Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio
Autor(a) principal: | |
---|---|
Data de Publicação: | 2023 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UFMA |
Texto Completo: | https://tedebc.ufma.br/jspui/handle/tede/tede/4743 |
Resumo: | In Brazil, the main performance evaluation exam in basic education is the National Secondary Education Examination (ENEM), which is also used to enroll students in higher education. In 2020, with the arrival of COVID-19, basic education institutions needed to change their educational model from face-to-face teaching to the use of distance learning methodologies, which may have affected the quality of education received. Therefore, there is a need to understand the effects that the COVID-19 pandemic caused to ENEM. This master’s thesis aims to identify the main impacts caused by the pandemic on ENEM, considering all of Brazil. To this end, the complete process of Educational Data Mining (MDE) was carried out, based on the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, in ENEM in 5 different years, in order to understand the years pre-pandemic and the first two years of the pandemic. In particular, this study used techniques of descriptive exploratory analysis, correlation and hierarchical grouping to identify the impacts caused on the ENEM. The results show that participants with higher incomes performed better, private schools outperformed other types of schools, the number of present and absentees in the exam was lower in the pandemic years, and there was a change in the socioeconomic characteristics of the participants. . Finally, the pandemic did not negatively impact student performance, but the characteristics of the participants who took the exam changed and the number of absentees and present in the exam was drastically impacted. |
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TELES, Ariel Soareshttp://lattes.cnpq.br/5012476998883237COUTINHO, Luciano Reishttp://lattes.cnpq.br/5901564732655853TELES, Ariel Soareshttp://lattes.cnpq.br/5012476998883237COUTINHO, Luciano Reishttp://lattes.cnpq.br/5901564732655853CABREJOS, Luis Jorge Enrique Riverohttp://lattes.cnpq.br/8534667641706692BRANDÃO, Anarosa Alves Francohttp://lattes.cnpq.br/7369959680190589http://lattes.cnpq.br/6205700748197509WEBER NETO, Nelson2023-06-05T12:17:33Z2023-04-28WEBER NETO, Nelson. Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio. 2023. 79 f. Dissertação (Programa de Pós-Graduação em Ciência Da Computação/CCET) - Universidade Federal do Maranhão, São Luís, 2023.https://tedebc.ufma.br/jspui/handle/tede/tede/4743In Brazil, the main performance evaluation exam in basic education is the National Secondary Education Examination (ENEM), which is also used to enroll students in higher education. In 2020, with the arrival of COVID-19, basic education institutions needed to change their educational model from face-to-face teaching to the use of distance learning methodologies, which may have affected the quality of education received. Therefore, there is a need to understand the effects that the COVID-19 pandemic caused to ENEM. This master’s thesis aims to identify the main impacts caused by the pandemic on ENEM, considering all of Brazil. To this end, the complete process of Educational Data Mining (MDE) was carried out, based on the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, in ENEM in 5 different years, in order to understand the years pre-pandemic and the first two years of the pandemic. In particular, this study used techniques of descriptive exploratory analysis, correlation and hierarchical grouping to identify the impacts caused on the ENEM. The results show that participants with higher incomes performed better, private schools outperformed other types of schools, the number of present and absentees in the exam was lower in the pandemic years, and there was a change in the socioeconomic characteristics of the participants. . Finally, the pandemic did not negatively impact student performance, but the characteristics of the participants who took the exam changed and the number of absentees and present in the exam was drastically impacted.No Brasil, o principal exame de avaliação do desempenho da educação básica é o Exame Nacional do Ensino Médio (ENEM), que também é utilizado para o ingresso de alunos no ensino superior. Em 2020, com a