132
input vs. output, 318–319
knowledge, role of, 334–337
long-term, 319, 324, 325–326,
331, 358, 361, 368
metaphors in, 363
repression of, 104, 124, 128
research in, 358–360
retrieval from, 325–326, 331,
335, 356
social–cultural context of,
340–341
strategies in, 8, 332–334, 355,
358, 427
Memory span, 324–325, 326
Mental embryology, 31
Mental imagery, 36, 100, 107, 186,
197, 323, 332
Mental operations
behavior and, 309
compensation, 60
in concrete operational period, 36,
46, 48
in formal operational period, 36,
51, 53
information processing and, 319,
346, 360
origins of, 2
in preoperational period, 45
reversibility, 46, 48–49, 125, 168
Mental representations, 44–45,
51, 62
Mercantilistic view of human nature.
See Human nature
Mesosystem, 189, 190
Metacognition, 337, 357, 364
Metamemory, 56–57, 337–339,
356. See also Memory
Methodologies
in Erikson’s theory, 138–139
in ethology, 221–224, 238–239
in Freud’s theory, 111–113
in Gibson’s theory, 385–387
in information-processing theory,
328–330, 361–362
in Piaget’s theory, 34–35,
78–79
in Vygotsky’s theory, 174–176
Microenvironments, 271. See also
Environment
Microgenetic methods, 174, 179,
328–329, 342, 355, 416,
427
Microsystem, 189, 190
Middlemarch (Eliot), 363
Mirror neuron system, 313, 369
Mistrust. See Basic trust vs. basic
mistrust (in Erikson’s
theory)
Modeling
abstract, 290, 296
Baddeley’s memory model, 324,
366
Bayesian networks (models), 312,
369–373, 403, 409, 427
computational models (See
Computational models)
connectionist models (See
Connectionist models)
overlapping-waves model, 353,
353–354
stimulus–response model, 234,
280–281, 323, 423, 431
for working memory, 369
Models, 5
Modularity, 411
Molecular genetics, 257–258. See
also Genetics
Moral disengagement, 301
Moral Judgment of the Child, The
(Piaget), 28
Moral reasoning. See Reasoning
Moratorium person, 149
“Moses of Michelangelo, The”
(Freud), 98
Motivation
cognitive ability and, 179, 184,
241, 304
conscious, 108
controlling, 180, 309
imitation and, 296
intrinsic, 62, 423
unconscious, 98, 127
Multimodal stimulation, 385
Multitasking, 360
Narratives and conversations, devel-
opment through, 202–203
Nativism vs. empiricism. See Nature
vs. nurture
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486 c SUBJECT INDEX
Nature vs. nurture
in connectionist models, 425
in Erikson’s theory, 145, 425
in ethology, 235, 425
in Freud’s theory, 123
genetics, 21, 425
in Gibson’s theory, 393, 425
in information-processing theory,
356–357, 425
introduction to, 19–22, 21
in learning theory, 305
in neuroscience, 22, 425
in Piaget’s theory, 63–65, 425
review of, 425
in social learning theory, 305,
425
in Vygotsky’s theory, 178–179,
425
Neo-Freudians, 132
Neo-Piagetian theory
Case’s theory, 83–85, 85
Fischer’s theory, 85–88, 154
introduction to, 82
origins of, 23
themes in, 88–89
Nervous energy. See Drive energy;
Libido; Psychic energy;
Tension
Neural networks. See also
Connectionist models;
Neuroscience
imaging of, 249, 255
imitation and, 313, 424
increased specialization in, 251
maintaining, 131, 410
strengthening, 20, 255, 426–427
Neural transmission, 250, 356
Neuroconstructivism, 92, 254
Neurodevelopmental disorders,
92, 254
Neurogenetics, 268–269. See also
Genetics
Neuroimaging
information processing and, 318
purpose of, 91, 215, 249, 254,
398–399
research in, 131, 367
types of, 91
Neurolaw, 256
Neuropsychoanalysis, 131
Neuroscience. See also Brain;
entries beginning with
cognitive
applications of, 255–256, 403
attachment research, 242
brain development, 250–253
connectionist models in, 347
developmental cognitive neurosci-
ence, 91, 131
introduction to, 248–250
nature vs. nurture, 21, 22, 425
research in, 256–257, 270,
367–368
theoretical issues in, 253–255,
424, 427
Nonlogical thought, 124–125. See
also Thought
Numerical reasoning. See
Reasoning
Object permanence
development of, 306, 407, 417
ethological view of, 243
Piagetian view of, 8, 42–43, 76,
77, 88, 89, 90, 92, 188
Object relations, 129
Observational learning. See
Learning
Oedipus complex, 105, 117, 118,
127, 141
Ontogenetic causes of behavior, 237
Ontogenetic change, 218
Operant conditioning, 280, 282–
284, 288, 331. See also
Conditioning
Operations, 48–50, 52. See also
Concrete operational
period; Formal operational
period
Optimal adaptation, 237. See also
Adaptation
Optimal level of development, 86
Oral stage (in Freud’s theory), 109,
113–116, 122, 226
Organismic view of human nature.
See Human nature
Origins of Intelligence in Children,
The (Piaget), 37
Overimitation, 312. See also
Imitation
Overlapping-waves model, 353,
353–354. See also
Modeling
Paradigms, 429–431
Parallel distributed processing, 348
Peer collaborations. See Collaborative
problem solving
Peer interactions, 230–232
Pendulum problem, 52, 62, 69
Penis envy, 118, 129
Perceptual conscious. See
Conscious
Perceptual learning. See Gibson’s
ecological theory of
perceptual development
Performance, theory of, 74
Personality. See also Ego; Id;
Superego
abnormal, 111
anal, 98, 127, 141
development of, 96, 100, 104,
108, 114, 121–122, 124,
135, 140, 417
disturbed, 109
identity diffusion and, 143
social learning and, 286, 292
Personality and Psychotherapy
(Dollard & Miller), 286
Person-in-context. See Developing-
person-in-context
Phallic stage (in Freud’s theory),
109, 117–118, 122
Philosophy of science, 7, 69
Phonological loop, 324–325, 326
Phylogenetic causes of behavior,
223, 237, 272
Phylogenetic change, 218, 239. See
also Change
Physical maturation
Bandura’s view of, 303, 305, 425
biological aspects, 10
cognition and, 22
Erikson’s view of, 134, 144
ethological aspects, 215, 234
Freudian view of, 109, 121
Piagetian view of, 61, 63, 64,
425
Piaget’s cognitive-structural theory
applications of, 65–66
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SUBJECT INDEX c 487
assumptions in, 3–4
biographical sketch of Piaget,
26–29
biological approach to, 31
contemporary research, 89–92
developmental issues, position on,
21, 62–65
ecological validity of, 69–70
equilibration in (See Equilibration)
focus of, 5, 24, 26
formula for development in, 64–65
genetic epistemology, 29–31
hypothetical constructs in, 3–4
logicomathematical experiences,
32, 49, 53, 64, 65, 71, 81
mechanisms of development in,
57–62, 426, 427
methodology of, 34–35, 78–79
modifications of, 80–82
orientation to, 29–35
origins of, 23
social experiences, 64–65
stage approach to, 16, 32–55,
70–72, 80
strengths of, 66–70
structuralism in, 32
weaknesses of, 70–79
Plasticity, 218–219, 245, 247,
250–251, 256, 270, 367
Play, concept of, 144–145, 167
Pleasure principle, 100, 102, 121
Pluralist–constructivist model, 200
Polymorphisms. See Genetic
polymorphisms
Preconscious behavior, 105,
107, 108
Preoperational period, 36, 41,
43–48, 55, 73
Primary circular reactions, 37–38
Primary-process thought, 102, 103.
See also Thought
Principles of Perceptual Learning
and Development (Gibson),
379
Private speech, 172–173. See also
Egocentric speech
Probabilistic models, 269, 312. See
also Modeling
Problem-based learning. See
Collaborative learning
Problem solving
by children, 83–84, 164, 167
collaborative, 166, 192–193
development of skills in, 104, 425
ethological study of, 232–233
guided participation, 166
microgenetic method, 174 (See
also Microgenetic methods)
zone of proximal development,
163 (See also Zone of
proximal development
(Vygotsky))
Processing space. See Executive
processing space
Production deficiency, 333, 337
Production systems, 346–347, 351
Prospectivity, 394
Psychic energy, 100, 101
Psychoanalytic theory. See also
Freud’s psychoanalytic
theory
expansion of, 146
importance of, 96, 98–99
nonlogical thought in, 124–125
Psychological energy, 100
Psychopathology, 130–131, 229,
236, 242, 253, 269, 424
Psychopathology of Everyday Life,
The (Freud), 111
Psychosexual stages of development
in Erikson’s theory, 133, 134
in Freud’s theory, 108, 118, 134
(See also specific stages)
Psychosocial development,
134–135. See also
Erikson’s psychoanalytic
theory
Qualitative vs. quantitative
development
in Erikson’s theory, 145, 424
in ethology, 234–235
in Freud’s theory, 122–123, 424
in Gibson’s theory, 393
in information-processing theory,
356, 364, 424, 425
introduction to, 17–19
organismic, 419
in Piaget’s theory, 62–63, 424
review of, 424–425
in social learning theory, 305, 424
in Vygotsky’s theory, 178, 424
Reaction formation, 104, 125
Readiness
cognitive, 92, 176, 305, 310
for learning, 180, 183, 220, 242,
305, 364, 366
measurement of, 174
in Piaget’s theory, 65, 67, 73
Reality principle, 100, 121
Reasoning. See also Collaborative
problem solving; Thought
causal, 46, 352, 408
by children, 27, 68–69, 83, 86,
89, 125, 157
concrete operational, 77
formal operational, 78
limitations in, 50
moral, 192, 196, 300–301, 411
numerical, 249
origin of reasoning tests, 27
preverbal vs. verbal, 410
scientific, 89, 171, 343
semilogical, 46–47
spatial, 249
transitive, 239
Reductionist strategy, 188, 214,
279–280, 423
Reflective abstraction, 80
Reflexes
attachment and, 224, 225, 226
classical conditioning, 282
in ethology, 423
in Fischer’s theory, 87
in fixed action patterns, 216–217,
234
in infants, 216, 217, 224, 246
as innate behavior, 216, 217,
218, 234, 280, 414–415,
423
in learning theory, 278
nature vs. nurture, 63, 69
in sensorimotor period, 36–37, 54
Regression, 33, 104, 114
Rehearsal, cognitive and enactive,
394
Reinforcement
conflict and, 73, 307
imitation and, 67, 287
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488 c SUBJECT INDEX
Reinforcement (continued )
in learning theory, 4, 10, 13, 16,
67, 278, 282–284, 321,
423
in natural settings, 310
observational learning and, 290,
310
self-regulation and, 315
social, 67, 293, 306
vicarious, 288
Relational aggression. See
Aggression
Relational-developmental-systems
theory, 417
Repression
anxiety and, 109
attachment and, 226
consciousness and, 103, 105
internal conflicts and, 121
of memories, 104, 124, 128
Oedipus complex and, 127
of sexual desire, 118
Resistant attachment, 229. See also
Attachment
Retention, 140, 295, 315
Retrieval, from memory, 325–326,
331, 335, 356. See also
Memory
Reversibility. See Mental reversibility
Rigidity of thought, 46. See also
Thought
Robotics, 170, 321–322,
373–374
Rule-assessment approach, 328,
345
Scaffolding, 167
Schemes
concrete operations, 51
coordinating secondary, 39–40
defined, 32
primary circular reactions, 37–38
Schooling, effects of
culture and, 175, 194, 196–198,
200
self-efficacy and, 298
Scientific reasoning. See Reasoning
Scientific theory, 3, 23, 429–431
Scientific vs. spontaneous concepts,
181
Scripts, 336–337, 357, 367
Secondary circular reactions, 38–39
Secondary-process thought, 102–
103. See also Thought
Secure attachment, 228, 229, 236,
240. See also Attachment
Selected environment, 293. See
also Environment
Selective memory, 333–334, 334.
See also Memory
Self-absorption. See Generativity
vs. stagnation and self-
absorption (in Erikson’s
theory)
Self-concept, 116, 129, 187, 199,
396
Self-correction, 225, 327
Self-efficacy, 296–299, 302–303
Self-modification, 326–327, 351,
363
Self-regulation
aggression and, 418
in connectionist models, 427
gender roles and, 302
genetic influences on, 261–262
importance of, 423
in Piaget’s theory, 62, 122, 423
in social learning theory, 422,
423
in Vygotsky’s theory, 168, 180,
423
Self-righting tendency, 217
Semilogical reasoning, 46–47. See
also Reasoning
Sensitive periods, 219
Sensorimotor period (development)
Fischer’s view of, 87–88
motor exploration in, 220,
368–369
object permanence, 42–43
origins of, 2
overview of, 42, 54
stages in Piaget’s theory, 36–42
thought without speech, 172
Sexuality
of children, 117–119, 128–129
culture and, 193
genital stage and, 110, 119
infantile, 98, 151
maturity, 306
repression of memories of,
104, 124, 128 (See also
Repression)
Shame and doubt. See Autonomy
vs. shame and doubt (in
Erikson’s theory)
Shaping, 282
Signaling behaviors, 225, 227
Signs, 44, 170. See also Symbols
Sign stimuli, 216–217, 234, 272,
423
Situational influences on behavior,
308–309
Skills, 86. See also Abilities
Skinner box, 278, 283
Skinnerian operant learning theory,
4, 13. See also Learning
theory
Social change, 198–200. See also
Change
Social cognition, 47–48, 125, 175,
365. See also Cognition;
Intelligence
Social cognitive theory, 278, 288.
See also Learning theory
Social constructionists, 6
Social deviance, 417
Social information processing, 341.
See also Information pro-
cessing
Social learning theory. See also
Learning theory
aggression in, 13
applications of, 306–308
causal model of, 292–293
classical learning theory vs., 428
contemporary research, 311–314
cultural effects, 292
developmental issues, position on,
21, 304–306
gender-role development in,
302–303
history of, 286–289
introduction to, 278–279
mechanisms of development in,
303–304, 426, 427
moral judgments and behavior in,
300–301
observational learning,
289–292
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orientation to, 289–300
origins of, 2, 23, 24, 286
progress in, 428
psychoanalytic theory and, 99
selective social learning, 314
strengths in, 308–309
testability of, 309
weaknesses in, 309–311
Social reciprocity, 243
Sociocultural theory. See Vygotsky’s
sociocultural theory
Solidarity, 190, 194. See also
Intimacy and solidarity
vs. isolation (in Erikson’s
theory)
Spatial reasoning. See Reasoning
Species-specific innate behavior,
215–217, 305
Specific and general learning skills,
220–221. See also Skills
Specific language impairment, 351.
See also Language
Speech. See also Communication;
Language
angry vs. neutral, 254
development of, 171–174
ecology of, 387
egocentric, 45, 172
inner, 169, 172
oral pleasure and, 134
private, 172–173
spontaneous, 34
Spontaneous vs. scientific concepts,
181
Stage approach
in Erikson’s theory, 134–137
in Freud’s theory, 108–110,
113–120
in Piaget’s theory, 16, 32–34,
70–72, 80
in Vygotsky’s theory, 178
Stagnation. See Generativity vs.
stagnation and self-
absorption (in Erikson’s
theory)
Statistical learning, 312, 372, 409,
427. See also Learning
Stepping reflex, 392, 414. See also
Reflexes
Stimulation, 381–384
Stimulus–response model, 234,
280–281, 323, 423, 431.
See also Modeling
Strategies
choosing, 326–327
cognitive, 170, 284, 368
constructing, 355
cultural, 154, 171, 197
development of, 74, 353–354,
357, 414
for mathematical understanding,
197, 297, 338, 342
in memory development, 8,
332–334, 355, 358, 427
prosocial, 231
reductionist, 279–280
Stress
activation of responses to, 264
anxiety and, 219, 270
in environment, 189
responding to, 242, 262,
268–270
Structural approach (in Freud’s
theory), 101–106
Structuralism, 32, 62
Sublimation, 101
Superego. See also Ego; Id
defined, 101
development of, 105, 117, 119,
123
function of, 117
organization of, 423
structural relationships, 105,
105–106
Symbols, 44, 197
Task analysis, 327–328, 346, 357
Temporal–spatial representations,
50
Tension, 100, 121, 161
Tension-reduction process, 144
Tertiary circular reactions, 40
Theories. See also specific
theories
development issues, position
on, 419
foundational, 405
historical progress of, 428–431,
434
overview of, 403
principles of, 402
themes in, 403–419
Theory of mind, 89, 125–126, 174,
404, 405, 407, 408–409
Theory theory
application of, 404–409
conceptual development, 403
domain-specific development, 72,
91, 410–411, 425, 428
how children develop, 424, 426,
427
organismic quality of, 419, 422
purpose of, 2
Thought. See also Reasoning
abstract vs. concrete, 168, 181
complexity of, 360–361
concrete operational vs. formal
operational, 53–54, 58
controlling, 170, 173, 252–253
development of, 11, 73, 123,
157, 243–244
environment and, 31, 51, 86, 103
formal operational, 52, 53, 61
general structures of, 35
hypothetico-deductive thought, 52
irrational, 125, 304
language and, 9, 44–45
learning and, 66
nonlogical, 124–125
preconscious vs. conscious, 107
primary-process, 102, 103
rational vs. irrational, 125, 304,
424
representational vs. sensorimotor,
44–45
rigidity of, 46
secondary-process, 102–103
without speech, 172 (See also
Speech)
Thought and Language (Vygotsky),
158
Toilet training, 99, 104, 114,
116–117, 287
Topographic approach (in Freud’s
theory), 106–108
Totem and Taboo (Freud), 98
Transitive reasoning, 239. See also
Reasoning
Triadic reciprocal causation, 292,
304, 305, 315
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490 c SUBJECT INDEX
Triadic reciprocal determinism, 190
Trust. See Basic trust vs. basic
mistrust (in Erikson’s
theory)
Unconscious behavior, 105, 107,
108, 127, 132
Universality of Piaget’s stages, 34
Utilization deficiency, 334
Vicarious reinforcement, 288. See
also Reinforcement
Visual cliff, 377, 379, 386, 390
Visuospatial sketchpad, 324, 325
Vygotsky’s sociocultural theory
applications of, 179–182
assimilation of, 204–205
background sketch of Vygotsky,
155–158
child-in-activity-in-culture con-
cept, 158–163, 168, 179
compared to social learning the-
ory, 289
contemporary research, 192–207
developmental issues, position on,
21, 177–179
individual mental functioning in,
167–169
intellectual functioning in,
169–174
introduction to, 154–155
mechanisms of development in,
176–177, 426, 427
methodology of, 174–176
orientation to, 158–176
origins of, 23, 24
progress in, 428
proximal development (See Zone
of proximal development
(Vygotsky))
strengths of, 182–184
weaknesses of, 184–188
Walden Two (Skinner), 283
Why War? (Freud), 98
Working memory. See also Memory
applications of, 357
automatization and, 354
components of, 324–326
efficiency of, 83
executive functioning and, 173,
366, 411
importance of, 339, 357, 428
increasing, 88, 91, 326, 351,
367, 427
information processing and, 364
language learning and, 247
modeling, 369
performance and, 333, 361
stress and, 365
theory of mind and, 411–412
theory of performance and, 74
Worldview, 14, 419, 422–424.
