使用聚类方法分析2012年至2017年ENEM的服务人员

Afonso Matheus Sousa Lima, Alexander Ylnner Choquenaira Florez, Alexis Iván Aspauza Lescano, João Victor De Oliveira Novaes, Natalia De Fatima Martins, C. Traina Junior, Elaine Parros Machado de Sousa, José Fernando Rodrigues Junior, Robson Leonardo Ferreira Cordeiro
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引用次数: 0

摘要

数据分析越来越多地被用作一种公正和准确的方式来评估社会的许多方面及其多年来的演变。本文分析了2012年至2017年巴西最重要的高等教育考试(ENEM)中学生的特征。目的是利用聚类方法(K-means),了解巴西地区、ENEM的知识领域、学校类型和可及性。为了使数据库均匀化并避免各种统计偏差,对数据库进行了广泛而仔细的清理。这篇文章客观地呈现了这项工作的结果,因此它可能是有用的,并作为社会教育学科的工作或对更好地理解ENEM近年来的发展感兴趣的研究的数字基础。最后,及时提出了对分组结果的一些讨论和限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of ENEM’s attendants between 2012 and 2017 using a clustering approach
Data analysis is increasingly being used as an unbiased and accurate way to evaluate many aspects of society and their evolution over the years. This article presents an analysis of student’s characteristics, between 2012 and 2017, in the most important exam for entry into higher education in Brazil, the Exame Nacional do Ensino Médio (ENEM). The intention is to gain insights of Brazilian regions, ENEM’s areas of knowledge, type of school and accessibility, using a clustering method (K-means). An extensive and careful cleaning of the database was made in order to homogenize it and avoid types of statistical bias. The results of this work are presented objectively in the article, so it may be useful and used as a numerical base in works of socio-educational disciplines or studies that are interested in better understanding the evolution of ENEM in recent years. Finally, some discussions and restrictions on grouping results were presented in a timely manner.
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