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

A small programming-education study found that classroom observation missed how a student learned with AI. Builders of learning tools should avoid equating visible agent use with the underlying process.

arXiv · Jul 24, 2026
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Source Summary

The experience report follows **two computing educators and one undergraduate student** through **three conversations** about AI-assisted programming. The student's account exposed learning processes that classroom observation had not revealed.

Practical Implication

Builders of coding-agent education tools should make process, reasoning, and disclosure easier to inspect. Assessment and product decisions based only on visible behavior may misread how learners use AI and what they understand.

Agent-Ready Context
The experience report follows **two computing educators and one undergraduate student** through **three conversations** about AI-assisted programming. The student's account exposed learning processes that classroom observation had not revealed.

Builders of coding-agent education tools should make process, reasoning, and disclosure easier to inspect. Assessment and product decisions based only on visible behavior may misread how learners use AI and what they understand.

This is a reflective trio-ethnography, not a broad evaluation of students or teaching methods. Its value is in surfacing assumptions; the material provides no quantitative evidence that the approach improves learning outcomes.
Context Map
industrycoding#adoption
Uncertainty
This is a reflective trio-ethnography, not a broad evaluation of students or teaching methods. Its value is in surfacing assumptions; the material provides no quantitative evidence that the approach improves learning outcomes.