Gender-balanced TAs from an Unbalanced Student Body

Increasing participation of women and underrepresented minorities is a key challenge in the field of Computer Science Education. Balanced representation of these groups among teaching assistants in Computer Science courses influences recruitment and retention of underrepresented students. At the same time, the status-quo reduced participation of these students makes it more difficult to hire instructional staff from underrepresented groups. In this paper, we describe our experience evaluating candidates with teaching-demonstration videos, followed by in-person interviews, to hire a gender-balanced set of undergraduate TAs for a large-scale CS2 course. Our research goal is to quantitatively assess gender balance throughout the hiring process. Our initial applicant pool is just one-sixth women, but we found that women applicants perform better in our application process than men, resulting in a gender-balanced course staff without making hiring decisions based on the gender of applicants. We show that our approach results in a more gender-balanced teaching staff than hiring based on applicant GPA. We also use course-evaluation data to demonstrate that women perform as well as men as teaching assistants in CS2, and that the overall quality of our teaching assistants has remained high after the hiring-process change.