Dropout in Undergraduate Computing Programs in Brazil

• Ícaro Vasconcelos Alvim State University of Feira de Santana (UEFS)
• Roberto A. Bittencourt University of Victoria http://orcid.org/0000-0002-8854-8956
• Rodrigo S. Duran Federal Institute of Mato Grosso do Sul (IFMS) https://orcid.org/0000-0003-1840-2895

DOI: https://doi.org/10.5753/educomp.2024.237328

Abstract

Motivation: Student dropout in higher education has social, economic, institutional and personal impacts. Given the historically high levels of dropout in information technology programs, its negative effects are potentially even more serious due to the growing demand for qualified professionals. However, it is still rare to find studies that comprehensively investigate dropout rates in computing programs, comparing program types and student profiles over a large time span. Objectives: Presenting an overview of dropout rates in undergraduate programs in the field of Computing in Brazil in the period between 2015 and 2019 based on data from the Higher Education Census of the National Institute of Educational Studies and Research Anísio Teixeira (INEP), investigating potential differences in dropout rates between programs, student demographic features and daily study shifts. Method: Data on programs and students in the field of Computing in the period of interest were extracted from INEP microdata and differences in dropout rates between program types and profiles of different groups of students (e.g., affirmative actions, gender, race/ethnicity) were computed. Results: The results indicate that the difference in dropout rates in different program types is very small. The largest difference in dropout is between students who receive student financial aid or not. Furthermore, significant differences were also found between students from public and private institutions, between scholarship holders and non-scholarship holders, and between students from different daily study shifts. Smaller differences were found between students who receive social support or not, between affirmative action and non-affirmative action students, and between students from in-person and from distance learning programs. Discussion: The results point to the importance of socioeconomic factors in student dropout. However, factors such as gender and race/ethnicity, when observed in isolation, did not substantially impact student dropout in computing programs, contrasting with results from studies carried out in other countries.

Keywords: Dropout, Higher education, Computing, INEP, Brazilian Higher Education Census

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