Ren, McDowell & Zhou (2026) — arXiv preprint (cs.HC, cs.AI).
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-ai-interaction 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.
Related Pages
- cs-education — trio-ethnography reveals invisible AI-supported learning processes
- student-ai-interaction — interpretation-focused complement to behavioral usage studies
- over-reliance — educator assumptions of over-reliance revised through student dialogue
- scaffolding — students shown to seek scaffolding via AI in ways invisible to observers
- ai-literacy — supports framing students as reflective agents in AI use
Citation
APA: Ren, McDowell & Zhou (2026). Beyond Perspectives: A Trio-Ethnography of Interpretation Evolution in LLM-Supported Programming Education. arXiv:2607.22463. arXiv preprint.