Factors affecting generative artificial intelligence, such as ChatGPT , use in higher education: An application of technology acceptance model
Abstract
The adoption of generative artificial intelligence (GAI) tools, such as ChatGPT, in higher education presents numerous opportunities and challenges. The use of GAI technologies in various fields, including education, has accelerated as technology develops. The widely used language model ChatGPT, developed by OpenAI, has become progressively more important, especially in the field of education. This study employs the technology acceptance model to investigate the factors influencing the employment of ChatGPT within the higher education sector of Pakistan. This study employed the PLS‐SEM method for probing data collected from 368 Pakistani university students. The findings indicate that ChatGPT trust positively mediates the affiliation between ChatGPT self‐efficacy, ChatGPT actual use, ChatGPT use for information and ChatGPT use for interaction. Further, ChatGPT usefulness and ChatGPT ease of use significantly moderate the association between ChatGPT self‐efficacy and ChatGPT trust. Educators must encourage students to use ChatGPT safely to preserve their critical thinking, problem‐solving abilities and creativity during assessments. This study contributes to understanding generative AI tools such as ChatGPT that are used in educational settings and provides insights for administrators and policymakers aiming to implement these technologies effectively.
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According to the Technology Acceptance Model (Shahzad et al., 2024), the advocacy for institutional policy by trusted academics has generally been shown to be a successful strategy for the adoption of technology by staff and students (Faden et al., 2002).
“According to the Technology Acceptance Model (Shahzad et al., 2024), the advocacy for institutional policy by trusted academics has generally been shown to be a successful strategy for the adoption of technology by staff and students (Faden et al., 2002).”
From A university framework for the responsible use of generative AI in research (2026) · cites this paper as Shahzad et al., 2024
Cites
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194 · see citing works
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · see citing works
Assessing measurement model quality in PLS-SEM using confirmatory composite analysis
Hair, J. F., Howard, M. C., & Nitzl, C. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2019.11.069 · Cited by 5,446 · see citing works
Ray, P. P. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.04.003 · Cited by 2,463 · see citing works
Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023) · The International Journal of Management Education · doi:10.1016/j.ijme.2023.100790 · Cited by 1,261 · see citing works
Al-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A., & Habibi, A. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11816-3 · Cited by 637 · see citing works
Strzelecki, A. (2024) · Innovative Higher Education · doi:10.1007/s10755-023-09686-1 · Cited by 477 · see citing works
Use of ChatGPT in academia: Academic integrity hangs in the balance
Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102370 · Cited by 394 · see citing works
ChatGPT awareness, acceptance, and adoption in higher education: The role of trust as a cornerstone
Shahzad, M. F., Xu, S., & Javed, I. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00478-x · Cited by 274 · see citing works
Self-citationShahzad, M. F., Xu, S., & Zahid, H. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-12949-9 · Cited by 204 · see citing works
Self-citationNiu, B., & Mvondo, G. F. N. (2024) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2023.103562 · Cited by 178 · see citing works
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Ursavaş, Ö. F., Yalçın, Y., İslamoğlu, H., Bakır-Yalçın, E., & Cukurova, M. (2025) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-025-00535-z · Cited by 69 · see citing works
Pellas, N. (2025) · Education Sciences · doi:10.3390/educsci15010102 · Cited by 56 · see citing works
A university framework for the responsible use of generative AI in research
Smith, S. M., Tate, M., Freeman, K., Walsh, A., Ballsun-Stanton, B., & Lane, M. (2026) · Journal of Higher Education Policy and Management · doi:10.1080/1360080x.2025.2509187 · Cited by 46 · see citing works
Soleimani, S., Farrokhnia, M., van Dijk, A., & Noroozi, O. (2025) · Innovations in Education and Teaching International · doi:10.1080/14703297.2025.2530767 · Cited by 8 · see citing works
Guoan, Z., Mengting, P., & Shaobo, W. (2025) · 2025 14th International Conference on Educational and Information Technology (ICEIT) · doi:10.1109/iceit64364.2025.10975838 · Cited by 1 · see citing works
Ayanda, A. O. (2026) · International Journal of Applied Resilience and Sustainability · doi:10.70593/deepsci.0203003
- Authors
- Shahzad, M. F., Xu, S., & Asif, M.
- Affiliations
- Beijing University of Technology (CN)
- University of Education (PK)
- Corresponding author
- Xu, Shuo
- Venue
- British Educational Research Journal
- Publisher
- Wiley
- Published
- 2024-10-19
- Volume
- 51
- Issue
- 2
- Pages
- 489-513
- ISSN
- 0141-1926 (ISSN-L)
- 1469-3518
- OpenAlex
- W4403567703
- Cited by
- 103
- References
- 11
- Citations by year
- 2026: 50 · 2025: 50 · 2024: 3
- FWCI
- 38.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- British Educational Research Journal (publishedVersion)
- Funders
- National Natural Science Foundation of China (72474016, 72074014)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI, ChatGPT, technology acceptance model, higher education, university students, trust in AI, self-efficacy, perceived usefulness, perceived ease of use, artificial intelligence adoption, moderating effect, Pakistani higher education
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