IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v12y2025i1d10.1057_s41599-025-05775-y.html
   My bibliography  Save this article

Bridging AI literacy and UTAUT constructs: structural equation modeling of AI adoption among Chinese university students

Author

Listed:
  • Qi Ke

    (SEGi University)

  • Yunhong Gong

    (Qujing Normal University)

  • Changping Ke

    (Qujing Normal University)

Abstract

In the rapidly evolving landscape of artificial intelligence (AI), understanding the factors that influence individuals’ intentions to adopt AI technologies is crucial, particularly within educational contexts. This study addresses a critical gap in the literature by examining how AI literacy interacts with the constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT)—Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions—to shape university students’ behavioral intentions to adopt AI technologies. Data from 359 Chinese university students were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that AI Literacy is a significant predictor of Behavioral Intention to adopt AI, with Social Influence, Performance Expectancy, and Effort Expectancy serving as important mediators. Notably, Facilitating Conditions did not have a significant effect on Behavioral Intention in this context. The results underscore the importance of enhancing AI Literacy among university students to foster positive adoption intentions, particularly through social and expectancy-related factors, providing practical implications for educators and policymakers aiming to promote AI integration in higher education.

Suggested Citation

  • Qi Ke & Yunhong Gong & Changping Ke, 2025. "Bridging AI literacy and UTAUT constructs: structural equation modeling of AI adoption among Chinese university students," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-13, December.
    • Handle: RePEc:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-05775-y
    DOI: 10.1057/s41599-025-05775-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-025-05775-y
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-025-05775-y?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

    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:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-05775-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.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.