Exploring ChatGPT as a Scaffolding Tool for Posing Mathematical Problems: Insights from Primary Pre-service Teachers
Keywords:
mathematical problem posing, pre-service teacher education, ChatGPT, instructional scaffolding, artificial intelligence in education, reflective teaching developmentAbstract
The study reported in this article investigated ChatGPT’s role as a digital scaffolding tool for pre-service primary teachers engaged in mathematical problem posing focused on word problems, an area underexplored in research on generative AI in pre-service teacher education. Grounded in the Zone of Proximal Teacher Development (ZPTD) framework, the research examined how AI-mediated interactions support cognitive, metacognitive, and pedagogical dimensions of instructional design. Twenty-two pre-service mathematics teachers participated in a three-phase qualitative exploratory case study involving independent problem posing (Task A), AI assisted problem posing with ChatGPT (Task B), and subsequent written reflections and semi-structured interviews. Thematic analysis of task outputs, interaction logs, and reflective data revealed that ChatGPT provided multidimensional scaffolding (cognitive, metacognitive, strategic, affective, and pedagogical), which collectively enhanced participants’ task quality and depth of reflection. AI-assisted tasks showed notable improvements in contextual relevance, problem structure, cognitive demand, and creativity compared to mathematical problems posed independently. Participants reported substantial shifts in instructional awareness, moving from procedural task design toward student-centred and imaginative problem construction. These findings suggest ChatGPT has potential as a reflective learning partner, supporting development of pedagogical reasoning and instructional creativity in teacher education. The study extends the ZPTD framework to AI-mediated contexts, offering theoretical and practical insights for integrating generative AI into professional learning for pre-service teachers.
References
Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), Article ep429. https://doi.org/10.30935/cedtech/13152
Aktaş, M. C. (2022). Problem-posing research in mathematics education: A bibliometric analysis. Journal of Pedagogical Research, 6(4), 217–233. https://doi.org/10.33902/JPR.202217414
Anthony, G., Hunter, J., & Hunter, R. (2015). Supporting prospective teachers to notice students’ mathematical thinking through rehearsal activities. Mathematics Teacher Education and Development, 17(2), 7–24.
Athanassopoulos, S., Manoli, P., Gouvi, M., Lavidas, K., & Komis, V. (2023). The use of ChatGPT as a learning tool to improve foreign language writing in a multilingual and multicultural classroom. Advances in Mobile Learning Educational Research, 3(2), 818–824. https://doi.org/10.25082/amler.2023.02.009
Baharullah. (2009). Penerapan pendekatan problem posing berlatar pembelajaran kooperatif di sekolah dasar [The implementation of a problem posing approach in a cooperative learning setting in primary schools]. Sigma: Suara Intelektual Gaya Matematika, 1(1), 1–9. https://journal.unismuh.ac.id/index.php/sigma/en/article/view/7339
Baker, R. S. (2021). Artificial intelligence in education: Bringing it all together. In A. Schleicher (Ed.), OECD Digital education outlook 2021: Pushing the frontiers with artificial intelligence, blockchain, and robots (pp. 43–54). OECD Publishing. https://doi.org/10.1787/f54ea644-en
Baumanns, L., & Rott, B. (2024). Problem-posing tasks and their influence on pre-service teachers’ creative problem-posing performance and self-efficacy. The Journal of Mathematical Behavior, 73, 101130. https://doi.org/10.1016/j.jmathb.2024.101130
Belland, B. R., Kim, C. M., & Hannafin, M. J. (2013). A framework for designing scaffolds that improve motivation and cognition. Educational psychologist, 48(4), 243–270. https://doi.org/10.1080/00461520.2013.838920
Beswick, K. (2012). Teachers’ beliefs about school mathematics and mathematicians’ mathematics and their relationship to practice. Educational Studies in Mathematics, 79(1), 127–147. https://doi.org/10.1007/s10649-011-9333-2
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Buchholtz, N., & Huget, J. (2024). ChatGPT as a reflection tool to promote the lesson planning competencies of pre-service teachers. In E. Faggiano, A. Clark-Wilson, M. Tabach & H.-G. Weigand (Eds.), Proceedings of the 17th ERME Topic Conference MEDA 4 (pp. 129–136). University of Bari Aldo Moro.
