Predictive Study of the Factors and Challenges Affecting the Usability of E-Learning Platforms in the Light of COVID-19

Abstract

In the light of the accelerating trends in recent years towards the adoption of e-learning and its delivery platforms, e-learning has become a strategic solution to face many challenges, especially those imposed by the coronavirus pandemic (COVID-19). The findings of previous studies revealed the effectiveness of e-learning in reducing negative effects resulting from COVID-19. However, those studies emphasized the need for more research on the factors that enhance the effectiveness of e-learning, especially those factors related to instructional design, attractiveness, availability, and usability. Therefore, the study explored the factors that affect the usability of e-learning platforms by developing a predictive model to reveal student satisfaction with the use of e-learning platforms. The model consisted of four predictive factors (learnability, efficiency, effectiveness, and the instructional design of electronic content).  In order to achieve the objective of the study, a scale was designed. It included five variables and 36 items. The results concluded that the factors in the scale (learnability, efficiency, effectiveness, and the instructional design of electronic content) contribute to the explanation of 62% of the variance value in the dependent variable (student satisfaction). Also, the factors of the instructional design of electronic content, and the effectiveness of using e-learning platforms showed a high ability to predict usability through the indicator of student satisfaction with the use of e-learning platforms. In addition, the results unveiled that the factors of learnability and efficiency did not show a significant effect in predicting usability. Finally, the prediction model had a moderate degree in predicting the changes that could affect the dependent variable (usability through the indicator of student satisfaction).