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Open AccessArticle
Exploring Generation Z’s Acceptance of Artificial Intelligence in Higher Education: A TAM and UTAUT-Based PLS-SEM and Cluster Analysis
by
Réka Koteczki
Réka Koteczki *
and
Boglárka Eisinger Balassa
Boglárka Eisinger Balassa
Vehicle Industry Research Center, Széchenyi István University, 1. Egyetem tér, 9026 Győr, Hungary
*
Author to whom correspondence should be addressed.
Educ. Sci. 2025, 15(8), 1044; https://doi.org/10.3390/educsci15081044 (registering DOI)
Submission received: 2 July 2025
/
Revised: 7 August 2025
/
Accepted: 13 August 2025
/
Published: 14 August 2025
Abstract
In recent years, the rapid growth of artificial intelligence (AI) has significantly transformed higher education, particularly among Generation Z students who are more open to new technologies. Tools such as ChatGPT are increasingly being used for learning, yet empirical research on their acceptance, especially in Hungary, is limited. This study aims to explore the psychological, technological, and social factors that influence the acceptance of AI among Hungarian university students and to identify different user groups based on their attitudes. The methodological novelty lies in combining two approaches: partial least-squares structural equation modelling (PLS-SEM) and cluster analysis. The survey, based on the TAM and UTAUT models, involved 302 Hungarian students and examined six dimensions of AI acceptance: perceived usefulness, ease of use, attitude, social influence, enjoyment and behavioural intention. The PLS-SEM results show that enjoyment (β = 0.605) is the strongest predictor of the intention to use AI, followed by usefulness (β = 0.167). All other factors also had significant effects. Cluster analysis revealed four groups: AI sceptics, moderately open users, positive acceptors, and AI innovators. The findings highlight that the acceptance of AI is shaped not only by functionality but also by user experience. Educational institutions should, therefore, provide enjoyable and user-friendly AI tools and tailor support to students’ attitude profiles.
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MDPI and ACS Style
Koteczki, R.; Balassa, B.E.
Exploring Generation Z’s Acceptance of Artificial Intelligence in Higher Education: A TAM and UTAUT-Based PLS-SEM and Cluster Analysis. Educ. Sci. 2025, 15, 1044.
https://doi.org/10.3390/educsci15081044
AMA Style
Koteczki R, Balassa BE.
Exploring Generation Z’s Acceptance of Artificial Intelligence in Higher Education: A TAM and UTAUT-Based PLS-SEM and Cluster Analysis. Education Sciences. 2025; 15(8):1044.
https://doi.org/10.3390/educsci15081044
Chicago/Turabian Style
Koteczki, Réka, and Boglárka Eisinger Balassa.
2025. "Exploring Generation Z’s Acceptance of Artificial Intelligence in Higher Education: A TAM and UTAUT-Based PLS-SEM and Cluster Analysis" Education Sciences 15, no. 8: 1044.
https://doi.org/10.3390/educsci15081044
APA Style
Koteczki, R., & Balassa, B. E.
(2025). Exploring Generation Z’s Acceptance of Artificial Intelligence in Higher Education: A TAM and UTAUT-Based PLS-SEM and Cluster Analysis. Education Sciences, 15(8), 1044.
https://doi.org/10.3390/educsci15081044
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