See also specific
worldviews
Young Man Luther (Erikson), 138
Zone of proximal development
(Vygotsky)
analysis of, 163–167, 265
cognition and, 186, 204
collaboration in, 177
defined, 163
dynamic assessment of, 174,
179–180
scaffolding and, 86
vagueness of, 182, 184–185
14_MIL_7898_bm_subject_index_477_490.indd 490 20/01/16 12:02 AM
http://www.macmillanlearning.com
Cover
Half Title Page
Title Page
Copyright Page
Contents
Preface
Chapter 1: Introduction
What Is a Theory?
What Is a Developmental Theory?
Of What Value Is a Developmental Theory?
Organizing Information
Guiding Research
What Main Issues of Developmental Psychology Do Theories Address?
What Is the Basic Nature of Humans?
Is Development Qualitative or Quantitative?
How Do Nature and Nurture Contribute to Development?
What Is It That Develops?
Summary
Chronology of Developmental Theories
Organization of This Book
Suggested Readings
Chapter 2: Piaget’s Cognitive-Stage Theory and the Neo-Piagetians
Biographical Sketch
General Orientation to the Theory
Genetic Epistemology
Biological Approach
Structuralism
Stage Approach
Methodology
Description of the Stages
Sensorimotor Period (Roughly Birth to 2 Years)
Preoperational Period (Roughly 2 to 7 Years)
Concrete Operational Period (Roughly 7 to 11 Years)
Formal Operational Period (Roughly 11 to 15 Years)
An Overview
Memory
Mechanisms of Development
Cognitive Organization
Cognitive Adaptation
Cognitive Equilibration
Section Overview
Position on Developmental Issues
Human Nature
Qualitative Versus Quantitative Development
Nature Versus Nurture
What Develops
Applications
Evaluation of the Theory
Strengths
Weaknesses
Piaget’s Own Modifications of His Theory
The Neo-Piagetians
Robbie Case
Kurt Fischer
Neo-Piagetian Themes
Contemporary Research
Infants’ Advanced Competencies
Domain-Specific Concepts
Mechanisms of Development
Summary
Suggested Readings
Chapter 3: Freud’s and Erikson’s Psychoanalytic Theories
FREUD
Biographical Sketch
General Orientation to the Theory
Dynamic Approach
Structural Approach
Topographic Approach
Stage Approach
Normal–Abnormal Continuum
Methodology
Description of the Stages
Oral Stage (Roughly Birth to 1 Year)
Anal Stage (Roughly 1 to 3 Years)
Phallic Stage (Roughly 3 to 5 Years)
Period of Latency (Roughly 5 Years to the Beginning of Puberty)
Genital Stage (Adolescence)
Case Study of “Little Hans”
Mechanisms of Development
Position on Developmental Issues
Human Nature
Qualitative Versus Quantitative Development
Nature Versus Nurture
What Develops
Applications
Evaluation of the Theory
Strengths
Weaknesses
Contemporary Research
ERIKSON
Biographical Sketch
General Orientation to the Theory
Psychosocial Stages
Emphasis on Identity
Expansion of Psychoanalytic Methodology
Description of the Stages
Stage 1: Basic Trust Versus Basic Mistrust (Roughly Birth to 1 Year)
Stage 2: Autonomy Versus Shame and Doubt (Roughly 2 to 3 Years)
Stage 3: Initiative Versus Guilt (Roughly 4 to 5 Years)
Stage 4: Industry Versus Inferiority (Roughly 6 Years to Puberty)
Stage 5: Identity and Repudiation Versus Identity Diffusion (Adolescence)
Stage 6: Intimacy and Solidarity Versus Isolation (Young Adulthood)
Stage 7: Generativity Versus Stagnation and Self-Absorption (Middle Adulthood)
Stage 8: Integrity Versus Despair (Late Adulthood)
Mechanisms of Development
Position on Developmental Issues
Applications
Evaluation of the Theory
Strengths
Weaknesses
Contemporary Research
Summary
Suggested Readings
Chapter 4: Vygotsky and the Sociocultural Approach
Biographical Sketch
General Orientation to the Theory
Child-in-Activity-in-Cultural-Context as the Unit of Study
Zone of Proximal Development
The Sociocultural Origins of Individual Mental Functioning: The Intermental Constructs the Intramental
Tools Provided by a Culture Mediate Intellectual Functioning
Methodology
Mechanisms of Development
Position on Developmental Issues
Human Nature
Qualitative Versus Quantitative Development
Nature Versus Nurture
What Develops
Applications
Evaluation of the Theory
Strengths
Weaknesses
A Related Approach: Developing-Person-In-Context
Contemporary Research
Collaborative Problem Solving
Research Across Cultures
Social Change
Immigrant Families
Development Through Narratives and Conversations
Concluding Comments About Contemporary Vygotskian–Sociocultural Research
Summary
Suggested Readings
Chapter 5: Biological Approaches: Ethology, Developmental Neuroscience, Genetics
Ethology
History of the Theory
General Orientation to the Theory
Contributions to Human Developmental Psychology
Mechanisms of Development
Position on Developmental Issues
Applications
Evaluation of the Theory
Contemporary Research
Developmental Neuroscience
Brain Development
Theoretical Issues
Applications
Summary
Genetics
Models of Gene X Environment Interactions
Epigenetic Models
Theoretical Issues
Applications
Summary
Integrated, Multilevel Biological Theoretical Perspectives
Summary
Suggested Readings
Chapter 6: Social Learning Theory
History of the Theory
Learning Theory
Social Learning Theory
General Orientation to the Theory
Observational Learning
Causal Model Includes Environment–Person–Behavior System
Cognitive Contributions to Learning
Self-Efficacy and Agency
Examples of Developmental Research: Moral Judgments and Gender Roles
Moral Judgments and Behavior
Gender-Role Development
Mechanisms of Development
Position on Developmental Issues
Human Nature
Qualitative Versus Quantitative Development
Nature Versus Nurture
What Develops
Applications
Evaluation of the Theory
Strengths
Weaknesses
Contemporary Research
Cognitive Approaches to Learning
Imitation
Selective Social Learning from Others
Summary
Suggested Readings
Chapter 7: Information-Processing Theory
History of the Theory
General Orientation to the Theory
Humans as Information-Processing Systems
Development as Self-Modification
Task Analysis
Methodology
Major Developmental Approaches
Memory
Metamemory
Mathematical Understanding
Rules for Problem Solving
Computational Modeling
Mechanisms of Development
Position on Developmental Issues
Human Nature
Qualitative Versus Quantitative Development
Nature Versus Nurture
What Develops
Applications
Evaluation of the Theory
Strengths
Weaknesses
Contemporary Research
Executive Function
Developmental Cognitive Neuroscience
Embodied Cognition
Bayesian Computational Models
Developmental Robotics
Summary
Suggested Readings
Chapter 8: Gibson’s Ecological Theory of Perceptual Development
Biographical Sketch
General Orientation to the Theory
Ecological Approach: Affordances
Information Is Specified in Stimulation
Humans as Active Perceivers
Methodology
What Infants Learn About
Communication
Interaction with Objects
Locomotion in the Spatial Layout
Mechanisms of Development
Position on Developmental Issues
Human Nature
Qualitative Versus Quantitative Development
Nature Versus Nurture
What Develops
Applications
Evaluation of the Theory
Strengths
Weaknesses
Contemporary Research
Summary
Suggested Readings
Chapter 9: Theories Today: Themes and Perspectives
Generally Accepted Theoretical Principles
Overview of Theorizing Today
Themes Driving Theorizing and Research Today
1. How general are developmental changes?
2. How can complex, dynamic change be captured theoretically?
3. How can theories best depict long-term development?
4. How can theories best depict universal and diverse aspects of development?
Position on Developmental Issues
Summary
Suggested Readings
Chapter 10: Reflections
Developmental Issues Revisited
Human Nature
Qualitative Versus Quantitative Development
Nature Versus Nurture
What Develops
Moving Toward Mechanisms of Development
Historical Progress of Developmental Theories
Critical Psychology: Are Theories of Development Gendered?
Conclusions
References
Name Index
Subject Index
Back Cover
2016-02-25T03:46:11+0000
Preflight Ticket Signature
Developmental Psychology
1992, \W. 28, No. 6,
1018
-1029
Copyright 1992 by the American Psychological Association, Inc.
0012-1649/92/13.00
Developmental Psychology in the Context of Other Behavioral Sciences
Robert A. Hinde
St John’s College, Cambridge
and Medical Research Council Group on the Development and Integration of Behaviour
Madingley, Cambridge, United Kingdom
Certain characteristics of psychology that have been instrumental to its success, such as emphases
on an experimental approach, on group means, on theory-driven research, and on analysis but not
synthesis, can be detrimental to progress if taken too far. In addition, psychology’s success has led
to its fragmentation into subdisciplines, with too little cross-fertilization. Future progress may
depend on a focus not only on individuals, but also on individuals in a network of social relation-
ships whose course is influenced by social norms and values. In this connection, it is helpful to
distinguish a number of levels of social complexity and to come to terms with the dialectical
relations between them. We must pay more attention to description as a first stage in the analysis of
process, recognizing that description can never be perfect and that it must embrace the several
levels of social complexity. We must also come to terms with the relations between the several levels
of complexity, and thus between the several subdisciplines appropriate to them. This multidisci-
plinary approach can be based on a study of relatively stable human behavioral characteristics and
must include the relations among individuals, relationships, and culture. Some pointers can be
found in a judiciously used evolutionary approach.
A centenary is a time to look back, to see how much has been
achieved in the preceding decades. But the enormous progress
made by developmental psychology hardly needs underlining,
and self-congratulatory backslapping would be out of place in a
journal to be read by developmental psychologists. A centen-
ary is also a time to look forward, to assess the present con-
straints on further progress and ask how they can be overcome.
Let us then start with some gross generalizations, not because
I
believe for a moment that they are without exceptions, but be-
cause they help focus attention on some current problems in
developmental psychology.
In its early days, psychology needed to establish itself as a
distinct discipline and to achieve recognition as a respectable
branch of science. It achieved distinctiveness from biology/phy-
siology by focusing on the psyche, and from philosophy pri-
marily by adopting an experimental approach. It achieved re-
spectability by attempting to ape physics—again by the use of
the experimental method—and also by attempting a hypothe-
tico-deductive approach, by an emphasis on objectivity, and
also by the use of statistical tools.
Each of these, taken too far, has brought problems. A focus
on the psyche came into conflict with pressures to study behav-
ior objectively, which in turn led to a neglect of process. An
overemphasis on an experimental approach led to an underem-
phasis on people in the real world and to single-variable studies.
I am grateful to Patrick Bateson (1991) for editing a series of essays
that brought together many of the issues discussed in this article, and
to him, John Fentress, and Joan Stevenson-Hinde for comments on an
earlier draft of the article.
Correspondence concerning this article should be addressed to Rob-
ert A. Hinde, The Master’s Lodge, St. John’s College, Cambridge CB2
1TP, United Kingdom.
Attempts to ape physics led to an underestimation of the im-
portance of description: much of classical physics dealt with
everyday events for whose analysis description was unneces-
sary, but the complexity of human behavior demands an initial
descriptive phase.
The undervaluing of description led also to a belief that re-
search should always be theory-driven. This is fair enough if not
overstated, but it can lead to an unwillingness to allow the data
to suggest problems. During the forties and fifties, a hypothe-
tico-deductive approach led to a particularly narrow, theory-
driven approach, with a focus on limited experimental situa-
tions. Although theory-driven research is often a first priority,
important advances can also follow if novel phenomena are
seized and studied with the best tools available. Examples are
provided by Bowlby’s (e.g., 1969) following up of the finding
that disturbed adolescents had had major and repeated separa-
tion experiences in childhood, Andrew’s (1991) discovery of
the effects of testosterone on the persistence of motor patterns
and the duration for which events are held in the working mem-
ory, or Horn’s (1985, 1991) discovery of asymmetries in brain
function in chicks. Finally, an overemphasis on statistics can
lead to a focus on group means with a neglect of individual
differences.
These caveats are not intended to play down in any way the
extraordinary progress made by psychology in general or by
developmental psychology in particular. But a retrospective
view and a recognition of past constraints can warn usof future
dangers. And there is one further issue that is a direct result of
psychology’s success: its fragmentation into subdisciplines. De-
velopmental psychology has, properly, become a field in its own
right but, as a result, has become partially cut off from clinical,
personality, physiological, and social psychology and from biol-
ogy. Developmental psychology has focused largely on changes
1018
APA CENTENNIAL: INTEGRATING BEHAVIORAL SCIENCE 1019
with age and on group averages, but we need also to understand
individuals, the primary concern of much clinical and personal-
ity psychology. Physiological analysis leads to functions of
parts, and although individuals function as wholes, that func-
tioning depends on, but cannot be entirely explained by, pro-
cesses within parts. And physiological analysis can aid behav-
ioral understanding. A recent example is the manner in which
Rosenblatt’s (1991) survey of the physiology of parturition
poses new questions about the onset of maternal responsive-
ness. Social psychology is concerned largely with group phe-
nomena, and developmentalists—knowing that children grow
up in groups, that relationships are crucial to their develop-
ment, and that values, expectations, and hopes held by the
child and others shape development—need social psychologi-
cal expertise. And ethology, as we shall see, can contribute prin-
ciples and perspectives of importance to developmental psy-
chologists.
We have here demands that could conflict: science proceeds
by analysis, but one needs synthesis and the study of wholes as
well; one needs to specialize, but that means studying only
parts of a whole; one needs to describe phenomena, but one
also needs to understand process; one needs concepts to cope
with intangibles, but one must not lose discipline. It would be
folly to suggest that these problems can be readily solved, but
the following sections address a series of relevant and interre-
lated issues.
There are three main themes. The first concerns the need to
focus not only on individuals, but also on individuals in a net-
work of relationships, and this in turn requires us both to distin-
guish levels of social complexity and to come to terms with the
dialectical relations between them. The second is that descrip-
tion is a necessary first step, but can never be perfect. Our
categories and concepts are essential heuristically but are never
absolute, because we have at present no entirely satisfactory way
of coping with entities that are both isolatable and intercon-
nected and mutually influence each other. The third is the need
to integrate developmental psychology with other disciplines.
Here, because of my own biases, I refer especially to ethology,
though I am aware that some of the ideas I ascribe to ethology
also had other roots.
Levels of Complexity
Children grow up in a network of relationships and usually
within families, which form parts of larger groups. It is thus
necessary to come to terms with a series of levels of social
complexity: physiological and psychological systems, individ-
uals, short-term interactions between individuals, relationships
involving a succession of interactions between two individuals
known to each other, groups, and societies (Figure 1). Each of
these levels has properties not relevant to lower levels, and at
each level new descriptive and explanatory concepts are
needed. For instance, we may describe the behavior of two
individuals in an interaction as “meshing” well, but meshing is
a concept irrelevant to the behavior of an individual in isola-
tion. Furthermore, each level affects and is affected by other
levels. Thus the course of an interaction depends both on the
natures of the participating individuals and on the relationship
of which it forms a part, and the nature of a relationship is
influenced both by the component interactions and by the
group in which it is embedded. Furthermore, each of these
levels influences, and is influenced by, the physical environ-
ment and by the sociocultural structure of ideas, values, myths,
beliefs, institutions with their constituent roles, and so on,
more or less shared by the individuals in the relationship,
group, or society in question.
Recognition of these levels is in no way an argument for unidi-
rectional reductionism, because the dialectical relations be-
tween levels are crucial (cf. Fentress, 1991). Each level, includ-
ing that of the individual, must be thought of not as an entity
but rather in terms of processes continually influenced by the
dialectical relations between levels (Hinde, 1987,199 la). It will
be apparent that such an approach always demands liaison be-
tween a variety of disciplines.
Each level, as well as the sociocultural structure, has both
objective and subjective aspects. For example, relationships
have objective aspects that are apparent to an outside observer
and subjective aspects that are specific to each participant,
known in their entirety only to him or her, and shared only
partially. Similarly, the objective aspects of the sociocultural
structure may be partially codified in laws and customs, but
the subjective aspects may be subtly different for each indi-
vidual.
The position taken here is not so extreme as that of some who
espouse dialectical determinism (review Hopkins & Butter-
worth, 1990). It is of course basic that development must be
studied at several levels simultaneously and that stability is, if
not always momentary, at least dynamic. But though emphasiz-
ing process, 1 would argue that the view that organism and
environment are inseparable is not helpful. Although the diffi-
culties of boundary definition matter and must be borne in
mind, the essential thing is to come to terms with the continu-
ous interplay (e.g, Markova, 1990; Mead, 1934). And while re-
jecting linear causal chains, I would stop short of saying that
development can never be adequately predicted on the basis of
individual elements, although that perhaps reflects an aspira-
tion rather than an achievable goal.
