Psychological factors enhanced heterogeneous learning interactive graph knowledge tracing for understanding the learning process

This paper proposes Psy-KT, a knowledge tracing model that predicts student performance on future exercises by incorporating four psychological factors (frustration, confusion, concentration, boredom) alongside traditional exercise history and skill mastery, using heterogeneous graphs and Item Response Theory. The model is validated on four public datasets and aims to provide personalized adaptive learning recommendations.

Introduction With the rapid expansion of online education, there is a burgeoning interest within the EdTech space to offer tailored learning experiences that cater to individual student's abilities and needs. Within this framework, knowledge tracing tasks have garnered considerable attention. The primary objective of knowledge tracing is to develop a model that assesses a student's proficiency in a particular skill based on their historical performance in exercises, enabling predictions regardin

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