One of the fundamental techniques to gather research for a paper is the use of an Annotated Bibliography. As a human-computer interaction researcher, finding relevant literature to support a study is also part of preparing an analytical research paper.
IMPORTANT: To support your research journey, read the
Levy & Ellis (2006) article
on maximizing your research opportunities in Information Systems Research.
There must be five entries with a PROPERLY cited APA citation and a description of the article that is 100-125 words. The attached document has five entries that are already present and add new entries to it other than already existing ones.
An example entry is:
Hyman, J. A. (2015). Developing Instructional Materials and Assessments for Mobile Learning. In International Handbook of E-Learning Volume 1 (pp. 347-358). Routledge
In Hyman (2015), a review of the required elements needed to create instructional materials for an e-learning and m-learning setting is identified. Hyman then proposes a mobile learning framework that focuses on design, environment, activity, and technology to guide the courseware developer in creating user-friendly yet meaningful instruction that is targeted for delivery in the mobile context.
2
Annotated Bibliography – Mobile Human Computer Interaction
Bace, M., Staal, S., & Bulling, A. (2020, April 1). How Far Are We from Quantifying Visual Attention in Mobile HCI?
IEEE Pervasive Computing,
19(2), 46–55. https://doi.org/10.1109/mprv.2020.2967736
In, Bace et al. (2020) explains the need for better understanding and managing attention in mobile HCI due to the fragmented attentional behavior caused by the widespread use of mobile devices. Previous methods for quantifying user attention faced limitations, and high-resolution front-facing cameras combined with computer vision for gaze estimation have been proposed as a solution. However, the methods require greater accuracy. Eye contact is proposed as an alternative due to its coarser nature and ease of detection. The study focuses on key challenges and sources of error, including face and eye visibility and head pose, and proposes concrete future research directions. The importance of accurate gaze estimation for eye contact detection and developing higher-level attention metrics toward pervasive attentive user interfaces are also highlighted.
Bace, M., Staal, S., & Bulling, A. (2019).
Accurate and Robust Eye Contact Detection During Everyday Mobile Device Interactions. https://doi.org/10.48550/arxiv.1907.11115
In, Bace et al. (2019), the authors propose a new method for quantifying human attention in mobile human-computer interaction. The method analyzes visual attention during everyday interactions on mobile devices. The focus is on eye contact detection, which has become an important research area in mobile HCI. The method is based on a state-of-the-art unsupervised eye contact detection method but is modified to address specific challenges in mobile interactions. Through evaluations of two datasets, the method shows significant improvements in eye contact detection across different mobile devices, users, and environmental conditions. The authors believe that their method opens the door for researchers from various domains to study and quantify attention allocation in the wild during mobile interactions.
Kaewkitipong, L., Chen, C., Han, J., & Ractham, P. (2022, November 5). Human–Computer Interaction (HCI) and Trust Factors for the Continuance Intention of Mobile Payment Services.
Sustainability,
14(21), 14546. https://doi.org/10.3390/su142114546
In, Kaewkitipong et al. (2022), the authors conducted a study aimed at investigating the factors affecting the continued use of mobile payment apps and services, focusing on the relationship between human-computer interaction (HCI) and trust. An online survey was conducted with 544 mobile users. The results showed that trust significantly impacted the users’ continuance usage of mobile payment services compared to HCI. The results also indicated that system quality was the most crucial factor in improving mobile HCI experiences, followed by skill in using the services and the perceived task-technology fit. The study provides insights for mobile payment service developers to improve the user experience.
Komninos, A., Katsaris, K., Nicol, E., Dunlop, M., & Garofalakis, J. (2020).
Mobile Text Entry Behaviour in Lab and In-the-Wild studies: Is it different? https://doi.org/10.48550/arxiv.2003.06323
The Komninos et al. (2020) paper presents a study investigating the difference between text entry behavior in a lab setting and real-world use. The study uses machine learning techniques to distinguish between the two accurately and finds that lab text entry behavior is distinguishable from real-world use. The results have implications for the design of future studies on text entry in mobile HCI and aim to support input with virtual smartphone keyboards.
Rafiq, K. R. M., Hashim, H., & Yunus, M. M. (2022, May 3). New Qualitative Perspective in Human–Computer Interaction: Designing Mobile English for STEM.
Frontiers in Psychology,
13. https://doi.org/10.3389/fpsyg.2022.863422
In, Rafiq et al. (2022), the authors explore the needs of STEM (Science, Technology, Engineering, Mathematics) learners to improve their English language competency through a mobile module. The research centers on qualitative data from semi-structured interviews with seven STEM learners aged 17. This study is essential for mobile app designers and course designers as it provides insight into STEM learners’ needs to improve their English language skills. The findings can be used to design a mobile app that caters to the perspectives of STEM learners, enhancing mobile HCI and success in second language acquisition.
Order an Essay Now & Get These Features For Free:
Turnitin Report
Formatting
Title Page
Citation
Outline
