Conference Agenda

Challenge-Based Learning (CBL) and Game-Based Learning (GBL) have emerged as effective pedagogical strategies to enhance student engagement, motivation, and deep learning in engineering education. This study explores the impact of integrating CBL and GBL in an undergraduate integral calculus course within an engineering program, using a space exploration narrative to contextualize mathematical concepts. The intervention was structured around an eight-week mission where students applied definite and indefinite integrals, areas, volumes of revolution, optimization, and differential equations to solve real-world space navigation challenges. A total of 104 first-year engineering students, divided into an experimental group (CBL + GBL) and a control group (traditional learning), participated in the study.

Quantitative results indicate a significant increase in motivation (+48%), interest in the course (+45%), and teamwork perception (+42%) in the experimental group compared to the control group. The most notable effect was a 70% increase in interest in space and orbital mechanics, demonstrating the effectiveness of thematic and problem-driven learning. Although students found the game-based approach more challenging, they also rated it as significantly more enjoyable. Qualitative feedback highlighted greater engagement, deeper conceptual understanding, and improved collaboration among peers.

These findings suggest that embedding interactive, problem-driven learning experiences into engineering mathematics instruction enhances motivation, academic interest, and real-world application competencies. The study provides evidence supporting the integration of game-based challenges and thematic narratives in STEM education, reinforcing the role of active and immersive learning strategies in shaping future engineers.

This research examines how the use of the flipped class to achieve significant learning of derivatives of implicit functions affects academic performance in fourth-semester students of the Pedagogy of Experimental Sciences of Mathematics and Physics at the University of Guayaquil. To achieve this objective, a quasi-experimental study was carried out, selecting two parallels from the fourth semester. One of the groups was taught through the flipped class, while the other was taught a traditional class on the same topic. Subsequently, the same test was administered to both groups and the results were compared. In the end, significant differences were observed in the means, with the mean, of the experimental group being higher than the control group.

In this article the author explores the application of differential equations and mathematical algorithms in the use of drones as high-precision artillery weapons, comparable to modern missiles in cost and effectiveness. The Kalman filter is employed to estimate the target's position and velocity by combining measurements with a motion model. Additionally, the mathematical impact of all-terrain electric scooters on infantry effectiveness is analyzed, adapting Lanchester’s combat models. Finally, the 1:5 ratio in urban combat is derived, demonstrating how its application enables the neutralization of occupying forces attempting to seize a city.

This article explores the notion of artificial prime numbers in the context of specific sets of integers. A formal definition is presented, their properties are discussed, and they are compared to the classical notion of primality. Furthermore, potential applications of these numbers in number theory and cryptography are analyzed.

The present study examines the impact of integrating Artificial Intelligence (AI) into mathematics teaching at an engineering school, using MATLAB as a pedagogical tool in the Linear Algebra course. The methodology, based on Theoretical Dynamic Learning (TDL), combines practical applications, theory, and collaborative tools supported by AI.

In the analysis of results, a significant increase in the course pass rate was observed, reaching 88% in the experimental group compared to 64% in the control group that used traditional methods. Practical activities, such as MATLAB-based workshops, fostered meaningful learning by connecting mathematical concepts with real-world problems.

The findings suggest that implementing AI not only enhances the understanding of abstract concepts but also promotes collaborative work and prepares students for advanced professional challenges. This innovative approach presents opportunities to replicate and expand the methodology in other disciplines and educational levels.