MODELING OF AN ADAPTIVE E-LEARNING SYSTEM FOR IMPROVED LEARNING PERFORMANCE - Emmanuel Onwuka Ibam; Olumide Sunday Adewale; Oluwatoyin Catherine Agbonifo; Ibrahim Makinde Akindeji (Bakti Nusantara Institute, 2023)
Majority of the online learning systems in use today, lack proper integration of adaptive, collaborative, personalized and ubiquitous concepts in their design and implementation. Integration of these basic concepts in online learning systems will enable adaptation, individualization, and collaboration of learning resources to learners’ preferences, with an added advantage of accessibility to online resources anywhere and anytime. Hence, the research proposes an Adaptive E-Learning System (AES) model that incorporates activities sequencing in a personalised, adaptive, collaborative and ubiquitous learning environment. The system model consists of the system (software) architectural diagram and mathematical model of activity sequence. The design is presented using the UML activity diagram and the class diagram. The full implementation of the system is currently being carried out and is being tested with real life cases.