Investigating Teachers' Readiness for Revolutionizing Education with Artificial Intelligence: Private School Teachers as an Example
DOI:
https://doi.org/10.51454/jet.v7i2.938Keywords:
Education, Teacher's Readiness, Technology Acceptance, AI IntegrationAbstract
Artificial intelligence (AI) is transforming education, yet empirical research on educators' readiness to develop in regions such as the Kurdistan Region of Iraq (KRI) remains scarce. To address this gap, this quantitative cross-sectional study investigates private school teachers’ readiness to integrate AI by synthesizing the Technology Acceptance Model (TAM) and Teacher Self-Efficacy (TSE) frameworks. Data was collected via a purposive sample of KRI teachers (N=107). Readiness was measured across three dimensions: knowledge, practicality, and ethics. Construct validity was established using Confirmatory Factor Analysis (CFA), followed by multiple linear regression. Results revealed that while teachers possess high conceptual AI knowledge, they exhibit significant hesitation toward practical, high-stakes implementation. Crucially, the inferential analysis yielded a novel finding: theoretical pedagogical knowledge (= 0.506, < .001), rather than practical technical self-efficacy, significantly predicts teachers' ethical readiness. This study makes a vital contribution to the literature by demonstrating that, to overcome ethical implementation barriers in developing educational contexts, institutional policy must pivot from providing basic technical exposure to delivering rigorous, conceptual AI pedagogical training.
Downloads
References
Balaskas, S., Panagiotarou, A., & Riggas, C. (2025). Determinants of ChatGPT adoption intention in higher education: Expanding on TAM with the mediating roles of trust and risk. Information, 16(2), 82. https://doi.org/10.3390/info16020082
Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman and Company.
Bautista, A., Estrada, C., Jaravata, A. M., Mangaser, L. M., Narag, F., Soquila, R., & Asuncion, R. J. (2024). Preservice teachers' readiness towards integrating AI-based tools in education: A TPACK approach. Educational Process: International Journal, 13(3), 40-68. https://doi.org/10.22521/edupij.2024.133.3
Celik, I. (2023). Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior, 138, 107468. https://doi.org/10.1016/j.chb.2022.107468
Chiu, T. K. F. (2023). The impact of Generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 31(1), 1-17. https://doi.org/10.1080/10494820.2023.2253861
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228-239. https://doi.org/10.1080/14703297.2023.2190148
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
De Guzman, M. A. G., Tenedero, P. P. P., Gapas, W. G. A., & Deabanico, A. M. (2024). AI anxiety and readiness of English language teachers and students: A Philippine university case study. Asian Journal of English Language Studies, 12(2), 1-26. https://doi.org/10.59960/12.2.a1
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(4), 460-474. https://doi.org/10.1080/14703297.2023.2195846
Göçen, A., & Aydemir, F. (2020). Artificial intelligence in education and schools. Research on Education and Media, 12(1), 13-21. https://doi.org/10.2478/rem-2020-0003
Habib, M. U., Sattar, A., Iqbal, M. J., & Saleem, S. (2025). AI driven tutoring vs. human teachers examining the on student teacher relationship. Review of Applied Management and Social Sciences, 8(1), 363-374. https://doi.org/10.47067/ramss.v8i1.466
Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542-570. https://doi.org/10.1111/ejed.12533
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., ... & Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32(3), 504-526. https://doi.org/10.1007/s40593-021-00239-1
Howlader, M. H., Tohan, M. M., Zaman, S., Chanda, S. K., Jiaxin, G., & Rahman, M. A. (2025). Factors influencing the acceptance and usage of ChatGPT as an emerging learning tool among higher education students in Bangladesh: A structural equation modeling. Cogent Education, 12(1), 2504224. https://doi.org/10.1080/2331186X.2025.2504224
Kowalska-Pyzalska, A. (2023). Diffusion of innovative energy services: Consumers' acceptance and willingness to pay. Elsevier.
Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410
Maddux, J. E. (Ed.). (2013). Self-efficacy, adaptation, and adjustment: Theory, research, and application. Springer Science & Business Media.
Manrique, P. C. J., & Palomares, N. R. (2024). Embracing the future: Exploring teachers perspective and readiness for integrating artificial intelligence (AI) in mathematics classroom in selected public and private senior high school. Ignatian International Journal for Multidisciplinary Research, 2(5), 2654-2675. https://doi.org/10.5281/zenodo.11124430
Moorhouse, B. L. (2024). Beginning and first-year language teachers’ readiness for the generative AI age. Computers and Education: Artificial Intelligence, 6, 100201. https://doi.org/10.1016/j.caeai.2023.100201
OECD. (2021). OECD Digital Education Outlook 2021: Pushing the frontiers with artificial intelligence, blockchain and robots. OECD Publishing. https://doi.org/10.1787/589b283f-en
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. UNESCO.
Reuben, B., & Kabilan, M. K. (2024). Assessment of university lecturers' readiness to adopt artificial intelligence (AI) technology in North-East of Nigeria. International Journal of Advanced Research in Education and Society, 6(2), 482-490.https://doi.org/10.55057/ijares.2024.6.2.41
Sawant, D. G., & Piraji, P. N. (2024). Technology-assisted language learning and readiness of teachers of English in AI era. In Proceedings of Exploring Languages and Literatures for Evolving Pedagogical Practices. Royal Global University.
Selwyn, N. (2024). On the limits of artificial intelligence (AI) in education. Nordisk tidsskrift for pedagogikk og kritikk, 10(1), 3-14. https://doi.org/10.23865/ntpk.v10.5699
Sumandal, A. H. (2023). Teachers’ self-efficacy with artificial intelligence (AI) based educational tools. Ignatian International Journal for Multidisciplinary Research, 1(1), 1-10. https://doi.org/10.5281/zenodo.8310052
Vaidya, S. D., & Seetharaman, P. (2008). Beyond technology acceptance models: A case of collaborative technology. Working Paper Series, Indian Institute of Management.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Parween Yaqub Saadi, Shamal Abdullah Abdullah, Karwan Kakabra Kakamad
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
