An analysis of student dropout in Engineering courses at a Brazilian Public University

• Autor(a) principal: Silva, Matheus Leme da
• Data de Publicação: 2020
• Outros Autores: Oliveira, Sandra Cristina de, Santos, Monique Matsuda dos, Scalco, Andréa Rossi
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/5159
• topic: Educación superior; Deserción; Ingeniería; Análisis estadístico.; Ensino superior; Evasão escolar; Engenharia; Análise estatística.; Higher education; Dropout; Engineering; Statistical analysis.

The aim of this study is to evaluate three undergraduate courses in Engineering offered in Experimental Campuses at UNESP, and specifically to describe the student dropout possibility of these courses as the function of explanatory variables (socioeconomic, demographic and academic). It is a descriptive research with a quantitative approach. A census survey of information concerning (evaded and non-evaded) students of the academic period from 2003 to 2013 was carried out in the UNESP Database. The response variable ‘student situation’ was formulated as a function of 24 explanatory variables specifically covering attributes prior to students entering university. This relationship was investigated using multivariate statistical technique based on logistic regression. The adjusted models were able to correctly predict about 72% of cases of dropout/permanence in these courses. The results showed that describing the chance of dropping out involves academic factors, such as modality of high school completed, if the student had attended a preparatory course for the entrance exam, the number of times that the student has taken entrance exam, if the student had started some higher education course, and classification in the entrance exam, and socioeconomic factors, such as gender, skin color, if the student had exercised paid activity, and family income. Finally, the proposed method was evidenced, which may assist Higher Education Institutions in the preliminary analysis of the real risk of dropout, as well as in the development of new research on student dropout in higher education with a focus on Engineering.