ARTIFICIAL INTELLIGENCE PEDAGOGICAL APPROACH FOR FOSTERING CONCEPTUAL UNDERSTANDING IN COLLEGE MATHEMATICS
DOI:
https://doi.org/10.20319/ictel.2026.246262Keywords:
Artificial Intelligence, Mathematical Education, College Level, Pedagogical ApproachAbstract
In this paper, we studied the implications of Artificial Intelligence (AI) in mathematics courses at the college level, with a concentration on its impact on students’ conceptual understanding. AI offers a wide range of innovative tools and adaptive platforms that enable instructors to explain math concepts in inventive and engaging ways. Our study examines how these tools can improve students' understanding, as these platforms facilitate individualized learning experiences, represent concepts in various ways, and offer immediate feedback. Our goal is to evaluate the success of AI-driven techniques in supporting different learning methodologies and improving student engagement in the mathematical classroom. The findings shall assist us in recognizing the power of AI in transferring teaching approaches in college education to enhance conceptual learning.
References
Abar, C. A. A. P., Dos Santos Dos Santos, J. M., & de Almeida, M. V. (2024). Contributions of the integration between computational thinking and artificial intelligence for mathematics education. In Springer International Publishing (pp. 290–299). https://doi.org/10.1007/978-3-031-54256-5_27
Abiola, O., Ajuwon, A., Shukurat, E., & Chiekezie, N. (2024). Innovative teaching strategies in mathematics and economics education: Engaging students through technology, AI, and effective mentoring. Open Access Research Journal of Science and Technology, 11(2). https://doi.org/10.53022/oarjst.2024.11.2.0103
Borah, P., & Borah, A. (2024). A review of the use of artificial intelligence in teaching and learning of mathematics. International Journal on Science and Technology, 15(4). https://doi.org/10.71097/ijsat.v15.i4.1190
Canonigo, A. (2024). Leveraging AI to enhance students' conceptual understanding and confidence in mathematics. Journal of Computer Assisted Learning, 40, 3215–3229. https://doi.org/10.1111/jcal.13065
Choustoulakis, E. (2024). Integrating artificial intelligence (AI) tools into teaching mathematical economics in tertiary education. European Journal of Open Education and E-learning Studies, 9(1).
https://doi.org/10.46827/ejoe.v9i1.5683
El Shara, I. (2025). The effect of using MatGPT on mathematical proficiency among undergraduate students. International Journal of Information and Education Technology, 15(4).
https://doi.org/10.18178/ijiet.2025.15.4.2284
Fathi, T., Saad, A., Larhzil, H., Lamri, D., & Ibrahmi, E. (2025). Integrating generative AI into STEM education: Enhancing conceptual understanding, addressing misconceptions, and assessing student acceptance. Disciplinary and Interdisciplinary Science Education Research.
https://doi.org/10.1186/s43031-025-00125-z
Li, C., Lyu, B. (2025). Investigating the motivational and knowledge affordances of conversational AI using induction, concretization, and exemplification in math learning. British Journal of Educational Technology. https://doi.org/10.1111/bjet.13612
Li, C., Zhu, W., Xing, W., & Guo, R. (2024). Analyzing student attention and acceptance of conversational AI for math learning: Insights from a randomized controlled trial. In Proceedings of the 14th Learning Analytics and Knowledge Conference. https://doi.org/10.1145/3636555.3636895
Li, Z., & Li, M. (2025). Research on talent cultivation in advanced mathematics education through artificial intelligence. Journal of Contemporary Educational Research, 9(4). https://doi.org/10.26689/jcer.v9i4.9890
Panaoura, R. (2025). Teaching mathematics in the artificial intelligence era: Challenges and concerns in higher education. Social Education Research. https://doi.org/10.37256/ser.6220256730
Shao, H., & Tang, G. (2025). Empowering mathematical problem-posing pedagogy with generative AI: A theoretical framework and case study. In Proceedings of the 14th International Conference on Educational and Information Technology (ICEIT) (pp. 111–115).
https://doi.org/10.1109/iceit64364.2025.10975950
Tang, W. (2025). Artificial intelligence in mathematics education: Trends, challenges, and opportunities. International Journal of Research in Mathematics Education, 3(1). https://doi.org/10.24090/ijrme.v3i1.13496
Torres Peña, R., Peña González, D., Chacuto López, E., Ariza, E., & Vergara, D. (2024). Updating calculus teaching with AI: A classroom experience. Education Sciences. https://doi.org/10.3390/educsci14091019
Trindade, M., Edirisinghe, G., & Luo, L. (2025). Teaching mathematical concepts in management with generative artificial intelligence: The power of human oversight in AI-driven learning. The International Journal of Management Education. https://doi.org/10.1016/j.ijme.2024.101104
Xing, W., Song, Y., Li, C., Liu, Z., Zhu, W., & Oh, H. (2025). Development of a generative AI-powered teachable agent for middle school mathematics learning: A design-based research study. British Journal of Educational Technology. https://doi.org/10.1111/bjet.13586
Xu, X. (2025). Game-based adaptive learning in probability education. International Journal of Information and Education Technology, 15(1). https://doi.org/10.18178/ijiet.2025.15.1.2212
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright of Published Articles
Author(s) retain the article copyright and publishing rights without any restrictions.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
