ProIQA: A Process-Based Framework for Fine-Grained Math Item Quality Assessment

arXiv:2609.15292 · cs.AI · Submitted 2026-09-14 · Read on arXiv

cs.AI

Submitted: 2026-09-14

Updated: 2026-09-15

Comments: Accepted by ICDM 2026, project: https://github.com/qky7/ProIQA

Code: https://github.com/qky7/ProIQA

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 10× in this paper · explained in 1 episode
• Structured Reasoning — 9× in this paper · explained in 3 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Automatic Item Generation — 5× in this paper
• Cognitive Depth — 5× in this paper · explained in 2 episodes
• Core — 5× in this paper · explained in 2 episodes
• Verification — 5× in this paper · explained in 2 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Representation Learning — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Calibration — 3× in this paper · explained in 7 episodes
• Graph Neural Networks — 3× in this paper
• Item Response Theory — 3× in this paper
• Transformer — 3× in this paper · explained in 2 episodes
• F1 Score — 2× in this paper · explained in 3 episodes
• GNNs — 2× in this paper · explained in 2 episodes
• Hallucination — 2× in this paper · explained in 3 episodes
• Knowledge Graph — 2× in this paper · explained in 7 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Alignment Verification — 1× in this paper · explained in 1 episode
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Existing Item Quality Assessment — 1× in this paper
• Failure Modes — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Graph Isomorphism Network — 1× in this paper
• Hypergraph — 1× in this paper · explained in 2 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Knowledge graphs — 1× in this paper · explained in 2 episodes
• Multi-objective Optimization — 1× in this paper · explained in 4 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Structural Integrity — 1× in this paper · explained in 3 episodes
• Supervised Fine-Tuning — 1× in this paper
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Recent Advances in Neural Question Generation
• Automatic Generation and Evaluation of Reading Comprehension Test Items with Large Language Models
• Elementary Math Word Problem Generation using Large Language Models

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