Basic School Teachers’ Behavioural Intentions to Use ChatGPT: A Unified Theory of Acceptance and Use of Technology (UTAUT) Perspective
DOI:
https://doi.org/10.53103/cjess.v6i6.579Keywords:
ChatGPT, Teacher Education, Artificial Intelligence, Behavioural IntentionsAbstract
Artificial Intelligence systems such as ChatGPT have brought so many implications to teachers’ classroom practices in the digital age. This requires scientific investigations to appreciate the factors that predict teachers’ behavioural intention to use ChatGPT at the pre-tertiary levels of the Ghana’s educational system. This study examined the topic by collecting data from 94 basic school teachers across kindergarten, primary, and high school grades. Data analysis was done using SPSS and SmartPLS. Results of the study show that effort expectancy and social influence did not predict teachers’ intention to use ChatGPT. Contrary, performance expectancy and facilitating conditions predicted their intention to use it. The study therefore recommended to stakeholders to provide the requisite education and curricular modifications to facilitate a responsible and ethical integration of ChatGPT into their pedagogical tools.
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References
Abdul-Gafaar, S., Nyaaba, R. A., Anechama, R., & Anhwere, D. K. (2024). Exploring cognitive dissonance among undergraduate students at the University of Cape Coast: Investigating resistance and acceptance in the adoption of technology. Creative Education, 15, 2499-2520. https://doi.org/10.4236/ce.2024.1512152
Adam, W., Pratama, I., P. Y., Handika, I., & Qudratuddarsi, H. (2025). Chatgpt acceptance and use for generation z pre-service science teacher: A survey study. Afeksi: Jurnal Penelitian dan Evaluasi Pendidikan, 6(4), 1-14. https://afeksi.id/jurnal/index.php/afeksi
Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), ep429. https://doi.org/10.30935/cedtech/13152
Antwi, B. O., Agyapong, D., & Owusu, D. (2026). Supply Chain Finance Strategies, Artificial Intelligence Adoption, and Sustainable Performance: The Mediating Role of Supply Chain Resilience in Ghanaian Manufacturing. https://ssrn.com/abstract=7541471
Arkorful V, Arthur F, Opoku E, Ameen A, Salifu I, Nortey SA, et al. (2026) AI literacy among basic school teachers in Ghana: A structural equation modelling analysis. PLoS One, 21(4), e0347117. https://doi.org/10.1371/journal.pone.0347117
Arthur, F., Boateng, E., Opoku, E., Gyedu, F. O., Asare-Bediako, S., Quayson, E., Salifu, I., Attom, E. R., & Nortey, S. A. (2026). Exploring artificial intelligence anxiety among basic school teachers in Ghana. Sage Journals, 16(1), 1-20. https://doi.org/10.1177/2158244025140713
Arthur, F., Gyedu, F. O., Quayson, E., Quaye, S. A., Boateng, E., Inkoom, M., Nortey, S. A., & Frempong, D. (2026). What drives preservice teachers’ use of generative AI as instructional media? A structural and configurational analysis. Frontiers in Artificial Intelligence, 9, 1853130. https://doi.org/10.3389/frai.2026.1853130
Ayubian, S., Chávez, G. A., Wiafe, E., Shahsavari, V., Khamisani, N., Quidwai, N. S., S., Simmons, D., Rios, A., Sadique, F., & Clark, J. S. (2026). Teachers and generative ai: a systematic review of adoption, competence, professional development, and socio-technical experiences. Education Sciences, 16, 1501. https://doi.org/10.3390/educsci16091501
Barkouk, A., Ouerdi, L., Jallal, M., Serhier, Z., & Othmani, B. (2026). Practices and attitudes regarding MOOCs and artificial intelligence use among medical students in Morocco. Canadian Journal of Educational and Social Studies, 6(5), 170-185. https://doi.org/10.53103/cjess.v6i5.573
