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Abstract
This study investigates the effects of generative artificial intelligence (GenAI) tools on the professional competency development of higher education teachers. A mixed-methods design was employed, combining a quasi-experimental approach with semi-structured interviews. A total of 186 university teachers from Uzbekistan participated in the study. Results indicated that GenAI integration significantly enhanced teachers' Technological Pedagogical Content Knowledge (TPACK) scores (p < .001), with notable improvements in digital competencies and self-efficacy levels. Qualitative data revealed that GenAI tools facilitated lesson planning, personalized instruction, and assessment optimization. However, concerns regarding ethical issues, academic integrity, and over-reliance on AI were also identified. The study proposes a GenAI-TPACK pedagogical model and provides practical recommendations for teacher preparation programs in higher education contexts.
References
Atlas, S. (2023). ChatGPT for higher education and professional development: A guide to conversational AI. DigitalCommons@URI.
Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman and Company.
Basilotta-Gómez-Pablos, V., Matarranz, M., Casado-Aranda, L. A., & Otto, A. (2022). Teachers' digital competencies in higher education: A systematic literature review. International Journal of Educational Technology in Higher Education, 19(1), 1-16. https://doi.org/10.1186/s41239-021-00312-8
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
Cabero-Almenara, J., Barroso-Osuna, J., Rodríguez-Gallego, M., & Palacios-Rodríguez, A. (2020). La competencia digital docente: El caso de las universidades andaluzas. Aula Abierta, 49(4), 363-372. https://doi.org/10.17811/rifie.49.4.2020.363-372
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
Chan, C. K. Y., & Hu, W. (2023). Students' voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), 1-18. https://doi.org/10.1186/s41239-023-00411-8
Chiu, T. K. F. (2024). The impact of generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and midjourney. Interactive Learning Environments, 32(10), 6187-6203. https://doi.org/10.1080/10494820.2023.2253861
Chiu, T. K. F., & Rospigliosi, P. (2025). Developing intelligent-TPACK (I-TPACK) framework from unpacking AI literacy and competency: Implementation strategies and future research direction. Interactive Learning Environments. https://doi.org/10.1080/10494820.2025.2545053
Creswell, J. W., & Clark, V. L. P. (2017). Designing and conducting mixed methods research (3rd ed.). Sage Publications.
Dille, K. B., & Røkenes, F. M. (2021). Teachers' professional development in formal online communities: A scoping review. Teaching and Teacher Education, 105, 103431. https://doi.org/10.1016/j.tate.2021.103431
Harris, L., Chen, X., & Williams, J. (2024). ChatGPT adoption in higher education: A study of faculty generation cohort, self-efficacy, and innovativeness. Technology, Knowledge and Learning. https://doi.org/10.1007/s10758-025-09865-3
Hava, K., & Babayiğit, Ö. (2024). Exploring the relationship between teachers' competencies in AI-TPACK and digital proficiency. Education and Information Technologies, 29, 17683-17705. https://doi.org/10.1007/s10639-024-12939-x
Ivankova, N. V., & Stick, S. L. (2007). Students' persistence in a distributed doctoral program in educational leadership in higher education: A mixed methods study. Research in Higher Education, 48(1), 93-135. https://doi.org/10.1007/s11162-006-9025-4
Kim, S. (2024). Effects of AI-convergence TPACK educational program on pre-service teachers' pedagogical content knowledge. Computers & Education, 214, 105024. https://doi.org/10.1016/j.compedu.2024.105024
Kim, S., & Kwon, O. (2023). Identifying AI competencies within the TPACK framework for K-12 education. Educational Technology & Society, 26(3), 45-59.
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(2), 537-550. https://doi.org/10.1177/00336882231162868
Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. International Journal of Management Education, 21(2), 100790. https://doi.org/10.1016/j.ijme.2023.100790
Lu, J., Zheng, R., Gong, Z., & Huifen, X. (2024). Supporting teachers' professional development with generative AI: The effects on higher order thinking and self-efficacy. British Journal of Educational Technology, 55(4), 1523-1541. https://doi.org/10.1111/bjet.13412
Mai, D. T. T., Da, C. V., & Hanh, N. V. (2024). The use of ChatGPT in teaching and learning: A systematic review through SWOT analysis approach. Frontiers in Education, 9, 1328769. https://doi.org/10.3389/feduc.2024.1328769
Mante, D. A., Opoku, O. G., & Chineta, O. M. (2025). Examining the moderating role of generative AI in advancing teachers' professional competencies through self-directed learning: Evidence from Ghana. Interactive Learning Environments. https://doi.org/10.1080/10494820.2025.2556811
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
Moorhouse, B. L. (2024). Beginning and first-year language teachers' readiness for the generative AI age. Computers and Education: Artificial Intelligence, 6, 100211. https://doi.org/10.1016/j.caeai.2024.100211
Moorhouse, B. L., & Kohnke, L. (2024). Developing language teachers' professional generative AI competence: An intervention study in an initial language teacher education course. System, 124, 103376. https://doi.org/10.1016/j.system.2024.103376
Ning, Y., Zhang, C., Xu, B., Zhou, Y., & Wijaya, T. T. (2024). Teachers' AI-TPACK: Exploring the relationship between knowledge elements. Sustainability, 16(3), 978. https://doi.org/10.3390/su16030978
Qadir, J. (2023). Engineering education in the era of ChatGPT: Promise and pitfalls of generative AI for education. IEEE Global Engineering Education Conference (EDUCON), 1-9. https://doi.org/10.1109/EDUCON54358.2023.10125121
Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological pedagogical content knowledge (TPACK): The development and validation of an assessment instrument for preservice teachers. Journal of Research on Technology in Education, 42(2), 123-149. https://doi.org/10.1080/15391523.2009.10782544
Smolikevych, N. (2019). Teacher professional competencies. Scientific Research and Development: Modern Communication Science, 8(3), 135-139.
Tondeur, J., Howard, S., Van Zanten, M., Van Rooij, S. W., & Scherer, R. (2023). The HeDiCom framework: Higher Education teachers' digital competencies for the future. Educational Technology Research and Development, 71, 33-53. https://doi.org/10.1007/s11423-023-10193-5
Tschannen-Moran, M., & Hoy, A. W. (2001). Teacher efficacy: Capturing an elusive construct. Teaching and Teacher Education, 17(7), 783-805. https://doi.org/10.1016/S0742-051X(01)00036-1
Wang, Y., Liu, C., & Tu, Y. F. (2023). Factors affecting the adoption of AI-based applications in higher education. Educational Technology & Society, 26(1), 116-131.
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