2023 ASEE Annual Conference & Exposition

In an effort to increase the percentage of female students in the Computer Science (CS) Department at [College/Dept/Univ Name here], we have conducted an in-depth data analysis of student enrollment, persistence, and performance in early programming courses (CS1 through CS3) during the pandemic period (Fall 2019 to Spring 2022). Currently, the department has a female enrollment of less than 12%, which is below the national average of 20%. Through this study, we aim to identify the most appropriate strategies for female students to broaden their participation in computing.

As a part of the study, we collected data on the introductory course sequence, CS1 Programming I, CS2 Programming II, and CS3 Programming with Data Structure. The data included quasi-cohort course outcomes, quasi-cohort persistence, retention graduation, day 1 to census day enrollment, completion by transfer status, outcomes by major, and student support. In addition, to understand in-depth the level of preparedness and the level of satisfaction of women and minority students in computing, we also collected additional data. This effort included collecting the results of midterm exams, quizzes, course projects, assignments, and the final exam from CS1, CS2, and CS3. Moreover, we conducted surveys with these students to determine their satisfaction with interactions with peers and instructors, as well as their confidence level in the CS major.

Through the data analyses and discussion, we found that female students’ academic performance is as good as, or even better than, their male classmates. However, compared to male students, female students tend to be less confident and satisfied with their academic performance. The withdrawal rate is higher among female students than male students. The discussion of these results contributes toward identifying possible practices that would broaden participation in computer science for women.