Academic performance profiles : a descriptive model based on data mining
- Autores
- La Red Martínez, David Luis; Karanik, Marcelo; Giovaninni, Mirta Eve; Pinto, Noelia
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Academic performance is a critical factor considering that poor academic performance is often associated with a high attrition rate. This has been observed in subjects of the first level of Information Systems Engineering career (ISI) of the National Technological University, Resistencia Regional Faculty (UTN-FRRe), situated in Resistencia city, province of Chaco, Argentine. Among them is Algorithms and Data Structures, where the poor academic performance is observed at very high rates (between 60% and about 80% in recent years). In this paper, we propose the use of data mining techniques on performance information for students of the subject mentioned, in order to characterize the profiles of successful students (good academic performance) and those that are not (poor performance). In the future, the determination of these profiles would allow us to define specific actions to reverse poor academic performance, once detected the variables associated with it. This article describes the data models and data mining used and the main results are also commented
Fil: La Red Martínez, David Luis. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina
Fil: Karanik, Marcelo. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina
Fil: Giovaninni, Mirta Eve. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina
Fil: Pinto, Noelia. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina
Peer Reviewed - Materia
-
academic performance profiles
data warehouses
data mining
knowledge discovery in databases - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-nd/3.0/us/
- Repositorio
.jpg)
- Institución
- Universidad Tecnológica Nacional
- OAI Identificador
- oai:ria.utn.edu.ar:20.500.12272/1028
Ver los metadatos del registro completo
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Academic performance profiles : a descriptive model based on data miningLa Red Martínez, David LuisKaranik, MarceloGiovaninni, Mirta EvePinto, Noeliaacademic performance profilesdata warehousesdata miningknowledge discovery in databasesAcademic performance is a critical factor considering that poor academic performance is often associated with a high attrition rate. This has been observed in subjects of the first level of Information Systems Engineering career (ISI) of the National Technological University, Resistencia Regional Faculty (UTN-FRRe), situated in Resistencia city, province of Chaco, Argentine. Among them is Algorithms and Data Structures, where the poor academic performance is observed at very high rates (between 60% and about 80% in recent years). In this paper, we propose the use of data mining techniques on performance information for students of the subject mentioned, in order to characterize the profiles of successful students (good academic performance) and those that are not (poor performance). In the future, the determination of these profiles would allow us to define specific actions to reverse poor academic performance, once detected the variables associated with it. This article describes the data models and data mining used and the main results are also commentedFil: La Red Martínez, David Luis. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; ArgentinaFil: Karanik, Marcelo. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; ArgentinaFil: Giovaninni, Mirta Eve. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; ArgentinaFil: Pinto, Noelia. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; ArgentinaPeer Reviewed2016-09-28T12:22:45Z2016-09-28T12:22:45Z2015-03-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdf1857-7881http://hdl.handle.net/20.500.12272/1028enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/3.0/us/Acceso AbiertoAttribution-NonCommercial-NoDerivs 3.0 United Statesreponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2025-10-16T10:10:40Zoai:ria.utn.edu.ar:20.500.12272/1028instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2025-10-16 10:10:40.974Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse |
| dc.title.none.fl_str_mv |
Academic performance profiles : a descriptive model based on data mining |
| title |
Academic performance profiles : a descriptive model based on data mining |
| spellingShingle |
Academic performance profiles : a descriptive model based on data mining La Red Martínez, David Luis academic performance profiles data warehouses data mining knowledge discovery in databases |
| title_short |
Academic performance profiles : a descriptive model based on data mining |
| title_full |
Academic performance profiles : a descriptive model based on data mining |
| title_fullStr |
Academic performance profiles : a descriptive model based on data mining |
| title_full_unstemmed |
Academic performance profiles : a descriptive model based on data mining |
| title_sort |
Academic performance profiles : a descriptive model based on data mining |
| dc.creator.none.fl_str_mv |
La Red Martínez, David Luis Karanik, Marcelo Giovaninni, Mirta Eve Pinto, Noelia |
| author |
La Red Martínez, David Luis |
| author_facet |
La Red Martínez, David Luis Karanik, Marcelo Giovaninni, Mirta Eve Pinto, Noelia |
| author_role |
author |
| author2 |
Karanik, Marcelo Giovaninni, Mirta Eve Pinto, Noelia |
| author2_role |
author author author |
| dc.subject.none.fl_str_mv |
academic performance profiles data warehouses data mining knowledge discovery in databases |
| topic |
academic performance profiles data warehouses data mining knowledge discovery in databases |
| dc.description.none.fl_txt_mv |
Academic performance is a critical factor considering that poor academic performance is often associated with a high attrition rate. This has been observed in subjects of the first level of Information Systems Engineering career (ISI) of the National Technological University, Resistencia Regional Faculty (UTN-FRRe), situated in Resistencia city, province of Chaco, Argentine. Among them is Algorithms and Data Structures, where the poor academic performance is observed at very high rates (between 60% and about 80% in recent years). In this paper, we propose the use of data mining techniques on performance information for students of the subject mentioned, in order to characterize the profiles of successful students (good academic performance) and those that are not (poor performance). In the future, the determination of these profiles would allow us to define specific actions to reverse poor academic performance, once detected the variables associated with it. This article describes the data models and data mining used and the main results are also commented Fil: La Red Martínez, David Luis. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina Fil: Karanik, Marcelo. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina Fil: Giovaninni, Mirta Eve. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina Fil: Pinto, Noelia. Universidad Tecnológica Nacional. Facultad Regional Resistencia. Grupo de Investigación Educativa sobre Ingeniería; Argentina Peer Reviewed |
| description |
Academic performance is a critical factor considering that poor academic performance is often associated with a high attrition rate. This has been observed in subjects of the first level of Information Systems Engineering career (ISI) of the National Technological University, Resistencia Regional Faculty (UTN-FRRe), situated in Resistencia city, province of Chaco, Argentine. Among them is Algorithms and Data Structures, where the poor academic performance is observed at very high rates (between 60% and about 80% in recent years). In this paper, we propose the use of data mining techniques on performance information for students of the subject mentioned, in order to characterize the profiles of successful students (good academic performance) and those that are not (poor performance). In the future, the determination of these profiles would allow us to define specific actions to reverse poor academic performance, once detected the variables associated with it. This article describes the data models and data mining used and the main results are also commented |
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2015 |
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2015-03-10 2016-09-28T12:22:45Z 2016-09-28T12:22:45Z |
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eng |
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