Tracing Mathematical Proficiency Through Problem-Solving Processes

This paper introduces KT-PSP, a knowledge tracing formulation that incorporates students' problem-solving processes in mathematics, and proposes StatusKT, an LLM-based framework that extracts mathematical proficiency indicators from students' written solution processes to predict future performance and provide interpretable assessments of student understanding.

Knowledge Tracing (KT) aims to model student's knowledge state and predict future performance to enable personalized learning in Intelligent Tutoring Systems. However, traditional KT methods face fundamental limitations in explainability, as they rely solely on the response correctness, neglecting the rich information embedded in students'problem-solving processes. To address this gap, we propose Knowledge Tracing Leveraging Problem-Solving Process (KT-PSP), which incorporates students'problem-s

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