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Many college students have neither the interest in nor the academic preparation for pursuing the study of science, technology, engineering, and mathematics (STEM). This is especially true for computer science (Code.org, 2021). Consequently, the U.S. likely faces a mismatch between its projected technology labor force needs and the majors of future college graduates (Justice et al., 2022; U.S. Bureau of Labor Statistics, 2023). A further complication of this mismatch is that the majority of U.S. students who study technology are males from middle-class White or Asian Rim ethnic (Fry et al., 2021). Lower-income youth from all race/ethnic backgrounds, females, and students from Black, Latinx, some Asian American Pacific Islander (AAPI), and Native American ethnic groups are underrepresented in computer science (CS) relative to their proportion in the overall U.S. population (U.S. Census Bureau, 2018). This disproportionality leaves large segments of the U.S. population outside the professional computing community. Addressing the second issue could help alleviate the first problem by bringing currently marginalized segments of the population into technology fields. This article presents a descriptive case study of a three-year middle school intervention designed to improve the likelihood that more low-income, female, and racial/ethnic minoritized middle school youth will be inspired and prepared to study technology in high school enroute to pursuing technology majors in college. It describes the development, implementation, and outcomes of a partnership between the University of North Carolina at Charlotte (UNC Charlotte) and Wilson STEM Academy, a public middle school serving the underrepresented populations previously described (Mickelson, 2015). 

Female, Black, Latinx, Native American, low-income, and rural students remain underrepresented among computer science undergraduate degree recipients. Along with student, family, and secondary school characteristics, college organizational climate, curricula, and instructional practices shape undergraduates’ experiences that foster persistence until graduation. Our quasi-experimental project, Improving the Persistence and Success of Students from Underrepresented Populations in Computer Science (I-PASS), is designed to augment students’ persistence until they earn their computer science degree. Drawing on prior research, including Tinto's model of effective institutional actions for retention, I-PASS Scholars—all low-income, female and/or members of underserved demographics groups— receive a four-year scholarship; mentoring, tutoring, advising; and opportunities to integrate into the academic and social life of the campus. Students’ written reflections and attitude surveys suggest I-PASS's components foster their retention by, among other mechanisms, enhancing their computer science identity development and sense of belonging in the major.