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
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/32363
Ver los metadatos del registro completo
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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. |
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2013 |
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2013-10 |
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