Cognitive Diagnostic Models

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12 papers1 paper in the last four weeks, down 75% on the four weeks before. 0.0% of all new papers.

Making Reasoning Visible: Configuration-Aware Diagnostic Modeling for Adaptive Scaffolding in Structured Reasoning Tasks
Oct 26, 2026Trystan Geoffre, Zheng Yuan, Thierry GeoffreUser Modeling Cognitive Diagnostic Models
University of Fribourg, Switzerland · University of Sheffield, England · University of Luxembourg, Luxembourg
Curriculum Brain: Constructing Curriculum Knowledge Graphs as a Substrate for Cognitive Diagnosis
Oct 5, 2026Shrideep Tamboli, Chiranjeevi Maddala, Eshal MinhajKG Construction Educational Assessment
AI Ready School
Ability-Residual Decoupled Modeling for Affective Cognitive Diagnosis
Sep 18, 2026Boyuan Zhao, Meng YeCognitive Diagnostic Models Educational Data Mining
Key Laboratory of Modern Teaching Technology, Shaanxi Normal University, 199 Chang’an South Road, Xi’an, 710062, Shaanxi, China.
Beyond ID Embeddings: Process-Grounded Language Modeling for Cognitive Diagnosis
Sep 11, 2026Minghang Liu, Yuanzhuo Wang, Qiang Qiu +2LLM Grounding Cognitive Modeling
State Key Laboratory of AI Safety, Institute of Computing Technology, CAS · University of Chinese Academy of Sciences
Privacy-Preserving Heterogeneous Multi-LLM Federated Inference for Cognitive Diagnosis
Sep 1, 2026Yagna Manasa Boyapati, Chong Yu, Tianyu Jiang +1Cognitive Diagnostic Models AI in Education
Department of Computer Science University of Cincinnati
Quantum Sparse Autoencoders for Q-Matrix Estimation in Cognitive Diagnosis
Sep 1, 2026Arif Hassan Zidan, Yi Pan, Bowen Guo +5Cognitive Diagnostic Models Quantum Machine Learning
School of Computer and Cyber Sciences, Augusta University, Augusta, GA, USA · School of Computing, University of Georgia, Athens, GA, USA · Department of Graduate Psychology, James Madison University, Harrisonburg, VA, USA +2
Aligning LLM-Simulated and Human Examinees for Psychometric Calibration: A Cognitive Diagnostic Profiling Approach
Jul 28, 2026Wenjie Zhou, Yunting Liu, Renjiao Tang +1Cognitive Modeling Cognitive Diagnostic Models
Berkeley School of Education, University of California, Berkeley · Department of Family Social Science, University of Minnesota Twin Cities, Minneapolis
Multilayer Q-Matrix-Embedded Neural Network for Cognitive Diagnosis (M-QCDNet): Structure-Aware Deep Learning Architecture for Psychometric Interpretability
Jul 1, 2026Yiyao YangEducational Assessment Interpretable ML
Columbia University, New York, NY, United States
Interpreting Learning Under Competing Models: Joint and Stepwise Approaches for Dynamic Cognitive Diagnosis
Jun 5, 2026Yawen Ma, Sahoko Ishida, Kate Cain +1Computational Cognitive Modeling Educational Assessment
School of Mathematical Sciences, Lancaster University, Lancaster, LA1 4YF, Lancashire, United Kingdom · Department of Computer Science, University of Oxford, Oxford, United Kingdom · Department of Psychology, Lancaster University, Lancaster, LA1 4YF, Lancashire, United Kingdom +1
Beyond Scores: Diagnostic LLM Evaluation via Fine-Grained Abilities
Apr 14, 2026Xu Zhang, Xudong Gong, Jiacheng Qin +5LLM Evaluation Cognitive Diagnostic Models
College of Computer Science and Technology, National University of Defense Technology, Changsha, Hunan, China · State Key Laboratory of Complex & Critical Software Environment, Changsha, Hunan, China · School of Humanities and Social Sciences, School of Public Administration, Beihang University, Beijing, China +1
Embedding Enhancement via Fine-Tuned Language Models for Learner-Item Cognitive Modeling
Apr 5, 2026Yuanhao Liu, Zihan Zhou, Kaiying Wu +5Cognitive Diagnostic Models Computerized Adaptive Testing
East China Normal University Shanghai, China · Tencent Inc Shenzhen, China · Shanghai Innovation Institute Shanghai, China
A Framework for Human-AI Q-Matrix Refinement: A NeuralCDM Evaluation
Mar 30, 2026Ying Zhang, Ningxi Cheng, Yizhu Gao +5Cognitive Diagnostic Models Educational Assessment
AI4STEM Education Center, University of Georgia, Athens, GA, USA

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Making Reasoning Visible: Configuration-Aware Diagnostic Modeling for Adaptive Scaffolding in Structured Reasoning Tasks

Trystan Geoffre, Zheng Yuan, Thierry Geoffre

University of Fribourg, Switzerland · University of Sheffield, England · University of Luxembourg, Luxembourg

User Modeling Cognitive Diagnostic Models

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Modeling the latent, multi-step reasoning processes of learners is a core challenge for adaptive tutoring systems, which often rely on simple right/wrong answers rather than understanding how students think. Instantiated here for grammatical reasoning, this study introduces a diagnostic framework that makes students' step-by-step problem-solving visible by analyzing their action sequences in an interactive learning game. The framework computes five interpretable strategy dimensions (e.g., systematic error correction, random guessing), estimates coordination demand from task structure and behavioral patterns, and classifies reasoning into four distinct states. Analyzing 36,234 interactions from 234 students working on 42 morphosyntactic exercises, we found that reasoning strategies vary primarily by context rather than stable traits (intraclass correlation = 0.14), and students show high persistence in unproductive states; specifically, 74.6% of failures driven by high coordination demand (rather than simple knowledge gaps) are followed by another failure without intervention. Our early warning model predicts validation success with strong accuracy (AUC = 0.826 using strategy patterns alone; 0.902 with additional sequential context) while avoiding circular reliance on current error counts. These findings demonstrate that making latent reasoning processes visible enables earlier, more targeted scaffolding that responds to how students are thinking rather than simply whether they succeed. While demonstrated in language learning, the framework provides a generalizable, interpretable architecture for diagnosing complex, structured reasoning in any domain.