Exploring ChatGPT’s Role in Learning Integrating Factors in Differential Equations: A Case Study of Engineering Students at the University of Antofagasta, Chile | Chapter 3 | New Horizons of Science, Technology and Culture Vol. 3

 

At the University of Antofagasta, Chile, during the second semester of 2024, a qualitative case study was conducted with three engineering students studying differential equations. The main objective was to explore the perception of ChatGPT in the learning of the integrating factor of the differential equation (y³ + x) dx + xy²dy = 0, in engineering students. To do this, the study sought to investigate and analyse the interaction that students have when using this tool and to know the answers they obtain while solving the differential equation. The preliminary findings suggest that ChatGPT can serve as a complementary resource for understanding concepts, offering detailed explanations and practical calculations. This study provides valuable information on the integration of ChatGPT artificial intelligence in higher education, highlighting the need for adequate academic supervision to maximise its benefits and mitigate potential disadvantages in the learning process.

 

Author(s) Details

Jorge Olivares Funes
Department of Mathematics, University of Antofagasta, 1240000 Antofagasta, Chile.

 

Pablo Martin
Department of Physics, University of Antofagasta, 1240000 Antofagasta, Chile.

 

Carlos Portillo
University of Antofagasta, 1240000 Antofagasta, Chile.

Felipe Galleguillos
Antofagasta Energy Development Center, 1240000 Antofagasta, Chile.

 

Please see the book here:- https://doi.org/10.9734/bpi/nhstc/v3/5906

GeoGebra and ChatGPT as Support Tools to Find Particular and General Solutions in Non-homogeneous Linear Second-Order Differential Equations | Chapter 5 |Mathematics and Computer Science: Research Updates Vol. 5

This work focuses on the solution of non-homogeneous linear differential equations of second order, using technological tools such as GeoGebra and ChatGPT. These tools are especially useful in the context of the differential equations course for mathematics pedagogy students at the Universidad de Antofagasta, Chile. The use of GeoGebra, a free software, has grown in the teaching of mathematics, since it allows students to better visualise and understand mathematical concepts. On the other hand, artificial intelligence, ChatGPT, has proven to be a valuable resource in learning, providing explanations and examples that facilitate the understanding of the topics. The combination of both technological resources not only improves the learning experience but also enhances the teaching of mathematics, making students more motivated and engaged. In conclusion, this innovation in the teaching of differential equations seeks not only to solve calculations but also to foster a more dynamic and effective learning environment.

 

Author (s) Details.

Jorge Olivares
Department of Mathematics, University of Antofagasta, Chile.

 

Melissa Sanchez
Department of Mathematics, University of Antofagasta, Chile.

 

Alexandra Burgos
Department of Mathematics, University of Antofagasta, Chile.

 

Pablo Martin
Department of Physics, University of Antofagasta, Chile.

 

Please see the book here:- https://doi.org/10.9734/bpi/mcsru/v5/5324

 

ChatGPT and GeoGebra to Support the Learning of First-Order Linear Differential Equations in Engineering Students | Chapter 4 | Mathematics and Computer Science: Research Updates Vol. 5

 

In the teaching of mathematics, and particularly of differential equations, students often face multiple difficulties in understanding abstract concepts. To address these challenges, two powerful tools, GeoGebra and ChatGPT, have been integrated to enrich the learning of engineering students at the University of Antofagasta, Chile. GeoGebra, recognised for its dynamic and interactive potential, allows the construction of graphical and animated representations that make visible the behaviour of the solutions of first-order linear differential equations, while ChatGPT acts as a guide for students in the interpretation of concepts and the resolution of doubts. This combination of interactive visualisation and conversational support allows students not only to access a mix of innovative technological resources but also to reinforce their learning and strengthen their mathematical competencies through a methodology that is accessible and adapted to their needs.

 

Author (s) Details

Jorge Olivares
Department of Mathematics, Universidad de Antofagasta, Antofagasta, Chile.

 

Melissa Sanchez
Department of Mathematics, Universidad de Antofagasta, Antofagasta, Chile.

 

Pablo Martín
Department of Mathematics, Universidad de Antofagasta, Antofagasta, Chile.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/mcsru/v5/5176

Incorporation of GeoGebra Applets and ChatGPT to Strengthen the Learning of Exact Equations in Engineering Students | Chapter 8 | Mathematics and Computer Science: Contemporary Developments Vol. 7

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.

 

Author (s) Details

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.

 

Pablo Martin de Julian

Department of Physics, University of Antofagasta, 1240000 Antofagasta, Chile.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/mcscd/v7/2443