Conference

Toward recommending learning tasks in a learner-centered approach

This paper presents a rule-based recommender system designed to support learner-centered education by assisting students in selecting learning tasks of varying difficulty levels. While offering choice enhances personalization, students may struggle to identify the most suitable tasks. The proposed system provides personalized recommendations, helping learners choose tasks that maximize their learning outcomes and engagement.