tutor testing

INSIDE aligned simulated student actions with internal dialogue, but reasoning fidelity remained partial

Rose Niousha, Minwoo Kang, Narges Norouzi

Conference on Language Modeling 2026

Niousha, Kang and Norouzi introduce INSIDE, a framework that fine-tunes LLM student simulators on paired internal-dialogue traces and observable actions across cognitive, affective, and action dimensions. It improved action fidelity and achieved reasoning alignment up to 57.9 percent across evaluated models. The result advances simulator evaluation but leaves substantial mismatch and does not justify replacing trials with real learners.