Enhancing E-Learning Performance through the Integration of UTAUT, TTF and SET Models: A Conceptual Paper

Abstract

E-learning has become an essential tool in today’s world, offering flexibility and accessibility to learners across the globe. However, the effectiveness of the system is often challenged by factors such as inadequate infrastructure, poor internet connection and underutilization of resources. These issues have led to insufficient e-learning assessment and incomprehensive research models for evaluating e-learning performance. The objective of this study is to propose a new framework that integrates the unified theory of acceptance and use of the technology (UTAUT), task-technology fit (TTF), and self-efficacy theory (SET) to enhance e-learning performance. By synthesizing these models, this study intends to provide an all-encompassing framework to understand the determinants of e-learning performance and offer practical insights for enhancing learner adoption and effectiveness. The proposed framework is not only contributing to the developments of new theoretical knowledge in the literature by identifying key determinants factors but also offers fresh perspectives for practitioners and policymaker. It aims to enhance the execute educational process in the post-COVID19 era and help to design more effective e-learning systems moving forward.