Unveiling the Complexities of Student Satisfaction in E-learning: An Integrated Framework for the Context of COVID-19

Amidst the global pandemic’s reshaping of education, our study investigates e-learning dynamics in Canadian higher education. Integrating the Technology Acceptance Model (TAM), the DeLone and McLean Information Systems Success Model (D&M ISS), and the Expectation Confirmation Model (ECM), we introduce the innovative C-RES framework. This framework, which stands for COVID-19 Remote E-learning System, uniquely addresses the complexities of e-learning systems and their role in student satisfaction during COVID-19. Through Structural Equation Modeling (SEM) analysis of responses from a diverse pool of graduate students across Canada, we uncover relationships among psycho- logical factors, quality dimensions, and social influences. We demonstrate how self-efficacy, IT anxiety, and perceived system and information quality significantly influence students’ ease of use and usefulness perceptions, impacting their satisfaction and commitment to Learning Management Systems (LMS). Our findings reveal that e-learning quality lies not only in technology but also in content, and highlight the significant influence of individual confidence and community dynamics on student experiences. These insights provide actionable strategies for enhancing the effectiveness and resilience of e-learning systems, especially in crises. While focusing on the Canadian pandemic context, our research suggests exploring demographic influences in future studies. This thesis serves as a foundation for future e-learning explorations, pushing educational technology boundaries during global disruptions and offering key strategies for resilience and effectiveness in higher education.