Early detection of the academic performance of university students from first year through discriminant analysis
Descripción del Articulo
This work aims to identify students who would only pass at most two out of five enrolled courses from semester 2016-2 of the General Studies Program of Universidad de Lima. The study is based on predictive models constructed with data collected on semester 2016-1 through discriminant analysis. The s...
| Autores: | , , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2017 |
| Institución: | Universidad de Lima |
| Repositorio: | Revistas - Universidad de Lima |
| Lenguaje: | español |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/1791 |
| Enlace del recurso: | https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/1791 |
| Nivel de acceso: | acceso abierto |
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Early detection of the academic performance of university students from first year through discriminant analysisDetección temprana del rendimiento académico de estudiantes universitarios de primer ciclo mediante el análisis discriminanteSaavedra-Sánchez-Dávila, LutzgardoRamos-Ramírez, Julio CésarMitacc-Meza, MáximoDel-Águila-Ríos, Víctor RicardoThis work aims to identify students who would only pass at most two out of five enrolled courses from semester 2016-2 of the General Studies Program of Universidad de Lima. The study is based on predictive models constructed with data collected on semester 2016-1 through discriminant analysis. The student’s population was divided in three domains of study. Then, independent predictive models for academic performance were constructed using Fisher’s classification functions which were evaluated by performance indicators and the Receiver Operating Characteristic curve (ROC).En este estudio se ha procurado identificar a los ingresantes que aprobarían a lo más dos de los cinco cursos en los que se matricularon para el semestre 2016-2 del Programa de Estudios Generales de la Universidad de Lima. Dicha identificación se basó en modelos de predicción, construidos con datos del semestre 2016-1 mediante el uso de análisis discriminante. La población de ingresantes se dividió en tres dominios de estudio y se construyeron modelos independientes de predicción para el rendimiento académico utilizando las funciones de clasificación de Fisher, evaluadas mediante los indicadores de rendimiento y la curva Receiver Operating Characteristic (ROC).Universidad de Lima2017-12-21info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/179110.26439/ing.ind2017.n035.1791Ingeniería Industrial; No. 035 (2017); 77-98Ingeniería Industrial; Núm. 035 (2017); 77-982523-63261025-992910.26439/ing.ind2017.n035reponame:Revistas - Universidad de Limainstname:Universidad de Limainstacron:ULIMAspahttps://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/1791/1807info:eu-repo/semantics/openAccessoai:ojs.pkp.sfu.ca:article/17912023-07-21T20:49:45Z |
| dc.title.none.fl_str_mv |
Early detection of the academic performance of university students from first year through discriminant analysis Detección temprana del rendimiento académico de estudiantes universitarios de primer ciclo mediante el análisis discriminante |
| title |
Early detection of the academic performance of university students from first year through discriminant analysis |
| spellingShingle |
Early detection of the academic performance of university students from first year through discriminant analysis Saavedra-Sánchez-Dávila, Lutzgardo |
| title_short |
Early detection of the academic performance of university students from first year through discriminant analysis |
| title_full |
Early detection of the academic performance of university students from first year through discriminant analysis |
| title_fullStr |
Early detection of the academic performance of university students from first year through discriminant analysis |
| title_full_unstemmed |
Early detection of the academic performance of university students from first year through discriminant analysis |
| title_sort |
Early detection of the academic performance of university students from first year through discriminant analysis |
| dc.creator.none.fl_str_mv |
Saavedra-Sánchez-Dávila, Lutzgardo Ramos-Ramírez, Julio César Mitacc-Meza, Máximo Del-Águila-Ríos, Víctor Ricardo |
| author |
Saavedra-Sánchez-Dávila, Lutzgardo |
| author_facet |
Saavedra-Sánchez-Dávila, Lutzgardo Ramos-Ramírez, Julio César Mitacc-Meza, Máximo Del-Águila-Ríos, Víctor Ricardo |
| author_role |
author |
| author2 |
Ramos-Ramírez, Julio César Mitacc-Meza, Máximo Del-Águila-Ríos, Víctor Ricardo |
| author2_role |
author author author |
| description |
This work aims to identify students who would only pass at most two out of five enrolled courses from semester 2016-2 of the General Studies Program of Universidad de Lima. The study is based on predictive models constructed with data collected on semester 2016-1 through discriminant analysis. The student’s population was divided in three domains of study. Then, independent predictive models for academic performance were constructed using Fisher’s classification functions which were evaluated by performance indicators and the Receiver Operating Characteristic curve (ROC). |
| publishDate |
2017 |
| dc.date.none.fl_str_mv |
2017-12-21 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/1791 10.26439/ing.ind2017.n035.1791 |
| url |
https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/1791 |
| identifier_str_mv |
10.26439/ing.ind2017.n035.1791 |
| dc.language.none.fl_str_mv |
spa |
| language |
spa |
| dc.relation.none.fl_str_mv |
https://revistas.ulima.edu.pe/index.php/Ingenieria_industrial/article/view/1791/1807 |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Universidad de Lima |
| publisher.none.fl_str_mv |
Universidad de Lima |
| dc.source.none.fl_str_mv |
Ingeniería Industrial; No. 035 (2017); 77-98 Ingeniería Industrial; Núm. 035 (2017); 77-98 2523-6326 1025-9929 10.26439/ing.ind2017.n035 reponame:Revistas - Universidad de Lima instname:Universidad de Lima instacron:ULIMA |
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Universidad de Lima |
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ULIMA |
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ULIMA |
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Revistas - Universidad de Lima |
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Revistas - Universidad de Lima |
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1847425934582349824 |
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13.402391 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
