On the Role of Generative AI in Fractals Teaching: Solutions and Class Proposals Designed by Chatbots and Mathematics Teachers
DOI:
https://doi.org/10.46328/ijemst.5713Keywords:
Fractals, Sierpinski triangle, Chatbots, Mathematics teachers, Generative AI, Artificial intelligenceAbstract
Fractal Geometry (GF) comprises problems characterized by having particular geometric and analytical properties based on the concept of self-similarity. Fractals constitute a breaking point in relation to classical Geometry. In addition, many natural phenomena exhibit fractal features, leading to several useful practical applications. In spite of this, fractals are rarely included in curriculum design and, let alone, seen in actual classrooms. This also leads to a lack of resources for teaching fractals at different educational levels. In this context, generative AI (GenAI) can bring an opportunity to produce resources for teaching fractals. In this work we present the results of a study oriented to analyze and compare the productions of in-service Mathematics teachers and GenAI models (namely ChatGPT, Copilot and Gemini) related to a particular fractal: the Sierpinski Triangle. The solutions to the problem as well as the class proposals built by both teachers and chatbots were compared in terms of a number of proposed categories (such as correctness of the results, level of mathematical justification, specificity of class proposal in several aspects). Our findings have multiple practical implications in terms of the design of methodological proposals including GenAI in fractals teaching.
References
Sureda, P., Parra, V., Corica, A.R., Godoy, D., & Schiaffino, S. (2025). On the role of Generative AI in fractals teaching: Solutions and class proposals designed by chatbots and mathematics teachers. International Journal of Education in Mathematics, Science, and Technology (IJEMST), 13(5), 11298-1316. https://doi.org/10.46328/ijemst.5713
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