Research Article

Integrating Artificial Intelligence Literacy into Mathematics Teacher Education: an Integrative Conceptual Framework for AI-Supported Classroom Practice

1 Isa Kaita College of Education, Dutsin-Ma, Katsina State
2 Department of Mathematics and Computer Science Education, Umaru Musa Yar’adua University, Katsina, Katsina State, Nigeria
3 Department of Mathematics, Eranova University, Abuja, Nigeria
* Corresponding author: shakiss4real@gmail.com
Published: Aug, 2026
Pages: 158–167
Views: 20
Downloads: 3

Abstract

The rapid advancement of artificial intelligence (AI) is transforming mathematics education and creating new opportunities for enhancing teaching and learning. However, effective AI integration depends on teachers’ ability to use AI critically, ethically, and pedagogically. This conceptual paper examines the integration of AI literacy and AI tools into mathematics teacher education and classroom practice and proposes an integrative framework for preparing future-ready mathematics teachers. Drawing on a comprehensive review of contemporary literature, the paper explores the concept and dimensions of AI literacy, the pedagogical applications of AI tools, and the theoretical foundations underpinning AI integration. The proposed framework synthesizes the Technological Pedagogical Content Knowledge (TPACK) framework, the UNESCO AI Competency Framework for Teachers, Self-Determination Theory, and Diffusion of Innovations Theory, positioning AI literacy as the central competency linking mathematics teacher education, AI-supported classroom practice, and improved learning outcomes. The paper argues that AI technologies can enhance mathematics education only when teachers possess the knowledge, ethical awareness, and pedagogical competence required for their responsible use. It further highlights implications for teacher education, professional development, educational policy, and future research, while emphasizing the need to embed AI literacy within mathematics teacher education to support effective and responsible AI integration.

References

  1. Chai, C.-S., Koh, J. H.L., & Tsai, C. C. (2013). A review of technological pedagogical content knowledge (TPACK). Educational Technology & Society, 16, 31-51.
  2. https://www.jstor.org/stable/jeductechsoci.16.2.31
  3. Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
  4. Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20, Article No. 22. https://doi.org/10.1186/s41239-023-00392-8
  5. Deci, E. L., & Ryan, R. M. (1985). Intrinsic Motivation and Self-Determination in Human Behavior. New York: Plenum Press. http://dx.doi.org/10.1007/978-1-4899-2271-7
  6. Holmes, W., Bialik, M., & Fadel, C. (2021). Artificial intelligence in education: Promises and implications for teaching and learning (2nd ed.). Center for Curriculum Redesign.
  7. Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. https://doi.org/10.35542/osf.io/5er8f
  8. Kholid, M. N., Hendriyanto, A., Sahara, S., Muhaimin, L. H., Juandi, D., Sujadi, I., Kuncoro, K. S., & Adnan, M. (2023). A systematic literature review of Technological, Pedagogical and Content Knowledge (TPACK) in mathematics education: Future challenges for educational practice and research. Cogent Education, 10(2), Article 2269047. https://doi.org/10.1080/2331186X.2023.2269047
  9. Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54, 537-550. https://doi.org/10.1177/00336882231162868
  10. Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13, article 410. https://doi.org/10.3390/educsci13040410
  11. Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16). Association for Computing Machinery. https://doi.org/10.1145/3313831.3376727
  12. Luckin, R., & Cukurova, M. (2019). Designing educational technologies in the age of AI: a learning sciences-driven approach. British Journal of Educational Technology, 50, 2824-2838. https://doi.org/10.1111/bjet.12861
  13. Miao, F., & Holmes, W. (2023). Guidance on Generative AI in Education and Research (pp. 14-17). UNESCO.
  14. 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
  15. Ng, D. T. K., Leung, J. K. L., Chu, K. W. S., & Qiao, M. S. (2021). AI literacy: Definition, teaching, evaluation and ethical issues. Proceedings of the Association for Information Science and Technology, 58(1), 504–509. https://doi.org/10.1002/pra2.487
  16. Niess, M. L. (2005). Preparing teachers to teach science and mathematics with technology: Developing a technology pedagogical content knowledge. Teaching and Teacher Education, 21(5), 509–523. https://doi.org/10.1016/j.tate.2005.03.006
  17. Ogbu, E. E. (2024). Assessing the readiness and attitudes of Nigerian teacher educators towards adoption of artificial intelligence in educational settings. Journal of Educational Technology and Online Learning (ICETOL), 7(4), 473-487. https://doi.org/10.31681/jetol.1503305
  18. Ouyang, F., Zheng, L. and Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27, 7893-7925. https://doi.org/10.1007/s10639-022-10925-9
  19. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
  20. Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson. https://www.amazon.com/artificial-intelligence-a-modern-approach/dp/0134610997
  21. Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, article 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
  22. Siemens, G., & Baker, R. S. D. (2012). Learning analytics and educational data mining: Towards communication and collaboration. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, 252–254. https://doi.org/10.1145/2330601.2330661
  23. Tunjera, N., & Chigona, A. (2025). AI literacy in pre-service teachers’ preparation programs: A global meta-analysis. In Proceedings of the 24th European Conference on e-Learning (ECEL 2025) (Vol. 24, No. 1, pp. 363–370). Academic Conferences International Limited. https://doi.org/10.34190/ecel.24.1.4174
  24. UNESCO. (2022). Recommendation on the Ethics of Artificial Intelligence. Paris: UNESCO.
  25. UNESCO. (2023). Guidance for Generative AI in Education and Research.
  26. https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research
  27. UNESCO. (2024). AI competency framework for teachers. UNESCO.
  28. Voogt, J., Fisser, P., Pareja Roblin, N., Tondeur, J., & van Braak, J. (2013). Technological pedagogical content knowledge a review of the literature. Journal of Computer Assisted Learning, 29, 109-121. https://doi.org/10.1111/j.1365-2729.2012.00487.x
  29. Zawacki-Richter, O., Marin, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16, Article 39. https://doi.org/10.1186/s41239-019-0171-0
How to Cite

Akissani, I., Aminu, N., & Shodubi, S. O. (2026). Integrating Artificial Intelligence Literacy into Mathematics Teacher Education: an Integrative Conceptual Framework for AI-Supported Classroom Practice. Journal of Studies in Science and Mathematics Education, 6(1), 158–167. https://doi.org/10.67203/jossme.2026.l1csjtl8

I. Akissani, N. Aminu, and S. O. Shodubi, "Integrating Artificial Intelligence Literacy into Mathematics Teacher Education: an Integrative Conceptual Framework for AI-Supported Classroom Practice," Journal of Studies in Science and Mathematics Education, vol. 6, no. 1, pp. 158–167, August 2026. doi: 10.67203/jossme.2026.l1csjtl8

Share this article:
Facebook X / Twitter LinkedIn