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

Abstract

-cross Abstract: Novice math teachers often encounter students' mistakes that are difficult to diagnose and remediate. Misconceptions are especially challenging because teachers must explain what went wrong and how to solve them. Although many existing large language model (LLM) platforms can assist in generating instructional feedback, these LLMs loosely connect pedagogical knowledge and student mistakes, which might make the guidance less actionable for teachers. To address this gap, we propose MisEdu-RAG, a dual-hypergraph-based retrieval-augmented generation (RAG) framework that organizes pedagogical knowledge as a concept hypergraph and real student mistake cases as an instance hypergraph. Given a query, MisEdu-RAG performs a two-stage retrieval to gather connected evidence from both layers and generates a response grounded in the retrieved cases and pedagogical principles. We evaluate on \textit{MisstepMath}, a dataset of math mistakes paired with teacher solutions, as a benchmark for misconception-aware retrieval and response generation across topics and error types. Evaluation results on \textit{MisstepMath} show that, compared with baseline models, MisEdu-RAG improves token-F1 by 10.95\% and yields up to 15.3\% higher five-dimension response quality, with the largest gains on \textit{Diversity} and \textit{Empowerment}. To verify its applicability in practical use, we further conduct a pilot study through a questionnaire survey of 221 teachers and interviews with 6 novices. The findings suggest that MisEdu-RAG provides diagnosis results and concrete teaching moves for high-demand misconception scenarios. Overall, MisEdu-RAG demonstrates strong potential for scalable teacher training and AI-assisted instruction for misconception handling. Our code is available on GitHub: https://github.com/GEMLab-HKU/MisEdu-RAG.

Authors 3

Zhihan Guo, Yuting Lu, Jionghao Lin

Specification

Official page: arxiv.org/abs/2604.04036
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
Arxiv announce type: replace
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
arXiv id: 2604.04036
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
Categories: cs.IR, cs.CL
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
PDF: arxiv.org/pdf/2604.04036
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
Primary category: cs.IR
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh
Published: 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

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T19

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2 h ago

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Authors: Zhihan Guo, Yuting Lu, Jionghao Lin

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Value	Valid from → to	Status	Source	Confidence	Extractor
https://arxiv.org/abs/2604.04036	11 Sept 2026 21:03 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

11 Sept 2026
New paperPaperMisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers
New paper: MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers
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arXiv (Atom API + RSS)	rss.arxiv.org/rss/cs.CL	feed	T1· Official	41 min ago	1

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