chegada da COVID-19, as instituições de educação básica precisaram mudar seu modelo educacional com ensino presencial para a utilização de metodologias de ensino à distância, o que pode ter afetado a qualidade da educação recebida. Portanto, há uma necessidade por entender os efeitos que a pandemia da COVID- 19 causaram ao ENEM. Esta dissertação de mestrado tem o objetivo de identificar os principais impactos causados pela pandemia no ENEM, considerando todo o Brasil. Para tanto, foi realizado o processo completo de Mineração de Dados Educacionais (MDE), baseado na metodologia Cross Industry Standard Process for Data Mining (CRISP- DM), no ENEM em 5 anos diferentes, a fim de compreender os anos pré-pandemia e os dois primeiros anos da pandemia. Em particular, esse estudo usou técnicas de análise exploratória descritiva, correlação e agrupamento hierárquico para identificar os impactos causados no ENEM. Os resultados mostram que os participantes com maiores rendas tiveram melhor desempenho, as escolas privadas tiveram um desempenho superior aos outros tipos de escolas, o número de presentes e ausentes no exame foi menor nos anos da pandemia, e houve uma mudança nas características socioeconômicas dos participantes. Por fim, a pandemia não impactou negativamente no desempenho dos estudantes, mas as características dos participantes que realizaram o exame mudaram e o número de ausentes e presentes no exame foi drasticamente impactado.Submitted by Jonathan Sousa de Almeida (jonathan.sousa@ufma.br) on 2023-06-05T12:17:33Z No. of bitstreams: 1 NELSONWEBERNETO.pdf: 1846275 bytes, checksum: 2440cfc117d0b57f47956f60e7d405db (MD5)Made available in DSpace on 2023-06-05T12:17:33Z (GMT). No. of bitstreams: 1 NELSONWEBERNETO.pdf: 1846275 bytes, checksum: 2440cfc117d0b57f47956f60e7d405db (MD5) Previous issue date: 2023-04-28application/pdfporUniversidade Federal do MaranhãoPROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIA DA COMPUTAÇÃO/CCETUFMABrasilDEPARTAMENTO DE INFORMÁTICA/CCETmineração de dados educacionais;COVID-19;educação;ENEM;pandemia;análise de dados.data mining;COVID-19;education;ENEM;pandemic;data analysis.Ciência da ComputaçãoEducaçãoMinerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino MédioData mining to understand the impact of the COVID-19 pandemic on the National High School Examinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFMAinstname:Universidade Federal do Maranhão (UFMA)instacron:UFMAORIGINALNELSONWEBERNETO.pdfNELSONWEBERNETO.pdfapplication/pdf1846275http://tedebc.ufma.br:8080/bitstream/tede/4743/2/NELSONWEBERNETO.pdf2440cfc117d0b57f47956f60e7d405dbMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82255http://tedebc.ufma.br:8080/bitstream/tede/4743/1/license.txt97eeade1fce43278e63fe063657f8083MD51tede/47432023-06-05 09:17:33.596oai:tede2: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Biblioteca Digital de Teses e Dissertaçõeshttps://tedebc.ufma.br/jspui/PUBhttp://tedebc.ufma.br:8080/oai/requestrepositorio@ufma.br||repositorio@ufma.bropendoar:21312023-06-05T12:17:33Biblioteca Digital de Teses e Dissertações da UFMA - Universidade Federal do Maranhão (UFMA)false |
dc.title.por.fl_str_mv |
Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio |
dc.title.alternative.eng.fl_str_mv |
Data mining to understand the impact of the COVID-19 pandemic on the National High School Exam |
title |
Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio |
spellingShingle |
Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio WEBER NETO, Nelson mineração de dados educacionais; COVID-19; educação; ENEM; pandemia; análise de dados. data mining; COVID-19; education; ENEM; pandemic; data analysis. Ciência da Computação Educação |
title_short |
Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio |
title_full |
Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio |
title_fullStr |
Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio |
title_full_unstemmed |
Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio |
title_sort |
Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio |
author |
WEBER NETO, Nelson |
author_facet |
WEBER NETO, Nelson |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
TELES, Ariel Soares |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/5012476998883237 |
dc.contributor.advisor-co1.fl_str_mv |
COUTINHO, Luciano Reis |
