Incorporation of GeoGebra Applets and ChatGPT to Strengthen the Learning of Exact Equations in Engineering Students

Authors

  • Jorge Olivares Funes Department of Mathematics, University of Antofagasta, 1240000 Antofagasta, Chile.
  • Byron Droguett Parada Department of Physics, University of Antofagasta, 1240000 Antofagasta, Chile.
  • Pablo Martin de Julian Department of Physics, University of Antofagasta, 1240000 Antofagasta, Chile.
  • Alexandra Burgos Villegas Department of Mathematics, University of Antofagasta, 1240000 Antofagasta, Chile.

DOI:

https://doi.org/10.9734/bpi/mcscd/v7/2443

Keywords:

Dif. equation, GeoGebra, engineering education, ChatGpt

Abstract

This paper presents the integration of GeoGebra applets and ChatGPT artificial intelligence in the learning of exact differential equations in the university context. GeoGebra has established itself as a powerful tool in teaching mathematical concepts, thanks to its ability to dynamically visualize and model, which facilitates deeper understanding and motivates the students. Meanwhile, ChatGPT provides detailed solutions, and step-by-step explanations that complement autonomous learning and reinforce mathematical problem-solving.
The combination of GeoGebra and ChatGPT creates a dynamic learning environment that not only supports the visualization and experimentation of complex concepts, but also promotes interaction, offering an alternative to the traditional pencil-and-paper approach. This integration is especially relevant for engineering students in differential equations and multivariable calculus courses, as it provides a more comprehensive and effective learning experience, enhancing both their theoretical and practical skills.

Published

2024-11-09

How to Cite

Jorge Olivares Funes, Byron Droguett Parada, Pablo Martin de Julian, & Alexandra Burgos Villegas. (2024). Incorporation of GeoGebra Applets and ChatGPT to Strengthen the Learning of Exact Equations in Engineering Students. Mathematics and Computer Science: Contemporary Developments Vol. 7, 133–143. https://doi.org/10.9734/bpi/mcscd/v7/2443