Performance Analysis of People with Disabilities at the National High School Examination - ENEM

• Autor(a) principal: de Oliveira, Caue Gomes
• Data de Publicação: 2020
• Outros Autores: Barwaldt, Regina, Lucca, Giancarlo
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Tear: Revista de Educação Ciência e Tecnologia
• Texto Completo: https://periodicos.ifrs.edu.br/index.php/tear/article/view/4038

Abstract: Currently, admission to higher education takes place mainly by conducting the National High School Examination (ENEM), which reaches five million participants per year. This test made it easy to attend a university, be it public or private, however, for disabled people, being a university student is still a major obstacle. This article presents an analysis of the participants who have physical and psychological disabilities who provided the ENEM, through a predictive model, in order to assist in understanding the candidate's final performance. Using data mining techniques applied in the database related to the test held in 2018, a machine learning algorithm, C4.5, was used, which generates an interpretable pattern through a decision tree, to predict what was the candidate's final performance, according to some characteristics, such as: socioeconomic, demographic, ethnic, age group and academic background, checking whether such attributes influence the final performance. Keywords: Mining of educational data. ENEM. C4.5. Disabled people.