Understanding Who Enrolls in Introductory Computing Courses at Community Colleges

Abstract

Effective teaching requires understanding where students are coming from. Retaining students who have been historically underrepresented in computing requires the same, especially in introductory courses. This paper draws from surveys of students in introductory computing courses at seven geographically dispersed community colleges. We use K-means cluster analysis to differentiate students based on their responses to questions measuring constructs related to student success in computing courses and persistence. The resulting five clusters were compared on outcome variables, including final grades, intent to persist in computing, and gender and race/ethnicity. We focus on community colleges because they are uniquely well-positioned to broaden participation in computing; however, the implications extend beyond the community college context. We conclude by discussing methodological and pedagogical implications, including how findings can challenge assumptions and stereotypes about introductory computing students.