Fuzzy comprehensive evaluation system and decision support system for learning management of higher education online courses

A Learning Management System (LMS) facilitates the implementation and effectiveness of online learning by providing sufficient tools for the organization, delivery, and administration of online courses. Traditional learning platforms lack diverse learning styles and limit the ability to provide personalized attention and support. However, the factors affecting the online learning experience are fuzziness and uncertainty. The research articles propose a Fuzzy Analytic Hierarchy Evaluation System (FAHES) that integrates an Analytic Hierarchy Process (AHP) and a Fuzzy Comprehensive Evaluation System (FCES) to analyze the efficiency of online courses over existing challenges. A key component of FAHES is its decision-support facilities that incorporate fuzzy Logic, which allows educational institutions to make well-informed decisions when providing recommendations. AHP aims to create a structured hierarchy out of complex criteria and sub-criteria, allowing for pairwise comparisons and combining expert opinions, resulting in weights that reflect these priorities. Then, the FCES aggregates weighted inputs from multiple criteria and analyzes fuzzy data to evaluate the performance management of online courses. Thus, the model provides a clear and actionable evaluation by methodically assessing complex online learning systems while including and managing subjectivity and ambiguity. This approach provides a clear understanding of different factors influencing learning outcomes, interaction efficiency, personalized recommendations, and learner satisfaction through a multi-level evaluation framework. Hence, online course design and delivery improvement is achieved by providing practical insights and suggestions derived from the evaluation findings.