发表机构
Mercer University; University of Texas at San Antonio（梅森大学; 德克萨斯大学圣安东尼奥分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究通过三人民族志研究，探讨两位教学理念不同的计算机教育工作者和一名学生在大语言模型支持的编程教育中，如何通过对话使解释演变，揭示课堂外学习过程，促使教育工作者反思，为教学适应提供参考。
AI 中文摘要
生成式人工智能正在重塑编程教育，但教育工作者往往仅从课堂观察中推断学生在人工智能支持下的学习情况。本经验报告展示了一项三人民族志研究，涉及两位教学理念不同的计算机教育工作者和一名本科计算机科学专业学生，以考察这些解释如何通过对话演变。在三次对话中，教育工作者反思了学生对人工智能的使用，讨论了编程教学法的变化，并在接触学生的实际经历后重新审视了他们的假设。学生的叙述并非简单地证实或反驳教育工作者的观点，而是揭示了课堂上基本不可见的学习过程，促使两位教育工作者重新思考关于人工智能使用、评估、透明度和编程教学的假设。我们认为，三人民族志研究提供了一种有价值的反思方法，有助于计算机教育工作者超越可观察到的学生行为，更深入地理解人工智能支持的学习，并为生成式人工智能时代的教学适应提供参考。
英文摘要
Generative AI is reshaping programming education, yet educators often infer students' AI-supported learning from classroom observations alone. This experience report presents a trio-ethnography involving two computing educators with different teaching philosophies and one undergraduate computer science student to examine how these interpretations evolve through dialogue. Across three conversations, the educators reflected on students' AI use, discussed changes to programming pedagogy, and revisited their assumptions after engaging with the student's lived experiences. Rather than simply confirming or contradicting the educators' perspectives, the student's narratives revealed learning processes that were largely invisible in the classroom, prompting both educators to reconsider assumptions about AI use, assessment, transparency, and programming instruction. We argue that trio-ethnography offers a valuable reflective approach for helping computing educators move beyond observable student behaviors toward a richer understanding of AI-supported learning and for informing instructional adaptation in the era of generative AI.
