Learner Modeling for Personalized E-Learning: A Comparative Analysis of Approaches
Youssef El Kourchi, Nabil El Akkad · 2025
Personalized learning has received a significant amount of attention as an educational approach that customizes learning materials for individual learners to their strengths, interests, and skills. The learner model is central to this approach and modifies content based on learners' knowledge, skills, learning styles, and motivations. This study contemplates the fundamental aspects of learner models for personalization, and the methods by which they are designed, and provides a comparative review of current approaches by reviewing seven studies. The review demonstrates the limitations of learner models in these studies, specifically on cognitive factors; learner profiles; and in more modern examples, learning styles, affective factors, and behavioral factors to realize personalization. The importance and necessity for an integrated learner model that can develop personalized learning with cognitive, behavioral, emotional, and personality characteristics is very much reinforced by this paper. The paper also argues for the further application of artificial intelligence or AI-based technologies in learner modeling and the implementation of fully personalized e-learning. By providing a systematic understanding of learner models, their evolution, and their impact on modern e-learning systems, this study aims to pave the way for future advancements in personalized education.