Understanding Computing Identity Development Through Mentorship and Epistemic Network Analysis

Abstract

Computing identity plays an important role in students' participation, persistence, and sense of belonging in computing, yet identity development can be difficult to capture through survey measures alone. This study examines how computing identity is expressed in open-ended survey responses from 37 participants in computing-related fields. Using a Quantitative Ethnography approach, we applied Epistemic Network Analysis (ENA) to model co-occurrence patterns among six identity-related constructs: recognition, interest, competence, sense of belonging, self-doubt, and imposter syndrome. We compared the structure of computing identity narratives between participants who reported mentorship support and those who did not. Findings showed that participants with mentorship support had stronger connections among interest, competence, recognition, and sense of belonging, suggesting a more integrated and supportive identity structure. In contrast, participants without mentorship support showed stronger connections involving self-doubt and imposter syndrome, indicating that uncertainty and feelings of not belonging were more closely connected in their narratives. A two-sample t-test comparing ENA scores showed a statistically significant difference between the two groups along the X-axis, with a large effect size (Cohen's d = 1.72). These findings suggest that mentorship is associated with differences in the structure of computing identity and may help individuals connect their interests, abilities, recognition, and belonging within computing.