Affiliation:
1. Federal Institute of Mato Grosso do Sul, Brazil
2. Federal University of Technology - Parana (UTFPR), Brazil
3. Universidade Estadual de Maringá, Brazil
4. Universidade Federal do Rio Grande do Sul, Brazil
5. Sâo Paulo State University (Unesp), School of Technology and Sciences, Presidente Prudente, Brazil
Abstract
Motivation
: Enrollments in Brazilian computing degrees are at an all-time high, but graduation numbers have not increased at the same rate. Moreover, enrollment growth has mainly attracted male students, steadily expanding the gender gap in Brazilian computing programs. Such high attrition rates have a great economic impact and may disproportionately affect women and students of color. Previous works investigated reasons for student drop-out and retention in specific courses or barriers to entrance in computing programs in narrower contexts or in a single institution.
Objectives
: We investigate potential actionable factors for intent to drop out in computing programs and what factors might lead students to remain in a computing program in several Brazilian institutions. We investigated how such factors may be affected by students’ race/ethnicity, gender, and socioeconomic status.
Method
: We analyzed Likert-style answers from an online survey with 3,193 students currently enrolled in Brazilian computing programs.
Results
: The results show that students value salary/job-related factors as the most important factors to potentially remain in a computing program. The excess of theoretical courses and the difficulty of programming and mathematics courses are the top-ranked factors by students to potentially abandon a computing degree. However, while there is little effect of gender, race/ethnicity, or socioeconomic status in retention factors, potential drop out factors such as a the fact that it is a male-dominated field, harassment, and the difficulty of courses were rated as more important by women. Also, costs and the difficulty of courses are relevant factors for the intent to drop out when analyzing students’ race/ethnicity and socioeconomic status.
Discussion
: We explore the implications of our findings for Computing programs, particularly (but not restricted to) the Brazilian context. We conjecture reasons for such students’ perspectives regarding intent to drop out and retention factors and provide recommendations of actions for instructional designers, curriculum developers, and other key stakeholders to address issues related to gender, students’ wellness, perceived authenticity of courses, and other relevant factors. Since we only observed small interactions between race/ethnicity and retention and intent to drop out factors, which may indicate a lack of sensitivity from the instrument, we present suggestions to address such limitations in future work.
Publisher
Association for Computing Machinery (ACM)
Subject
Education,General Computer Science
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