A Case Study of Applying the Classification Task for Students' Performance Prediction

Detalhes bibliográficos
Autor(a) principal: Guerra, M. S.
Data de Publicação: 2018
Outros Autores: Asseiss Neto, H., Oliveira, S. A. [UNESP]
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/160101
Resumo: This paper presents a study involving the application of data mining techniques for extracting knowledge from the academic database of the Federal Institute of Mato Grosso do Sul (IFMS). The main goal is the prediction of students' performance on specific classes of the Internet Systems course. Extra students' information such as age and gender are also considered. Knowledge Discovery in Databases (KDD) is described and its steps are applied in this study. The classification task is used to generate decision trees that are tested on different datasets. The results show a success rate of 75.8% on the classification of new and unknown students based on the decision trees models generated.
id UNSP_e8d1a25ba3a1ec5b7367f66814c3d1de
oai_identifier_str oai:repositorio.unesp.br:11449/160101
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling A Case Study of Applying the Classification Task for Students' Performance Predictiondata miningclassification taskacademic databaseThis paper presents a study involving the application of data mining techniques for extracting knowledge from the academic database of the Federal Institute of Mato Grosso do Sul (IFMS). The main goal is the prediction of students' performance on specific classes of the Internet Systems course. Extra students' information such as age and gender are also considered. Knowledge Discovery in Databases (KDD) is described and its steps are applied in this study. The classification task is used to generate decision trees that are tested on different datasets. The results show a success rate of 75.8% on the classification of new and unknown students based on the decision trees models generated.Inst Fed Mato Grosso Do Sul, Tres Lagoas, MS, BrazilUniv Estadual Paulista, Ilha Solteira, SP, BrazilUniv Estadual Paulista, Ilha Solteira, SP, BrazilIeee-inst Electrical Electronics Engineers IncInst Fed Mato Grosso Do SulUniversidade Estadual Paulista (Unesp)Guerra, M. S.Asseiss Neto, H.Oliveira, S. A. [UNESP]2018-11-26T15:47:29Z2018-11-26T15:47:29Z2018-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article172-177application/pdfIeee Latin America Transactions. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 1, p. 172-177, 2018.1548-0992http://hdl.handle.net/11449/160101WOS:000425326100026WOS000425326100026.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporIeee Latin America Transactions0,253info:eu-repo/semantics/openAccess2023-11-29T06:14:19Zoai:repositorio.unesp.br:11449/160101Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:01:56.581504Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A Case Study of Applying the Classification Task for Students' Performance Prediction
title A Case Study of Applying the Classification Task for Students' Performance Prediction
spellingShingle A Case Study of Applying the Classification Task for Students' Performance Prediction
Guerra, M. S.
data mining
classification task
academic database
title_short A Case Study of Applying the Classification Task for Students' Performance Prediction
title_full A Case Study of Applying the Classification Task for Students' Performance Prediction
title_fullStr A Case Study of Applying the Classification Task for Students' Performance Prediction
title_full_unstemmed A Case Study of Applying the Classification Task for Students' Performance Prediction
title_sort A Case Study of Applying the Classification Task for Students' Performance Prediction
author Guerra, M. S.
author_facet Guerra, M. S.
Asseiss Neto, H.
Oliveira, S. A. [UNESP]
author_role author
author2 Asseiss Neto, H.
Oliveira, S. A. [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Inst Fed Mato Grosso Do Sul
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Guerra, M. S.
Asseiss Neto, H.
Oliveira, S. A. [UNESP]
dc.subject.por.fl_str_mv data mining
classification task
academic database
topic data mining
classification task
academic database
description This paper presents a study involving the application of data mining techniques for extracting knowledge from the academic database of the Federal Institute of Mato Grosso do Sul (IFMS). The main goal is the prediction of students' performance on specific classes of the Internet Systems course. Extra students' information such as age and gender are also considered. Knowledge Discovery in Databases (KDD) is described and its steps are applied in this study. The classification task is used to generate decision trees that are tested on different datasets. The results show a success rate of 75.8% on the classification of new and unknown students based on the decision trees models generated.
publishDate 2018
dc.date.none.fl_str_mv 2018-11-26T15:47:29Z
2018-11-26T15:47:29Z
2018-01-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Ieee Latin America Transactions. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 1, p. 172-177, 2018.
1548-0992
http://hdl.handle.net/11449/160101
WOS:000425326100026
WOS000425326100026.pdf
identifier_str_mv Ieee Latin America Transactions. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 16, n. 1, p. 172-177, 2018.
1548-0992
WOS:000425326100026
WOS000425326100026.pdf
url http://hdl.handle.net/11449/160101
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv Ieee Latin America Transactions
0,253
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 172-177
application/pdf
dc.publisher.none.fl_str_mv Ieee-inst Electrical Electronics Engineers Inc
publisher.none.fl_str_mv Ieee-inst Electrical Electronics Engineers Inc
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808129014294904832

Registros relacionados