IDEAS home Printed from https://ideas.repec.org/a/taf/tbitxx/v44y2025i7p1306-1319.html
   My bibliography  Save this article

The impact of gamified interaction on mobile learning APP users’ learning performance: the moderating effect of users’ learning style

Author

Listed:
  • Jun Fan
  • Zhen Wang

Abstract

This study investigates the effect of gamified interaction through mobile learning applications (APPs) to optimise users’ learning performance. This paper draws on social presence theory and social support theory to construct a model of gamified interaction. We conducted a survey questionnaire with a sample of 368 users from English learning APPs and used structural equation modelling to assess their learning performance. Our results reveal that not all dimensions of gamified interaction enhance learning performance directly. Some dimensions of gamified interaction can optimise users’ social presence and perceived social support, which in turn, improve users’ learning performance. In addition, learning style can influence users’ sense of social presence and perceived social support when they are facing the same gamified interactions. This study highlights the important determinants influencing users’ learning performance in the context of gamified mobile learning by incorporating three overlooked factors, gamified interaction, users’ learning experience and learning style. For managers of those learning APPs who want to attract more users it is advisable to carry out various gamified interactions through differentiated gamified tools based on users’ learning style, which can meet users’ psychological needs and thereby enhance effective learning experience.

Suggested Citation

  • Jun Fan & Zhen Wang, 2025. "The impact of gamified interaction on mobile learning APP users’ learning performance: the moderating effect of users’ learning style," Behaviour and Information Technology, Taylor & Francis Journals, vol. 44(7), pages 1306-1319, April.
  • Handle: RePEc:taf:tbitxx:v:44:y:2025:i:7:p:1306-1319
    DOI: 10.1080/0144929X.2020.1787516
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0144929X.2020.1787516
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/0144929X.2020.1787516?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:44:y:2025:i:7:p:1306-1319. 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.