Integrating artificial intelligence in education: How pre-service mathematics teachers use ChatGPT for 5E lesson plan design
Amine Nur Yanar 1, Özkan Ergene 2 *
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1 Institute of Educational Sciences, Department of Mathematics Education, Sakarya University, Sakarya, Türkiye
2 Education Faculty, Department of Mathematics, Sakarya University, Sakarya, Türkiye
* Corresponding Author

Abstract

This study examines the utilization of ChatGPT by pre-service mathematics teachers during the 5E lesson planning process, focusing on its affordances, constraints, and potential as a supportive tool in education. Twenty-one pre-service mathematics teachers, selected through purposive sampling, participated in the study. Data collection included 5E lesson plans, ChatGPT interaction transcripts, and participant interview responses, which were analyzed using content analysis within the framework of the instrumental approach. ChatGPT was utilized for lesson planning across categories addressing instructional and pedagogical content, encompassing fourteen distinct purposes distributed across the stages of the 5E lesson plan design: five for the engagement stage, five for exploration, six for explanation, five for elaboration, and four for evaluation. Interviews revealed both the affordances and constraints of ChatGPT, noting that while it provided creative and practical ideas, it often required well-structured prompts to yield relevant results. Despite its challenges, participants expressed their intention to use ChatGPT professionally to enhance lesson planning and instructional practices. ChatGPT is a valuable yet evolving tool for fostering innovation and efficiency in mathematics education, with implications for teacher training and future research on AI integration.