Description
How can one cope with multiple levels of analysis simulta-
neously? How can one nail down entities constituted by continu-
ous dynamic processes? Description and categorization are
clearly necessary as a preliminary to—or as a part of (Carey,
1990)—analysis, but in describing such phenomena one inevita-
bly simplifies the complexity of real life. A delicate balance
must be struck between using categories and concepts that one
can handle and distorting nature. And that one is compromis-
ing must not be forgotten.
This is a lesson that is being learned slowly by ethologists. For
example, the early concept of the Fixed Action Pattern (FAP),
used to refer to a species characteristic movement pattern,
seemed clearcut. Gradually, it became apparent that all FAPs
were variable, and the concept became replaced with that of the
Modal Action Pattern (Barlow, 1977). Similar issues arise in
child development. In studies of preschoolers, “aggressive be-
havior” seemed a clearcut category, but experience soon
showed that the category boundaries are hard to define and
1020 ROBERT A. HINDE
SOCIETY
SOCIO-CULTURAL
STRUCTURE
INTERACTION
INDIVIDUAL BEHAVIOUR
PHYSIOLOGICAL FACTORS
Figure 1. The dialectical relations between successive levels of social complexity.
PHYSICAL
ENVIRONMENT
that the category is itself heterogeneous. But subdivision met
similar problems. The subcategories into which it is usually
divided (e.g., instrumental aggression and teasing aggression
[Feshbach, 1970]) themselves have shady boundaries. It is
nearer the truth (though not necessarily facilitatory of research)
to recognize that aggressive acts involve other behavioral sys-
tems—for instance, tendencies to acquire objects (flcquisitive-
ness) or status (assertivenesty—and that the nature of the aggres-
sion shown depends on interactions between these systems (Fig-
Aggressiveness
Acquisitiveness
Assertiveness
Figure 2. Model of the relations among three propensities and ag-
gressive behavior. (Aggression would be shown if the current state were
represented by a point above the striped surface.)
ure 2). As another example, Stevenson-Hinde (1991) has argued
that although fear behavior and attachment behavior are to be
thought of as discrete behavioral systems, “the postulation of
discrete behavioural systems should not obscure relations be-
tween them. Activation of a fear behaviour system may lead to
activation of an attachment behaviour system” (pp. 325-326)
and activation of the attachment behavior system may inhibit
the fear.
This tendency for systems to change their state or even their
properties according to the broader context within which they
are operating has been repeatedly stressed by Fentress (e.g.,
1991). For instance, at a lower level of analysis, Getting and
Dekin (1985) have shown that the neural networks operative in
the swimming of the mollusc Tritonia are reconfigured into
different functional circuits according to the behavioral state of
the animal and that the neurones involved cannot be clearly
categorized as motor neurones, central pattern generators, and
so forth. And at higher levels of social complexity, relationships
or families may change their characteristics with the context.
Fentress sees the difficulties in understanding behavior and
development as stemming in large part from the difficulty of
comprehending that, at all levels of complexity, systems must
be both self-organizing and interactive with other systems.
“Varying forms of behavioural taxonomy clarify certain proper-
ties of expression while potentially obscuring others. Unitary
‘boxes connected by arrows’ taxonomies often do not work, in
part because they too easily draw our attention away from the
properties of the arrows that in turn may affect the properties
of the boxes” (Fentress, 1991, p. 98).
From this perspective, it is not surprising that individuals
behave differently in different social contexts. Stevenson-
Hinde (1986) has pointed out that so-called “child characteris-
tics” refer to characteristics that lie on a continuum from indi-
APA CENTENNIAL: INTEGRATING BEHAVIORAL SCIENCE 1021
vidual characteristics to relationship or situation characteris-
tics, with height and weight but few if any psychological charac-
teristics at the individual end, temperament dimensions close
to but at varying distances from it, and attachment categories
near the relationship end.
It is possible that we should view some age changes in the
same way. We are accustomed to the concept of “age-appro-
priate behavior,” ascribing underlying similarities across ages to
“heterotypic continuity” (Kagan, 1971) and the changes to
changes in the system concerned, but they could also be caused
by changes in relations with other systems. For example, digit
span increases between infancy and adulthood, but the evi-
dence indicates that memory span remains constant after
about age 4, the changes being caused by a domain-specific
increase in knowledge about the materials (Carey, 1990).
Because of this lability in the elements and in the relations
between elements, every generalization should be accompa-
nied by a statement of its limitations—a requirement that
makes description of both behavior and context even more nec-
essary. As an example of the importance of this, Radke-Yarrow,
Richters, and Wilson (1988) found that higher rates of initial
child compliance were related to more positive mother-child
relationships only in families categorized as “stable,” and ma-
ternal use of harsh enforcement was associated with more nega-
tive mother-child relationships only in “chaotic” families.
Again, Stevenson-Hinde and Shouldice (1990) found that
mothers of securely attached children tended to overestimate
their children’s shyness, whereas mothers of insecurely attached
children tended to underestimate.
Therefore, we must recognize that description and classifica-
tion nearly always involve trying to push nature into pigeon
holes when the fit is by no means perfect and that, for psycholo-
gists, description must embrace the several levels of social com-
plexity.
Developmental psychology, concerned with what children do
or can do at different ages, has not neglected description, but it
is worth emphasizing two issues. First, at the behavioral level,
there are two routes to description: (a) one that refers ultimately
to patterns of muscular contraction, and (b) one that refers to
the consequences of action or the meanings behind action.
Each has its uses and advantages (Hinde, 1966). Taking a lead
from studies of lower species, such as fish, some researchers
(e.g., Blurton Jones, 1972) have attempted to describe children’s
behavior by focusing solely on the former route. However, chil-
dren are not fish, and such attempts have proved on the whole
sterile. Better ways for describing children’s behavior, which do
not assume that behavior is all we are interested in and take
account of the meanings behind actions, are available (e.g.,
Caldwell, 1969; Lytton, 1973).
Second, description is necessary at each level of social com-
plexity, and the more complex the phenomenon, the more se-
lective description must be. A special problem arises in the
description of relationships (and higher order phenomena). De-
velopmental psychologists normally study interactions, for in-
stance, studying mother-child play across a number of dyads
and making generalizations across dyads. Relationships involve
a number of types of interaction and cannot be described from
generalizations across dyads about interactions, because the
different interactions within each relationship affect each
Interactions
approach
Dyad
A – B
C – D
E – F
A – B
C – D
E – F
Relationships
Dyad
Interaction type
X S > Generalization
J
Y > > Generalization
J
approach
Interaction type
A – B X-“|
A – B Y \ > Generalization
A – B zJ
C – D
C – D
C – D
Y > > General izat ion
Figure 3. The contrast between achieving generalizations about
interactions and generalizations about relationships.
other. Rather, each relationship must be described, and only
then can generalizations be made across dyads (Figure 3).
Attachment theory involves a procedure for categorizing
some aspects of mother-child relationships (Ainsworth, Blehar,
Waters, & Wall, 1978; Cassidy & Marvin, 1989). A means for
classifying other characteristics of relationships is given by
Hinde (1979,1991a).
Relations Between Levels
Even though analysis tends to move from more complex lev-
els to less, the importance of crossing and recrossing in both
directions cannot be overestimated. The relations between lev-
els of social complexity are well established in studies of physiol-
ogy and behavior (e.g., Andrew, 1991; Horn, 1991; Hutchison,
1991), but they are equally important in developmental studies.
It is not only that similar principles of organization may be
repeated at different levels, it is also necessary to trace causal
relations between them.
Both the experiences a child has in interactions with others
and the effects of those experiences on the child himself or
herself depend on his or her nature. Those interactions will
affect and be affected by the relationships of which they form
part, and those relationships are similarly related to the family
or group. Each of these levels may also be affected by the socio-
cultural structure, by the myths and values current in the fam-
ily, group, or society. Thus we need to come to terms with the
dialectical relations between levels.
Consider, as an example, the genesis of a fear of snakes. Chil-
dren brought up in an institution who have never seen a snake
1022 ROBERT A. HINDE
show little fear if they first encounter one at 30 months, but they
avoid a snake crawling on the ground from about 3 years
(Prechtl, 1950). Children also show spontaneous fears of other
objects or situations that might have posed a real threat in hu-
man’s environment of evolutionary adaptedness, such as
spiders, heights, darkness, and being alone. Humans are much
less prone to develop spontaneous fears of other situations that
are genuinely lethal in modern society but that were not present
earlier in evolutionary history, such as cars or bombs (Marks,
1987). It is thus not unreasonable to suppose that a propensity
to fear, or to learn to fear, snakes is part of the human biological
heritage.
Anecdotal evidence suggests that the extent of the fear is
much influenced by social referencing. The child looks at
others, and especially at a trusted other, and imitates their re-
sponse (Emde, 1980; Klinnert, Campos, Sorce, Emde, &
Svedja, 1983). Comparative evidence provides strong support
for this view thus: (a) Wild-reared rhesus monkeys tested in the
laboratory nearly always show fear of snakes; (b) laboratory-
reared monkeys do not show fear of snakes; (c) laboratory-
reared monkeys shown a videotape of a wild-reared monkey
showing fear of a snake become afraid of snakes thereafter; and
(d) laboratory-reared monkeys shown a “doctored” videotape of
a wild-reared monkey apparently showing fear of a flower do
not become afraid of either flowers or snakes (Mineka, 1987).
There is thus clear evidence that rhesus monkeys have a pro-
pensity to fear snakes that depends for its full realization on the
experience of seeing others respond fearfully to snakes. This in
turn increases the plausibility of a similar explanation of snake
fears in humans.
Some individuals develop snake phobias, showing a fear of
snakes out of all proportion to the threat they present, a fear
that is irrational and is beyond voluntary control. It is reason-
able to suggest that the role of snakes as a symbol in our culture
is related to these issues. Snakes play an important part, and
have played an even more important part, in our mythology. In
the myth of the garden of Eden, in the Rubens paintings of
snakes gnawing at the genitals of those cast down into Hell,
snakes symbolize evil. Therefore, if we are really to understand
fear of snakes and the symbolic role of snakes, we must come to
terms with a series of dialectical relations among the propensity
Fear of Snakes
Snake Myths Behaviour of
caregiver
Propensity to
fear snakes
.Snake fear
& phobias
Figure 4. The genesis of fear of snakes.
to fear snakes, social referencing within relationships, and
snake myths within the sociocultural structure (see Figure 4 and
further discussion in Hinde, 1991a).
Let us consider a very different example that also suggests
complex links between the levels of social complexity. In a
study of families in a research apartment in Bethesda, Mary-
land, Radke-Yarrow et al. (1988) found the following: (a) There
was a high level of concordance in negative affect between the
members of mother-child dyads, indicating strong interdepen-
dence within the dyad, (b) In families in which the mother-
younger child were concordant in negativity, both mother-
older child relationships and sibling relationships tended also
to be concordant, (c) Mothers showed more negative affect in
families of low socioeconomic (SES) status. When the instabil-
ity and unpredictability of life circumstances in the families
were examined, it appeared that the link between low SES and
maternal negative affect was primarily due to the corrosive
hardship of unpredictability and disorganization, (d) As men-
tioned earlier, the relations between indices of maternal control
interactions and the nature of the mother-child relationship
varied with family stability. Thus higher rates of child compli-
ance were related to more positive mother-child relationships
only in stable families, and maternal use of harsh enforcement
was related to more negative mother-child relationships only in
more negative ones, (e) The relation between child characteris-
tics and the mother-child relationship differed according to
the sex of the child. Thus shy girls had more positive relation-
ships with their mothers than nonshy girls, whereas shy boys
had worse relationships than nonshy boys. Radke-Yarrow et al.
ascribed this difference to other child characteristics associated
with shyness. A very similar finding in Britain by Simpson and
Stevenson-Hinde (1985) was ascribed to maternal values: Mac-
coby and Sants (personal communication) showed that Califor-
nian mothers like little girls to be shy and little boys not to be.
Although these data were cross-sectional, they strongly suggest
influences among individual characteristics, relationships, fam-
ily characteristics, and the sociocultural structure of beliefs and
values. Dunn’s (1991) important studies of sibling relationships
within the family led to a similar conclusion.
Not clearly demonstrated by these data, but important in the
long run, are influences up the levels of complexity. The nature
of the family depends on those of the family members and on
their relationships, and the values and beliefs of a society stem
ultimately from processes in individuals.
Nature-Nurture: Relatively Stable Characters,
Constraints on Learning
For logistical reasons, every study in developmental psychol-
ogy has limits. One cannot trace all the dialectical relations
shown in Figure 1 in every investigation. A starting point is
therefore needed. Can one identify simple items or properties
of behavior that can fill this role? The previous discussion of
the difficulties of describing behavior indicates that one must
be content with approximations, with categories heuristically
useful but shady at the edges.
A false start involved the view that behavior or propensities
could be divided into those that are innate and those that are
learned or otherwise acquired. Although this error has long
APA CENTENNIAL: INTEGRATING BEHAVIORAL SCIENCE 1023
been recognized (Bateson, 199 la, 1991b; Oyama, 1985), it still
persists. Development involves an interplay between the indi-
vidual and the environment. The current state of the individual
influences which genes are expressed, and individuals influ-
ence and change the world they encounter. At the present time
twin and adoption studies are providing new insights into the
interactions between genetic and environmental factors in de-
velopment (e.g., Plomin & de Fries, 1983; Scarr & Kidd, 1983).
Although the dichotomy of innate versus learned behavior is
false, it is possible to arrange characters along a continuum
from those that are relatively stable with respect to environmen-
tal influence to those that are relatively labile (Barlow, 1989;
Hinde, 1966,1991a). Thus there are some characters that ap-
pear in virtually the whole range of environments in which life
is possible (“stable” characters): either the processes involved in
their development are so regulated that they appear over a wide
range of experiential influences, or the factors relevant to their
development are ubiquitous. By contrast, characters at the la-
bile end of the continuum appear only over a narrow range of
conditions. It will be noted that this formulation differs from
the innate-learned dichotomy in that (a) it involves a contin-
uum and (b) a characteristic may be influenced by experience
but yet is stable because the relevant influences lack specificity
or are ubiquitous. However, the level of analysis at which the
character is denned may be crucial. Thus the broad details of
the motor pattern of smiling form a stable human characteris-
tic, yet its fine details and the circumstances in which it is given
are labile. Furthermore, development may be stable up to a
certain point and labile thereafter, or labile first and stable
later.
For some (but not all) problems such relatively stable charac-
ters can provide us with starting points, provided, however, that
we remember that they will be subject to variation. It is imprac-
ticable to make a list of such characters, partly because a list of
mundane characters would be tedious, and partly because the
cross-cultural data are not adequate to prove cross-cultural sta-
bility for any characters. However, they might include aspects of
perception, motor patterns, stimulus responsiveness, motiva-
tion, cognitive processes, predispositions to learn (including
the capacity for language), and so on (see Hinde, 199la).
Of course, each such “relatively stable” character itself poses a
developmental problem. Because the degree to which genes are
expressed may depend on the environment, and because suscep-
tibility to the environment may depend on the genetic constitu-
tion, the constraints on their variability themselves involve an
interplay between genetic and environmental influences. The
same is true for subsequent development.
The importance of constraints on learning and predisposi-
tions to learn must be emphasized here (Hinde & Stevenson-
Hinde, 1973; Seligman & Hager, 1972). The earlier work on this
subject concerned animals, where cross-species comparisons
threw genetic constraints on development into relief. For in-
stance, the chaffinch (a small bird) has to learn its song, but it
will learn only songs with a note structure similar to the spe-
cies-characteristic song. The bullfinch learns preferentially the
song its father (biological or adoptive) sang (Thorpe, 1961).
Even the capacity to acquire individual distinctiveness in sing-
ing behavior, essentially creative in nature, is to be seen in this
light (Marler, 1991).
Humans as a species presumably also have similar con-
straints, though we recognize them only in the observation that
some tasks or experiences are difficult to learn. Indeed it can be
agreed that efficient learning requires inbuilt constraints (John-
son-Laird, 1990). Within the human species, similar con-
straints probably operate in autism. Autism is known to have
genetic “bases” and involves specific deficits in understanding
of emotion caused by beliefs (Baron-Cohen, 1991). It has also
been suggested that male and female humans differ in their
predispositions to learn (Hinde, 1987).
Constraints or predispositions may equally well be environ-
mental in origin in both animals (Bateson, 1987; Gottlieb,
1991) and humans (e.g., Butterworth & Bryant, 1990; Sameroff
& Chandler, 1975). Insofar as an individual is what he or she is
as a consequence of prior experience, and future development
depends on current state, all development is channeled by expe-
rience.
Relationships and Individuals
The critical question for the developmental psychologist is
how individual characteristics are affected by the relationships
experienced. Strong associations between parenting practices
and child characteristics, involving social behavior (e.g.,
Baumrind, 1971; Bretherton, 1985; Maccoby & Martin, 1983),
affective behavior (e.g., Easterbrooks & Emde, 1988; Radke-
Yarrow et al., 1988), and cognitive dimensions (e.g., Goswami &
Bryant, 1990) have been demonstrated, and although it must be
assumed that influences operate both ways, in at least some
cases there is an effect of parenting practices on the child.
But the issues are not simple. First, some individual charac-
teristics may be influenced by relationships more than others,
and the extent to which any one characteristic is affected may
change during development. Thus the propensity to show fear
may be relatively independent of relationships from 0 to 6
months, subsequently modified by relationships and reinforce-
ment, and later still become relatively fixed (Stevenson-Hinde,
1988).
Second, in the case of relatives, and especially parents, it is by
no means easy to distinguish genetic from experiential influ-
ences. First, similarities in genetic constitution may predispose
the child to respond to environmental events similarly to, for
example, the parents. Second, similarities in genetic constitu-
tion may cause the child to select or create an environment
similar to that to which the parents preferentially respond.
