Using Multi-criteria Evaluation of E-learning System: A Methodology Based on Learning Outcomes

Abstract

Academic research on E-learning system has been widely influenced by COVID-19 pandemic. As evaluating online learning can directly promote the design of more effective learning environments. As evaluating E-learning systems while considering factors such as system content, pedagogical issues, adaptation, learning agents and learning outcomes dimensions can be considered as a complex multi-criteria decision making problem. This paper presents a methodology to support researchers and practitioners in a effectively adopting analytical techniques such as Analytic hierarchy process, Entropy Method, and the Criteria Importance through Inter-criteria Correlation in E-learning evaluation. The paper experiments with multiple learning scenarios and the results provide various alternatives for decision making.