IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6239-622-7_35.html

Adoption of AI Tools for Learning: A Tpb-Tam Integrated Model with FOMO as a Moderator- A Case Study at Hanoi University of Science and Technology (HUST)

In: Proceedings of the International Conference on Emerging Challenges: Business Dynamics in Disruptive Economy (ICECH 2025)

Author

Listed:
  • Nguyen Thanh Huong

    (Hanoi University of Science and Technology, Faculty of Management, School of Economics and Management)

  • Tran Kim Hao

    (Hanoi University of Science and Technology, Faculty of Management, School of Economics and Management)

  • Truong Chu Tra My

    (Hanoi University of Science and Technology, Faculty of Management, School of Economics and Management)

  • Nguyen Ngoc Lien

    (Hanoi University of Science and Technology, Faculty of Management, School of Economics and Management)

  • Tran Pham Ha Phuong

    (Hanoi University of Science and Technology, Faculty of Management, School of Economics and Management)

  • Ha Do Anh Tu

    (Faculty of Mathematics and Informatics Hanoi University of Science and Technology)

Abstract

Research purpose: This study examines the behavioral intention and actual usage of AI-powered learning tools among university students by integrating the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), with Fear of Missing Out (FOMO) included as a moderating factor. Research motivation: While AI tools are increasingly adopted in education, there is limited understanding of how behavioral and technological factors jointly influence their use, especially in the Vietnamese higher education context. This research addresses this gap, focusing on Hanoi University of Science and Technology (HUST), a leading institution in science and technology education in Vietnam. Research design, approach, and method: Data were collected from 409 undergraduate students through a structured survey. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the proposed hypotheses. Main findings: The results indicate that perceived behavioral control, subjective norms, and attitude toward AI tools significantly predict students’ behavioral intention, whereas perceived enjoyment and computer self-efficacy do not. Behavioral intention positively influences actual usage, and FOMO strengthens the relationship between intention and behavior. Practical/managerial implications: The findings highlight the dominance of utilitarian over hedonic motivations in AI adoption for learning. Educators, universities, and AI developers should prioritize functionality, accessibility, and social influence factors over enjoyment to enhance technology adoption in educational settings.

Suggested Citation

  • Nguyen Thanh Huong & Tran Kim Hao & Truong Chu Tra My & Nguyen Ngoc Lien & Tran Pham Ha Phuong & Ha Do Anh Tu, 2026. "Adoption of AI Tools for Learning: A Tpb-Tam Integrated Model with FOMO as a Moderator- A Case Study at Hanoi University of Science and Technology (HUST)," Advances in Economics, Business and Management Research, in: Nguyen Danh Nguyen & Pham Thi Kim Ngoc (ed.), Proceedings of the International Conference on Emerging Challenges: Business Dynamics in Disruptive Economy (ICECH 2025), pages 569-580, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6239-622-7_35
    DOI: 10.2991/978-94-6239-622-7_35
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:spr:advbcp:978-94-6239-622-7_35. 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: http://www.springer.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.