Third, parents may be predisposed genetically to provide their
children with an environment conducive to the development of
particular characteristics. For example, shy parents may both
pass on genes associated with a predisposition to develop a
behavioral style that might be labeled as shy and create an envi-
ronment in which their children saw few strangers. Finally, par-
ents and others may react differently to children of different
genotypes (e.g., Jaspers & Leeuw, 1980; Plomin, 1986; Plomin &
de Fries, 1983; Scarr & McCartney, 1983).
With regard to the processes whereby interactions within re-
lationships have long-term effects on child behavior, until re-
cently most work focused on reinforcement and modeling.
Current interest centers on possible cognitive intermediaries
between attachment relationships and subsequent interactions.
1024 ROBERT A. HINDE
The quality of the child’s attachment relationship with the
mother predicts the character of later peer interactions (e.g.,
Sroufe, 1983; Sroufe & Fleeson, 1986; Turner, 1991), suggesting
that it affects some aspects of the child. Bowlby (1969), taking a
lead from Craik (1943), postulated that the child forms internal
working models of self, of others, and of their relationships.
During the last decade, this idea has achieved increasing promi-
nence. Initially, although heuristically useful, it was too ill-de-
fined to serve as a scientific concept (cf. MacCorquodale &
Meehl, 1954). For instance Main, Kaplan, and Cassidy (1985, p.
68) described it as “a mental representation of an aspect of the
world, others, self, or relationships to others that is of special
relevance to the individual,” and elsewhere as “a set of
conscious and/or unconscious rules for the organization of in-
formation.” In this and other articles, additional properties
were ascribed to the concept, many of which were isomorphic
with the phenomena they were seeking to explain (Hinde,
1989a). Furthermore, there were both methodological and con-
ceptual differences in the way in which the concept was used by
different workers (Crittenden, 1990). Now, however, the con-
cept of internal working model is in an exciting stage of develop-
ment, involving inputs from work on cognition by both cogni-
tive psychologists (e.g., Johnson-Laird, 1983,1990) and develop-
mental psychologists/psychiatrists (e.g., Stern, 1985, 1991).
Bretherton (1990) conceptualized internal working models as
systems of hierarchically organized schemata, with the models
of self, others, and the world interlinked and mutually influenc-
ing each other (cf. Fentress, 1991). Used in this way, the concept
is becoming more than a useful metaphor and is able to inte-
grate data on psychopathology, the transmission of patterns of
parenting across generations, the relations between communi-
cation within attachment relationships and communication
about such relationships to third parties.
Effects of Relationships on Relationships
A child grows up in a network of relationships, and the dif-
ferent relationships may affect each other (Hinde & Stevenson-
Hinde, 1988a, 1988b). The influence of relationships on rela-
tionships has been of interest to three groups of workers. Pri-
matologists have come to recognize that relationships affect
relationships within primate groups and, with observational
and experimental evidence, that the mother-infant relationship
is crucially affected by others (Hinde, 1972,1983). Child devel-
opmentalists have demonstrated that the quality of a particular
relationship in the family may be related to that of another. For
instance, the marital relationship may be related to the mother-
child relationship (Christensen & Margolin, 1988; Easter-
brooks & Emde, 1988; Engfer, 1988; Meyer, 1988), the mother-
child relationship may be related to the sibling relationship
(Dunn, 1988a, 1988b), divorce may have long-term sequelae for
the children (Hetherington, 1988; see also Rutter, 1988), and
effects of inadequate parenting may be transmitted across gen-
erations (Belsky & Pensky, 1988; Caspi & Elder, 1988; Gross-
man, Fremmer-Bombik, Rudolph, & Grossman, 1988; Patter-
son & Dishion, 1988). Some of the mechanisms involved are
summarized by Hinde and Stevenson-Hinde (1988b).
A third group concerned with the effects of relationships on
relationships has been the family systems theorists. Although
there are many points of contact between them and develop-
mental psychologists working on similar problems (P. Minu-
chin, 1985), the family systems theorists (themselves diverse)
have developed a rather distinctive orientation and vocabulary.
They emphasize the family as an open system, with organized
patterns of interaction that are circular in form. The family
system has homeostatic features that maintain the stability of
the patterns within it, but may periodically undergo perturba-
tions requiring a reorganization of patterns. The individuals
constituting the family are seen as interdependent and distrib-
uted across subsystems which have their own integrity and
whose interactions are governed by implicit rules and bound-
aries (e.g., P. Minuchin, 1988).
It will be apparent that many of the properties emphasized
by family systems theorists are compatible with the interdepen-
dent yet self-organizing systems whose importance is empha-
sized by Fentress (1991) at lower levels of analysis (see earlier
discussion). It is important to recognize that the family as a
whole can have properties with some degree of independence
from the behavior of its component units—analogous (only) to
Hoyle’s (1964) finding at a quite different level that the regular
stepping movements of insects are not accompanied by fixed
patterns of electrical activity in the motor neurones. Further-
more, the concepts of family systems theorists are clearly po-
tentially compatible with the dialectical relations between lev-
els shown in Figure 1.
My own view is that the level of dyadic relationships merits
special attention for developmental psychologists, in that it is
by interactions within relationships that development is af-
fected. From there it is possible to assess how interactions and
relationships are affected by third parties (e.g., Clarke-Stewart,
1978; Corter, Abramovitch, & Pepler, 1983; Barrett & Hinde,
1988), other relationships, and the sociocultural structure. To
foster further links between family systems theorists and devel-
opmental psychologists, it would be desirable to clear up a few
conceptual issues (Hinde, 1989b). For instance:
1. Family systems theorists emphasize the family as an “orga-
nized whole” and ascribe to it homeostatic properties. But the
maintenance of the family as a functioning unit depends on the
behavior of individuals within their relationships. Family orga-
nization may derive either from personal goal seeking—in
which individuals attempt to create a family that suits their own
personal needs, and the resulting pattern of relationships is a
consequence but not a goal of the behavior of individuals—as
well as from interpersonal goal seeking, involving efforts to
make the constituent relationships conform to an ideal or de-
sired pattern. In both cases, the goals may be unconscious or
loosely defined. In any case, the processes that contribute to
stability are diverse and may reside in one or more individuals
or relationships. And it may involve attempts to approach an
equilibrium or goal state whatever the current state, to ap-
proach it only so long as the current state remains within cer-
tain limits, or to avoid an undesirable state.
2. The same individual may belong to more than one subsys-
tem. Thus the mother is part of both the spouse and the
mother-child subsystem. An advantage of this subsystem ap-
proach is that it permits description of separate patterns for
different subsystems composed of the same people (e.g.,
spouses are also parents). An advantage of the relationships
APA CENTENNIAL: INTEGRATING BEHAVIORAL SCIENCE 1025
approach advocated here is that it calls attention to the effects
of interactions on interactions within a relationship and be-
tween relationships, so that a mother’s marriage may affect (or
be affected by) the mother-child relationship. But there is a
clear need for an unambiguous definition of the subsystem con-
cept. For instance, does the concept have a subjective reality for
the participants? If it does, how does it differ from relation-
ships? If it does not, as would appear to be the case with the
“three generational subsystem” postulated by P. Minuchin
(1985), is its reality confined to the mind of the therapist?
3. Some family therapists downplay the role of the individ-
ual so far as to hold that attempts “to quantify the relative input
of members of a system” do not make sense in a systems frame-
work (P. Minuchin, 1985, p. 300). Developmental psychologists
may disagree, especially if the questions asked are concerned
with changes in or differences between relationships or families
and are carefully phrased (Hinde, 1979).
4. Earlier, the importance of distinguishing between the ob-
jective and the subjective reality of aspects of the sociocultural
structure was noted. This distinction could be important to
family systems theorists. Are family tasks, family myths, and
family style descriptive concepts useful to the therapist, or are
they (consciously or unconsciously) part of the perceptions of
the participants, and thereby influencing process? And the fam-
ily world view, concerned with the family’s self-perceptions, may
be shared by family members, but there may also be marked
differences between family members in the way they perceive
the family.
These somewhat academic points are perhaps tangential to
the clinical achievements of the family systems approach and
are intended only to supplement the important efforts made by
P. Minuchin (1985) and others to bridge the gap between clini-
cians and developmentalists. In my own view, the means by
which relationships affect relationships pose crucial problems
for developmental psychology.
Individual Differences
Developmental psychology’s successes would have been im-
possible without the use of statistical techniques. Nevertheless,
their widespread and proper use has resulted in a focus on
group means and a neglect of individual differences, although
it is often differences that help us understand processes (Dunn,
1991; Rutter, 1991). Furthermore, a neglect of individual differ-
ences can lessen the value of the data to the clinician who is
attempting to deal with individual cases. The advantages of a
case study approach have recently been described forcefully by
Radke-Yarrow (1991): for example, bringing balance to re-
search dominated by group or variable-oriented research and
greater understanding of the relations between behavioral sys-
tems; light thrown on children at the extremes and on children
who show resilience in adverse circumstances or who fail in
favorable ones; and the sharpening up of data on turning points
in development usually obscured by group variance, thus per-
mitting process to be studied more directly. To the biologist,
individual differences raise the further question as to whether
they merely represent noise in the system or whether they are
adaptive: some examples of the application of this approach to
children are given in a later section.
As Radke-Yarrow (1991) pointed out, a revival of interest in
individual case studies is a recent phenomenon, and statistical
techniques for dealing with multiple levels of data on few indi-
viduals are at present poorly developed (but see D. H. Barlow &
Hersen, 1984; Kazdin, 1982). Although this certainly does not
mean that case studies should not be pursued, there is another
approach that could take us some of the way. Statistical tech-
niques that rely on linear correlational procedures can be mis-
leading, and for many purposes it is preferable to attempt to
categorize children (Hinde & Dennis, 1986). Examination of
those children who appear to be exceptions to the initial catego-
rization can lead one to new generalizations. Iteration of such a
procedure can approach the individual.
An example that goes some of the way toward this goal is
shown in Figure 5, which plots an index of maternal warmth
against maternal strong control in 4-year-olds. The children are
categorized according to whether they were in the top third,
middle third, or bottom third on aggression in preschools. In
three replications, aggression was found to be lower when con-
trol and warmth were more or less in balance, that is, in the
central area, termed authoritative after Baumrind (1971), than
in the authoritarian, permissive, or indulgent areas. This of
course does not necessarily mean that the dimensions plotted
were the crucial ones: in fact, the mother-child relationships
differed between areas in many dimensions in addition to
warmth and control. But there were a few high aggressives in
the authoritative area and a few low aggressives in the others.
These exceptions were found to differ from other individuals in
the same area on some of these other aspects of the mother-
child relationship. If the sample size were adequate this proce-
dure could be iterated to approach the individual level.
Links With Ethology
Many developmental psychologists imagine that any input
biology/ethology might have concerns parallels between ani-
mal and human behavior. Of course, parallels can be found,
especially in relatively simple patterns—for instance, in rooting
behavior and the Moro reflex. Some human expressive move-
ments can be traced back to prehuman forms (e.g., Eibl-Eibes-
feldt, 1975; van Hooff, 1972). But anthropomorphism is danger-
ous, and parallels can be misleading. In some cases they are
revealing only if one finds the right level of analysis. For exam-
ple, behavioral development is disturbed by separating infant
from mother for a week or two in both rhesus monkeys and
humans. However, the evidence indicates that human children
are more disturbed if they are away from home in a strange
place during the separation period, whereas rhesus monkeys
are more upset if they stay in the familiar group environment
and the mother goes away. The difference seems to be that, in
rhesus monkeys, the mother-infant relationship is more dis-
turbed under the latter conditions, because the mother has to
reestablish her relationships with her group companions when
she returns as well as to cope with her demanding infant. What
is common between monkeys and humans is that the more the
mother-infant relationship is disrupted, the more the infant is
disturbed (Hinde & McGinnis, 1977; cf. Rutter, 1991).
As this last example shows, rather than simple parallels, one
should look for principles abstracted from animal data whose
1026 ROBERT A. HINDE
o
o
O
Authoritarian
I
Indulgent
-1.5 -1 -.5 0 .5 1
Maternal warmth
1.5
Figure 5. Relations between maternal warmth and maternal control at home, and the aggression shown
by 4-year-olds in preschool. (The children are categorized according to whether they were in the top third
[circled crosses], middle third [open circles], or bottom third [filled circles] on aggression.)
applicability to the human species can be tested. A classic ex-
ample is Bowlby’s (1969) use of Harlow’s data on rhesus mon-
keys (Harlow & Zimmerman, 1959) to show that contact com-
fort, and not just food reinforcement as had previously been
supposed, was crucial in the mother-child relationship.
Ethologists, unlike developmental psychologists, have em-
phasized that full understanding of a structure or behavior de-
mands answers to four distinct questions. Thus the question
“Why does the thumb move in a different way from the
fingers?” could be answered developmentally (the growth of
digit rudiments and nerve fibres), causally (the structure of
bones, muscles, and nerves), functionally (the thumb’s role in
grasping, etc.), or in terms of evolution (the human species’
monkeylike ancestors presumably had similar thumbs). The
importance of the last two questions has been overemphasized
by some sociobiologists and neglected by most developmental
psychologists. However, such issues can make a not inconsider-
able contribution to understanding child development.
First, they have implications for practice. Thus the finding
that, across mammals, the frequency of suckling is inversely
related to the concentration of the milk and that humans have
relatively dilute milk was a strong argument against schedule
feeding (Blurton-Jones, 1972). The studies of Klaus and Ken-
nell (1976; Kennell, 1986) showing that allowing mothers to
have immediate postpartum contact with their infants has at
least short-term (but not necessarily long-term [Fleming &
Corter, 1988]) beneficial effects were influenced by compara-
tive functional considerations. And, at a more theoretical level,
Bowlby (1969) cast new light on the so-called “irrational fears
of childhood” (fears of darkness, falling, being left alone, etc.)
by arguing that they would have been functional in our environ-
ment of evolutionary adaptedness.
Second, diverse facts about human behavior, which appear
initially to be isolated and independent, can be integrated from
an evolutionary perspective. Thus various aspects of the
mother-infant relationship are seen to form a functional whole
when seen against the probable sociosexual arrangements in
our environment of evolutionary adaptedness (Hinde, 1984).
Third, the links between situations and outcomes can some-
times be understood in functional terms. For example, infanti-
cide and voluntary abortion are more common when the infant
is not the putative parents’ own, the infant has poor reproduc-
tive potential, or circumstances are adverse and reproductive
effort might be wasted. If the incidence of infanticide or abor-
tion is taken as an indicator of parental motivation, the data are
in harmony with the view that motivation is low when further
parental investment in the current offspring might decrease the
mother’s long-term reproductive success (Daly & Wilson,
1984).
It has even been suggested that behavior that seems maladap-
tive in our society may have been functional in others. Thus De
Vries (1984) found that children with a “difficult” temperament
were more likely to survive famine, perhaps because they were
more demanding. Similarly, Main and Weston (1982) suggested
that the behavior of infants whose relationships with their
mothers were avoidant permitted the maintenance of organiza-
tion, control, and flexibility with mothers who do not welcome
physical contact and who are restricted in emotional expression
(see also Egeland & Farber, 1984). It has also been suggested
that the relations between early family relationships and subse-
quent personality or behavioral characteristics are adaptive
(Belsky, Steinberg, & Draper, 1991; Hinde, 1986, 1991b), al-
though the evidence is far from secure.
A fourth possible payoff from an evolutionary-functional
approach is that our changing adjustment to our changing cul-
ture could be greatly facilitated by an understanding of where
we started. This does not imply that there are human character-
istics that are independent of culture, but rather that it is helpful
to distinguish biological desiderata, resulting from natural se-
lection in our environment of evolutionary adaptedness, from
APA CENTENNIAL: INTEGRATING BEHAVIORAL SCIENCE 1027
the desiderata of our particular culture, and to consider the
relations of each to the psychological desideratum of mental
health (Hinde & Stevenson-Hinde, 1990).
Conclusion
My plea, therefore, is for a truly multidisciplinary approach
that focuses on the dialectical relations between levels of social
complexity and, most particularly, on those relations among
the individual, interactions, and relationships. Such an ap-
proach requires not only a descriptive base but also recognition
that description can never be precise, and that both descriptive
and explanatory concepts are concerned with entities that are
interconnected and mutually influence each other.
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Accepted June 16,1992 •
What Is the Shape of Developmental Change?
Karen E. Adolph1, Scott R. Robinson2, Jesse W. Young3, and Felix Gill-Alvarez1
1New York University
2University of Iowa
3Stony Brook University
Abstract
Developmental trajectories provide the empirical foundation for theories about change processes
during development. However, the ability to distinguish among alternative trajectories depends on
how frequently observations are sampled. This study used real behavioral data, with real patterns of
variability, to examine the effects of sampling at different intervals on characterization of the
underlying trajectory. Data were derived from a set of 32 infant motor skills indexed daily during
the first 18 months. Larger sampling intervals (2-31 days) were simulated by systematically removing
observations from the daily data and interpolating over the gaps. Infrequent sampling caused
decreasing sensitivity to fluctuations in the daily data: Variable trajectories erroneously appeared as
step-functions and estimates of onset ages were increasingly off target. Sensitivity to variation
decreased as an inverse power function of sampling interval, resulting in severe degradation of the
trajectory with intervals longer than 7 days. These findings suggest that sampling rates typically used
by developmental researchers may be inadequate to accurately depict patterns of variability and the
shape of developmental change. Inadequate sampling regimes therefore may seriously compromise
theories of development.
Developmental Trajectories
Understanding developmental change is a central goal for developmental science. However,
despite numerous treatises by prominent developmental theorists in a variety of areas urging
researchers to focus on change processes (e.g., Elman, 2003; Flavell, 1971; Siegler, 1996;
Thelen & Smith, 1994), developmental psychologists have made surprisingly little progress
toward understanding the process of developmental change. Part of the problem is historical.
Much of the work in developmental psychology has concentrated on descriptions of children’s
behavior at various ages or on the earliest manifestations of particular abilities. Decades of
reliance on cross-sectional designs, demonstration proofs, and broad-sweeping longitudinal
approaches have left researchers with a gallery of before and after snapshots, studio portraits
of newborns, and fossilized milestones, but little understanding of the process of development
itself. What we need are accurate, fine-grained depictions of developmental trajectories for
cognitive, language, perceptual, motor, and social skills.
