The Impact of AI on Primary School Teachers' TPACK Transformation Challenges in the Chinese Education Context
Keywords:
assessment; Chinese education context; ethical concern; pedagogical transformation; TAPCK-AIAbstract
Existing research on artificial intelligence (AI) in education largely relies on general technology adoption frameworks and higher education contexts, offering limited empirical insight into AI-driven TPACK transformation in primary schools. The study aims to examine how AI use influences the interactions among technological, pedagogical, and content knowledge (TPACK) of primary school teachers and to explore teachers’ perceptions of the transformative and constraining effects of AI on pedagogical practice. A mixed-methods design was employed, combining a survey and semi-structured interviews. Survey data were collected from 500 primary school teachers across 50 schools that had implemented AI-supported instruction, while 50 teachers were purposively selected for in-depth interviews. Quantitative data were analyzed using descriptive statistics and regression; qualitative data were analyzed using thematic analysis. The survey findings indicated moderate to high levels of AI-driven TPACK, with AI-technological pedagogical knowledge emerging as the strongest predictor of integrated TPACK-AI transformation. The qualitative findings revealed that teachers perceive AI as enhancing lesson design, differentiation, and content representation, while also introducing pedagogical constraints related to ethical concerns, developmental appropriateness, and classroom management. This study extends the literature by empirically positioning AI not just as a tool to adopt, but as a pedagogical co-actor that shifts what counts as competent integration at the TPACK intersection, especially under primary-school constraints.
https://doi.org/10.26803/ijlter.25.3.5
References
Adiyono, A., Suwartono, T., Nurhayati, S., Dalimarta, F. F., & Wijayanti, O. (2025). Impact of artificial intelligence on student reliance for exam answers: A case study in IRCT Indonesia. International Journal of Learning, Teaching and Educational Research, 24(3), 519-544. https://doi.org/10.26803/ijlter.24.3.22
Arifani, Y. (2019). The application of small WhatsApp groups and the individual flipped instruction model to boost EFL learners’ mastery of collocation. Computer-Assisted Language Learning Electronic Journal, 20(1), 52-73.
Arifani, Y., Asari, S., Anwar, K., & Budianto, L. (2020). Individual or collaborative “WhatsApp" learning? A flipped classroom model of EFL writing instruction. Teaching English with Technology, 20(1), 122-139.
Ayanwale, M. A., Sanusi, I. T., Adelana, O. P., Aruleba, K. D., & Oyelere, S. S. (2022). Teachers’ readiness and intention to teach artificial intelligence in schools. Computers and Education: Artificial Intelligence, 3, 100099. https://doi.org/10.1016/j.caeai.2022.100099
Bergdahl, N., & Sjöberg, J. (2025). Attitudes, perceptions and AI self-efficacy in K-12 education. Computers and Education: Artificial Intelligence, 8, 100358. https://doi.org/10.1016/j.caeai.2024.100358
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 Behaviour, 138, 107468. https://doi.org/10.1016/j.chb.2022.107468
Chiu, T. K. F., Meng, H., Chai, C. S., King, I., Wong, S., & Yeung, Y. (2023). Creation and evaluation of a pre-tertiary AI curriculum. Computers & Education: Artificial Intelligence, 4, 100121.https://doi.org/10.1016/j.caeai.2023.100121
Collie, R. J., & Martin, A. J. (2024). Teachers’ motivation and engagement to harness generative AI for teaching and learning: The role of contextual, occupational, and background factors. Computers and Education: Artificial Intelligence, 6, 100224. https://doi.org/10.1016/j.caeai.2024.100224
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE.
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). SAGE.
Filiz, O., Kaya, M. H., & Adiguzel, T. (2025). Teachers and AI: Understanding the factors influencing AI integration in K-12 education. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13463-2
Giannakos, M. N., et al. (2024). The promise and challenges of generative AI in education. Behaviour & Information Technology. https://doi.org/10.1080/0144929X.2024.2394886
Habibi, A., Muhaimin, M., Danibao, B. K., Wibowo, Y. G., Wahyuni, S., & Octavia, A. (2023). ChatGPT in higher education learning: Acceptance and use. Computers and Education: Artificial Intelligence, 5, 100190. https://doi.org/10.1016/j.caeai.2023.100190
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modelling (PLS-SEM) (3rd ed.). SAGE.
