Robust Data Findings of E-Learning Analytics Recommender Systems and Their Impact on System Adoption for Student Experiences

Abstract

E-learning recommender systems have an import role in Saudi Arabia to facilitate the education empowerment of women. The understanding of the key factors that affect adoption is critical to achieving educational equality in outcomes in countries with gender-based cultural practices. Therefore, this study examined 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 predictor of student adoption and post-adoption of an e-learning recommender system. This study determined that adoption is significantly linked to the ability to effectively navigate and utilise the e-learning systems. Therefore, 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.