E-learning systems

This study investigates the optimization of cross-course learning paths in e-learning environments, addressing the challenge of navigating vast educational resources and aligning them with diverse learner needs. We propose a novel cross-course learning path planning model that integrates resources from multiple courses to tailor educational experiences to individual learner profiles. The model employs a modified affinity function, the item response theory (IRT), and a knowledge graph to effectively match learners' abilities with material difficulties and prerequisites.