Predicting academic performance using automatic learning techniques: A review of the scientific literature

Descripción del Articulo

El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
Detalles Bibliográficos
Autores: Molina-Astorayme, Jacob, Cabanillas-Carbonell, Michael
Formato: objeto de conferencia
Fecha de Publicación:2020
Institución:Universidad Privada del Norte
Repositorio:UPN-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.upn.edu.pe:11537/26929
Enlace del recurso:https://hdl.handle.net/11537/26929
https://doi.org/10.1109/EIRCON51178.2020.9254065
Nivel de acceso:acceso abierto
Materia:Rendimiento académico
Inteligencia artificial
Enseñanza con ayuda de computadoras
Educación superior
https://purl.org/pe-repo/ocde/ford#2.02.04
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dc.title.es_PE.fl_str_mv Predicting academic performance using automatic learning techniques: A review of the scientific literature
title Predicting academic performance using automatic learning techniques: A review of the scientific literature
spellingShingle Predicting academic performance using automatic learning techniques: A review of the scientific literature
Molina-Astorayme, Jacob
Rendimiento académico
Inteligencia artificial
Enseñanza con ayuda de computadoras
Educación superior
https://purl.org/pe-repo/ocde/ford#2.02.04
title_short Predicting academic performance using automatic learning techniques: A review of the scientific literature
title_full Predicting academic performance using automatic learning techniques: A review of the scientific literature
title_fullStr Predicting academic performance using automatic learning techniques: A review of the scientific literature
title_full_unstemmed Predicting academic performance using automatic learning techniques: A review of the scientific literature
title_sort Predicting academic performance using automatic learning techniques: A review of the scientific literature
author Molina-Astorayme, Jacob
author_facet Molina-Astorayme, Jacob
Cabanillas-Carbonell, Michael
author_role author
author2 Cabanillas-Carbonell, Michael
author2_role author
dc.contributor.author.fl_str_mv Molina-Astorayme, Jacob
Cabanillas-Carbonell, Michael
dc.subject.es_PE.fl_str_mv Rendimiento académico
Inteligencia artificial
Enseñanza con ayuda de computadoras
Educación superior
topic Rendimiento académico
Inteligencia artificial
Enseñanza con ayuda de computadoras
Educación superior
https://purl.org/pe-repo/ocde/ford#2.02.04
dc.subject.ocde.es_PE.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.02.04
description El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2021-06-22T22:31:01Z
dc.date.available.none.fl_str_mv 2021-06-22T22:31:01Z
dc.date.issued.fl_str_mv 2020-11-17
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/conferenceObject
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dc.identifier.citation.es_PE.fl_str_mv Molina, J. & Cabanillas, M. (2020). Predicting academic performance using automatic learning techniques: A review of the scientific literature. Engineering International Research Conference (EIRCON), 1-4. https://doi.org/10.1109/EIRCON51178.2020.9254065
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/11537/26929
dc.identifier.journal.es_PE.fl_str_mv Engineering International Research Conference (EIRCON)
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1109/EIRCON51178.2020.9254065
identifier_str_mv Molina, J. & Cabanillas, M. (2020). Predicting academic performance using automatic learning techniques: A review of the scientific literature. Engineering International Research Conference (EIRCON), 1-4. https://doi.org/10.1109/EIRCON51178.2020.9254065
Engineering International Research Conference (EIRCON)
url https://hdl.handle.net/11537/26929
https://doi.org/10.1109/EIRCON51178.2020.9254065
dc.language.iso.es_PE.fl_str_mv eng
language eng
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eu_rights_str_mv openAccess
rights_invalid_str_mv Atribución-NoComercial-CompartirIgual 3.0 Estados Unidos de América
https://creativecommons.org/licenses/by-nc-sa/3.0/us/
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dc.publisher.es_PE.fl_str_mv IEEE
dc.publisher.country.es_PE.fl_str_mv PE
dc.source.es_PE.fl_str_mv Universidad Privada del Norte
Repositorio Institucional - UPN
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spelling Molina-Astorayme, JacobCabanillas-Carbonell, Michael2021-06-22T22:31:01Z2021-06-22T22:31:01Z2020-11-17Molina, J. & Cabanillas, M. (2020). Predicting academic performance using automatic learning techniques: A review of the scientific literature. Engineering International Research Conference (EIRCON), 1-4. https://doi.org/10.1109/EIRCON51178.2020.9254065https://hdl.handle.net/11537/26929Engineering International Research Conference (EIRCON)https://doi.org/10.1109/EIRCON51178.2020.9254065El texto completo de este trabajo no está disponible en el Repositorio Académico UPN por restricciones de la casa editorial donde ha sido publicado.ABSTRACT Considering the problems and challenges faced by educational institutions in analyzing student performance and improving their educational management, the various automatic learning techniques were examined, which will allow them to generate accurate predictions through the data collected from their students. The present research is a systematic review of literature based on the articles published in IEEE Xplore, Scopus, Science Direct and Scielo where 80 articles were found that according to our inclusion and exclusion criteria were systematized 47. We observed the various techniques used for automatic learning to develop predictive models based on academic performance, we can determine that the most used techniques were the classification. In this way, automatic learning techniques will allow educational institutions to publicize the academic performance of their students in order to improve the educational quality they offer.Revisión por paresLos Olivosapplication/pdfengIEEEPEinfo:eu-repo/semantics/openAccessAtribución-NoComercial-CompartirIgual 3.0 Estados Unidos de Américahttps://creativecommons.org/licenses/by-nc-sa/3.0/us/Universidad Privada del NorteRepositorio Institucional - UPNreponame:UPN-Institucionalinstname:Universidad Privada del Norteinstacron:UPNRendimiento académicoInteligencia artificialEnseñanza con ayuda de computadorasEducación superiorhttps://purl.org/pe-repo/ocde/ford#2.02.04Predicting academic performance using automatic learning techniques: A review of the scientific literatureinfo:eu-repo/semantics/conferenceObjectCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-81037https://repositorio.upn.edu.pe/bitstream/11537/26929/1/license_rdf80294ba9ff4c5b4f07812ee200fbc42fMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.upn.edu.pe/bitstream/11537/26929/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD5211537/26929oai:repositorio.upn.edu.pe:11537/269292021-06-22 17:31:06.722Repositorio Institucional UPNjordan.rivero@upn.edu.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Predicting academic performance using automatic learning techniques: A review of the scientific literature
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