dc.contributor.advisor-co1Lattes.fl_str_mv |
http://lattes.cnpq.br/5901564732655853 |
dc.contributor.referee1.fl_str_mv |
TELES, Ariel Soares |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/5012476998883237 |
dc.contributor.referee2.fl_str_mv |
COUTINHO, Luciano Reis |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/5901564732655853 |
dc.contributor.referee3.fl_str_mv |
CABREJOS, Luis Jorge Enrique Rivero |
dc.contributor.referee3Lattes.fl_str_mv |
http://lattes.cnpq.br/8534667641706692 |
dc.contributor.referee4.fl_str_mv |
BRANDÃO, Anarosa Alves Franco |
dc.contributor.referee4Lattes.fl_str_mv |
http://lattes.cnpq.br/7369959680190589 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/6205700748197509 |
dc.contributor.author.fl_str_mv |
WEBER NETO, Nelson |
contributor_str_mv |
TELES, Ariel Soares COUTINHO, Luciano Reis TELES, Ariel Soares COUTINHO, Luciano Reis CABREJOS, Luis Jorge Enrique Rivero BRANDÃO, Anarosa Alves Franco |
dc.subject.por.fl_str_mv |
mineração de dados educacionais; COVID-19; educação; ENEM; pandemia; análise de dados. |
topic |
mineração de dados educacionais; COVID-19; educação; ENEM; pandemia; análise de dados. data mining; COVID-19; education; ENEM; pandemic; data analysis. Ciência da Computação Educação |
dc.subject.eng.fl_str_mv |
data mining; COVID-19; education; ENEM; pandemic; data analysis. |
dc.subject.cnpq.fl_str_mv |
Ciência da Computação Educação |
description |
In Brazil, the main performance evaluation exam in basic education is the National Secondary Education Examination (ENEM), which is also used to enroll students in higher education. In 2020, with the arrival of COVID-19, basic education institutions needed to change their educational model from face-to-face teaching to the use of distance learning methodologies, which may have affected the quality of education received. Therefore, there is a need to understand the effects that the COVID-19 pandemic caused to ENEM. This master’s thesis aims to identify the main impacts caused by the pandemic on ENEM, considering all of Brazil. To this end, the complete process of Educational Data Mining (MDE) was carried out, based on the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, in ENEM in 5 different years, in order to understand the years pre-pandemic and the first two years of the pandemic. In particular, this study used techniques of descriptive exploratory analysis, correlation and hierarchical grouping to identify the impacts caused on the ENEM. The results show that participants with higher incomes performed better, private schools outperformed other types of schools, the number of present and absentees in the exam was lower in the pandemic years, and there was a change in the socioeconomic characteristics of the participants. . Finally, the pandemic did not negatively impact student performance, but the characteristics of the participants who took the exam changed and the number of absentees and present in the exam was drastically impacted. |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-06-05T12:17:33Z |
dc.date.issued.fl_str_mv |
2023-04-28 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
WEBER NETO, Nelson. Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio. 2023. 79 f. Dissertação (Programa de Pós-Graduação em Ciência Da Computação/CCET) - Universidade Federal do Maranhão, São Luís, 2023. |
dc.identifier.uri.fl_str_mv |
https://tedebc.ufma.br/jspui/handle/tede/tede/4743 |
identifier_str_mv |
WEBER NETO, Nelson. Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio. 2023. 79 f. Dissertação (Programa de Pós-Graduação em Ciência Da Computação/CCET) - Universidade Federal do Maranhão, São Luís, 2023. |
url |
https://tedebc.ufma.br/jspui/handle/tede/tede/4743 |
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por |
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Universidade Federal do Maranhão |
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PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIA DA COMPUTAÇÃO/CCET |
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UFMA |
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Brasil |
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DEPARTAMENTO DE INFORMÁTICA/CCET |
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Universidade Federal do Maranhão |
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