The staggering variety of developmental trajectories has also contributed to the lack of progress
in understanding change processes. The shape of developmental change might assume any
number of patterns (Figure 1). For instance, a trajectory might show smooth and monotonic
improvements with age, proceeding at a steady pace as in children’s use of retrieval strategies
in addition (Siegler, 1996), or with accelerating or decelerating rates of change, as in infants’
Correspondence should be addressed to: Karen E. Adolph, Department of Psychology, New York University, 4 Washington Place, Rm
410, New York, NY 10003, Tel: (212) 998-9058, Email: Karen.Adolph@nyu.edu.
NIH Public Access
Author Manuscript
Psychol Rev. Author manuscript; available in PMC 2009 March 11.
Published in final edited form as:
Psychol Rev. 2008 July ; 115(3): 527–543. doi:10.1037/0033-295X.115.3.527.
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acquisition of new words (McMurray, 2007) and improvements in toddlers’ walking skill
(Adolph, Vereijken, & Shrout, 2003), respectively. The path of change may show
discontinuities such as abrupt, stage-like shifts in performance between periods of relative
stability, as in children’s stage-like success on many Piagetian tasks (Schultz, 1998), their
abrupt shift from ignoring to marking the past tense of verbs (Marcus, et al., 1992), and the
sudden transition to grasping while reaching (Wimmers, Savelsbergh, Beek, & Hopkins,
1998). Variability may increase during the period of acquisition, with a series of reversals
vacillating between less and more mature expressions of the skill, as in children’s conservation
of volume (van der Maas & Molenaar, 1992). Or a variable acquisition period may entail use
of multiple, unsystematic use of strategies between incorrect and correct endpoints, as in
(Church & Goldin-Meadow, 1986) and their acquisition of a theory of mind (Flynn, 2006).
Discontinuities can take on other shapes, such as episodic changes, where development
advances like climbing a staircase, with sudden improvements in children’s conceptual
understanding separated by long periods in a single stage (Case & Okamoto, 1996) or small
fits and starts of physical growth separated by periods of stasis (Lampl, Veldhuis, & Johnson,
1992). Discontinuities can involve reversible patterns of change, as in the U-shaped course of
children’s success on math equivalence problems (McNeil, 2007), infants’ alternating stepping
movements (Thelen, 1984), and the classic description of over-regularizations in past tense
verb forms (Marcus, 1992), or the inverted-U-shaped trajectory of cognition over the life span
(Craik & Bialystok, 2006), and infants’ zigzag-shaped error rate in detecting threats to balance
as they learn to sit, crawl, cruise, and walk (Adolph, 2005).
Such descriptions of developmental trajectories play an instrumental role in formulating and
testing theories of development (Gottlieb, 1976; Siegler, 2006; Smotherman & Robinson,
1995; Wohlwill, 1973). For example, a contentious theoretical debate was spurred by
descriptions of a sudden, stage-like increase in children’s rate of word learning, the so-called
“vocabulary spurt,” or “naming explosion” (Bloom 2004; Ganger & Brent, 2004). According
to the classic description, at about 18 months of age, when children have acquired
approximately 50 words, they display a sharp transition from an initial stage of slow vocabulary
growth to a later stage of faster growth. Several influential theories were advanced to explain
the putative shift, invoking major cognitive or linguistic changes that coincided with the spurt
(e.g., Gopnik & Meltzoff, 1987; Reznick & Goldfield, 1992). However, recent work shows
that for most children the increase in the rate of word learning is best fit by a quadratic rather
than a logistic function (Ganger & Brent, 2004). Without a stage-like spurt in the trajectory,
theories positing a sudden, fundamental change in cognitive or linguistic abilities become
superfluous.
As illustrated by this example, regardless of whether the theoretical perspective is one of
discontinuity or continuity, spurts or quadratics, theoretical accounts of how change occurs are
built upon the foundation of an accurate portrayal of the pattern of developmental change
(Wohlwill, 1970, 1973). And, as we demonstrate in this paper, an accurate characterization of
the developmental trajectory depends on the rate at which observations are sampled.
The Problem of Sampling Rate
More than 75 years ago, Vygotsky (1978) criticized researchers’ reliance on sampling methods
that merely characterize the stable endpoints in cognitive development. As a remedy, he
proposed a “microgenetic method” of sampling at small time intervals to observe development
in progress. More recent researchers also have cautioned against over-reliance on cross-
sectional and long-term longitudinal designs (Wohlwill, 1970, 1973), and have espoused the
microgenetic method for capturing the process of developmental change (e.g., Granott &
Parziale, 2002; Kuhn, 1995; Siegler, 2006; Thelen & Ulrich, 1991).
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However, apart from the general criticism that researchers’ typical sampling intervals are too
large, the microgenetic method does not quantify the potential consequences of various rates
of data collection for detecting and characterizing different patterns of development.
Proponents of the microgenetic method have offered general suggestions that researchers
should collect observations spanning the entire period of change from one stable state to
another, and that the frequency of observations should be high relative to the rate of change of
the phenomenon (Siegler, 2006). But these proponents have not addressed the problem of how
to decide whether a sampling interval is small enough to detect the shape of the underlying
trajectory. That is, when does one stable state end and another begin? Is the development step-
like or is there an intervening period of variability, partial or intermittent expression, or
disruption of performance? Similarly, critics of developmental methodology have recognized
that overly large sampling intervals in longitudinal research can cause important patterns of
change to go undetected, and have suggested that developmental researchers sample at smaller
intervals (Burchinal & Appelbaum, 1991; Collins, 2006; Hertzog & Nesselroade, 2003;
McArdle & Epstein, 1987). But how small is small enough?
In fields of inquiry such as physiology, psychobiology, health psychology, and neuroscience,
principles are available to guide the selection of an appropriate sampling rate to ensure recovery
of the underlying pattern. For instance, the Nyquist-Shannon sampling theorem (Nyquist,
1928/2002; Shannon, 1949/1998) provides an algorithm for calculating the minimum sampling
rate to fully characterize complex waveforms. The sampling theorem stipulates that for a
waveform composed of one or more frequencies, with a maximum relevant bandwidth (B), the
minimum sampling frequency (fs) necessary to reconstruct the original waveform must be at
least twice the bandwidth (fs > 2B). In other words, sampling frequency must be at least twice
as frequent as the highest frequency component. For example, recording sounds at 20 kHz, the
upper limit for human auditory perception, would require sampling the waveform at a minimum
of 40 kHz (which is one reason why mp3 digital sound files have such poor quality for higher
frequency sounds). Assumptions about the maximum relevant bandwidth are dictated by the
nature of the research question. A study of human color discrimination would not require light
wavelengths to be sampled beyond the blue end of the visible spectrum.
Ironically, the same developmental psychologists who scrupulously use principles such as the
Nyquist-Shannon theorem to select sampling rates to estimate functions for physiological and
psychophysical variables rely on intuition, convenience, and tradition to select sampling
intervals to characterize developmental change in said functions. For example, to describe age-
related changes in the ERP associated with face and object recognition, Webb, Long, and
Nelson (2005) sampled the EEG at 100 Hz to ensure that they could characterize specific
components of the EEG response distributed during the first 1500 ms after presentation of the
stimulus. But, they relied on arbitrary two-month intervals to chart the developmental trajectory
of the ERP signals. To describe the development of stereoacuity in infants, Held, Birch, and
Gwiazda (1980) estimated the psychophysical functions by ensuring a sufficiently high
sampling rate to distribute intervals of visual angle along the inflection of the curve. Yet, they
relied on an arbitrary, one-month sampling interval to estimate infants’ developmental
trajectories and onset ages. Similarly, Adolph (1997) described developmental changes in
infants’ perception of affordances for crawling and walking by sampling at sufficiently small
intervals of difficulty to ensure robust estimates of the psychophysical functions, while relying
on an arbitrary three-week sampling interval to estimate the developmental trajectories.
A recommended remedy for researchers’ sampling dilemma is to design the spacing of
observations based on a formal theoretical model about the shape of the underlying
developmental function (Boker & Nesselroade, 2002; Burchinal & Appelbaum, 1991). Such
a model would dictate the minimum number of data points and their optimal spacing in time
(e.g., a linear function requires only two observations at each end of the acquisition period).
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However, formal rules such as the Nyquist theorem are applicable only when the data consist
of complex waveforms and the maximum frequency of interest is known in advance. If the
temporal scale of developmental changes also were known in advance, then applying a formal
rule like the Nyquist might be possible (e.g., sample at twice the frequency of the smallest
significant change). Unfortunately, most developmental data are not periodic and are not
generated by simple mathematical functions, where the relevant scale of temporal change can
be obtained by deduction. Thus, developmental researchers must determine patterns of
developmental change empirically and discover, rather than deduce, the temporal scale of
events that make a difference in the process of change.
The problem is compounded because, as Collins and Graham (2002) point out, empirically
derived sampling intervals lead to a “chicken and egg” situation: Without prior knowledge
about the shape of the underlying trajectory to inform a statistical function, researchers cannot
know how frequently to space their observations. And, the underlying function that determines
the shape of the developmental trajectory cannot be discovered empirically without making a
decision about sampling interval. Often, researchers do not even have prior information about
the approximate ages that span the period of developmental change.
Implications for the Shape of Change
Few examples of developmental research have systematically assessed the empirical costs and
benefits of large and small sampling intervals on descriptions of developmental change. A
notable exception is Lampl and colleagues’ research on patterns of physical growth (Johnson,
Veldhuis, & Lampl, 1996; Lampl, Johnson, & Frongillo, 2001; Lampl, Veldhuis, & Johnson,
1992). Traditionally, children’s growth is characterized as a continuous function from birth to
adulthood, with more rapid growth rates during infancy and adolescence. However, when
children’s height is measured every day, growth appears to be episodic. Infants’ height, for
example, can increase 1.65 cm in the course of a single day, separated by long periods of days
or weeks during which no growth occurs. Sampling at weekly intervals results in developmental
trajectories that preserve the episodic nature of children’s growth but reduce the observed
number of growth spurts, increase the amplitude of the spurts, and prolong the periods of stasis.
And sampling at quarterly or yearly intervals, as in traditional studies of growth, results in the
smooth, continuous growth curves on standard growth charts.
Even within a 24-hour period, growth is not continuous. In a tour de force of micro-
measurement, Lampl and colleagues (Noonan et al., 2004) demonstrated episodic growth on
two time scales: brief periods of substantial growth on a scale of minutes and days, flanked by
long periods of no growth on an hourly and weekly scale. Leg growth in freely moving lambs
was measured with a microtransducer surgically implanted across the tibial growth plate. Bone
length was sampled at 167-sec intervals over a period of 3 weeks, synchronized with video
recordings of the lambs’ activity. Periods of bone growth revealed by the microtransducer
coincided with periods of recumbency revealed by the video recordings, and periods when
bones did not grow coincided with periods of loading the limbs in stance or locomotion. The
authors calculated that 90% of bone growth occurs while lying down, even though lambs spend
just over 50% of their time in a recumbent position, and little or no growth occurs while standing
or walking. Clearly, tradition, intuition, and convenience that informed traditional studies of
physical growth have been inadequate for capturing the richness of the actual trajectory.
The case of physical growth shows how increased sampling resolution from years to days to
minutes can provide novel insights into developmental process. The episodic growth pattern
from minute to minute indicates that bones lengthen only when compressive forces on the leg
are absent. Paradoxically, other research has demonstrated that the presence of physical forces
applied to bone promote growth by stimulating the expression of genes that regulate cartilage
and bone formation (Muller, 2003). Together, these research findings imply that cellular
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processes involved in regulating physical growth must be coordinated and synchronized on a
temporal scale previously unsuspected.
As exemplified by the research on physical growth, overly large sampling intervals will cause
interval data to appear smooth and continuous, regardless of whether the underlying trajectory
is episodic or U-shaped. Similarly, overly large sampling intervals will distort the shape of
change for binary data (skills that are indexed as absent or present). Figure 2 shows the potential
impact of sampling at monthly intervals on characterizing patterns of development using actual
data from daily observations of two infants’ progress in balancing upright. The top panel (A)
shows a step function, where the infant exhibited a single transition from not-standing to
standing, from one day to the next. The bottom panel (B) shows a variable developmental
function, where standing was expressed intermittently (21 times) over a protracted transition
period of several weeks. For skills with variable trajectories and reversals, interpolating over
the existing data points—which is what all developmental researchers do when measurements
are collected at weekly, monthly, and yearly intervals—can distort the shape of the
developmental trajectory. Infrequent observations will cause binary data to appear as a step
function, with a single abrupt transition, regardless of whether the underlying trajectory is
variable, with a series of reversals. As illustrated by the gray curves in the figure, the variable
data in (B) will appear to follow the same developmental path as the stage-like data in (A).
Implications for the Timing of Change
Overly large sampling intervals are also likely to produce errors in estimating onset ages—the
earliest age at which children consistently and reliably express a behavior, skill, or
physiological milestone. Identification of onset ages plays a prominent role in normative and
clinical studies of human development, screening for developmental delay, and experimental
manipulations of development in animals. The onset ages of cognitive and motor milestones
are commonly used to document developmental delays in clinical populations, such as the
delay in autistic and deaf children’s acquisition of theory of mind (Peterson & Siegal, 1999).
Age at onset is used to compare the development of different skills such as language
comprehension and production (Clark & Hecht, 1983), or to compare the development of the
same skill expressed in different contexts, such as the age of attaining conservation of quantities
in different cultures (Dasen, 1984), or the age of reaching for objects in the light and in the
dark (Clifton, Muir, Ashmead, & Clarkson, 1993). Researchers use age at onset to assess effects
of prior experiences on the development of a target skill, such as interactions with siblings on
acquiring a theory of mind (Perner, Ruffman, Leekam, 1994), experience with pottery making
on the onset of conservation (Price-Williams, Gordon, & Ramirez, 1969), or the effect of
sleeping prone versus supine on the subsequent development of crawling (Majnemer & Barr,
2005). Measures of experience in human infants typically are calculated as the number of days
between onset and test dates, for assessing effects of crawling experience, for example, on
improvements in perceptual, cognitive, and social tasks (Campos et al., 2000).
It is easy to imagine how sampling at longer intervals will result in reduced accuracy in
estimating the onset age of skills that exhibit abrupt, step-like transitions (e.g., monthly
sampling risks 1-month delays in estimates of onset ages; see Figure 2A). But it is less intuitive
how the choice of sampling interval affects the accuracy of estimating onset ages in skills with
variable developmental trajectories. As shown in Figure 2B, infrequent sampling is likely to
miss the period of variability, and thereby provide a later estimate of the onset age.
Occasionally, the observations will fall on a day when the skill is present, but not yet stable,
and thus distort the estimate of onset by providing a prematurely early estimate.
As we have argued in the foregoing account, the rate at which behavior is sampled is likely to
have a significant impact on our ability to discern the shape and timing of developmental
change. Sampling at inappropriately large intervals can yield an erroneous picture of the
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underlying developmental trajectory, which in turn may provide misleading inferences for
developmental theory. But the real cost is not just in misrepresenting the pattern of change. It
is the loss of the ability to distinguish among alternative trajectories, such as the ones depicted
in Figure 1. An important principle of empirical science is that theories and hypotheses must
be falsifiable. It should be possible in principle to obtain some set of measurements that would
not accord with the theory (Popper, 1959). Inferences about particular developmental
trajectories are not falsifiable unless the data could have revealed alternative patterns of change.
Confidence in the shape of a developmental trajectory depends on whether the data were
sampled at appropriate intervals to permit the possible detection of alternative paths. And
because there are no generally accepted rules or theorems to guide selection of a sampling
interval in a particular developmental context, appropriate sampling intervals must be
determined empirically.
Current Study
In the present study, we aimed to meet the challenge of the microgenetic method by establishing
empirically whether the different sampling rates typically used by developmental psychologists
in microgenetic and longitudinal research—days, weeks, and months—are sufficient to
accurately characterize the pattern of developmental change. Our aims were four-fold. First,
we sought to demonstrate that real data with real patterns of variability could yield dramatically
different trajectories when sampled at rates commonly used in developmental research. Second,
we aimed to quantify how quickly researchers lose the picture of developmental change when
sampling at increasingly large intervals. It is a mathematical certainty that coarser sampling
will be less sensitive to fluctuations in the data, but it is not clear at what rate researchers will
incur the cost of misrepresenting the underlying trajectory. Third, we assessed the consequence
of different sampling intervals for estimating onset ages—the earliest manifestation of stable
expression of skills and abilities. And fourth, we tested whether the effects of sampling interval
generalize across children, the first 18 months of life, and a range of different skills.
Specifically, this study measured the impact of collecting developmental data at intervals of
varying length on loss of sensitivity to detect the underlying trajectory. To ensure that natural
patterns of variability would be included in the data, we compiled a real data set of daily changes
in 32 infant motor skills (sitting, crawling, standing, walking, etc.) obtained from parent
checklist diaries, rather than an artificial data set of experimenter-generated data. We focused
on motor skills because motor performance is overt and amenable to objective, reliable
measurement, new motor skills are highly salient to parents, and motor development has a long
history of longitudinal and microgenetic research. However, in principle, the data set could
have been constructed from any skills appearing at any point in the lifespan, indexed in terms
of competence rather than performance, and obtained in the laboratory or during home visits
rather than by parents’ reports.
Following in the long tradition of language studies (e.g., Darwin, 1877/1974; Dromi, 1987),
parents served as informants by noting the presence or absence of each skill at the end of the
day in a checklist diary. Although readers’ first inclination may be skepticism regarding
parental reports, home observations integrated over the course of the day may be the best way
to determine if a skill is in children’s repertoire because parents are with their children in many
different situations, including contexts that are likely to elicit and support the emergence of
new skills (Bodnarchuk & Eaton, 2004). For language skills, laboratory tests and experimenter
home visits grossly underestimate children’s early abilities, necessitating parental reports to
avoid false negatives (Bates, 1993). For motor skills, parent checklist diaries of basic motor
skills are concordant with experimenter home visits (Bodnarchuk & Eaton, 2004).
