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)

Nguyen Thanh Huong (), Tran Kim Hao, Truong Chu Tra My, Nguyen Ngoc Lien, Tran Pham Ha Phuong and Ha Do Anh Tu
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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

A chapter in Proceedings of the International Conference on Emerging Challenges: Business Dynamics in Disruptive Economy (ICECH 2025), 2026, pp 569-580 from Springer

Abstract: 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.

Keywords: Artificial intelligence (AI); TAM; TPB; Fear of missing out (FOMO); AI tool adoption; higher education (search for similar items in EconPapers)
Date: 2026
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DOI: 10.2991/978-94-6239-622-7_35

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