SOURCE-LINKED INTELLIGENCE
Beyond ID Embeddings: Process-Grounded Language Modeling for Cognitive Diagnosis
Cognitive Diagnosis Models (CDMs) play a pivotal role in personalized online learning. Traditional CDMs rely on discrete, ID-based embeddings to represent students, exercises, and concepts. This paradigm diverges from the nature of learner cognition, where knowledge is not stored and retrieved as isolated symbols. As a result, CDMs suffer from semantic limitations when new exercises or concepts appear. In this paper, we propose a Process-aware Language Cognitive Diagnosis (PLCD) framework that uses language-derived structures as cognitive priors and response records to calibrate student poster
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-11T03:51:20.000Z
First collected: 2026-09-20T18:42:18.733Z. This is not the publication date.