AI 中文总结
本研究提出一项评估AI生成教育材料可访问性的协议，通过对比三种提示配置条件，发现明确配置WCAG标准可显著提升内容可访问性合规性，为社区提供可复用的评估工具以应对AI内容的可访问性问题。
AI 中文摘要
生成式AI工具越来越多地生成文档、幻灯片、图像、音频和视频等教育材料，但人们对这些内容是否符合可访问性要求知之甚少。本文提出一项评估AI生成教育材料可访问性的协议，该协议针对网页内容可访问性指南（WCAG），涵盖五种内容类型及多种工具。该协议对同一工具应用三种条件进行对比：无任何可访问性表述的通用指令；明确配置WCAG标准的单一提示；加载一次后无需重复指定的持久可复用可访问性配置文件。评估结合各内容类型对应的WCAG rubric与可访问性专家的启发式验证，以解决自动扫描工具的已知局限。此前证据表明，生成式AI工具默认会复制不可访问的做法，而明确配置可显著提升合规性。本文将该讨论扩展至WCAG清单未覆盖的维度：AI合成内容常见的视觉与信息过载。主要贡献在于方法论层面：提供可复现的协议与开放评估工具，附带案例记录未配置的AI内容对残障人士造成的障碍。本文还报告了首次探索性应用：使用某一模型、每种条件及类型各一件制品、单评估者评分，基于rubric的合规性得分从通用条件下的合并均值24.2%升至WCAG配置条件下的96.7%；持久配置文件条件未被使用。该协议是供社区在完整基准规模下应用与扩展的可复用资源。除协议外，本研究旨在提升对生成式AI可能引入的可访问性障碍的认识，鼓励创作者在使用这些工具时考虑可访问性。
英文摘要
Generative AI tools increasingly produce educational materials: documents, slides, images, audio, and video, yet little is known about whether this content meets accessibility requirements. This paper presents a protocol for evaluating the accessibility of AI-generated educational materials against the Web Content Accessibility Guidelines (WCAG), across five content types and multiple tools. The protocol compares three conditions applied to the same tool: a generic instruction with no accessibility language; a single prompt explicitly configured with WCAG criteria; and a persistent, reusable accessibility profile loaded once rather than re-specified each time. Evaluation combines a WCAG rubric per content type with heuristic validation by accessibility experts, addressing a known limitation of automated scanners. Prior evidence shows generative AI tools reproduce inaccessible practices by default, and that explicit configuration measurably improves compliance. This paper extends that discussion to a dimension WCAG checklists miss: visual and informational overload common in AI-synthesized content. The main contribution is methodological: a reproducible protocol and open evaluation instrument, with cases documenting the barriers non-configured AI content creates for people with disabilities. A first exploratory application is also reported: a rubric-based compliance score rose from a pooled mean of 24.2% under the generic condition to 96.7% under the WCAG-configured condition, using one model, one artifact per condition and type, and single-evaluator scoring; the persistent-profile condition was not exercised. The protocol is a reusable resource for the community to apply and extend at full benchmark scale. Beyond the protocol, this work aims to raise awareness of accessibility obstacles generative AI can introduce, and encourage creators to consider accessibility when using these tools.
Comments36 pages, 18 tables