Chen, P., Lee, H., Huang, Y., & Wu, T. (2026). Unpacking the heterogeneity of pre-service teachers’ ChatGPT acceptance: A latent profile analysis across STEM and non-STEM disciplines. International Journal of STEM Education, 13, 33. https://doi.org/10.1186/s40594-026-00634-x
Cordero, J., Torres Zambrano, J., & Cordero-Castillo, A. (2025). Integration of Generative Artificial Intelligence in Higher Education: Best Practices. Education Sciences, 15(1), 32. https://doi.org/10.3390/educsci15010032
Dake, D. K., Gbagbo, F. Y. (2026). ChatGPT’s benefits, acceptance, and ethical challenges for teaching and learning in key African countries: A systematic review of literature from 2022 to 2024. Discover Education, 5, 62. https://doi.org/10.1007/s44217-025-01074-5
Dempere J., Modugu K., Hesham, A. & Ramasamy, L. K. (2023). The impact of ChatGPT on higher education. Front. Educ. 8, 1206936. https://doi.org?10.3389/feduc.2023.1206936
Farinosi, M., & Melchior, C. (2025). To adopt or to ban? Student perceptions and use of generative AI in higher education. Humanities and Social Sciences Communications, 12, 1684. https://doi.org/10.1057/s41599-025-05982-7
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurements error. Journal of Marketing, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Hair, J. F., Hult, G. T. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd edn.). Sage Publications, Inc.
Han, A., Zhou, X., Cai, Z., Han, S., Ko, R., & Corrigan, S. (2024). Teachers, parents, and students’ perspectives on integrating generative ai into elementary literacy education.
Harrison, L. M., Hurd, E., & Brinegar, K. M. (2023). Critical race theory, books, and ChatGPT: Moving from a ban culture in education to a culture of restoration. Middle School Journal, 54(3), 2-4, https://doi.org/10.1080/00940771.2023.2189862
Jauhiainen, J. S., & Guerra, A. G. (2023). Generative AI and ChatGPT in School Children’s Education: Evidence from a School Lesson. Sustainability, 15, 14025. https://doi.org/10.3390/su151814025
Khoza, N. G., & van der Walt, F. (2025). A systematic review on AI-enhanced pedagogies in higher education in the Global South. Front. Educ. 10, 1667884. https://doi.org/doi:10.3389/feduc.2025.1667884
Kishore, S., Hong, Y., Nguyen, A., & Qutab, S. (2023). Should ChatGPT be banned at schools? Organizing visions for generative artificial intelligence (AI) in education. ICIS Proceedings, 1-26.
Köse, N., & Kudratovna, K. M. (2026). Determinants of ChatGPT acceptance among pre-service English language teaching students in Uzbekistan. Discover Education, 5, 315. https://doi.org/10.1007/s44217-026-01169-7
Manzi, W. I., & Modise, M. A. (2026). Accounting teachers' voices on the integration of ChatGPT in Accounting Education: A case of South Africa. Journal of Education and Learning Technology (JELT), 7(2), 321-335. https://doi.org/10.38159/jelt.20267221
Modiba, F. S., van den Berg, A., & Mago, S. (2025). Opportunities and challenges of generative artificial intelligence supporting research in African classrooms. South African Journal of Higher Education, 39(3), 173-193. https://dx.doi.org/10.20853/39-3-6272
Naznin, K., AlMahmud, A., Nguyen, M. T., & Chua, C. (2025). ChatGPT integration in higher education for personalized learning, academic writing, and coding tasks: A systematic review. Computers, 14, 53. https://doi.org/10.3390/computers14020053
Nguyen, A., Kremantzis, M., Essien, A., Petrounias, I., & Hosseini, S. (2024). Enhancing student engagement through artificial intelligence (AI): Understanding the basics, opportunities, and challenges. Journal of University Teaching and Learning Practice, 21(16).