Keywords

References

  • Angeli, C., & Valanides, N. (2009). Epistemological and methodological issues for the conceptualization, development, and assessment of ICT-TPCK: advances in technological pedagogical content knowledge (TPCK). Computers & Education, 52(1), 154–168. https://doi.org/10.1016/j.compedu.2008.07.006
  • Artigue, M. (2002). Learning mathematics in a CAS environment: The genesis of a reflection about, instrumentation and the dialectics between technical and conceptual work. International Journal of Computers for Mathematical Learning, 7(3), 245–274. https://doi.org/10.1023/A:1022103903080
  • Backfish, I., Lachner, A., Hische, C., Loose, F., & Scheiter, K. (2020). Professional knowledge or motivation? Investigating the role of teachers’ expertise on the quality of technology-enhanced lesson plans. Learning & Instruction, 66, 101300. https://doi.org/10.1016/j.learninstruc.2019.101300
  • Bishop, J. M. (2021). Artificial intelligence is stupid and causal reasoning will not fix it. Frontiers in Psychology, 11, 2603. https://doi.org/10.3389/fpsyg.2020.513474
  • Boddy, N., Watson, K., & Aubusson, P. (2003). A trial of the five Es: A referent model for constructivist teaching and learning. Research in Science Education, 33, 27–42. https://doi.org/10.1023/A:1023606425452
  • Bybee, R. (2002). Scientific inquiry, student learning, and the science curriculum. In R. Bybee (Ed.), Learning science and the science of learning (pp. 25-36). NSTA Press.
  • Bybee, R. W., Taylor, J. A., Gardner, A., Van Scotter, P., Powell, J. C., Westbrook, A., & Landes, N. (2006). The BSCS 5E instructional model: Origins and eectiveness. Colorado Springs.
  • Campbell, M. A. (2000). The effects of the 5e learning cycle model on students understanding of force & motion concepts [Unpublished master’s thesis]. University of Central Florida, Florida.
  • Castro, R. A. G., Cachicatari, N. A. M., Aste, W. M. B., & Medina, M. P. L. (2024). Exploration of ChatGPT in basic education: Advantages, disadvantages, and its impact on school tasks. Contemporary Educational Technology, 16(3), ep511. https://doi.org/10.30935/cedtech/14615
  • De Angelis L, Baglivo F, Arzilli G, Privitera GP, Ferragina P, Tozzi AE and Rizzo C (2023) ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health. Frontiers Public Health, 11, 1166120. https://doi.org/10.3389/fpubh.2023.1166120
  • Ergene, O., & Caylan Ergene, B. (2025a). AI ChatBots’ solutions to mathematical problems in interactive e-textbooks: Affordances and constraints from the eyes of students and teachers. Education and Information Technologies, 30, 509–545. https://doi.org/10.1007/s10639-024-13121-z
  • Ergene, O., & Caylan Ergene, B. (2025b). Pre-service mathematics teachers’ and engineering students’ perceptions of chatgpt in mathematics: Development, validation and implementation study. Digital Experiences in Mathematics Education. Advance Online Publication. https://doi.org/10.1007/s40751-025-00176-x
  • Guin, D., & Trouche, L. (1999) The complex process of converting tools into mathematical instruments. The case of calculators. International Journal of Computers for Mathematical Learning, 3(3), 195–227. https://doi.org/10.1023/A:1009892720043
  • Gurl, T. J., Markinson, M. P., & Artzt, A. F. (2025). Using ChatGPT as a lesson planning assistant with preservice secondary mathematics teachers. Digital Experiences in Mathematics Education, 11(1), 114–139. https://doi.org/10.1007/s40751-024-00162-9
  • Hoyles, C., Noss, R., & Kent, P. (2004). On the integration of digital technologies into mathematics classrooms. International Journal of Computers for Mathematical Learning, 9(3), 309-326. https://doi.org/10.1007/s10758-004-3469-4
  • Jeon, J., & Lee, S. (2023). Large language models in education: A focus on the complementary relationship between human teachers and ChatGPT. Education and Information Technologies, 28, 15873–15892. https://doi.org/10.1007/s10639-023-11834-1
  • Karaman, M., & Goksu, I. (2024). Are lesson plans created by ChatGPT more effective? An experi- mental study. International Journal of Technology in Education, 7(1), 107–127. https://doi.org/10.46328/ijte.607
  • Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
  • Laborde, C. (2002). Integration of technology in the design of geometry tasks with Cabri-Geometry. International Journal of Computers for Mathematical Learning, 6, 283–317. https://doi.org/10.1023/A:1013309728825
  • Lilly, S., Bieda, K., & Youngs, P. (2024). How early-career elementary teachers vary in planning mathematics instruction. Journal of Mathematics Teacher Education, 27(1), 85–110. https://doi.org/10.1007/s10857-022-09551-6
  • Lim, W., Son, J.-W., & Kim, D.-J. (2018). Understanding preservice teacher skills to construct lesson plans. International Journal of Science and Mathematics Education, 16(3), 519–538. https://doi.org/10.1007/s10763-016-9783-1
  • Lo, C. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410
  • MacDowell, P., & Korchinsk, K. (2023). A collaborative future: New roles of students and teachers learning and creating with generative AI. In S. Bauchard, A. Rao, P. Shah, & C. Shryock (Eds.), CHAT (GPT): Navigating the impact of generative AI technologies on educational theory and practice (pp. 590–507). Pedagogy Ventures LLC.
  • Maheshwari, G. (2023). Factors influencing students’ intention to adopt and use ChatGPT in higher education: A study in the Vietnamese context. Education and Information Technologies, 29, 12167-12195. https://doi.org/10.1007/s10639-023-12333-z
  • Merriam, S.B. (2013). Qualitative research: a guide to design and implementation. John Wiley & Sons.
  • Miles, M. B. & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. Sage.
  • Ministry of National Education (MoNE). (2024). Middle school mathematics curriculum. Ministry of National Education
