Minerando dados para entender o impacto da pandemia da COVID-19 no Exame Nacional do Ensino Médio

Detalhes bibliográficos
Autor(a) principal: WEBER NETO, Nelson
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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spelling 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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language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Universidade Federal do Maranhão
dc.publisher.program.fl_str_mv PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIA DA COMPUTAÇÃO/CCET
dc.publisher.initials.fl_str_mv UFMA
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv DEPARTAMENTO DE INFORMÁTICA/CCET
publisher.none.fl_str_mv Universidade Federal do Maranhão
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