Teaching Language Models How to Code Like Learners: Conversational Serialization for Student Simulation
Artificial students -- models that simulate how learners act and respond within educational systems -- are a promising tool for evaluating tutoring strategies and feedback mechanisms at scale. However, most existing approaches rely on prompting large, proprietary language models, limiting adaptability to specific courses and raising concerns around privacy, cost, and dependence. In this work, we propose a framework for training open-weight artificial programming learners directly from authentic student process data. Our approach serializes temporal log traces into a conversational format, representing each student's problem-solving process as a dialogue between the learner and their autom...
| Authors | Charles Koutcheme, Juho Leinonen, Arto Hellas |
|---|---|
| Primary category | cs.AI |
| Published | 12 April 2026 |
| Last updated at source | 13 May 2026 |
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