Burgos, M., & Tizón-Escamilla, N. (2026). ChatGPT as a tool for posing of mathematical problems by prospective teachers. LUMAT: International Journal on Math, Science and Technology Education, 14(1), Article 3. https://doi.org/10.31129/LUMAT.14.1.2942
Cai, J., & Hwang, S. (2020). Learning to teach through mathematical problem posing: Theoretical considerations, methodology, and directions for future research. International Journal of Educational Research, 102, Article 101391. https://doi.org/10.1016/j.ijer.2019.01.001
Cameron, S., & Mesiti, C. (2024). What kind of mathematics teacher is ChatGPT? In J. Višňovská, E. Ross, & S. Getenet (Eds.), Surfing the waves of mathematics education. Proceedings of the 46th annual conference of the Mathematics Education Research Group of Australasia (pp. 135–142). MERGA.
Cameron, S., Mesiti, C., & Fijn, P. (2025). How knowledgeable is ChatGPT 4o? Assessing the pedagogical content knowledge of a generative artificial intelligence tool. In S. M. Patahuddin, L. Gaunt, D. Harris & K. Tripet (Eds.), Unlocking minds in mathematics education. Proceedings of the 47th Annual Conference of the Mathematics Education Research Group of Australasia (pp. 93–100). MERGA.
Clarke, D., & Hollingsworth, H. (2002). Elaborating a model of teacher professional growth. Teaching and Teacher Education, 18(8), 947–967. https://doi.org/10.1016/S0742-051X(02)00053-7
Collins, A., & Michalski, R. (1989). The logic of plausible reasoning: A core theory. Cognitive Science, 13(1), 1–49. https://doi.org/10.1016/0364-0213(89)90010-4
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
Cumhur, F. (2022). Pre-service teachers’ approaches to guiding students in problem solving process. Problems of education in the 21st century, 80(1), 144–161. https://doi.org/10.33225/pec/22.80.144
Dilling, F., & Herrmann, M. (2024). Using large language models to support pre-service teachers mathematical reasoning—an exploratory study on ChatGPT as an instrument for creating mathematical proofs in geometry. Frontiers in Artificial Intelligence, 7, 1460337. https://doi.org/10.3389/frai.2024.1460337
Drushlyak, M., Lukashova, T., Shamonia, V., & Semenikhina, O. (2025). ChatGPT-based simulation helps to develop the pre-service mathematics teachers’ critical thinking. International Journal of Instruction, 18(1), 153–172. https://doi.org/10.29333/iji.2025.1819a
Findell, B., Swafford, J., & Kilpatrick, J. (2001). Adding it up: Helping children learn mathematics. National Academies.
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & 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
Kilic, C. (2015). Analyzing pre-service primary teachers’ fraction knowledge structures through problem posing. Eurasia Journal of Mathematics, Science and Technology Education, 11(6), 1603–1619. https://doi.org/10.12973/eurasia.2015.1425a
Kusmaryono, I., Gufron, A. M., & Rusdiantoro, A. (2020). Effectiveness of scaffolding strategies in learning against decrease in mathematics anxiety level. Numerical: Jurnal Matematika dan Pendidikan Matematika, 4, 13–22. https://doi.org/10.25217/numerical.v4i1.770
Landis, J. R., & Koch, G. G. (1977). An application of hierarchical kappa-type statistics in the assessment of majority agreement among multiple observers. Biometrics, 33(2),363–374. https://doi.org/10.2307/2529786
Lestari, N. D. S., Suwarno, S., Pambudi, D. S., Kurniati, D., & Murtafiah, W. (2026). Decision-making skills of prospective mathematics teachers in designing numeracy tasks: A study of medium level pedagogical content knowledge. Mathematics Teacher Education and Development, 28(1), Article 2.
Li, L., & Patton, W. (2025). Streamlining online astronomy education: Integrating ChatGPT and Stellarium Planetarium software to serve as a virtual teaching assistant. Journal of Educational Technology Systems, 53(3), 205–218. https://doi.org/10.1177/00472395241309599
Lincoln, Y. S., Guba, E. G. (1985). Naturalistic inquiry. SAGE Publications.
Lortie, D. C. (2020). Schoolteacher: A sociological study. University of Chicago Press.
Malterud, K., Siersma, V. D., & Guassora, A. D. (2016). Sample size in qualitative interview studies: Guided by information power. Qualitative Health Research, 26(13), 1753–1760. https://doi.org/10.1177/1049732315617444
Ming, G. K., & Mansor, M. (2023). Exploring the impact of chat-GPT on teacher professional development: opportunities, challenges, and implications. Asian Journal of Research in Education and Social Sciences, 5(4), 54–67.
