Characterization of university drop-out at UNRN using data mining. A study case

Autores
Formia, Sonia; Lanzarini, Laura Cristina; Hasperué, Waldo
Año de publicación
2013
Idioma
español castellano
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
At the National University of Río Negro (UNRN), and its Atlantic Coast Delegation in particular, it is an increasing concern for the courses corresponding to the Bachelor's Degree in Systems, the drop-out and crumbling rates observed in the first four years of the Institution. This paper describes the process of identifying the most relevant features of the problem through which, using Data Mining (DM) techniques, a college drop-out model can be obtained for the academic unit mentioned above. In order to identify the most relevant features, after processing the data we will analyze attribute projections for the expected classes or responses. The results of its application to the student data from the courses of the UNRN have been satisfactory, which allows making some recommendations aimed at reducing the percentage of students who drop put from their courses.
XI Workshop tecnología informática aplicada en educación
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
attribute selection
attribute projection
data mining
Computer Uses in Education
university drop-out
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/32363

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network_name_str SEDICI (UNLP)
spelling Characterization of university drop-out at UNRN using data mining. A study caseFormia, SoniaLanzarini, Laura CristinaHasperué, WaldoCiencias Informáticasattribute selectionattribute projectiondata miningComputer Uses in Educationuniversity drop-outAt the National University of Río Negro (UNRN), and its Atlantic Coast Delegation in particular, it is an increasing concern for the courses corresponding to the Bachelor's Degree in Systems, the drop-out and crumbling rates observed in the first four years of the Institution. This paper describes the process of identifying the most relevant features of the problem through which, using Data Mining (DM) techniques, a college drop-out model can be obtained for the academic unit mentioned above. In order to identify the most relevant features, after processing the data we will analyze attribute projections for the expected classes or responses. The results of its application to the student data from the courses of the UNRN have been satisfactory, which allows making some recommendations aimed at reducing the percentage of students who drop put from their courses.XI Workshop tecnología informática aplicada en educaciónRed de Universidades con Carreras en Informática (RedUNCI)2013-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/32363spainfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:39:51Zoai:sedici.unlp.edu.ar:10915/32363Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:39:51.84SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Characterization of university drop-out at UNRN using data mining. A study case
title Characterization of university drop-out at UNRN using data mining. A study case
spellingShingle Characterization of university drop-out at UNRN using data mining. A study case
Formia, Sonia
Ciencias Informáticas
attribute selection
attribute projection
data mining
Computer Uses in Education
university drop-out
title_short Characterization of university drop-out at UNRN using data mining. A study case
title_full Characterization of university drop-out at UNRN using data mining. A study case
title_fullStr Characterization of university drop-out at UNRN using data mining. A study case
title_full_unstemmed Characterization of university drop-out at UNRN using data mining. A study case
title_sort Characterization of university drop-out at UNRN using data mining. A study case
dc.creator.none.fl_str_mv Formia, Sonia
Lanzarini, Laura Cristina
Hasperué, Waldo
author Formia, Sonia
author_facet Formia, Sonia
Lanzarini, Laura Cristina
Hasperué, Waldo
author_role author
author2 Lanzarini, Laura Cristina
Hasperué, Waldo
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
attribute selection
attribute projection
data mining
Computer Uses in Education
university drop-out
topic Ciencias Informáticas
attribute selection
attribute projection
data mining
Computer Uses in Education
university drop-out
dc.description.none.fl_txt_mv At the National University of Río Negro (UNRN), and its Atlantic Coast Delegation in particular, it is an increasing concern for the courses corresponding to the Bachelor's Degree in Systems, the drop-out and crumbling rates observed in the first four years of the Institution. This paper describes the process of identifying the most relevant features of the problem through which, using Data Mining (DM) techniques, a college drop-out model can be obtained for the academic unit mentioned above. In order to identify the most relevant features, after processing the data we will analyze attribute projections for the expected classes or responses. The results of its application to the student data from the courses of the UNRN have been satisfactory, which allows making some recommendations aimed at reducing the percentage of students who drop put from their courses.
XI Workshop tecnología informática aplicada en educación
Red de Universidades con Carreras en Informática (RedUNCI)
description At the National University of Río Negro (UNRN), and its Atlantic Coast Delegation in particular, it is an increasing concern for the courses corresponding to the Bachelor's Degree in Systems, the drop-out and crumbling rates observed in the first four years of the Institution. This paper describes the process of identifying the most relevant features of the problem through which, using Data Mining (DM) techniques, a college drop-out model can be obtained for the academic unit mentioned above. In order to identify the most relevant features, after processing the data we will analyze attribute projections for the expected classes or responses. The results of its application to the student data from the courses of the UNRN have been satisfactory, which allows making some recommendations aimed at reducing the percentage of students who drop put from their courses.
publishDate 2013
dc.date.none.fl_str_mv 2013-10
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