{"ID":2880982,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.12647","arxiv_id":"2508.12647","title":"Cognitive Structure Generation: From Educational Priors to Policy Optimization","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.","short_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 larg...","url_abs":"https://arxiv.org/abs/2508.12647","url_pdf":"https://arxiv.org/pdf/2508.12647v1","authors":"[\"Hengnian Gu\",\"Zhifu Chen\",\"Yuxin Chen\",\"Jin Peng Zhou\",\"Dongdai Zhou\"]","published":"2025-08-18T06:21:36Z","proceeding":"cs.AI","tasks":"[\"cs.AI\",\"cs.CY\",\"cs.LG\"]","methods":"[\"Reinforcement Learning\",\"Diffusion Model\",\"Generative Adversarial Network\"]","has_code":false}