IDEAS home Printed from https://ideas.repec.org/a/taf/tbitxx/v43y2024i15p3863-3892.html
   My bibliography  Save this article

Ai in e-learning: the affordance perspective

Author

Listed:
  • Jing Zhang
  • Zilong Liu
  • Haibin Lv
  • Ming Jiang

Abstract

The AI-enabled intelligent learning system (AEILS) is able to provide personalised and intelligent tutoring and is more capable of meeting individuals’ need. Nevertheless, limited studies focused on the effect of AI-specific factors on user behaviour. To fill this research gap, we identified the AEILS-specific affordances (i.e. interactivity, personalisation, competition, convenience) and explored their effect on user engagement and foreign language speaking anxiety (FLSA). In this paper, we integrate quantitative and qualitative studies to explore user behaviour in AEILS. Survey data was collected from 457 respondents and analysed using structural equation modelling with the smart-PLS software. The results showed that AEILS-specific affordances significantly affect flow experience and self-expansion, thus facilitating user engagement and alleviating FLSA. Semi-structured interviews were conducted to corroborate the findings of the quantitative study. These findings highlighted the importance of technology affordance in AEILS. This study contributed to the literature on IS and education by incorporating context-specific factors into account.

Suggested Citation

  • Jing Zhang & Zilong Liu & Haibin Lv & Ming Jiang, 2024. "Ai in e-learning: the affordance perspective," Behaviour and Information Technology, Taylor & Francis Journals, vol. 43(15), pages 3863-3892, November.
    • Handle: RePEc:taf:tbitxx:v:43:y:2024:i:15:p:3863-3892
    DOI: 10.1080/0144929X.2023.2287660
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0144929X.2023.2287660
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0144929X.2023.2287660?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:taf:tbitxx:v:43:y:2024:i:15:p:3863-3892. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tbit .

    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.