New Empirical Data Findings for Student Experiences of E-Learning analytics Recommender Systems and their Impact on System Adoption

Abstract

This article examines Saudi Arabian students' experiences of using an e-learning analytics recommender system during their study and the extent to which their experiences were predictors of their adoption and post-adoption of the system. A sample of 353 students from various universities in Saudi Arabia completed a survey questionnaire for data collection. Results showed that user experience is a significant predictors of student adoption and post-adoption of an e-learning recommender system. Based on these findings, this study concluded that universities must support students to develop their awareness of, and skills in using an e-learning recommender system to support students' long-term acceptance and use of the system.