Afonso Lima, Alexander Florez, Alexis Lescano, João Novaes, Natalia Martins, Caetano Traina Júnior, Elaine Sousa, José Rodrigues Júnior, Robson Cordeiro

Analysis of ENEM’s attendants between 2012 and 2017 using a clustering approach

Introduction

Analysis of enem’s attendants between 2012 and 2017 using a clustering approach. Analyze ENEM student characteristics (2012-2017) in Brazil using a clustering approach. Gain insights into regions, school types, and accessibility for higher education.

Abstract

Data analysis is increasingly being used as an unbiased and accurate way to evaluate many aspectsof society and their evolution over the years. This article presents an analysis of student’s characteristics, between2012 and 2017, in the most important exam for entry into higher education in Brazil, the Exame Nacional do EnsinoMédio (Enem). The intention is to gain insights of Brazilian regions, Enem’s areas of knowledge, type of school andaccessibility, using a clustering method (K-means). An extensive and careful cleaning of the database was made in orderto 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 interestedin better understanding the evolution of Enem in recent years. Finally, some discussions and restrictions on groupingresults were presented in a timely manner.

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