  • Newby, D. E. (2004). Using inquiry to connect young learns to science. National Charter Schools Institute.
  • Öztürk, N. (2013). The effect of activities based on 5E learning model in the unit titled light and sound at the sixth grade science and technology lesson on learning outcomes (Publication no. 333552) [Doctoral dissertation, Gazi University]. Council of Higher Education Thesis Center.
  • Patton, M. Q. (2015). Qualitative research and evaluation methods. Sage.
  • Pavlik, J. V. (2023). Collaborating with ChatGPT: Considering the implications of generative artificial intelligence for journalism and media education. Journalism & Mass Communication Educator, 78(1), 84-93. https://doi.org/10.1177/107769582211495
  • Pelton, T., & Pelton, L. F. (2023). Adapting ChatGPT to support teacher education in mathematics. In E. Langran, P. Christensen, & J. Sanson (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 1662–1670). Association for the Advancement of Computing in Education.
  • Pişkin Tunç, M. (2024). Examining pre-service mathematics teachers’ purposes of using Chatgpt in lesson plan development. Sakarya University Journal of Education, 14(2), 391–406. https://doi.org/10.19126/suje.1476326
  • Rabardel, P. (1995). Les hommes et les technologies-Approche cognitive des instruments contemporains [People and technology-A cognitive approach to contemporary tools]. Armand Colin.
  • Rabardel, P. (1999). Elements pour une approche cognitives des instrumentale en didactique des mathematiques [Elements for a cognitive and instrumental approach to mathematics didactics]. In M. Bailleul (Ed.), Ecole d’ete de didactique des mathematiques [Mathematics didactics summer school] (pp. 202-213). IUFEM de ean.
  • Rospigliosi, P. (2023). Artificial intelligence in teaching and learning: what questions should we ask of ChatGPT. Interactive Learning Environments, 31(1), 1–3. https://doi.org/10.1080/10494820.2023.2180191
  • Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?. Journal of Applied Learning and Teaching, 6(1), 9. https://doi.org/10.37074/jalt.2023.6.1.9
  • Ruthven, K. (2002). Instrumenting mathematical activity: Reflections on key studies of the educational use of computer algebra systems. International Journal of Computers for Mathematical Learning, 7(3), 275–291. https://doi.org/10.1023/A:1022108003988
  • Sheikh, S. (2020). Understanding the role of artificial intelligence and its future social impact. IGI Global.
  • Tapan Broutin, M. S. (2024). Exploring mathematics teacher candidates’ instrumentation process of generative artificial intelligence for developing lesson plans. Journal of Higher Education, 14(1), 165–176. https://doi.org/10.53478/yuksekogretim.1347061
  • Tapan-Broutin, M. S. (2023). Examination of questions asked by pre-service mathematics teachers in their initial experiences with ChatGPT. Journal of Uludag University Faculty of Education, 36(2), 707–732. https://doi.org/10.19171/uefad.1299680
  • Tashtoush, M., Wardat, Y., Aloufi, F., & Taani, O. (2022). The effect of a training program based on timss to developing the levels of habits of mind and mathematical reasoning skills among pre-service mathematics teachers. Eurasia Journal of Mathematics, Science and Technology Education, 18(11), em2182. https://doi.org/10.29333/ejmste/12557
  • Tate, T. P., Doroudi, S., Ritchie, D., & Xu, Y. (2023). Educational research and AI-generated writing: Confronting the coming tsunami. EdArXiv. https://doi.org/10.35542/osf.io/4mec3
  • Thanasi, T., & Mema, O. (2024). Enhancing mathematics education with artificial intelligence. EIRP Proceedings, 19(1), 518–523.
  • Thorp, H. H. (2023). ChatGPT is fun, but not author. Science, 379(6630), 313–313. https://doi.org/10.1126/science.adg7879
  • Trouche, L. (2004). Managing the complexity of human/machine interaction in computerized learning environment: Guiding students’ command process through instrumental orchestrations. International Journal of Computers for Mathematical Learning, 9(3), 281–307. https://doi.org/10.1007/s10758-004-3468-5
  • Trouche, L., & Drijvers, P. (2008). From artifacts to instruments: A theoretical framework behind the orchestra metaphor. In G. W. Blume & M. K. Heid (Eds.), Research on technology and the teaching and learning of mathematics- Volume 2: Cases and perspevtives (p.33–392). IAP.
  • Trust, T., Whalen, J., & Mouza, C. (2023). Editorial: ChatGPT: Challenges, opportunities, and implications for teacher education. Contemporary Issues in Technology and Teacher Education, 23(1), 1-23.
  • Urhan, S., Gençaslan, O., & Dost, Ş. (2024). An argumentation experience regarding concepts of calculus with ChatGPT. Interactive Learning Environments, 32(10), 7186-7211. https://doi.org/10.1080/10494820.2024.2308093
  • Van Dis, E. A., Bollen, J., Zuidema, W., Van Rooij, R., & Bockting, C. L. (2023). ChatGPT: five priorities for research. Nature, 614(7947), 224–226. https://doi.org/10.1038/d41586-023-00288-7
  • Wardat, Y., Tashtoush, M., AlAli, R., & Jarrah, A. (2023). ChatGPT: A revolutionary tool for teaching and learning mathematics. Eurasia Journal of Mathematics, Science and Technology Education, 19(7), 2286. https://doi.org/10.29333/ejmste/13272
  • Yadav, S., & Yadav, R. (2024). A comprehensive study to analyze the ChatGPT and its impact on students’ education. Educational Administration: Theory and Practice, 30(6), 1456–1465. https://doi.org/10.53555/kuey.v30i6.5518
  • Yin, R. K. (1994). Discovering the future of the case study. Method in evaluation research. Evaluation Practice, 15(3), 283–290. https://doi.org/10.1177/109821409401500309
  • Yoon, H., Hwang, J., Lee, K., Roh, K. H., & Kwon, O. N. (2024). Students’ use of generative artificial intelligence for proving mathematical statements. ZDM Mathematics Education, 56, 1531–1551. https://doi.org/10.1007/s11858-024-01629-0

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