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📄 Research Article

Beyond Perspectives: A Trio-Ethnography of Interpretation Evolution in LLM-Supported Programming Education

● high · 2026-07-27generative-ai, stem-education, teacher-role, student-experience, higher-ed, scaffolding, ai-literacy, llm, regulation

This experience report introduces trio-ethnography — structured dialogue between two computing educators with differing teaching philosophies and one undergraduate CS student — as a method for surfacing how educators' interpretations of students' AI use evolve. The central finding is that much AI-supported learning is invisible from the classroom: across three conversations, the student's lived-experience narratives revealed learning processes that neither educator could infer from observable behavior, prompting both to revise assumptions about AI use, assessment design, and transparency in CS Education.

The paper complicates the dominant framing of Student Experience research, which typically measures behavior (prompt logs, usage frequency) rather than interpretation. Educators here initially read student AI use through the lens of Over Reliance risk, but dialogue revealed more nuanced self-regulation and Scaffolding-seeking than surveillance-style observation suggested. This aligns with broader calls for AI Literacy frameworks that treat students as reflective agents rather than compliance subjects.

Methodologically, trio-ethnography offers a low-cost reflective instrument for faculty development: rather than instrumenting classrooms with analytics, it uses sustained cross-perspective conversation to update pedagogical beliefs. As an experience report with n=3 it makes no generalizability claims, but it provides a replicable protocol for departments adapting programming instruction in the generative-AI era.

Connected Concepts

  • CS Education
  • Student Experience
  • Over Reliance
  • Scaffolding
  • AI Literacy

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    • Citation

    Ren, McDowell & Zhou (2026). Beyond Perspectives: A Trio-Ethnography of Interpretation Evolution in LLM-Supported Programming Education. arXiv:2607.22463. arXiv preprint.