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As is customary in the literature, we treated the appearance and disappearance of motor skills
as binary, categorical data (present or absent). Like researchers in other developmental domains
that treat skills categorically (e.g., object permanence, conservation, and theory of mind), we
established operational definitions for the performance of each skill. For several skills, we
included multiple criteria for successful performance (e.g., walking < 3 m and walking > 3 m)
to determine whether more stringent criteria would affect the trajectory.
From the daily assessments, we constructed developmental trajectories for each skill at the
finest available grain of temporal resolution. Then we systematically removed observations to
simulate the effects of sampling at intervals ranging from daily to monthly, and reconstructed
the developmental trajectories based on the reduced number of observations. Key features of
the resulting trajectories were compared to the original data to determine the loss of sensitivity
for detecting various patterns of developmental change that result from different sampling
schedules. In addition, we formulated a method based on a neurally-inspired activation function
for objectively estimating onset ages for each skill. We compared the estimated onset ages
derived from the original daily observations with those derived from the simulations of larger
sampling intervals to determine the magnitude of error that could be attributed to sampling
frequency.
Method
Checklist Diary
We compiled a database of daily diary data from eleven families (5 boys, 6 girls). Nine infants
were Caucasian and two were Asian. All parents were middle class and highly educated. Eight
infants had parents who were doctoral students or professors in psychology or anthropology,
including the daughter of the first author, and thus most respondents were experienced in
methods of behavioral data collection. Parents began keeping diary records before their infants
could perform any of the target skills, and ended participation several weeks after their infants
could walk independently. One family stopped participation abruptly when the infant was 9
months old because of a medical emergency. For the other 10 infants, length of participation
ranged from 10.94 to 17.00 months (M = 12.59 months). One additional family ceased
participation after only 3 months because the parents found it to be too grueling; data from this
infant were not included in the database.
Parents were trained to make daily entries into a 3-page, paper-and-pencil, checklist diary
containing 32 gross motor skills involving balance and locomotion, all of which could be
performed in a minimally structured environment (i.e., with a floor and furniture). Instruction
manuals accompanied parents’ diaries with detailed descriptions of the criteria for each skill
(see Appendix 1), and a reminder for how to fill out the diary. The diaries were similar to those
used by Bodnarchuk and Eaton (2004), who showed that parents’ reports were concordant with
home visit observations. Data were collected for 22 additional stair climbing and sliding skills,
but these were not included in the current study because they required access to special
equipment not readily available on a daily basis.
Parents noted whether they had observed infants perform each skill at any point over the course
of the day. The diaries provided space for additional written comments about observed skills
that did not quite match criteria. Such comments about the first two participants—the first
author’s daughter and the son of another psychology professor—provided useful information
for revising skill definitions and criteria. Only skills with uniform definitions and criteria were
included in the final data set. Parents entered a question mark for days when they could not
remember whether they had witnessed the skill or if they had forgotten to fill in their diaries.
Parents also noted days when infants did not have normal access to the floor or to furniture
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(due to long car trips, camping trips, infants’ illness, etc.) and thus were precluded from
performing various skills due to situational factors.
Diaries were distributed to parents each month and were organized to minimize errors in
parents’ reports. Skills were grouped roughly by postural systems and order of appearance
(sitting, prone/crawling, standing/cruising/walking). The first page of the diary contained
sitting and early prone skills, the second page contained crawling and upright skills, and the
third page contained stair climbing and sliding skills. More stringent criteria for specific skills
(e.g., “walking > 3 m”) followed more lenient criteria (“walking < 3 m”). Some of the skills
in our dataset were ordered hierarchically, where demonstrated facility for a stricter criterion
necessarily assumed facility under a more lenient criterion (noted by asterisks in Appendix 1).
For example, once a child can consistently walk 3 meters or more it is not necessary to also
record walking less than 3 meters. Therefore, after infants demonstrated facility for at least 30
consecutive days with the stricter criterion, the entries for the lenient criterion were assumed
to be present.
During monthly lab visits, researchers collected parents’ completed diaries from the previous
month, interviewed parents about diary entries (confirmed infants’ expression of new skills,
cessation of old skills, and question-mark and no-access days), and distributed a new diary for
the current month. The interviewer reminded parents about the criteria for the various skills
using verbal descriptions, physical demonstrations of the behaviors, and by directing them to
the relevant definitions in the instruction manual.
Missing Data
Because our aim was to assess effects of sampling interval on characterization of the underlying
developmental trajectories, it was especially important to maintain high confidence in the
integrity of the time series. Days that parents noted with question marks and days in which
infants had no access to the floor constituted missing data. Given that the aim of the study was
to detect variability, we adopted a conservative strategy for interpolating over missing data.
For each skill, a software program written in our laboratory searched for the first instance of
existing data prior to the day for which data were missing and replaced the missing data entry
with that notation. The assumption underlying the interpolation rule was that infants were likely
to have continued doing what they last did until otherwise noted. At most, two consecutive
days of missing data were reconstructed in this way. If a skill contained more than two
consecutive days of missing data or if missing data constituted 5% or more of all entries, the
time series was not used for further analyses.
Overall, each infant contributed 4-30 skills (M = 23.73 skills) for a total of 99,971 usable diary
entries in the final data set across infants and skills. Several factors caused the large range in
the number of skills that each infant contributed. For the first two infants in the sample, we
revised the definitions and criteria for several skills, and thus eliminated several time series
collected under earlier definitions and criteria. For other infants, some of the time series
included more than 5% missing data due to days noted with question marks, days when infants
did not have access to the floor, and in the case of one infant, a lost month of entries. Across
the sample, some infants never performed certain skills (e.g., never crawled > 3 m). Finally,
several time series were either cut short or were not performed by the infant who withdrew
from the study because of a medical emergency.
Manipulation of Sampling Frequency
The critical tests involved varying sampling frequency, then interpolating over the intervening
points. The actual daily data entries provided the smallest sampling interval. We wrote software
to simulate the effect of sampling at longer intervals by systematically selecting observation
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points at 2- to 31-day intervals for each skill reported by each parent in the data set. For example,
to simulate a 2-day sampling interval, the program selected every second data point; to simulate
a 3-day sampling interval, the program selected every third data point. After resampling,
removed days were replaced with interpolated values. The process continued for each of the
remaining sampling intervals until the least frequent sample at 31-day intervals. Therefore,
every simulated time series had the same number of days as the original.
When observation points are distributed in time, the specific day that each sample is collected
can vary (e.g., sampling at a 2-day interval could be initiated on the first available day that
measurements were collected and on all odd numbered days thereafter, or the sample could
begin on the second day of data collection and proceed on all even numbered days). Failure to
take phase into account would allow for random sampling effects to influence the overall
trajectory, particularly if performance of the skill is variable. For example, the singular
occurrence of a skill on Day 31, but not on surrounding days, would appear as a stage-like
transition a month earlier if sampling at 30-day intervals beginning on Day 1 (i.e., 1, 31, 61,
91…) compared to the same rate of sampling beginning on Day 2 (2, 32, 62, 92…). To allow
for random variation due to the phase of sampling, the final data set was exhaustive and included
all possible phases at each sampling interval (e.g., 30 phase sets were created for each skill
when sampling was conducted at 30-day intervals).
The resulting final data set included the original data collected daily, and data sets resulting
from sampling at 2-31 day intervals at all possible phases. After sampling each simulated series
of observations, the software program interpolated over missing values by filling in daily values
based on the last available observation point. Although it would have been possible to use an
alternative rule, such as retroactively filling in missing data according to the next available
data point, we adopted a conservative assumption that a binary function continues on the same
trajectory until a demonstrated instance of a change. Because each of the original time series
resulted in 495 additional sampled time series, the original data set of 261 (infant × skill) time
series yielded a final data set of 129,456 unique time series.
Results
Effects of Sampling Interval on Observed Trajectories
We assessed the effect of variations in sampling interval on the shape of the observed trajectory
by counting the number of transitions between absent and present for each time series. A single
transition would represent an abrupt step-like trajectory from absent to present, as exemplified
by infant 11 who began standing on one day and stood every day thereafter (see Figure 2A,
which is also depicted as the data point nearest the origin in Figure 3A). Alternatively, multiple
transitions would represent a variable trajectory between absent and present, as exemplified
by infant 7 who vacillated 21 times between standing and not-standing (see Figure 2B and top
data point in left-most panel of Figure 3A).
Of the 261 time series in the data set, only 15.7% showed single abrupt transitions (either onsets
alone or a single onset and offset) at a one-day sampling interval. For the remaining 84.3% of
time series, the daily diary data showed variable trajectories, ranging from 3 to 72 transitions
during the acquisition period (M = 13.37 for those time series showing variable trajectories).
Inspection of all time series revealed that variable trajectories were characteristic of all infants
and skills. Between 65% and 100% of the time series for each infant showed multiple
transitions, regardless of sex. Similarly, between 67% and 100% of the time series for each
skill (expressed by at least two infants) showed multiple transitions, regardless of the kind of
skill, the strictness of the criterion for judging skill occurrence, or the average age at which the
skill was expressed.
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The consequence of larger sampling intervals was to obscure the true shape of the
developmental trajectory. Across the 32 motor skills in the data set, sampling at the simulated
rate of once per week caused 51.2% of the 220 variable time series to show a single transition
from absent to present. At the simulated rate of once per month, 91.4% of the variable time
series appeared to involve a single, abrupt transition. Overall, with monthly sampling, 242
(92.7%) of the 261 time series appeared to follow step-like trajectories (compared to the 15.7%
based on daily samples), yielding a very different picture of developmental change from that
of the daily data.
How quickly did we lose the picture of developmental change? Given fewer observations at
larger sampling intervals, one would expect a general loss of sensitivity to detect variability.
In fact, sampling at progressively larger intervals carried a tremendous cost: Sensitivity to
detect variability in the time series declined dramatically each time we widened the sampling
interval by one day. Figure 3A illustrates this precipitous drop-off in sensitivity for each child
for one skill, standing (also represented in Figure 2). Of the 8 children depicted in the graph,
only one (infant 11) exhibited a step-like transition from absence to presence when standing
was indexed daily. By the time sampling approached 14-day intervals, however, the child with
21 transitions (infant 7) was indistinguishable from the child with a single transition.
The black curves in Figure 3B show that the dramatic decrease in sensitivity was evident for
all of the 32 skills in the data set. The gray curve in the figure shows the group average across
sampling intervals. Although infants averaged 11.74 transitions (SD = 10.48) in their actual
daily diaries across all 32 skills, sampling once per week yielded only 2.51 transitions (SD =
2.10), on average, and sampling once per month yielded only 1.20 transitions (SD = 0.83). The
drop-off in sensitivity is more evident in Figure 3C, which depicts these same data expressed
as a percentage of the number of transitions observed with daily sampling. As shown by the
concentration of trajectories in the lower left of the figure, for most time series, fewer than 1
in 4 transitions (25%) were detected when sampling at larger than one-week intervals.
Moreover, time series with frequent transitions were disproportionately mischaracterized. The
only trajectories that were depicted accurately at larger sampling intervals were the 41 time
series (15.7% of all time series) with only 1 abrupt transition from absent to present, shown
by the superimposed horizontal lines at 100%.
Each day that the sampling interval widened resulted in fewer transitions detected. To quantify
how quickly sensitivity to variability was lost, we fit a variety of mathematical functions to the
data shown in Figure 3B. The loss of sensitivity to detect transitions was best described by an
inverse power function, meaning that the rate of loss of sensitivity was greatest at the smallest
sampling intervals and declined as intervals grew larger. As shown in Figure 3D, most of the
R2 values exceeded 0.8 for power functions fit through the data for each of the 240 time series
with multiple transitions at each of the 31 possible phases.
Effects of Sampling Interval on Estimated Onset Ages
Developmental researchers rely on onset age—the earliest date at which children can
consistently and reliably express a particular motor or cognitive skill—as a primary index of
developmental progress. As the foregoing discussion of sampling intervals suggests, measuring
developmental change at long intervals is likely to result in greater error in identifying the onset
of skill performance than measuring at shorter intervals. We sought to quantify the expected
magnitude of error in estimating the onset ages by calculating the deviation between the date
determined by a particular sampling frequency and the date determined by daily sampling.
When sampling at 31-day intervals, each unique phase set provided a separate estimate of the
onset age, and thus a distribution of 31 different estimates of the error of measuring onset age
relative to daily samples. In addition to phase differences, if onset is determined by a criterion
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other than first day of expression, the specific pattern of days in which a skill occurs within a
variable trajectory can influence the age identified as the onset of stable performance. Because
most time series were variable, we sought to vary the particular sequence of days in which the
skill was expressed to obtain a larger and more robust set of time series. By creating variants
through a constrained randomization procedure, we provided more time series for analysis at
all sampling intervals, including short intervals that provided fewer estimates of onset age (e.g.,
sampling on alternate days provides only two estimates, one for each phase). In applying a
randomization procedure, however, it was important to constrain the procedure to local
sequences within the time series, thereby leaving the overall arc of the trajectory the same.
We used a Monte Carlo randomization procedure to introduce slight variations in the dates at
which skills were expressed. In a typical randomization procedure, the sequence of events in
the entire time series is shuffled, producing a random reordering of the data set (e.g., Johnson
et al., 1996; Kleven, Lane, & Robinson, 2004). Clearly, if the sequence of events in the original
time series were completely randomized, no developmental pattern could be discerned. To
preserve the overall developmental pattern while creating random variations in the daily events,
randomization was constrained to restrict the temporal range within which shuffling occurred.
A similar procedure was applied by Loreau (1989), who constrained randomization on a
seasonal basis to maintain biological realism in a model of annual activity cycles and ecological
competition.
To implement our randomization procedure, each binary time series, after simulated sampling
and interpolation, was parsed into a sequence of bins comprising 14 consecutive days. The size
of this bin (14 days) was selected after exploring alternative bin widths, and was chosen to
provide a diversity of permutations while introducing minimal error in the overall
developmental profiles. Within each bin, daily events were randomly resampled without
replacement, creating a sequential permutation of the original bin (Crowley, 1992). Although
the specific dates of occurrence were reordered within bins throughout the time series, the
sequence of 14-day bins was not modified. Thus, for a time series of daily samples spanning
a year, there would be 26 14-day bins and therefore (14!)26 possible permutations. We selected
25 randomly generated time series from this set of possible permutations for each unique phase
set for further analysis. This approach resulted in the creation of many alternative time series
that differed in the specific dates that skills were expressed, but which preserved the same
general developmental trajectory.
The 129,456 density x phase combinations and 25 randomization procedures applied at each
simulated sampling interval resulted in a total of 3,236,400 time series of skill performance.
For each of these time series, we applied an objective algorithm to identify the onset age based
on the earliest age at which the skill was consistently and reliably performed. Determination
of the onset age is straightforward when the underlying developmental trajectory is a step-
function because skill performance exhibits a single transition from absence to presence in the
infant’s repertoire (see Figure 2A). However, objectively defining skill onset is more
problematic when the skill is performed on one day and not on the next (see Figure 2B).
In determining onset age, one might simply report the first day on which the skill was observed.
In some developmental research, however, the first date of observation is not used as the
criterion for onset because a singular performance followed by weeks of no expression may
be interpreted as anomalous or unrepresentative of a stable ability. Other criteria (e.g., skill
must be expressed on three consecutive days) are also arbitrary and seem to lead to exceptions
and additional criteria requiring qualitative inspection of each time series. In lieu of these
options, and to provide an automated method of determining the onset of stable performance
of each skill that could be applied to three million time series, we applied an objective algorithm
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to summate over variable periods of skill expression until a criterion level of skill performance
was reached.
The algorithm we used to objectively determine the onset age consisted of an activation
function that summated across consecutive days of variable skill performance. Although
inspired by the rules of summation that generate action potentials in a neuron, this function did
not involve processing of the data with an artificial neural network, but acted more generally
as a smoothing function over periods of variable expression. The critical parameters of the
activation function were a decay rate (d), a criterion onset threshold (Ton), and a criterion
inactivity threshold (Toff). Activity accumulated or decayed in the function over successive
days following equation 1, where At is the accumulated activity at time t, E is the value of the
event at time t (1 = skill present, 0 = skill absent), and d is decay rate, which specifies the
amount of activity that carries over from one day to the next.
(1)
With this simple smoothing rule, each day that a skill was performed added activity to the
function (much like a small synaptic potential contributes to the net depolarization of a neuron),
but activity decayed from one day to the next. When the skill was performed over consecutive
days, the function approximated a logarithmic function and activity summated toward an
asymptote that represented consistent and reliable performance. Over a span of days when the
skill was not performed, activity decayed toward zero as a negative exponential function. When
the cumulative activity, as determined by the particular pattern of skill expression over
successive days, exceeded the criterion onset threshold (Ton), the skill was considered stable
and the onset age was determined by tracing the rising slope of activity back to the preceding
minimum below the inactivity threshold (Toff, see Figure 4A). In practice, this algorithm
identified the first day a skill was expressed in cases where there was a single step-like transition
from one day to the next, and it consistently identified a date between the first day a skill was
expressed and the asymptote in trajectories with periods of variable expression.
We systematically explored the effects of varying different parameters in this function with a
subset of the data to maximize the number of time series for which an objective onset age could
be determined. To confirm the validity of this function, all four authors visually examined
representative graphs of the time series to identify an age by consensus for the onset of stable
and consistent performance. The subset of time series included skills that exhibited sudden
onset from one day to the next, and skills that showed protracted periods of intermittent
expression before skills were consistently expressed. Parameters of the activation function then
were adjusted to identify the same ages in the exemplar trajectories. For the results reported
below, we used a decay rate of 0.8, an upper onset threshold of 75% of asymptote, and a lower
inactivity threshold of 10% of asymptote as optimal for identifying onset ages across all types
of trajectories. With these settings, we identified onset ages for 3,045,764 time series (94.1%).
In most instances, failure to identify an onset age by these objective criteria was due to the
infrequent expression of the skill (on five or fewer days) in the time series (and thus, insufficient
activity accumulated to exceed the onset threshold).