Heine, S., & König, J. (2025). Applying artificial intelligence in teacher education: Preservice teachers’ attitudes and reflections in using ChatGPT for teaching and learning. European Journal of Teacher Education. https://doi.org/10.1080/02619768.2025.2540791
Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promise and implications for teaching. Educational Technology Research and Development, 70, 1809–1824. https://doi.org/10.1007/s11423-022-10102-9
Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: Systematic literature review. International Journal of Educational Technology in Higher Education, 20, 56. https://doi.org/10.1186/s41239-023-00426-1
Luckin, R., Cukurova, M., Kent, C., & Du Boulay, B. (2022). Empowering educators to be AI-ready. Computers & Education: Artificial Intelligence, 3, 100076. https://doi.org/10.1016/j.caeai.2022.100076
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
Mishra, P., Warr, M., & Islam, R. (2023). TPACK in the age of ChatGPT and generative AI. Journal of Digital Learning in Teacher Education, 39(4), 235–251. https://doi.org/10.1080/21532974.2023.2247480
Mishra, P., Oster, N., & Henriksen, D. (2024). Generative AI, teacher knowledge and educational research: Bridging short- and long-term perspectives. Tech Trends, 68, 205–210. https://doi.org/10.1007/s11528-024-00938-1
Moorhouse, B. L. (2024). Beginning and first-year language teachers’ readiness for the generative AI age. Computers & Education: Artificial Intelligence, 6, 100201. https://doi.org/10.1016/j.caeai.2024.100201
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
Ng, D. T. K., Wu, W., Leung, J. K. L., et al. (2024). Design and validation of the AI literacy questionnaire: The affective, behavioural, cognitive and ethical approach. British Journal of Educational Technology, 55(3), 1082–1104. https://doi.org/10.1111/bjet.13411
Prilop, C. N., Mah, D., Jacobsen, L., Hansen, R. R., Weber, K. E., & Hoya, F. (2025). Generative AI in teacher education: Educators’ perceptions of transformative potentials and the triadic nature of AI literacy explored through AI-enhanced methods. Computers & Education: Artificial Intelligence, 9, 100471. https://doi.org/10.1016/j.caeai.2025.100471
Roll, I., & Wylie, R. (2021). Evolution and revolution in AI in education. International Journal of Artificial Intelligence in Education, 31, 582–599. https://doi.org/10.1007/s40593-020-00229-3
Scherer, R., Siddiq, F., & Viveros, B. S. (2021). A meta-analysis of teachers’ technology acceptance. Educational Research Review, 33, 100376. https://doi.org/10.1016/j.edurev.2020.100376
Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. (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
Strzelecki, A. (2024). Students’ acceptance of ChatGPT in higher education: An extended unified theory of acceptance and use of technology. Innovative Higher Education, 49(2), 223–245. https://doi.org/10.1007/s10755-023-09686-1
Suryanti, S., Arifani, Y., & Sutaji, D. (2020, August). Augmented reality for integer learning: investigating its potential on students’ critical thinking. Journal of Physics: Conference Series, 1613(1), 012041). IOP Publishing.
Suryanti, S., Nusantara, T., Parta, I. N., & Irawati, S. (2022). Problem-based task in teacher training program: Mathematics teachers' beliefs and practices. Journal on Mathematics Education, 13(2), 257-274.
Wong, L.-H., & Looi, C.-K. (2024). Advancing the generative AI in education research agenda: Insights from the Asia-Pacific region. Asia Pacific Journal of Education, 44(1), 1–7. https://doi.org/10.1080/02188791.2024.2315704
Yue, M., Jong, M. S. Y., & Ng, D. T. K. (2024). Understanding K–12 teachers' technological, pedagogical, and content knowledge readiness and attitudes toward artificial intelligence education. Education and Information Technologies, 29, 19505–19536. https://doi.org/10.1007/s10639-024-12621-2
Zhai, X., Wang, M., & Ghani, U. (2022). AI education for K–12: A systematic review. Computers and Education: Artificial Intelligence, 3, 100076. https://doi.org/10.1016/j.caeai.2022.100076
Zhou, X., Li, Y., Chai, C. S., & Chiu, T. K. F. (2025). Defining, enhancing, and assessing artificial intelligence literacy and competency in K-12 education from a systematic review. Interactive Learning Environments, 1–23. https://doi.org/10.1080/10494820.2025.2487538
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Copyright (c) 2026 Chaowei Jiang, Tassanee Laknapichonchat, Chatchai Rakthin, Sri Suryanti

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