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Graduating in the Margins: An Analysis of Graduations Rates of Minoritized Women in Computing

Abstract

A review of the literature in broadening participation research in computing and in STEM more broadly reveals that, while substantial research is being conducted focused on students of color and women in computing, there has been little regard for the unique intersection of gender and race experienced by minoritized women (i.e., Black, Latina, Indigenous, Asian). What is needed is a more complex understanding of the experiences of marginalized groups in computing who live at various intersections of racism, sexism, classism, xenophobia, heterosexism, ableism, etc., an area of research called Intersectional Computing. To begin developing a deeper understanding of the factors impacting women of color in computing, the authors decided to first identify which universities are performing well. To this end, an analysis of graduation rates for students at four-year institutions between 2011 and 2018. These data were gathered from the National Center for Education Statistics Integrated Postsecondary Education Data System. A logistic regression analysis was conducted to understand the potential influence of various institutional factors. As a whole, the data suggest that minority-serving institutions (MSIs) outperform non-MSIs in awarding computing degrees to women of color; for women of color as a whole, all MSI designations (except Tribal Colleges and Universities, for which only two institutions have this designation) are associated with higher odds of producing a computing degree. For specific racial/ethnic breakdowns, some MSI designations may have higher odds of awarding a computing degree than others. Moreover, some MSI designations may be associated with lower odds of producing a computing degree to specific groups of women. This paper provides a brief discussion of the particular challenges faced by women of color in computing, details the characteristics of universities with top graduation rates, and discusses what might be learned from these institutions.

 

Citation

Daily, S., & Shelton, C., & He, A., & Eugene, W., & Orozco, T., & Thomas, J. (2022, August), Graduating in the Margins: An Analysis of Graduations Rates of Minoritized Women in Computing Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. https://peer.asee.org/41616


Categories

Computer Science, Computing, Diversity, Equity, Gender, Identity, Inclusion, Publications, Research