00
Days
00
Hrs
00
Min
00
Sec
Submit Your Paper

Analyzing the User Experience: A Comprehensive Assessment of Visual Design Elements in Artificial Intelligence Generated Inter-faces and Strategies for Enhanced Accessibility

Authors

Dinesh Kumar J

Department of Media Sciences, Anna University, Chennai, India (IN)

Uma Maheswari P

Department of Media Sciences, Anna University, Chennai, India (IN)

Anu Krithika

Department of Media Sciences, Anna University, Chennai, India (IN)

Article Information

DOI: 10.51583/IJLTEMAS.2025.1407000052

Subject Category: Articifical Intelligence

Volume/Issue: 14/7 | Page No: 432-442

Publication Timeline

Submitted: 2025-08-07

Published: 2025-08-07

Abstract

Abstract: This study examined how artificial intelligence (AI) techniques affect the creation of user-friendly mobile application interfaces. This study examined the effectiveness of incorporating accessibility standards into AI-generated user interfaces. There were two stages to the research. In the first phase, an AI tool was chosen, and by providing various prompts, various interfaces for a mobile application for food delivery were developed. In the second step, experts and users (older persons) assessed the AI-generated interfaces to see how the accessibility features were implemented. The outcome led to the selection of a certain interface, which was then manually constructed using guidelines to incorporate all the accessibility aspects. Once more, users and specialists participated in the testing to gauge the existence of accessibility. Using this procedure, the effectiveness of both manual and AI-generated user interfaces in integrating accessibility elements was assessed. All of these measurements' results showed that manually created interfaces had more accessibility features than AI-generated ones. To create efficient AI-generated interfaces with accessibility features, more research must be done on the subject and better models and prompts are required to support the functioning.

Keywords

Accessibility, Inclusive design, Artificial Intelligence, AI generated interfaces, User Experience Design, User Interface

Downloads

References

1. “ICIDH-2: International Classification of Functioning, Disability, and Health: Final Draft, Full Version. Classifica-tion, Assessment, Surveys and Terminology Team, World Health Organization.” 2001. WHO. [Google Scholar] [Crossref]

2. Bernard, M., C. H. Liao, and M. Mills. 2001. “The Effects of Font Type and Size on the Legibility and Reading Time of Online Text by Older Adults.” In CHI’01 Extended Abstracts on Human Factors in Computing Systems, 175–76. New York, NY: ACM Press. [Google Scholar] [Crossref]

3. Brinck, T., D. Gergle, and S. D. Wood. 2001. Usability for the Web: Designing Websites That Work. Elsevier. [Google Scholar] [Crossref]

4. Chapuis, O. 2011. “Impact of Target Size on Pointing Performance in Mobile Environments.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 3123–32. [Google Scholar] [Crossref]

5. Coursaris, C. K. 2008. “Web Site Iconography and Culture: A Comparison of Five Countries.” Journal of Infor-mation, Information Technology, and Organizations 3: 1–24. [Google Scholar] [Crossref]

6. Dey, A. 2011. “The Effects of Website Interface Design on User Performance: A Usability Approach.” In Proceedings of the 44th Annual Hawaii International Conference on System Sciences, 1–9. [Google Scholar] [Crossref]

7. Djamasbi, Soussan, Marisa Siegel, and Tom Tullis. 2011. “Visual Hierarchy and Viewing Behavior: An Eye Tracking Study.” In Human-Computer Interaction. Design and Development Approaches, 331–40. Berlin, Heidelberg: Springer Berlin Heidelberg. [Google Scholar] [Crossref]

8. Dumas, Joseph S., and Janice C. Redish. 1999. Practical Guide to Usability Testing. 2nd ed. Bristol, England: Intel-lect Books. [Google Scholar] [Crossref]

9. Faraday, Pete. 2000. “Visually Critiquing Web Pages.” In Eurographics, 155–66. Vienna: Springer Vienna. [Google Scholar] [Crossref]

10. Fitts, P. M. 1954. “The Information Capacity of the Human Motor System in Controlling the Amplitude of Move-ment.” Journal of Experimental Psychology 47 (6): 381–91. [Google Scholar] [Crossref]

11. Flanders, V. 2002. Son of Web Pages That Suck: Learn Good Design by Looking at Bad Design. SYBEX Inc. [Google Scholar] [Crossref]

12. Gray, W. D., and M. Salzman. 1998. “Damaged Merchandise? A Review of Experiments That Compare Usability Evaluation Methods”.” Compare Usability Evaluation Methods”, Human-Computer Interaction 13 (3): 203–61. [Google Scholar] [Crossref]

