Evaluating Online Learning Effectiveness Using AHP-TOPSIS: A Comprehensive Analysis of Student Feedback

Online learning has become central to education, yet faces persistent challenges like engagement, accessibility, and concentration that affect its effectiveness. Traditional assessments often overlook these multifaceted challenges, focusing on individual factors rather than the complete experience. This study presents a multi-criteria decision-making framework combining the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for a holistic evaluation. A survey of 1,469 students was conducted, with AHP prioritizing key factors—IT skills, engagement, and resource access—while TOPSIS ranks students based on these weighted criteria. Clustering analysis groups students into high, medium, and low performance clusters, providing actionable insights for enhancing online learning strategies. This approach offers a comprehensive framework for evaluating and refining online education practices to better support diverse student needs.