ChatGPT and mathematical modeling of motion for teaching linear functions in secondary education
Full Text (PDF)
Rosa Isela González-Polo 1 , Apolo Castaneda 2 *
More Detail
1 Universidad Autónoma del Estado de México Av. Filiberto Gómez s/n, Guadalupe, Barrio de Tlacopa 50010 Toluca de Lerdo, Estado de México, MEXICO2 Instituto Politécnico Nacional, Legaria 694, Col. Irrigación, Miguel Hidalgo, 11500 Ciudad de México, CDMX, MEXICO* Corresponding Author

Abstract

This exploratory study analyzes the pedagogical mediation conditions under which ChatGPT's intervention in mathematical modeling amplifies coordination among semiotic registers and favors functional thinking. Twelve second-year secondary school students participated in four teams that modeled the rectilinear motion of a person captured on video and constructed piecewise linear functions. From the articulation between the theory of semiotic representations and Realistic Mathematics Education, the study documented how the teams coordinated the four registers when interacting with ChatGPT. The analysis identifies four conditions that made that mediation productive: the selection of a contextualized situation, the iterative refinement of the prompt, the open stance of the teacher, and the availability of multiple representations as an object of contrast. Given its limited scope, the results offer a first approach to how generative artificial intelligence redistributes cognitive work toward conceptual analysis, and require replication in other groups.

Keywords

License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

INT ELECT J MATH ED, Volume 21, Issue 4, November 2026, Article No: em0900

https://doi.org/10.29333/iejme/19695

Publication date: 29 Oct 2026

Article Views: 17

Article Downloads: 10

Open Access References How to cite this article