AI RESEARCH
Confirming Correct, Missing the Rest: LLM Tutoring Agents Struggle Where Feedback Matters Most
arXiv CS.AI
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ArXi:2605.16207v1 Announce Type: new Effective tutoring requires distinguishing optimal, valid but suboptimal, and incorrect student solutions, a distinction central to intelligent tutoring systems (ITS) but untested for LLM-based tutors. As LLMs are increasingly explored as conversational complements to ITS, evaluating their diagnostic precision is essential. We present a benchmark of seven LLM feedback agents in propositional logic using knowledge-graph-derived ground truth across 10,836 solution--feedback pairs and three feedback conditions.