Abstract
ABSTRACT Community college transfer represents an important mechanism for advancing access to STEM degrees and careers. Yet, little is known about community college transfer pathways in computing. Utilizing longitudinal survey data, we rely on descriptive statistics and structural equation modeling to examine community college transfer pathways in computing over the course of the four years after students arrive at their receiving university. Findings document wide variation in community college transfer students’ pathways and highlight the importance of computing self-efficacy in predicting degree attainment, computing career pursuits, and graduate school aspirations in computing.
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