Human-Centered Experience Engineering through Cognitive Design Patterns in Web-Based Systems
DOI:
https://doi.org/10.15680/IJCTECE.2020.0306003Keywords:
human-centered design, cognitive design patterns, user experience engineering, web-based systems, cognitive load management, mental model alignment, attention guidance, decision support design, interaction consistency, feedback mechanisms, error prevention, error recovery design, component-based front-end architecture, design systems, experience architecture, usability evaluation methods, task-based usability testing, heuristic evaluation, user confidence, experience governance, enterprise web applicationsAbstract
Human-centered experience engineering has become a critical discipline in the design of complex web-based systems as interaction density, functional scope, and user expectations continue to grow. Traditional user interface design approaches often emphasize visual aesthetics or isolated usability improvements, while overlooking the cognitive processes that shape how users perceive, reason, and act during interaction. This paper proposes a structured framework for human-centered experience engineering grounded in cognitive design patterns that systematically align system behavior with human cognitive capabilities. The study examines foundational cognitive principles such as attention management, working memory limitations, mental model formation, decision-making effort, and error perception, and demonstrates how these principles can be translated into reusable design patterns for web systems. A taxonomy of cognitive design patterns is introduced and mapped to experience intents, followed by an architectural perspective that explains how these patterns are operationalized within component-based front-end systems. The paper further presents evaluation methodologies for assessing cognitive experience quality and validates the proposed approach through an enterprise web workflow case study. Governance and operationalization strategies are discussed to ensure consistency and scalability across teams and systems. The findings illustrate that embedding cognitive design patterns as architectural constructs leads to improved interaction clarity, reduced cognitive load, and increased user confidence, establishing a sustainable foundation for human-centered web experience engineering
References
1. Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. (2006). Attention web designers: You have 50 milliseconds to make a good first impression. Behaviour & Information Technology, 25(2), 115–126. https://doi.org/10.1080/01449290500330448
2. Tractinsky, N., Katz, A. S., & Ikar, D. (2000). What is beautiful is usable. Interacting with Computers, 13(2), 127–145. https://doi.org/10.1016/S0953-5438(00)00031-X
3. Pirolli, P., & Card, S. K. (1999). Information foraging. Psychological Review, 106(4), 643–675. https://doi.org/10.1037/0033-295X.106.4.643
4. Wickens, C. D. (2002). Multiple resources and performance prediction. Theoretical Issues in Ergonomics Science, 3(2), 159–177. https://doi.org/10.1080/14639220210123806
5. Vigo, M., Brown, J., & Conway, V. (2013). Benchmarking web accessibility evaluation tools: Measuring the harm of sole reliance on automated tests. Proceedings of the 10th International Cross-Disciplinary Conference on Web Accessibility. https://doi.org/10.1145/2461121.2461124
6. Petrie, H., Savva, A., & Power, C. (2015). Towards a unified definition of web accessibility. Proceedings of the 12th Web for All Conference. https://doi.org/10.1145/2745555.2746653
7. Giraud, S., Thérouanne, P., & Steiner, D. D. (2018). Web accessibility: Filtering redundant and irrelevant information improves website usability for blind users. International Journal of Human-Computer Studies, 111, 23–35. https://doi.org/10.1016/j.ijhcs.2017.10.011
8. Manoj Parasa. (2019). Policy-Centric AI Control Architectures for Enterprise Software Platforms: A Governance Framework for SAP SuccessFactors. International Journal of Core Engineering & Management, 6(5), 48–67. https://doi.org/10.5281/zenodo.17948338
9. Gillan, D. J., Holden, K., Adam, S., Rudisill, M., & Magee, L. (1992). How should Fitts’ law be applied to human-computer interaction? Interacting with Computers, 4(3). https://doi.org/10.1016/0953-5438(92)90018-B
10. Accot, J., & Zhai, S. (1997). Beyond Fitts’ law: Models for trajectory-based HCI tasks. CHI ’97 Extended Abstracts, 295–302. https://doi.org/10.1145/258549.258760
11. Fogg, B. J. (2003). How do users evaluate the credibility of Web sites?: A study with over 2,500 participants. Proceedings of the 2003 Conference on Designing for User Experiences. https://doi.org/10.1145/997078.997097
12. Proctor, R. W., & Schneider, D. W. (2018). Hick’s law for choice reaction time: A review. Quarterly Journal of Experimental Psychology, 71(6), 1281–1299. https://doi.org/10.1080/17470218.2017.1322622
13. Padur, S. K. R. (2017). Engineering resilient datacenter migrations: Automation, governance, and hybrid cloud strategies. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2(1), 340–348. https://doi.org/10.32628/CSEIT18312100
14. Liu, Z. (2004). Perceptions of credibility of scholarly information on the Web. Information Processing & Management, 40(6), 1027–1038. https://doi.org/10.1016/S0306-4573(03)00064-5
15. Routhu, K. K. (2017). The evolution of HR from on-premise to Oracle Cloud HCM: Challenges and opportunities. International Journal of Scientific Research and Engineering Trends, 3(1). https://doi.org/10.5281/zenodo.17669776
16. Tuch, A. N., Roth, S. P., Hornbæk, K., Opwis, K., & Bargas-Avila, J. A. (2012). Is beautiful really usable? Toward understanding the relation between usability, aesthetics, and affect in HCI. Computers in Human Behavior, 28(5), 1596–1607. https://doi.org/10.1016/j.chb.2012.03.024
17. Sudhir Vishnubhatla. (2018). From Risk Principles to Runtime Defenses: Security and Governance Frameworks for Big Data in Finance. In International Journal of Science, Engineering and Technology (Vol. 6, Number 1). Zenodo. https://doi.org/10.5281/zenodo.17452405
18. Joo, S., & Lee, J. (2010). How are usability elements, efficiency, effectiveness, and satisfaction, correlated with each other in the context of digital libraries? Proceedings of the American Society for Information Science and Technology, 47(1), 1–2. https://doi.org/10.1002/meet.14504701323
19. Polson, P. G., Lewis, C., Rieman, J., & Wharton, C. (1992). Cognitive walkthroughs: A method for theory-based evaluation of user interfaces. International Journal of Man-Machine Studies, 36(5), 741–773. https://doi.org/10.1016/0020-7373(92)90039-N

