Impact of Knowledge in Linear Algebra on Academic Performance in Quantitative Optimization Methods: A Data Analytical Approach (#1831)
Read ArticleDate of Conference
July 17-19, 2024
Published In
"Sustainable Engineering for a Diverse, Equitable, and Inclusive Future at the Service of Education, Research, and Industry for a Society 5.0."
Location of Conference
Costa Rica
Authors
Cardenas Escobar, Alba Zulay
Gazabón Arrieta, Fabian Alfonso
Diaz Mendoza, Armando Antonio
Ospina Mateus, Holmán
Abstract
The study focuses on the importance of linear algebra prerequisites for performance in the optimization subject in industrial engineering students. It is highlighted that mastery of linear algebra is essential to understand and solve complex engineering problems. The fundamental reasons that justify the relevance of this analysis are examined, such as the improvement of the curricular framework, decision-making on curricular advancement, improvement of student performance and alignment with the needs of the labor market. The methodology of the study includes the selection of a sample of students who took both subjects, the definition of relevant variables and the statistical analysis to evaluate the relationship between performance in linear algebra and optimization. A logistic regression will be applied to predict the probability of success in the optimization subject based on various variables.