Enfoque de análisis de datos visual - predictivo para el desempeño académico de los estudiantes de una universidad peruana
The academic success of university students is a result that depends in a multi-factorial way on the aspects related to the student and the career itself. In this work, we carry out a visual analysis of the data to obtain relevant information regarding the academic performance of students from a Per...
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| Otros Autores: | |
| Formato: | Tesis de maestría |
| Lenguaje: | inglés |
| Publicado: |
Universidad Peruana Unión
2021
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| Materias: | |
| Acceso en línea: | Enlace permanente (DOI o Handle) |
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| _version_ | 1881510080368607232 |
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| author | Orrego Granados, David Leandro |
| author2 | Lopez Gonzales, Javier Linkolk |
| author_browse | Lopez Gonzales, Javier Linkolk Orrego Granados, David Leandro |
| author_facet | Lopez Gonzales, Javier Linkolk Orrego Granados, David Leandro |
| author_sort | Orrego Granados, David Leandro |
| collection | Repositorio institucional |
| description | The academic success of university students is a result that depends in a multi-factorial way on the aspects related to the student and the career itself. In this work, we carry out a visual analysis of the data to obtain relevant information regarding the academic performance of students from a Peruvian university. This study was complemented with the construction of machine learning models to provide a predictive model of the students’ academic success. In specific, the XGBoost Machine Learning method achieved a performance of up to 91.5% of Accuracy. In this sense, this study offers a novel visual-predictive data analysis approach as a valuable tool for developing and targeting policies to support students with lower academic performance or to stimulate advanced students. The results obtained allow us to identify the relevant variables associated with the students’ academic performances. Moreover, we were able to give some insight into the academic situation of the different careers of the University. |
| escuela_str_mv | Escuela de Posgrado |
| format | info:eu-repo/semantics/masterThesis |
| id | oai:repositorio.upeu.edu.pe:20.500.12840/4892 |
| institution | UPeU |
| language | English |
| linea_str_mv | Inteligencia de Negocios |
| ocde_area_str_mv | Ingeniería y tecnología |
| ocde_disciplina_str_mv | Ingeniería eléctrica, electrónica e informática |
| ocde_str_mv | 2.02.04 |
| programa_nombre_str_mv | Maestría en Ingeniería de Sistemas con Mención en Dirección y Gestión en Tecnologías de Información |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Universidad Peruana Unión |
| publisherStr | Universidad Peruana Unión |
| record_format | dspace |
| sede_str_mv | Lima |
| spelling | Enfoque de análisis de datos visual - predictivo para el desempeño académico de los estudiantes de una universidad peruana Visual-predictive data analysis approach for the academic performance of students from a Peruvian university Orrego Granados, David Leandro Lopez Gonzales, Javier Linkolk Students Performances Learning analytics Educational Data Mining Business intelligence in education Machine learning The academic success of university students is a result that depends in a multi-factorial way on the aspects related to the student and the career itself. In this work, we carry out a visual analysis of the data to obtain relevant information regarding the academic performance of students from a Peruvian university. This study was complemented with the construction of machine learning models to provide a predictive model of the students’ academic success. In specific, the XGBoost Machine Learning method achieved a performance of up to 91.5% of Accuracy. In this sense, this study offers a novel visual-predictive data analysis approach as a valuable tool for developing and targeting policies to support students with lower academic performance or to stimulate advanced students. The results obtained allow us to identify the relevant variables associated with the students’ academic performances. Moreover, we were able to give some insight into the academic situation of the different careers of the University. 2021-10-12 2021-10-25T17:14:20Z 2021-10-25T17:14:20Z info:eu-repo/semantics/masterThesis https://hdl.handle.net/20.500.12840/4892 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/3.0/es/ application/pdf Universidad Peruana Unión PE oai:repositorio.upeu.edu.pe:20.500.12840/4892 2026-11-10T17:45:09Z |
| spellingShingle | Students Performances Learning analytics Educational Data Mining Business intelligence in education Machine learning Orrego Granados, David Leandro Enfoque de análisis de datos visual - predictivo para el desempeño académico de los estudiantes de una universidad peruana |
| title | Enfoque de análisis de datos visual - predictivo para el desempeño académico de los estudiantes de una universidad peruana |
| title_full | Enfoque de análisis de datos visual - predictivo para el desempeño académico de los estudiantes de una universidad peruana |
| title_fullStr | Enfoque de análisis de datos visual - predictivo para el desempeño académico de los estudiantes de una universidad peruana |
| title_full_unstemmed | Enfoque de análisis de datos visual - predictivo para el desempeño académico de los estudiantes de una universidad peruana |
| title_short | Enfoque de análisis de datos visual - predictivo para el desempeño académico de los estudiantes de una universidad peruana |
| title_sort | enfoque de analisis de datos visual predictivo para el desempeno academico de los estudiantes de una universidad peruana |
| topic | Students Performances Learning analytics Educational Data Mining Business intelligence in education Machine learning |
| topic_facet | Students Performances Learning analytics Educational Data Mining Business intelligence in education Machine learning |
| url | https://hdl.handle.net/20.500.12840/4892 |
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