Women in Computer Science: High School Math Exam, School Belonging, Academic Self-Efficacy, and Their Relationship to First-Semester Grades

Contribution: This study enhances the understanding of the factors that impact academic performance and self-efficacy among computer science (CS) students, specifically focusing on gender differences. Background: The motivation behind this study stems from the gender disparity observed within undergraduate CS programs. This gender gap undermines diversity within the tech industry and hampers its potential for innovation. Research Questions: Do female CS students exhibit lower levels of school belonging and academic self-efficacy? Are there gender differences in academic achievement? What is the predictive power of prior academic performance, academic self-efficacy, and sense of belonging on first-semester grades? Methodology: In this study, 113 undergraduate students (82 males) were surveyed. The questionnaire was administered midway through the semester, in early November. High school math exam scores were assessed along with self-reported measures of academic self-efficacy and sense of belonging. Findings: The findings revealed several noteworthy observations: Female students exhibited a statistically significant higher grade point average (GPA) at the end of the first semester despite reporting lower levels of academic self-efficacy. Regression analysis identified gender, academic self-efficacy, and high school math exam scores as significant predictors of first-semester GPA. Implications: The implications of the study underscore the importance of fostering a supportive learning environment within CS education. Specifically, this study advocates for implementing teaching practices that prioritize social aspects and help enhance field-specific self-efficacy for all students.