Impact of Knowledge in Linear Algebra on Academic Performance in Quantitative Optimization Methods: A Data Analytical Approach

Autores/as

  • Alba Zulay Cardenas Escobar Universidad Tecnológica de Bolívar - (CO), Colombia, Colombia
  • Fabian Alfonso Gazabón Arrieta Universidad Tecnológica de Bolívar - (CO), Colombia, Colombia
  • Armando Antonio Diaz Mendoza Universidad Tecnológica de Bolívar - (CO), Colombia, Colombia
  • Holmán Ospina Mateus Universidad Tecnológica de Bolívar - (CO), Colombia, Colombia

DOI:

https://doi.org/10.18687/LACCEI2024.1.1.1831

Palabras clave:

Linear algebra, Optimization, Industrial engineering, Prerequisites, Student performance

Resumen

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.

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Publicado

2024-04-09

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Articles

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

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