EduAgentQG: Multi-Agent Personalized Mathematics Question Generation with Explicit Diversity and Objective-Aware Evaluation

arXiv:2511.11635 · cs.CY, cs.AI, cs.CL · Submitted 2025-11-08 · Read on arXiv

cs.CY, cs.AI, cs.CL

Submitted: 2025-11-08

Updated: 2026-08-26

Code: https://github.com/Mind-Lab-ECNU/EduAgentQG

Terminology

• Alignment — 31× in this paper · explained in 1 episode
• Consistency — 24× in this paper · explained in 3 episodes
• Core — 11× in this paper · explained in 2 episodes
• Verification — 8× in this paper · explained in 2 episodes
• Multi-Agent Framework — 5× in this paper · explained in 3 episodes
• Multi-agent Collaborative Framework — 5× in this paper · explained in 2 episodes
• Knowledge Graph — 4× in this paper · explained in 7 episodes
• Multi-agent Collaboration — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Evaluation Dimensions — 3× in this paper · explained in 3 episodes
• RAG — 3× in this paper · explained in 3 episodes
• Structured Reasoning — 3× in this paper · explained in 3 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Iterative Refinement — 2× in this paper · explained in 3 episodes
• Knowledge graphs — 2× in this paper · explained in 2 episodes
• Monte Carlo Tree Search — 2× in this paper
• Robustness — 2× in this paper · explained in 5 episodes
• AI Literacy — 1× in this paper · explained in 1 episode
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 16 episodes

Sources

• Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints
• AI-Assisted Generation of Difficult Math Questions
• Math Multiple Choice Question Generation via Human-Large Language Model Collaboration
• MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection
• From Objectives to Questions: A Planning-based Framework for Educational Mathematical Question Generation
• SAND-Math: Using LLMs to Generate Novel, Difficult and Useful Mathematics Questions and Answers
• Learning by Analogy: Diverse Questions Generation in Math Word Problem
• BERTScore: Evaluating Text Generation with BERT
• Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
• Qwen2 Technical Report

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