Impact of Knowledge in Linear Algebra on Academic Performance in Quantitative Optimization Methods: A Data Analytical Approach
DOI:
https://doi.org/10.18687/LACCEI2024.1.1.1831Palabras clave:
Linear algebra, Optimization, Industrial engineering, Prerequisites, Student performanceResumen
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.Descargas
Publicado
2024-07-27
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Derechos de autor 2024 LACCEI
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Esta obra está bajo una Licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional.
LACCEI conserva el copyright de todos los artículos publicados bajo los términos de su acuerdo de transferencia de copyright. Como titular del copyright, LACCEI distribuye los artículos al público bajo la Licencia Internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0 (CC BY-NC-SA 4.0).
Cómo citar
Cardenas Escobar, A. Z., Gazabón Arrieta, F. A., Diaz Mendoza, A. A., & Ospina Mateus, H. (2024). Impact of Knowledge in Linear Algebra on Academic Performance in Quantitative Optimization Methods: A Data Analytical Approach. LACCEI, 1(10). https://doi.org/10.18687/LACCEI2024.1.1.1831