IDEAS home Printed from https://ideas.repec.org/a/igg/jide00/v10y2019i2p54-63.html
   My bibliography  Save this article

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

Author

Listed:
  • Hadeel Alharbi

    (University of New England, Armidale, Australia)

  • Kamaljeet Sandhu

    (University of New England, Armidale, Australia)

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.

Suggested Citation

  • Hadeel Alharbi & Kamaljeet Sandhu, 2019. "New Empirical Data Findings for Student Experiences of E-Learning analytics Recommender Systems and their Impact on System Adoption," International Journal of Innovation in the Digital Economy (IJIDE), IGI Global, vol. 10(2), pages 54-63, April.
    • Handle: RePEc:igg:jide00:v:10:y:2019:i:2:p:54-63
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJIDE.2019040104
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jide00:v:10:y:2019:i:2:p:54-63. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.