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CodeA11y: Making AI Coding Assistants Useful for Accessible Web Development

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Mowar, Peya, Peng, Yi-Hao, Wu, Jason, Steinfeld, Aaron, Bigham, Jeffrey P·2025·Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
DOI 10.1145/3706598.3713335
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Abstract

A persistent challenge in accessible computing is ensuring developers produce web UI code that supports assistive technologies. Despite numerous specialized accessibility tools, novice developers often remain unaware of them, leading to ~96% of web pages that contain accessibility violations. AI coding assistants, such as GitHub Copilot, could offer potential by generating accessibility-compliant code, but their impact remains uncertain. Our formative study with 16 developers without accessibility training revealed three key issues in AI-assisted coding: failure to prompt AI for accessibility, omitting crucial manual steps like replacing placeholder attributes, and the inability to verify compliance. To address these issues, we developed CodeA11y, a GitHub Copilot Extension, that suggests accessibility-compliant code and displays manual validation reminders. We evaluated it through a controlled study with another 20 novice developers. Our findings demonstrate its effectiveness in guiding novice developers by reinforcing accessibility practices throughout interactions, representing a significant step towards integrating accessibility into AI coding assistants.

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  • Even 'silent' tools that automate accessibility with minimal human intervention still require user oversight and understanding to perform effectively.

    “However, even 'silent' tools that automate accessibility with minimal human intervention still require user oversight and understanding to perform effectively [23].”

    From iTagPDF: Towards Finally Automating PDF Accessibility (2026) · cites this paper as [23]

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Cited by

Sorted by citations

Authors
Mowar, P., Peng, Y.-H., Wu, J., Steinfeld, A., & Bigham, J. P.
Affiliations
  • Carnegie Mellon University (US)
  • Apple (United States) (US)
ORCID
Venue
Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2025-04-25
Pages
1-15
DOI
10.1145/3706598.3713335
OpenAlex
W4409767605
Cited by
31
References
16
Citations by year
2026: 16 · 2025: 15
FWCI
30.85
Type
conference paper
Language
en
Open access
Licence
Locations
  • CHI Conference on Human Factors in Computing Systems (publishedVersion, cc-by)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University) (cc-by)
Topics
  • Social Sciences › Human Factors and Ergonomics › Digital Accessibility for Disabilities
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Research
  • Physical Sciences › Computer Science › Information Systems › Mobile and Web Applications
Keywords
AI coding assistants, web accessibility, assistive technology, code generation, accessibility evaluation

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