Towards Modeling Learner Performance with Large Language Models

arXiv:2403.14661v1 Announce Type: cross
Abstract: Recent work exploring the capabilities of pre-trained large language models (LLMs) has demonstrated their ability to act as general pattern machines by completing complex token sequences representing a wide array of tasks, including time-series prediction and robot control. This paper investigates whether the pattern recognition and sequence modeling capabilities of LLMs can be extended to the domain of knowledge tracing, a critical component in the development of intelligent tutoring systems (ITSs) that tailor educational experiences …

abstract act array arxiv capabilities control cs.cl cs.cy cs.lg general language language models large language large language models llms machines modeling paper pattern recognition performance prediction recognition robot series tasks token type work