For each child and each skill, we used the activation function to identify an onset age from the
original daily diary data. Then, we compared the original onset ages with estimated onset ages
for all of the other time series generated by the randomization procedure at each of the simulated
sampling intervals and phases. Figure 4B shows a series of histograms charting the distributions
of error estimates for one representative skill, standing, in all 8 of the infants for whom we had
useable data. As revealed by reading down the column of histograms, the magnitude of error
increased systematically with larger sampling intervals. As sampling interval increased, the
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distributions progressively shifted to the right, reflecting delays in identifying onset. At the
most extreme, the estimated onset age was delayed by 55 days.
The pattern of increasing error exemplified by standing was characteristic across the entire
data set (Figure 4C). With daily sampling, the magnitude of error introduced by the Monte
Carlo randomization procedure averaged 4.31 days (SD = 1.97) across infants and skills. In
other words, constraining our randomization of skill sequences within 14-day bins resulted in
relatively small variations in onset age. However, with progressively longer sampling intervals,
the average magnitude and range of error in estimating onset ages increased sharply. For
example, sampling at weekly intervals resulted in a mean absolute error of 6.31 days (SD =
4.43), and absolute errors >14 days occurred in 7.7% of estimated onset ages. (Errors larger
than about 14 days can seriously compromise theorizing about motor skills.) Sampling at 20
day intervals resulted in a mean absolute error of 11.06 days (SD = 7.74), and absolute errors
> 14 days in 21.4% of estimates. At a 30-day sampling interval, the mean absolute error
compared to daily samples was 15.06 days (SD = 9.86), and absolute errors > 14 days
constituted 37.5% of estimates. At the most extreme, the estimate of onset age differed from
the actual onset age calculated from daily sampling by 109 days.
Moreover, errors were not distributed symmetrically around the daily estimates of skill onset;
most errors were greater than 0, indicating a delayed estimate of the onset age. Sampling at
longer intervals resulted in estimates that were increasingly delayed. When sampled at 2-day
intervals, 19.5% of estimates were delayed relative to the actual onset age, compared with
20.1% occurring earlier and 60.4% on the correct date. Sampling at weekly intervals resulted
in 34.3% of all estimates occurring later than the actual onset age. At 30-day sampling intervals,
delay errors increased to 59.0% of all estimates. For all skills, acceleration errors did not change
across sampling intervals. But delay errors increased with longer sampling intervals: The rate
of increase followed a power function, R2 = 0.96.
Discussion
A fundamental goal of developmental science is to understand change processes. To achieve
this goal, researchers need accurate pictures of the shape of change, and such pictures require
repeated observations. Most developmental researchers, however, do not conduct longitudinal
and microgenetic studies because repeated observations are difficult and expensive to collect.
The problem is compounded because overly large sampling intervals distort depictions of
developmental change by obscuring important fluctuations in the data: Trajectories charted
with binary data will appear more abrupt than they really are, and trajectories charted with
interval or ratio data will smooth over important irregularities such as regressions and sudden
changes in the rate of change.
The present study addressed the problem of selecting sampling intervals for developmental
data by assessing the empirical costs of sampling at progressively larger intervals. The aim
was not merely to confirm the loss of detail with coarser sampling, but to determine how quickly
depictions of development may be altered by sampling data at the rates typically used by
developmental researchers. We compiled an illustrative dataset of 32 infant motor skills, and
sampled daily to provide a fine-grained depiction of developmental change. We used real,
rather than hypothetical data to ensure that our sampling regimes incorporated actual patterns
of variability into depictions of the shape of developmental change. Most skills showed a period
of variability (vacillating between occurrence and absence) before acquiring a stable period of
daily expression. When we simulated sampling at longer intervals (2-31 days), the picture of
a variable acquisition period was quickly lost, so that skills with variable trajectories showed
a single, step-like transition. Other critical aspects of the trajectories were also distorted: Most
skills showed large delays in estimating onset ages.
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Daily Changes in Infant Motor Skill Acquisition
A surprising finding that emerged from analyses of the original, daily time series was the large
number of transitions preceding stable performance. The widespread practice of using point-
onset dates for motor skills (e.g., Adolph, et al., 2003; Campos et al., 2000; Frankenburg &
Dodds, 1967) presupposes that most skills appear suddenly and are consistently expressed
thereafter. However, in the current study, a variable acquisition period characterized most skills
for every infant across the entire age range. For example, infants averaged 14.57 transitions
(SD = 4.96) for standing, as illustrated in Figure 2, and 13.37 transitions across all skills (SD
= 10.35). Is it really possible that infants vacillate between occurrence and absence of a skill
on a day-to-day basis? Perhaps the variability is just noise and is not developmentally
significant.
Several factors lend assurance that the diary reports were reliable indicators of daily
performance. First, the parents were a select group of observers. Eight infants had parents who
were professors or doctoral students, and who conducted behavioral research of their own. In
addition, parents were carefully trained on the criteria for each skill, and understood the
importance of noting question-mark days when they had insufficient data to mark a skill present
or absent. Most parents spontaneously annotated their diaries when infants’ performance did
not meet criterion (e.g., number of crawling steps, seconds of independent sitting), suggesting
that they took the criteria seriously, and were eagerly waiting for performance to reach
threshold. A second factor that inspires confidence in the daily data is a reliability study: A
less select group of 95 parents provided reliable reports of sitting, crawling, standing, and
walking skills using a daily checklist diary designed after the one used here (Bodnarchuk &
Eaton, 2004). Home visits by experimenters blinded to the diary entries yielded concordant
data for 11 of 12 measures. A third factor concerns the directional bias of parents’ errors. If
parents did err, the most likely errors were false positives. That is, observing infants pass
criterion on one day may have biased parents to produce “present” responses on the following
days. False positives, however, would produce fewer transitions in the time series for any skill,
suggesting that the number of transitions reported here are, if anything, an underestimate of
the true day-to-day variability.
Why then might infants have failed to express sitting, crawling, walking or other basic motor
patterns after demonstrating the ability to do so? Variable acquisition periods cannot be
attributed to a lack of opportunity. We only analyzed skills that could be performed in a normal
home environment (with floor, furniture, etc.), and that did not require special equipment or
resources (e.g., stairs). Moreover, we eliminated days when the family situation precluded
access to the floor (traveling, illness, etc.). Variable acquisition periods also cannot be
explained as an artifact of low base-rate levels of performance. Nearly all (94%) of the 261
time series eventually reached a stable pattern of daily performance, suggesting that infants
were highly motivated to perform the indexed skills.
A remaining possibility is that variable acquisition periods reflect a biological reality: As
infants acquire new motor skills, they perform close to the limits of their abilities, much like
athletes struggling to meet their personal best during competition. In early periods of skill
acquisition, infants’ peak skill level is far below the criterion level, and on a binary scale, the
skill is considered absent. At later periods, as infants’ abilities hover around the criterion
threshold, their top level of performance exceeds criterion on some days, but not others,
resulting in variable trajectories. Eventually, infants’ peak skill level comfortably surpasses
threshold, and skills are expressed on a consistent, daily basis. To achieve a more stringent
criterion for the same skill (e.g., walks > 3 m versus walks < 3 m), infants must acquire a still
higher level of peak performance.
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This “peak performance” interpretation implies that at least for gross motor skills, over the first
year and a half of life, infants continually push the envelope of possibility by attempting actions
that they haven’t quite mastered. Like Vygotsky’s (1978) concept of a “zone of proximal
development,” day-to-day variability in motor skill performance may reflect periods of
development when infants are operating close to their limits; they are most disrupted by
perturbations, and can benefit most from external support. This account also accords with
previous proposals that motor skills are more unstable and sensitive to context when they first
appear in infants’ repertoires (Thelen, Fisher, & Ridley-Johnson, 1984; Robinson &
Smotherman, 1992; Garciaguirre, Adolph, & Shrout, 2007). As infants’ peak abilities expand,
performance improves, and skills are expressed for longer durations and under more variable
and challenging circumstances.
A question that arises about daily variation in infants’ motor skills is whether even smaller
sampling intervals would have revealed something additional. As in the example of physical
growth, where episodic growth across days encompassed episodic growth across minutes, like
a set of nested Russian dolls, smaller, meaningful units of motor action are nested within daily
samples. For example, nested within the stuttering day-to-day trajectory of performance in
crawling and walking, infants also show a variable trajectory in their expression of locomotion.
On the scale of minutes and seconds, infants vacillate between short bouts of locomotion and
longer periods of rest (Adolph, Badaly, Garciaguirre, & Sosky, 2008; Badaly & Adolph,
2008; Chan, Lu, Marin, & Adolph, 1999). Variable expression from step to step produces a
temporally distributed and spatially variable practice regimen that is most effective in
promoting motor learning (Adolph & Berger, 2006). The intervening rest periods provide time
to consolidate effects of practice and to renew infants’ motivation. Thus, intermittent rest
periods may be especially important when infants must operate at peak performance simply to
execute crawling or walking steps.
These theoretical speculations about variable acquisition periods, however, depend on the
characterization of the developmental trajectory. Without evidence for variable acquisition
periods, the foregoing discussion of theoretical implications for motor skill acquisition would
be moot. And without sampling at a rate that renders the same picture as the daily data, there
would be no evidence for variable acquisition periods. Instead, we would be constructing an
account to explain step-like transitions in the development of motor skills. A similar dilemma
is posed for sampling development in other domains.
Empirical and Theoretical Costs of Sampling Decisions
Given the long history of microgenetic research (Vygotsky, 1978), methodologists’
exhortations to select sampling intervals for reasons other than convenience, tradition, or
intuition (Wohlwill, 1970, 1973), and formal demonstrations that long sampling intervals can
compromise conclusions about development (Boker & Nesselroade, 2002; Collins, 2006), one
might expect that developmental research would reflect the same care in choice of sampling
regime as in experimental design. Unfortunately, it does not. The general principle that we
must take sampling interval seriously in designing developmental studies is not reflected in
current practice.
Possibly, general awareness about sampling on a developmental time scale has not yet filtered
down to the rank and file. As Collins and Graham (2002) commented, a similar situation
prevailed 40 years ago for the use of power analyses to determine sample size: Originally,
power was a concept that statisticians worried about, but it was not widely applied in actual
research settings. Now researchers routinely use power analyses to design their experiments
as they balance the practical demands of minimizing sample size while avoiding the empirical
and theoretical pitfalls of type two errors.
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How quickly we lose the picture of developmental change—How seriously must
developmental researchers consider the problem of selecting a sampling interval? In previous
studies of infant motor skill acquisition that are touted in the literature as heroic examples of
microgenetic research, observations were collected at weekly or monthly intervals, two of the
larger intervals among our simulated sampling frequencies (Adolph, 1997; Corbetta &
Bojczyk, 2002; Thelen et al., 1993; Thelen & Ulrich, 1991; Vereijken & Thelen, 1997). In the
current study, daily sampling revealed that 84% of time series exhibited a variable pattern of
emergence. When we simulated sampling infants’ daily motor performance at larger intervals,
the picture of day-to-day variability was quickly lost. When sampled once per week, fewer
than half of these time series appeared variable, and when sampled monthly, only 9% appeared
variable. In other words, sampling motor skills once a month caused 75% of the developmental
trajectories to erroneously look abrupt and step-like, thus characterizing 93% of the entire time
series with step-like trajectories. It should come as no surprise then that researchers typically
consider the first appearance of motor skills to be the onset of a stable period of expression.
The shape of developmental change was not just distorted at the largest sampling intervals.
Relatively small increases in interval length resulted in unexpectedly large decrements in
sensitivity to variability. In fact, an inverse power function accurately described the rate of loss
of sensitivity in portraying actual developmental trajectories. These findings indicate that, in
the realm of motor development, the ability to detect variable developmental trajectories drops
off extremely rapidly at sampling intervals longer than 2 to 3 days. It is the rapidity of this
drop-off in sensitivity that is counter-intuitive, not the fact that infrequent sampling generally
reduces precision.
A second aspect of developmental profiles that was significantly affected by different sampling
rates was estimates of onset ages. Increasingly large sampling intervals caused an increased
rate of errors in estimating the earliest age of stable expression for motor skills. With one-
month sampling intervals, the average absolute error was 15 days, and 59% of errors were
biased toward delays. In areas such as infant motor development and language acquisition
where skills appear and disappear in relatively quick succession, errors of this magnitude are
likely to have serious consequences for both theory and application in studies of development.
Erroneous onset ages carry concomitant costs for estimating durations of experience (e.g., how
long a child has been walking or talking), developmental sequences (e.g., the ordering of motor
and linguistic events), and the duration of stable periods (e.g., telegraphic speech, over-
regularization of verb tense).
Risks of over-sampling—Of course, frequent sampling also carries potential costs. As
others have pointed out (Cohen, 1991; McCartney, Burchinal, & Bub, 2006), substantial
practical costs can be incurred by dense sampling. Collection of behavioral data, particularly
in experimental settings, often entails considerable time, effort, and expense that may present
logistical difficulties. Frequent sampling may have adverse effects on subject recruitment and
attrition because demands on participation can be considerable and onerous. Repeated testing
can alter participants’ responses to the experimental condition, although this problem can be
addressed explicitly by including a control group sampled less frequently. Dense sampling
over a long period exacerbates problems of data management and methods for summarizing
and analyzing data.
But does over-sampling carry the risk of misrepresenting developmental trajectories, thereby
causing researchers to misinterpret the research findings? Many time-based phenomena are
evident only when assessed on the appropriate time scale. For example, it might be difficult to
discern a 24-hr circadian rhythm while viewing an activity record plotted on a time scale of
seconds, or to detect the day-to-day variability in infants’ acquisition of crawling and walking
over a trajectory that included the bout-rest periods of locomotion on a time scale of seconds.
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More generally, researchers might fail to detect a developmentally significant pattern on a
larger time scale that is obscured by abundant low-level variability or noise in a densely
sampled time series.
The interpretive problem, however, arises solely from failure to adequately summarize data
obtained from dense sampling. There are no intrinsic interpretational problems that arise from
sampling frequently, because any time series can be resampled at a reduced rate or smoothed
to faithfully represent patterns at a lower grain of resolution. In fact, researchers routinely over-
sample physiological and movement data and then apply various smoothing functions to reduce
noise and to detect underlying patterns in the data. In other words, researchers can recover the
developmental pattern from over-sampled data, but the converse is not true: Researchers cannot
recover the developmental pattern from data sampled with overly large intervals.
Moreover, as illustrated by the findings in the present study, variable developmental trajectories
are not an inevitable consequence of high sampling rates. Although we found that infant motor
development is most often characterized by variable trajectories, the data also demonstrated
that 15.7% of the daily time series showed a sudden, step-like transition, with the skill appearing
from one day to the next. Contrary to the notion that high sampling rates might create the false
impression of variability, only with sufficiently frequent sampling is it possible to refute the
possibility that a developmental trajectory is variable, and that a step-function is a more
accurate depiction of the underlying pattern. This fact is well appreciated by evolutionary
scientists, who acknowledge the need for much finer resolution in the fossil record, on a
geological time scale, to distinguish between competing theories of evolutionary change, such
as gradualism versus punctuated equilibrium (Gould & Eldredge, 1993; Gingerich, 2001).
Beyond binary data—Can conclusions regarding the effects of sampling interval generalize
beyond the specifics of the dataset reported here? Sitting, standing, walking, and so on were
scored as binary data (either present or absent over the course of each day), and all skills reached
a level of stable, daily performance. Likewise, skills in other domains can be expected to attain
stable, daily performance (e.g., correct production of words, learning the multiplication tables).
Skills such as crawling, and cruising (and in other domains, weaning from breastfeeding, the
ability to distinguish speech sounds outside the native language, etc.) also attain stable offset
periods, where children never produce them again. But what of skills scored as a binary process
with base rates between 0 and 1? Symbolic play, for example, might achieve a stable base rate
during the preschool years between 0.8 and 1, and professional hitting averages in baseball
only rise to the neighborhood of 0.2 to 0.3. Going in the other direction, crying begins at 1 for
newborns, but thankfully decreases to a base rate closer to 0. How does a base rate less than 1
(and for offsets, a base rate greater than 0) affect the optimal selection of sampling interval?
A simple Markov switching model can help to clarify the issue of generalization to skills with
intermediate base rates. Even a high base rate will result in some days when the skill is not
expressed. Figure 5 provides an illustration. The black curves represent data from three
hypothetical time series; the gray curves represent a 15-day moving average that smoothes
over the same data. Suppose that the developmental trajectory involves a step-like switch from
an early period of absence (pE = 0) to a later period of probabilistic occurrence (pL < 1.0). For
instance, as shown in Figure 5A, a sudden, step-like shift from absence to a 0.95 probability
of daily expression would result in an average of five days when the skill was not expressed,
and 11 concomitant transitions (between absence and presence, and vice versa) within a 100-
day period that actually represents the stable base rate of the skill. Under these conditions,
sampling on a daily basis would reveal occasional transitions in the stable base rate, which
might be misidentified as a variable period of acquisition. In such a situation, it might seem
preferable to sample less frequently, say, once a week or once a month, to reduce the chance
of erroneously attributing transitions to a variable acquisition period rather than to a stable,
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more mature period with a base rate < 1. Obviously, if fewer samples are collected, fewer false transitions would be detected.
However, a reduced sampling rate would not provide a more accurate measure of the
developmental profile. Instead, it would fail to identify the correct onset age in a step-like
trajectory, and it would decrease the estimate of the number of transitions during the acquisition
period for time series with variable trajectories. In contrast, for step-like trajectories, dense
sampling would pinpoint the onset age. For variable trajectories, dense sampling would allow
researchers to distinguish a variable acquisition period from a post-acquisition period with a
stable base rate < 1, using the difference in the number of transitions (or some other measure
of variability, as revealed by a smoothing function) as an index.