Msambwa, M., Wen, Z., & Kangwa, D. (2025). The impact of AI on the personal and collaborative learning environments in higher education. European Journal of Education, 60(1). https://doi.org/10.1111/ejed.12909
Niraula, S. (2024). The impact of ChatGPT on academia: A comprehensive analysis of AI policies across UT system academic institutions. Advances in Mobile Learning Educational Research, 4(1), 973–982. https://doi.org/10.25082/amler.2024.01.009
Nurita, T., Yuliati, L., Mahdiannur, M. A., Ilhami, F. B., Fauziah, A. N. M., Hendratmoko, A. F., & Puspitarini, S. (2024). Increasing pre-service science teacher creativity through STEM problem-solving. Jurnal Penelitian Pendidikan IPA, 10(1), 72–79. https://doi.org/10.29303/jppipa.v10i1.6335
Patton, M. Q. (2015). Qualitative research and evaluation methods: Integrating theory and practice (4th ed.). SAGE Publications.
Pepin, B., Buchholtz, N., & Salinas-Hernández, U. (2025). A scoping survey of ChatGPT in mathematics education. Digital Experiences in Mathematics Education, 11(1), 9–41. https://doi.org/10.1007/s40751-025-00172-1
Rudolph, J., Ismail, M. F. B. M., & Popenici, S. (2024). Higher education’s generative artificial intelligence paradox: The meaning of chatbot mania. Journal of University Teaching and Learning Practice, 21(6). https://doi.org/10.53761/54fs5e77
Schoenfeld, A. H. (1992). On paradigms and methods: What do you do when the ones you know don’t do what you want them to? Issues in the analysis of data in the form of videotapes. The Journal of the Learning Sciences, 2(2), 179–214. https://doi.org/10.1207/s15327809jls0202_3
Schön, D. A. (1983). The reflective practitioner: How professionals think in action. Basic Books
Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. John Wiley & Sons.
Shulman, L. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57(1), 1–23. https://doi.org/10.17763/haer.57.1.j463w79r56455411
Silver, E. A. (1994). On mathematical problem posing. For the Learning of Mathematics, 14(1), 19–28.
Silver, E. A., Mamona-Downs, J., Leung, S. S., & Kenney, P. A. (1996). Posing mathematical problems: An exploratory study. Journal for Research in Mathematics Education, 27(3), 293–309. https://doi.org/10.2307/749366
Singer, F. M., Ellerton, N. F., & Cai, J. (Eds.) (2015). Mathematical problem posing: From research to effective practice. https://doi.org/10.1007/978-1-4614-6258-3
Stein, M. K., & Smith, M. S. (1998). Mathematical tasks as a framework for reflection: From research to practice. Mathematics Teaching in the Middle School, 3(4), 268–275. https://doi.org/10.5951/MTMS.3.4.0268
Subhaktiyasa, P. G., Ayu, S., Candrawati, K., Sumaryani, N. P., Sunita, W., & Syakur, A. (2023). Penerapan statistik deskriptif: Perspektif kuantitatif dan kualitatif. [The implementation of descriptive statistics: A quantitative and qualitative perspective]. Jurnal Edukasi Matematika dan Sains, 14(1), 96–104. https://doi.org/10.59672/emasains.v14i1.4450
Suwanti, V., Sa’dijah, C., & Muksar, M. (2024). Prospective Indonesian secondary mathematics teachers’ epistemological obstacles in designing project-based numeracy tasks: A case study. Mathematics Teacher Education and Development, 26(2), Article 2. https://mted.merga.net.au/index.php/mted/article/view/1131
Van de Pol, J., Volman, M., & Beishuizen, J. (2010). Scaffolding in teacher–student interaction: A decade of research. Educational Psychology Review, 22(3), 271–296. https://doi.org/10.1007/s10648-010-9127-6
Viberg, O., Grönlund, Å., & Andersson, A. (2023). Integrating digital technology in mathematics education: a Swedish case study. Interactive Learning Environments, 31(1), 232–243. https://doi.org/10.1080/10494820.2020.1770801
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Warford, M. K. (2011). The zone of proximal teacher development. Teaching and Teacher Education, 27(2), 252–258. https://doi.org/10.1016/j.tate.2010.08.008
Wells, G. (1999). Dialogic inquiry: Towards a socio-cultural practice and theory of education. Cambridge Press.
Wertsch, J. V. (1998). Mind as action. Oxford University Press.
Williams, R. T. (2024). The ethical implications of using generative chatbots in higher education. Frontiers in Education, 8, Article 1331607. https://doi.org/10.3389/feduc.2023.1331607
Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2), 89–100. https://doi.org/10.1111/j.1469-7610.1976.tb00381.x
Yelland, N. (2026). Reimagining multiliteracies: The transformative influence of generative AI on pedagogies. Pedagogies, 21(2), 375–384. https://doi.org/10.1080/1554480X.2025.2525270
Yin, R. K. (2018). Case study research and applications (Vol. 6). SAGE Publications.
Zawacki-Richter, O., Marín, 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(1). https://doi.org/10.1186/s41239-019-0171-0
