arXiv Computation and Language September 11, 2026 By Zhihan Guo, Yuting Lu, Jionghao Lin

MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers

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MisEdu‑RAG is a dual‑hypergraph retrieval‑augmented generation framework designed to help novice math teachers diagnose and remediate student misconceptions. It structures pedagogical knowledge as a concept hypergraph and real student mistake cases as an instance hypergraph, performing two‑stage retrieval to ground responses in both layers. On the MisstepMath dataset, MisEdu‑RAG outperforms baseline models, improving token‑F1 by 10.95% and achieving up to 15.3% higher quality across five dimensions, especially in diversity and empowerment.

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