Ofori, H. O., & Debreli, E. (2026). Psychological mechanisms of AI integration in ESL teaching: Teacher self-efficacy and classroom practice in Ghanaian senior high schools. Front. Psychol., 17, 1851325. https://doi.org/10.3389/fpsyg.2026.1851325
Ogugua, D. Yoon, S. N., & Lee, D. (2023). Academic integrity in a digital era: Should the use of ChatGPT be banned in schools? Global Business & Finance Review (GBFR), 8(7), 1-10. https://doi.org/10.17549/gbfr.2023.28.7.1
Örnek, F., Issah, M., Al-Mutawah, M. A., Abdel-Hameed, F. S. M., Alaam, S., & Örnek, B., N. (2026). Pre- service mathematics and science teacher’s perceptions of ChatGPT as future educators. Discover Education, 5, 534. https://doi.org/10.1007/s44217-026-01567-x
Peláez-Sánchez, I. C., Velarde-Camaqui, D. & Glasserman-Morales, L. D. (2024). The impact of large language models on higher education: Exploring the connection between AI and Education 4.0. Front. Educ., 9, 1392091. https://doi.org/0.3389/feduc.2024.1392091
Salifu, I., Arthur, F., Acquah, B. Y. S., Opoku, E., Nortey, S. A., & Boateng, E. (2025). Exploring graduate students’ use of generative artificial intelligence in Ghana: Insights from an extended UTAUT2 model, PLS SEM, IPMA and fsQCA. Discover Education, 4, 305. https://doi.org/10.1007/s44217-025-00603-6
Sarfo, J. O., Tachie-Donkor, G., Aggrey, E. K., & Mordi, P. (2024). Attitudes, perceptions, and challenges towards artificial intelligence adoption in Ghana and Nigeria: A systematic review with a narrative synthesis attitudes, perceptions, and challenges towards artificial intelligence. International Journal of Media and Information Literacy, 9(2), 1-16. https://doi.org/10.13187/ijmil.2024.2.437
Senechal, J., Ekholm, E., Aljudaibi, S., Strawderman, M., & Parthemos, C. (2023). Balancing the benefits and risks of large language AI models in K12 public schools. Metropolitan Educational Research Consortium, 1-13.
Twum, K. K., & Yalley, A. A. (2024). Marketing analytics acceptance: Using UTAUT, perceived trust, personal innovativeness in information technology and user attitude. Journal of Science and Technology Policy Management, 16(7), 1271-1295. https://doi.org/10.1108/JSTPM-01-2022-0001
Uǧraş, H., Uǧraş, M., Papadakis, S., & Kalogiannakis, M (2024). ChatGPT-Supported Education in Primary Schools: The Potential of ChatGPT for Sustainable Practices. Sustainability, 16, 9855. https://doi.org/10.3390/su16229855
Venkatesh, V., Morris, M. G., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://www.jstor.org/stable/30036540
World Bank. (2026). Education and skills working paper: Costing AI use in education in low-and middle-income countries. International Bank for Reconstruction and Development, World Bank.
Xiao, P., Chen, Y., & Bao, W. (2023). Waiting, banning, and embracing: an empirical analysis of adapting policies for generative ai in higher education. 1-33. CHI, 24, 1-10. https://doi.org/10.1145/3613904.3642438
Xie, Y. (2025). Research on the application of artificial intelligence technology in primary school English listening and speaking instruction. SHS Web Conferences, 222, 01007. https://doi.org/10.1051/shsconf/202522201007
Yarboi, P. Y., Adu-Manu, K. S., Amponsah, S., Oheneba-Sakyi, Y., & Barimah, A. (2026). A systematic review of ethical integration of generative ai in higher education. Education Sciences, 16, 1016. https://doi.org/10.3390/educsci16071016
Yu, H. (2023). Reflection on whether Chat GPT should be banned by academia from the perspective of education and teaching. Front. Psychol., 14, 1181712. https://doi.org?10.3389/fpsyg.2023.1181712
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Copyright (c) 2026 Kassim File Dangor, Peter Awonnatemi Agbedemnab
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