13. Gregor, P., A. F. Newell, and M. Zajicek. 2002. “The Experienced Web: Designing a Usability Tool for Older Users.” In Proceedings of the 2002 Conference on Universal Usability, 85–92. [Google Scholar] [Crossref]

14. Hill, A. L., and L. Scharff. 1996. Readability of Websites with Various Foreground/Background Color Combinations, Font Types, and Word Styles. [Google Scholar] [Crossref]

15. Hsu, C. L. 2014. “The Effects of Realistic Icons and Human Voice on Smartphone Interfaces for Elderly Us-ers.” Behavior & Information Technology 33 (7): 674–85. [Google Scholar] [Crossref]

16. Ivory, M. Y., and M. A. Hearst. 2002. “Improving Website Design.” IEEE Internet Computing 6 (2): 56–63. [Google Scholar] [Crossref]

17. Johnson, Jeff. 2000. GUI Bloopers: Don’ts and Do’s for Software Developers and Web Designers. Oxford, England: Morgan Kaufmann. [Google Scholar] [Crossref]

18. Kim, H., and J. Moon. 2018. “The Influence of Whitespace on Visual Attention and Persuasion: An Eye-Tracking Study.” International Journal of Human-Computer Interaction 34 (9): 822–33. [Google Scholar] [Crossref]

19. Kurniawan, Sri, and Panayiotis Zaphiris. 2005. “Research-Derived Web Design Guidelines for Older People.” In Proceedings of the 7th International ACM SIGACCESS Conference on Computers and Accessibility. New York, NY, USA: ACM. [Google Scholar] [Crossref]

20. Landa, R. 2014. White space is not your enemy: A beginner's guide to communicating visually through graphic, web, and multimedia design. CRC Press [Google Scholar] [Crossref]

21. Martins, Beatriz, and Carlos Duarte. 2024. “Large-Scale Study of Web Accessibility Metrics.” Universal Access in the Information Society 23 (1): 411–34. https://doi.org/10.1007/s10209-022-00956-x. [Google Scholar] [Crossref]

22. Murray, Costanzo. 1999. “Usability and the Web: An Overview.” Network Notes 61. [Google Scholar] [Crossref]

23. Nielsen, J. 1994. “Heuristic Evaluation.” In Usability Inspection Methods, edited by J. Nielsen and R. L. Mack. New York, NY: John Wiley & Sons. [Google Scholar] [Crossref]

24. Nielsen, J. 2010. White Space in User Interface Design. [Google Scholar] [Crossref]

25. Petrie, Helen, Andreas Savva, and Christopher Power. 2015. “Towards a Unified Definition of Web Accessibility.” In Proceedings of the 12th International Web for All Conference. New York, NY, USA: ACM. [Google Scholar] [Crossref]

26. Reber, Rolf, Norbert Schwarz, and Piotr Winkielman. 2004. “Processing Fluency and Aesthetic Pleasure: Is Beauty in the Perceiver’s Processing Experience?” Personality and Social Psychology Review: An Official Journal of the Socie-ty for Personality and Social Psychology, Inc 8 (4): 364–82. https://doi.org/10.1207/s15327957pspr0804_3. [Google Scholar] [Crossref]

27. Rubin, J., and D. Chisnell. 2008. The Handbook of Usability Testing. Indianapolis, IN: Wiley Publishing, Inc. [Google Scholar] [Crossref]

28. Shipley, A. 2002. “Creating an Inclusive Environment.” Disability Rights Commission. 2002. http://www.designingaccessiblecommunities.org/policies/CreatingInclusiveEnvironment.pdf. [Google Scholar] [Crossref]

29. Still, Jeremiah D. 2018. “Web Page Visual Hierarchy: Examining Faraday’s Guidelines for Entry Points.” Computers in Human Behavior 84: 352–59. https://doi.org/10.1016/j.chb.2018.03.014. [Google Scholar] [Crossref]

30. Tahir, M. H. 2018. “Icon Design for Use on Websites: The Impact of Visual Distinctiveness on Human-Computer Interaction.” Computers in Human Behavior 82: 72–83. [Google Scholar] [Crossref]

31. Tullis, Thomas, and William Albert. 2010. Measuring the User Experience: Collecting, Analyzing, and Presenting Us-ability Metrics. Morgan Kaufmann. [Google Scholar] [Crossref]

32. Wobbrock, Jacob O., Kristen Shinohara, and Alex Jansen. 2011. “The Effects of Task Dimensionality, Endpoint De-viation, Throughput Calculation, and Experiment Design on Pointing Measures and Models.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM. [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles

© 2026 IJLTEMAS · RSIS International. All rights reserved. ISSN 2278-2540.