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.

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Frontiers in Big Data Pub Date : 2025-03-12 eCollection Date: 2025-01-01 DOI:10.3389/fdata.2025.1485493
Sandio Maciel Dos Santos, Marcelino Silva da Silva, Fábio Manoel França Lobato, Carlos Renato Lisboa Francês
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引用次数: 0

Abstract

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.

在巴西高中教育数据库中使用贝叶斯网络:分析2019年至2022年COVID-19对par地区ENEM的影响
本研究考察了2019冠状病毒病大流行对巴西帕尔州学习成绩和学生参加国家高中考试(ENEM)的影响,重点关注社会经济因素、技术获取和地区差异之间的相互作用。该研究采用了混合方法,分析了ENEM结果(2020-2022)的定量数据以及对教育工作者和学生的定性访谈。调查结果表明,疫情加剧了原有的教育不平等现象,对低收入家庭学生和公立学校学生的影响尤其严重。家庭收入不超过一个最低工资标准的学生辍学率最高,凸显了远程学习技术和基础设施的有限获取所构成的障碍。一项统计分析显示,能够使用电脑和互联网的学生,尤其是私立学校的学生,成绩提高了20%。研究还发现,帕尔中部地区存在显著的地区差异,与贝尔萨姆大都市区相比,Marajó和东南帕尔在降低辍学率方面面临着更持久的挑战。这些结果突出表明,迫切需要制定针对特定区域的公共政策,解决教育资源差异问题,包括对数字基础设施和远程教育教师培训进行有针对性的投资。该研究的结论是,全面的支持项目,包括对学生的心理援助,对于建立一个更有弹性、更公平、能够抵御未来危机的教育体系至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.20
自引率
3.20%
发文量
122
审稿时长
13 weeks
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