通过三方对话揭示生成式AI编程教育中被忽视的学习过程。
Beyond Perspectives: A Trio-Ethnography of Interpretation Evolution in LLM-Supported Programming Education
- 三名成员开展对话式民族志，反思对AI辅助学习的刻板印象。
- 学生经历揭示课堂外的深层学习模式，促使教师调整教学理念。
- 适合关注AI教育实践与师生互动的教育研究者参考。
生成式AI正在重塑编程教育，但教师常仅凭课堂观察推断学生的学习情况。本经验报告采用三方民族志方法，包含两名具有不同教学理念的计算机教育者和一名本科生，通过三次对话探讨其认知如何演变。在交流中，教育者反思学生使用AI的行为，讨论教学法的变革，并在倾听学生真实经历后重新审视自身假设。学生的叙述揭示了课堂上难以察觉的学习过程，促使两位教育者重新思考关于AI使用、评估方式、透明度及编程教学的根本观念。我们主张，三方民族志为计算教育者提供了一种有价值的反思路径，使其超越可见行为，深入理解生成式AI背景下的学习本质，并支持教学策略的适应性调整。
原文摘要 · Abstract (English)
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.
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