Contrastive Cross-Course Knowledge Tracing via Concept Graph Guided Knowledge Transfer

TL;DR

This paper introduces TransKT, a novel contrastive cross-course knowledge tracing method that uses concept graphs and LLMs to transfer knowledge across courses, improving learner modeling accuracy.

Contribution

It proposes a new approach leveraging concept graphs guided by LLM prompts and contrastive learning to enhance cross-course knowledge transfer in KT models.

Findings

Improved accuracy in predicting learner performance across courses.

Effective use of LLMs for constructing concept graphs.

Enhanced knowledge state estimation through contrastive objectives.

Abstract

Knowledge tracing (KT) aims to predict learners' future performance based on historical learning interactions. However, existing KT models predominantly focus on data from a single course, limiting their ability to capture a comprehensive understanding of learners' knowledge states. In this paper, we propose TransKT, a contrastive cross-course knowledge tracing method that leverages concept graph guided knowledge transfer to model the relationships between learning behaviors across different courses, thereby enhancing knowledge state estimation. Specifically, TransKT constructs a cross-course concept graph by leveraging zero-shot Large Language Model (LLM) prompts to establish implicit links between related concepts across different courses. This graph serves as the foundation for knowledge transfer, enabling the model to integrate and enhance the semantic features of learners' interactions across courses. Furthermore, TransKT includes an LLM-to-LM pipeline for incorporating summarized semantic features, which significantly improves the performance of Graph Convolutional Networks (GCNs) used for knowledge transfer. Additionally, TransKT employs a contrastive objective that aligns single-course and cross-course knowledge states, thereby refining the model's ability to provide a more robust and accurate representation of learners' overall knowledge states.