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

Alharbi Hadeel, Kamaljeet Sandhu

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)54-63
JournalInternational Journal of Innovation in the Digital Economy
Volume10
Issue number2
DOIs
Publication statusPublished - 31 Dec 2019

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