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New Discoveries for User Acceptance of E-Learning Analytics Recommender Systems in Saudi Arabia

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  • Hadeel Alharbi

    (University of New England, Armidale, Australia)

  • Kamaljeet Sandhu

    (University of New England, Armidale, Australia)

Abstract

This article adopts e-learning analytics principles to provide a new model to explain the acceptance behaviour of recommender systems adoption with e-learning in the Saudi Arabian context and reflects the increasing focus of the Saudi Arabian Ministry of Education on delivering online educational services. This focus has come at the necessity to improve overall access to the education system, and higher education and has been driven with evidence of improving learning outcomes with electronic learning (e-learning) information and instructional technology with the use of e-learning analytics recommender systems. This review utilises the technology acceptance model as a theoretical framework to generate a set of interlocked hypotheses that go to explaining student behaviours towards technological acceptance and continued usage intention of recommender systems.

Suggested Citation

  • Hadeel Alharbi & Kamaljeet Sandhu, 2019. "New Discoveries for User Acceptance of E-Learning Analytics Recommender Systems in Saudi Arabia," International Journal of Innovation in the Digital Economy (IJIDE), IGI Global, vol. 10(1), pages 31-42, January.
    • Handle: RePEc:igg:jide00:v:10:y:2019:i:1:p:31-42
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