Use of Bayesian networks in Brazil high school educational database: analysis of the impact of COVID-19 on ENEM in Pará between 2019 and 2022
This study examines the impact of the COVID-19 pandemic on academic performance and student participation in the National High School Exam (ENEM) in the state of Pará, Brazil, focusing on the interaction between socioeconomic factors, access to technology, and regional disparities. The research empl...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-03-01
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| Series: | Frontiers in Big Data |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fdata.2025.1485493/full |
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| author | Sandio Maciel Dos Santos Marcelino Silva da Silva Fábio Manoel França Lobato Carlos Renato Lisboa Francês |
| author_facet | Sandio Maciel Dos Santos Marcelino Silva da Silva Fábio Manoel França Lobato Carlos Renato Lisboa Francês |
| author_sort | Sandio Maciel Dos Santos |
| collection | DOAJ |
| description | This study examines the impact of the COVID-19 pandemic on academic performance and student participation in the National High School Exam (ENEM) in the state of Pará, Brazil, focusing on the interaction between socioeconomic factors, access to technology, and regional disparities. The research employed a mixed-methods approach, analyzing quantitative data from ENEM results (2020–2022) and qualitative interviews with educators and students. The findings indicate that the pandemic exacerbated pre-existing educational inequalities, particularly affecting low-income students and those enrolled in public schools. The highest dropout rates were recorded among students with a family income of up to one minimum wage, highlighting the barriers posed by limited access to technology and infrastructure for remote learning. A statistical analysis revealed a 20% increase in scores among students with access to computers and the Internet, particularly in private schools. The study also found significant regional differences across Pará's mesoregions, with Marajó and Southeast Pará facing more persistent challenges in reducing dropout rates compared to the Metropolitan Region of Belém. These results underscore the urgent need for region-specific public policies that address disparities in educational resources, including targeted investments in digital infrastructure and teacher training for remote education. The study concludes that comprehensive support programs, including psychological assistance for students, are essential for building a more resilient and equitable educational system capable of withstanding future crises. |
| format | Article |
| id | doaj-art-e409b03047ff47af987ded63b23d48ec |
| institution | OA Journals |
| issn | 2624-909X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Big Data |
| spelling | doaj-art-e409b03047ff47af987ded63b23d48ec2025-08-20T02:04:28ZengFrontiers Media S.A.Frontiers in Big Data2624-909X2025-03-01810.3389/fdata.2025.14854931485493Use of Bayesian networks in Brazil high school educational database: analysis of the impact of COVID-19 on ENEM in Pará between 2019 and 2022Sandio Maciel Dos Santos0Marcelino Silva da Silva1Fábio Manoel França Lobato2Carlos Renato Lisboa Francês3Graduate Program in Electrical Engineering, Federal University of Pará, Belém, BrazilGraduate Program in Electrical Engineering, Institute of Engineering and Geosciences, Federal University of Western Pará, Santarém, Pará, BrazilInstitute of Engineering and Geosciences, Federal University of Western Pará, Santarém, Pará, BrazilGraduate Program in Electrical Engineering, Institute of Technology, Federal University of Pará, Belém, BrazilThis study examines the impact of the COVID-19 pandemic on academic performance and student participation in the National High School Exam (ENEM) in the state of Pará, Brazil, focusing on the interaction between socioeconomic factors, access to technology, and regional disparities. The research employed a mixed-methods approach, analyzing quantitative data from ENEM results (2020–2022) and qualitative interviews with educators and students. The findings indicate that the pandemic exacerbated pre-existing educational inequalities, particularly affecting low-income students and those enrolled in public schools. The highest dropout rates were recorded among students with a family income of up to one minimum wage, highlighting the barriers posed by limited access to technology and infrastructure for remote learning. A statistical analysis revealed a 20% increase in scores among students with access to computers and the Internet, particularly in private schools. The study also found significant regional differences across Pará's mesoregions, with Marajó and Southeast Pará facing more persistent challenges in reducing dropout rates compared to the Metropolitan Region of Belém. These results underscore the urgent need for region-specific public policies that address disparities in educational resources, including targeted investments in digital infrastructure and teacher training for remote education. The study concludes that comprehensive support programs, including psychological assistance for students, are essential for building a more resilient and equitable educational system capable of withstanding future crises.https://www.frontiersin.org/articles/10.3389/fdata.2025.1485493/fullCOVID-19ENEMeducational inequalityremote learningregional disparities |
| spellingShingle | Sandio Maciel Dos Santos Marcelino Silva da Silva Fábio Manoel França Lobato Carlos Renato Lisboa Francês Use of Bayesian networks in Brazil high school educational database: analysis of the impact of COVID-19 on ENEM in Pará between 2019 and 2022 Frontiers in Big Data COVID-19 ENEM educational inequality remote learning regional disparities |
| title | Use of Bayesian networks in Brazil high school educational database: analysis of the impact of COVID-19 on ENEM in Pará between 2019 and 2022 |
| title_full | Use of Bayesian networks in Brazil high school educational database: analysis of the impact of COVID-19 on ENEM in Pará between 2019 and 2022 |
| title_fullStr | Use of Bayesian networks in Brazil high school educational database: analysis of the impact of COVID-19 on ENEM in Pará between 2019 and 2022 |
| title_full_unstemmed | Use of Bayesian networks in Brazil high school educational database: analysis of the impact of COVID-19 on ENEM in Pará between 2019 and 2022 |
| title_short | Use of Bayesian networks in Brazil high school educational database: analysis of the impact of COVID-19 on ENEM in Pará between 2019 and 2022 |
| title_sort | use of bayesian networks in brazil high school educational database analysis of the impact of covid 19 on enem in para between 2019 and 2022 |
| topic | COVID-19 ENEM educational inequality remote learning regional disparities |
| url | https://www.frontiersin.org/articles/10.3389/fdata.2025.1485493/full |
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