For example, Figure 5B presents the same two-state model (pE and pL) as in 5A, but now
separated by a 60-day window (representing a variable acquisition period) in which the
underlying process randomly shifts between pE and pL. If pL is high (pL > .8), then the number
of transitions detected by daily sampling will be greater during the variable acquisition period
than during the later period of stable expression. But, as shown in Figure 5C, if pL is low (pL
< .5), then the number of transitions during the variable acquisition period will be less than the
number observed after the onset of stable expression. In both cases, a simple smoothing
function can reveal differences in the level of expression during the variable acquisition and
stable periods. Thus, the difference in the number of transitions over the entire time series
provides a clue as to whether the change from absence to stable expression is step-like or
variable. Even though the absolute number of transitions can be inflated during acquisition for
skills with base rates < 1, only dense sampling can reveal differences in the rate of expression
when expression of the skill is probabilistic.
Recording skills with greater precision does not alleviate the need for dense sampling to
characterize the developmental trajectory. The findings regarding sampling intervals should
also generalize from the binary data presented here to more precise levels of measurement
(ordinal, interval, and ratio scales). Ordinal data, for instance, present much the same problem
as binary data for dealing with variable trajectories. On an ordinal scale, sampling less
frequently would pose the risk of missing periods of vacillation between higher and lower
levels of performance, periods of inconsistent fluctuation between several levels, periods of
consistent expression at intermediate levels, or wholesale reversals in levels of performance.
Similarly, when skills are indexed with interval or ratio data, infrequent sampling over
development can lead to decreased sensitivity to detect periods of stability and instability (in
single observations, means, and measures of variability such as the coefficient of variation).
Interval and ratio data are conducive to interpolation and curve-fitting that smooth over
variations in the developmental trajectory, so that researchers may fail to detect brief episodes
of improvement (as in the case of physical growth) or decrement, interruptions in the expression
of skills, spikes in activity, accelerations (e.g., the vocabulary explosion) and decelerations, or
other changes in rate that are evident only when sampling on a finer time scale. Moreover,
because sensitivity to random sampling error is greater with larger sampling intervals,
estimation of onset ages based on achievement of a criterion level of performance, as measured
with ordinal or interval data, also would be subject to the same types of errors that we have
described for binary data.
Theoretical consequences—Developmental trajectories provide more than empirical
summaries of change over time: Historically, evidence that cognitive, perceptual, social, or
motor skills exhibit particular developmental trajectories (step-like, variable, linear, episodic,
U-shaped, etc.) has stimulated some of the most important theories in developmental
psychology. The concept of developmental stages illustrates the profound influence of
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empirical claims about developmental trajectories on theoretical work about developmental
change. Stage theories have enjoyed a long and influential history in developmental psychology
(e.g., Baltes, Reese, & Nesselroade, 1977; Brainerd, 1978; Piaget, 1954). Although the concept
of developmental stages encompasses qualitative changes, hierarchical reorganizations,
universal sequences, and so on (Fischer & Silvern, 1985), typically, a central feature of stage
theories involves the timing of development—extended, stable periods interrupted by shorter
periods of developmental change. Rapid, stage-like transitions from one stable pattern of
performance to the next are characteristic of phenomena ranging from moment-to-moment
fluctuations in sleep and waking states in rat pups (Blumberg, Seelke, Lowen, & Karlsson,
2005) to patterns of change on an evolutionary time scale (Gould & Eldredge, 1993).
Considerable effort has been devoted to constructing formal models that can account for abrupt
transitions between developmental stages. For example, theoretical accounts of stage-like
cognitive development include simulations using connectionist models (McClelland, 1989)
and rule-based approaches (Siegler, 1976), and mathematical models based on catastrophe
theory (van der Maas & Molenaar, 1992), dynamic systems theory (Thelen & Smith, 1994),
and other mathematical frameworks (van Rijn, van Someren, & van der Maas, 2003). For
instance, according to catastrophe theory and dynamic systems theory, enhanced variability is
a hallmark of transitions between stable attractors (Kelso, 1995; Thelen & Smith, 1994) such
as successive stages (Raijmakers & Molenaar, 2004). Thus, accurate assessment of the amount
and timing of variability is critical for empirically evaluating such models of cognitive
development.
The present study suggests that researchers’ ability to accurately characterize variable and step-
like trajectories in development is profoundly affected by sampling rate, and either trajectory
may be inferred erroneously as an artifact of inadequate sampling. Models of developmental
change become moot if the empirical evidence cannot distinguish among alternative
trajectories. That is, without an appropriate sampling interval, researchers would not be able
to detect a sufficient amount of variability to distinguish between punctate onset dates
(Wimmers et al., 1998), instability around times of transitions (Kelso, 1995), expression of
partial knowledge (Munakata, McClelland, Johnson, & Siegler, 1997), or other patterns of skill
onset.
Sampling Development
How can developmental researchers avoid the pitfalls of under-sampling? Unfortunately,
formal principles such as the Nyquist theorem are not applicable to developmental time series
because developmental trajectories can assume many different shapes, few of which are
periodic or conform strictly to mathematical functions. Instead, sampling rates must be
determined empirically based on the questions being addressed and developmental processes
being studied. Building on previous work (Siegler, 2006; Thelen & Ulrich, 1991), the present
study suggests some precepts to guide the empirical enterprise of identifying optimal sampling
rates to accurately capture the shape of developmental change.
(1). Determine the base rate—In most cases, skills of interest to developmental
psychologists eventually reach a level of stable, consistent performance. Estimating the typical
rate at which the skill is expressed is important in planning how to sample the acquisition period
and/or the more mature, stable period. For skills with stable periods of occurrence (or stable
periods of absence in the case of skills that disappear from children’s repertoires), determining
the base rate of occurrence will depend on the number of observations collected, not on the
rate of sampling. If the base rate is less than 1, applying a smoothing function may be useful
in determining an average rate of occurrence (see Figure 5).
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(2). Find the acquisition period—For most kinds of skills, researchers are likely to initiate
a study with some knowledge of the time frame encompassing significant development. Some
aspects of children’s behavior emerge over a span of weeks; other aspects may require years.
A preliminary investigation with economical sampling (at monthly intervals or longer) may
be useful to identify the approximate age range for the acquisition period, and thereby narrow
the span of time requiring more detailed examination. Note that the initial characterization of
the developmental trajectory from the preliminary study is unlikely to reveal a detailed and
accurate picture of the shape of developmental change, but may be necessary in planning more
detailed sampling in future efforts.
(3). Sample as small as you can—If the objective is to accurately portray the shape of a
developmental process, it is crucial to sample data at the minimum, practicable interval,
especially over the ages spanning the acquisition period. Researchers should consider the
default rate for most kinds of child behavior to be daily sampling: absence or presence over
the course of the day for skills indexed with binary data; highest level attained over the course
of the day for skills indexed with ordinal data; and a summary score such as the mean, sum,
or coefficient of variation over the course of the day for skills indexed with interval or ratio
data. One reason to consider daily sampling a privileged sampling interval is that it reflects the
nearly ubiquitous influence of 24-hour circadian rhythms on human psychological functions.
Skills expressed each day are interrupted by sleep each night, during which the day’s activities
and experiences may be absent, suppressed, forgotten, or consolidated (e.g., Stickgold,
2005). A second reason to consider daily sampling privileged is that the present study and
others (e.g., Ganger and Brent’s study of the vocabulary explosion and Lampl and colleagues’
work on physical growth) serve as demonstration proofs of important day-to-day changes in
multiple domains of development. Sampling less frequently than every day risks losing the
shape of those trajectories. Sampling multiple times each day may provide additional or
converging insights into development, as in the cases of infant walking and physical growth.
However, multiple samples per day also introduce variability that may not be meaningful
because circadian rhythms affect patterns of performance by changing children’s behavioral
state, motivation, and opportunity for performance.
(4). Look before the onset—To satisfy the objective of describing the entire trajectory,
especially the shape of the acquisition period, researchers will need to focus attention on the
ages when the skill is first expressed. A preliminary investigation using coarse sampling should
be useful for obtaining an initial estimate of an onset age, but as the findings of the present
study show, estimates of onset ages based on infrequent sampling are likely to produce large
delay errors, and such errors increase with larger sampling intervals. In trajectories based on
monthly samples, for example, estimates of onset age are three times more likely to occur after
the actual onset age. Therefore, the earliest expression of the skill is likely to occur before the
earliest onset age identified by relatively infrequent sampling. As a consequence, more dense
sampling efforts should include ages prior to the crude estimate of onset.
5. Look for changes in variability—For skills indexed by binary data, trajectories may
be step-like or variable. The latter will show fluctuations prior to attaining a stable level of
performance. If the base rate of occurrence is high but < 1 during the period of stable
performance (> .8), then a variable acquisition period will likely consist of an increased number
of transitions. In contrast, if the base rate is low (< .5), then a variable acquisition period should
show a lower number of transitions relative to the later period of stability. As shown in Figure
5B-C, application of a simple moving average or similar smoothing procedure can reveal
periods of enhanced variability regardless of the base rate. After smoothing, variable periods
appear as a lower rate of occurrence relative to later ages. Thus, smoothing techniques can be
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useful in demarcating changes in the level of variability of performance, which can help
researchers to verify that they have distinguished the acquisition and stable periods.
Concluding Remarks
Historically, much of developmental research has resembled the old saw about the man who
lost his keys in a dark alley and turned his attention to searching for them on the street, “where
the light was much better.” Understanding child development has benefited from descriptions
of age-related differences and demonstrations of the surprising abilities of infants. But
understanding the process of developmental change requires more. It requires solid empirical
foundations built upon accurate depictions of change over time. The implications of our
analysis of sampling intervals would appear to offer a bleak view of methodological difficulties,
even greater than those already recognized by researchers engaged in longitudinal and
microgenetic research. The payoff for dealing with the thorny methodological difficulties of
sampling rate is that accurate descriptions of developmental trajectories will be instrumental
to advancing theories of development. It is simply necessary for understanding the shape of
developmental change.
Appendix 1. Skills Analyzed from Daily Diaries
Skill Description
Sits (propped on hands) Sits on floor for ≥ 30 s, with legs outstretched, using hands for support.
*Sits (hands free) Sits on floor for ≥ 30 s, with legs outstretched, without using hands for support.
Sitting to prone Shifts from sitting position with legs outstretched to prone position.
Prone to sitting Shifts from prone or crawling position into sitting position with legs outstretched.
Kneel to stand (holding) Shifts from kneeling, sitting, or crawling position to standing position by holding onto furniture to pull
body upright.
*Squat to stand (hands free) Shifts from kneeling, sitting, or crawling position into a squat, and then stands up without pulling upright
on furniture.
Stands (holding) Balances upright for ≥ 3 s by holding onto furniture for support.
*Stands (hands free) Balances upright for ≥ 3 s without holding onto furniture for support.
Stand to sit (holding) Shifts from upright to sitting position while holding onto furniture for support.
*Stand to sit (hands free) Shifts from upright to sitting position without holding onto furniture for support.
Rolls front to back Shifts from lying prone to lying supine.
Rolls back to front Shifts from lying supine to lying prone.
Torso raised (propped on arms) Pushes head and chest off floor by propping on forearms or hands while lying prone.
*Torso raised (1 arm free) Pushes head and chest off floor by propping on 1 arm and using the other hand or arm to reach or manipulate
objects.
Rocks on hands and knees Rocks ≥ 2 oscillations while balanced on hands and knees.
Turns 180° prone Pivots in place ≥ 180° while on belly or hands and knees.
Crawls belly (< 3 m) Crawls forward < 3 m, before stopping, with belly resting on floor for duration of each crawling cycle. *Crawls belly (≥ 3 m) Crawls forward ≥ 3 m without stopping, with belly resting on floor for duration of each crawling cycle.
Crawls intermittent belly (< 3 m) Crawls forward < 3 m, before stopping, with belly alternately raised in air and resting on floor during each crawling cycle.
*Crawls intermittent belly (≥ 3 m) Crawls forward ≥ 3 m without stopping, with belly alternately raised in air and resting on floor during each
crawling cycle.
Crawls hands and knees (< 3 m) Crawls forward < 3 m, before stopping, balancing on hands and knees for duration of each crawling cycle. *Crawls hands and knees (≥ 3 m) Crawls forward ≥ 3 m without stopping, balancing on hands and knees for duration of each crawling cycle.
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Skill Description
Crawls hands and feet (< 3 m) Crawls forward < 3 m, before stopping, balancing on hands and feet for duration of each crawling cycle. *Crawls hands and feet (≥ 3 m) Crawls forward ≥ 3 m without stopping, balancing on hands and feet for duration of each crawling cycle.
Cruises 2 hands (< 3 steps) Takes < 3 upright steps, torso sideways, holding onto furniture for support with both hands. *Cruises 2 hands (≥ 3 steps) Takes ≥ 3 upright steps, torso sideways, holding onto furniture for support with both hands.
Cruises 1 hand (< 3 steps) Takes < 3 upright steps, torso frontward, holding onto furniture for support with 1 hand. *Cruises 1 hand (≥ 3 steps) Takes ≥ 3 upright steps, torso frontward, holding onto furniture for support with 1 hand.
Walks supported (2 hands held) Walks with both hands held by caregiver, supporting own weight.
*Walks supported (1 hand held) Walks with 1 hand held by caregiver, supporting own weight.
Walks (< 3 m) Walks independently < 3 m. *Walks (≥ 3 m) Walks independently ≥ 3 m.
*
Denotes skill with stricter definition than preceding skill.
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Figure 1.
Idealized shapes of developmental change, with age shown on the X-axis and an index of
behavioral expression or level of performance on the Y-axis. (a) Linear, (b) Accelerating, (c)
Asymptotic, (d) Step-like, (e) S-shaped, (f), Variable, (g) Unsystematic, (h) Stair-climbing, (i)
U-shaped, (j) Inverted-U-shaped.
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Figure 2.
Examples of developmental trajectories derived from daily data (black curves) for standing
(balancing upright for ≥ 3s without holding a support) in two infants. (a) Trajectory that exhibits
abrupt step-function from absent to present from one day to the next. Simulated monthly
sampling (gray curve) results in an error in identifying the skill onset age, but does not distort
the shape of the trajectory. (b) Variable trajectory, where skill vacillated 21 times between
absent and present over the course of several weeks. Simulated monthly sampling (gray curve)
misrepresents both the shape of the variable trajectory and the estimated onset age.
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Figure 3.
Effects of sampling interval on sensitivity to variability in developmental trajectories. (a) The
number of observed transitions between absence and presence for one skill (standing). Each
curve represents data for one of the 8 infants for whom we had a complete time series. Open
symbols depict data when the skill was sampled daily; lines show data averaged across all
possible phases at each of the 1- to 31-day sampling intervals. Note that the data point nearest
the origin represents the stage-like data from infant #11, shown in Figure 2A. The other 7 data
points show data for variable trajectories from other infants, including the top data point
depicting infant #7, shown in Figure 2B. (b) Number of observed transitions, presented as in
Figure 3A, for all 32 skills. The thick gray line represents the mean trajectory across all 261
time series. (c) The same data presented in Figure 3B expressed as a percentage of observed
transitions recorded at daily intervals. The horizontal line at 100% represents the 41 time series
with only 1 abrupt transition from absent to present (15.7% of all time series). Most time series
consisted of variable trajectories when measured daily, but more than 75% of transitions were
not detected when sampled at weekly intervals. (d) Distribution of R2 values for inverse power
functions fit to each of the 240 time series with multiple transitions. Most time series were best
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described by an inverse power function, indicating that modest increase in small sampling
intervals (< 1 week) resulted in a sharp decline in the ability to detect transitions.
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Figure 4.
Effects of sampling interval on estimates of onset ages. (a) Neurally-inspired activation
function and resulting estimate of the onset age applied to the daily data shown in Figure 1B
for standing in infant #7. The onset age is determined by identifying the first instance of activity
that exceeds a criterion threshold, then tracing the function back to the preceding period of
inactivity. In this case, the function identifies an onset age at 501 days (shown as vertical dashed
line). (b) Histograms showing errors in estimates of the onset age for one skill, standing, in all
8 of the infants for whom time series were available. Y-axis is expressed as a percentage of
total estimates. Note that larger sampling intervals result in a greater range of errors, a general
increase in the magnitude of errors, and a tendency for errors to be shifted toward later ages.
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(c) Number of days that estimates of onset ages deviated, either earlier or later, from estimates
derived from daily sampling. Data are presented for all available skills for each child (261 time
series) as a function of the sampling interval; the superimposed gray line shows the mean
absolute error resulting from sampling at different intervals.
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Figure 5.
Simulated developmental trajectories (dark lines) generated by a simple Markov switching
model. In each graph, the first 60 days represents a period where the behavior of interest is not
yet expressed (p = 0), and the final 100 days represents a period of consistent expression in
which the behavior occurs at a stable rate < 1. (a) A stage-like trajectory involving an abrupt
transition from absence (extended through the first 120 days) to a high base rate of occurrence
(p = .95) during the period of stable expression. (b) Trajectory involving an intervening
acquisition period (from day 61 to day 120) before achieving a stable period with a high base
rate (p = .95). During the acquisition period, behavior is generated by randomly switching
between the early regime (absence) and the later period of stability (high base rate). (c)
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Trajectory involving an intervening acquisition period before a stable period with a lower base
rate (p = .5). Regime switching occurs in the same way as in (b). In all three graphs, the thicker
gray line shows a 15-day moving average that depicts the same data; in graphs (b) and (c), this
smoothing function visually demarcates the variable acquisition period from the later period
of stable expression.
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PSYC 525
Video Discussion Assignment Instructions
You will complete 3 Discussion Videos in this course. For each Discussion, you will post one video thread of at least 3 minutes, and post 1 video reply of at least 1 minute. You can find instructions on how to submit a video discussion on each
Video
Discussion Assignment page under
Video
Discussion Resource.
Video Thread: You will create a video thread in response to the prompt provided below. Choose 1 of the 3 prompts below on which to comment.
Describe 1) the greatest opportunity for and 2) the main obstacle standing against the integration of Christian faith and developmental psychology. Support your response with examples.
Respond to the following statement: “I just can’t trust psychology…I mean, most of the theorists are secular. The only trustworthy source of truth is the Bible.”
From a biblical perspective, why should a person consider studying developmental psychology?
Note: Your assignment will be checked for originality via the Turnitin plagiarism tool.
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