International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

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 Volume 12, Issue 12 (December 2025), Pages: 31-43

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 Original Research Paper

Adoption of generative AI in higher education: Understanding usage through a technology acceptance model

 Author(s): 

 Hanan Alotaibi 1, *, Asmaa Alayed 2

 Affiliation(s):

  1Department of Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
  2College of Computing, Umm Al-Qura University, Makkah, Saudi Arabia

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    Full Text - PDF

 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0000-0002-0238-9051

 Digital Object Identifier (DOI)

  https://doi.org/10.21833/ijaas.2025.12.004

 Abstract

The aim of this study is to examine the adoption of Generative AI (GenAI) tools among faculty in higher education using a revised Unified Theory of Acceptance and Use of Technology (UTAUT) model. A quantitative survey was conducted with 244 faculty members from eight Saudi universities, and the data were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS. The results show that Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), and Behavioral Intention (BI) significantly influence the adoption of GenAI tools. Among these, PE and EE had the strongest positive impact on BI, stressing the importance of user-friendly design and faculty training, while SI had a weaker but still meaningful effect. Gender and academic position were also found to moderate adoption behaviors, indicating differences across faculty groups. This study extends the UTAUT model by introducing new moderating factors and provides empirical evidence from Saudi Arabia. It further recommends intuitive system design, technical support, training, and the development of an AI-friendly academic culture to promote effective integration of GenAI in higher education.

 © 2025 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Generative AI, Technology adoption, Higher education, UTAUT model, Faculty behavior

 Article history

 Received 4 July 2025, Received in revised form 27 October 2025, Accepted 11 November 2025

 Acknowledgment

The authors extend sincere gratitude to all participants who contributed to this study by completing the questionnaire. Their time, effort, and thoughtful responses provided essential data and valuable perspectives that greatly enhanced the quality and validity of this research. 

 Compliance with ethical standards

 Ethical considerations

This study complied with ethical research standards involving human participants. Informed consent was obtained from all participants before data collection. Participation was voluntary, responses were anonymous, and no personal identifying information was collected. All data were treated with strict confidentiality and used solely for academic purposes.

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Alotaibi H and Alayed A (2025). Adoption of generative AI in higher education: Understanding usage through a technology acceptance model. International Journal of Advanced and Applied Sciences, 12(12): 31-43

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 Figures

  Fig. 1  Fig. 2 

 Tables

  Table 1  Table 2  Table 3  Table 4  Table 5 

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