可见的采用，未追踪的贡献：来自GitHub的证据揭示HCI原型设计课程三个队列间的问责差距
Visible Adoption, Untracked Contribution: GitHub Evidence of the Accountability Gap Across Three Cohorts of an HCI Prototyping Course
AI总结：
通过分析203个GitHub仓库和23,065次提交，研究三个队列（2022、2023、2025年）中GenAI采用情况，发现工具披露率从0%升至66%，但贡献归属仍属少数，揭示问责缺口。
AI中文摘要：
本文通过计算分析203个包含学生活动的GitHub仓库和23,065次学生提交，对同一研究生级别HCI原型设计课程三个队列（2022年秋季、2023年和2025年）中学生GenAI采用的变化进行了纵向观察案例研究。基于先前对2023年队列的定性研究，我们区分了两个层次的AI问责追踪：披露（说明使用了AI工具）和归属（将特定工件或任务归功于AI工具）。我们发现，在三个队列中，工具披露从仓库的0%增长到66%，而明确的贡献归属仍然是少数实践，两者之间的差距揭示了即使是在披露的学生中，问责也缺失的地方。到2025年，AI已成为嵌入课程模板和学生构建设备的基础设施：学生越来越多地命名他们使用的工具，但很少具体说明这些工具贡献了什么。我们认为，基于披露的框架不足以应对氛围编码时代。失败不在于学生隐藏AI使用，而在于为偶发、可识别的行为建立的规范无法捕捉持续、环境性的共同创造。我们提供此案例研究作为研讨会讨论真正共同思考问责制样子的基础。
英文摘要：
This paper presents a longitudinal, observational case study of how student GenAI adoption shifted across three cohorts (Fall 2022, 2023, and 2025) of the same graduate-level HCI prototyping course, using computational analysis of 203 GitHub repositories with student activity and 23,065 student commits. Building on a prior qualitative study of the 2023 cohort, we distinguish two levels of AI accountability trace: disclosure (naming that an AI tool was used) and attribution (crediting a specific artifact or task to an AI tool). We find that tool disclosure grew from 0% to 66% of repositories across the three cohorts, while explicit contribution attribution remains a minority practice, and the gap between the two reveals where accountability is missing even among students who disclose. By 2025, AI is infrastructure embedded in course templates and student-built devices: students increasingly name the tools they used, but rarely specify what those tools contributed. We argue that disclosure-based frameworks are insufficient for the vibe-coding era. The failure is not that students conceal AI use; it is that a norm built for episodic, identifiable acts cannot capture continuous, ambient co-creation. We offer this case study as grounding for the workshop's conversation about what genuine co-thinking accountability looks like.
