Bibliographic citations
Mamani, A., (2024). Análisis de factores institucionales del rendimiento académico en la Universidad Tecnológica de los Andes, mediante discriminante lineal y arboles de decisión-2023 [Universidad Andina del Cusco]. https://hdl.handle.net/20.500.12557/7208
Mamani, A., Análisis de factores institucionales del rendimiento académico en la Universidad Tecnológica de los Andes, mediante discriminante lineal y arboles de decisión-2023 []. PE: Universidad Andina del Cusco; 2024. https://hdl.handle.net/20.500.12557/7208
@mastersthesis{renati/1123182,
title = "Análisis de factores institucionales del rendimiento académico en la Universidad Tecnológica de los Andes, mediante discriminante lineal y arboles de decisión-2023",
author = "Mamani Torres, Alfredo Crisologo",
publisher = "Universidad Andina del Cusco",
year = "2024"
}
The objective of this research was to analyze the institutional factors that are associated with academic performance at the Universidad Tecnológica de los Andes, through the techniques of linear discriminant analysis and decision trees-2023, statistical techniques such as discriminant analysis and the algorithm of decision trees were applied to meet the objective outlined, the research had a quantitative approach, correlational scope, while the research design is nonexperimental, cross-sectional type; likewise the study population are university students enrolled in the semester 2023-1 of the Universidad Tecnológica de los Andes. Obtaining a sample of 355 students. The data revealed a mixed picture of the academic performance of students in semester 20231. On the one hand, it is encouraging to note that 70.1% of the students have succeeded in their studies, while the failures suggest the existence of a considerable proportion of students who face academic challenges or who may be experiencing personal or motivational difficulties. The student environment factor is the most important, followed by the student-teacher relationship and finally institutional conditions, it is also observed that age has no impact on the discriminant function; the performance of the model has been accurate in its predictions by approximately 79.15%. From the application of the decision tree algorithm on the data collected from the students of the Universidad Tecnológica de los Andes, Cusco branch, it was found that the student environment factor is the most important factor in deciding whether a student will be classified as pass or fail. The second important factor is the institutional conditions scores, the third factor in order of importance is the student-teacher relationship, the algorithm performance (accuracy) is 76.9%.
This item is licensed under a Creative Commons License