Cognitive Structure Generation: From Educational Priors to Policy Optimization

• URL: http://arxiv.org/abs/2508.12647v1
• Date: Mon, 18 Aug 2025 06:21:36 GMT
• Title: Cognitive Structure Generation: From Educational Priors to Policy Optimization
• Authors: Hengnian Gu, Zhifu Chen, Yuxin Chen, Jin Peng Zhou, Dongdai Zhou,
• Abstract summary: This paper introduces a novel framework, Cognitive Structure Generation (CSG), to generate students' cognitive structures.<n> Experimental results on four popular real-world education datasets show that cognitive structures generated by CSG offer more comprehensive and effective representations for student modeling.
• Score: 10.932994688742475
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Cognitive structure is a student's subjective organization of an objective knowledge system, reflected in the psychological construction of concepts and their relations. However, cognitive structure assessment remains a long-standing challenge in student modeling and psychometrics, persisting as a foundational yet largely unassessable concept in educational practice. This paper introduces a novel framework, Cognitive Structure Generation (CSG), in which we first pretrain a Cognitive Structure Diffusion Probabilistic Model (CSDPM) to generate students' cognitive structures from educational priors, and then further optimize its generative process as a policy with hierarchical reward signals via reinforcement learning to align with genuine cognitive development levels during students' learning processes. Experimental results on four popular real-world education datasets show that cognitive structures generated by CSG offer more comprehensive and effective representations for student modeling, substantially improving performance on KT and CD tasks while enhancing interpretability.

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