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Sepi Hejazi Moghadam

Sepi Hejazi Moghadam

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    Equitable student persistence in computing research through distributed career mentorship
    Audrey Rorrer
    Cori Grainger
    Proceedings of 54th Technical Symposium on Computer Science Education (SIGCSE’23), ACM (2023)
    Preview abstract Google’s CS Research Mentorship Program (CSRMP) cultivates pursuit and persistence in the computing research trajectory for students from historically marginalized groups through virtual career mentorship from industry professionals, a peer community, and just-in-time resources. Since 2018, 287 Google mentors have engaged 1,018 students from 247 institutions in the U.S. and Canada. The program employs socioemotional support and advocacy to navigate systemic barriers by validating students’ intersectional identities in order to improve outcomes in core constructs for students: self-efficacy, sense of belonging, research skills, motivation to pursue graduate school and research careers, and intersectional capital. Evaluation outcomes from 400 matched respondents (68% response rate) indicate that CSRMP affects positive, statistically significant change in those constructs that largely persists across demographic subgroups. 80% aim to pursue computing research careers, and significantly fewer students are undecided about their future career. We were also able to identify disaggregated learnings: Black, Indigenous, and Latinx students are significantly less likely to submit to a research conference, and students from Historically Marginalized Groups (defined within) are significantly less likely to apply to a CS graduate program. We discuss key design elements of the program, how the findings are informing future iterations, and the potential for the model to scale. View details
    Understanding Immersive Research Experiences that Build Community, Equity, and Inclusion
    Audrey Rorrer
    Breauna Spencer
    Deborah Holmes
    Cori Grainger
    SIGCSE '21: Proceedings of the 2021 ACM SIGCSE Technical Symposium on Computer Science Education (2021)
    Preview abstract In this experience report, we describe the rationale and need for immersive research experiences (IREs) in computer science (CS) that are designed to foster an inclusive community that encourages pursuit of graduate education for undergraduate women. Google’s exploreCSR supports institutions across the US to execute IREs in computing throughout the academic year. We describe the program design and framework, the evaluation model, and present outcomes from two years of implementation across 29 institutions, with 1,983 (92% female) student participants collectively. The unique features of the program are that it aligns goals, measurements, and best practices across a national network of hands-on, localized IREs, resulting in peer communities and a sizable sample of undergraduates who identify as women and/or African-American/Black, American Indian/Alaska Native/Native American, Hispanic/Latinx, and/or Native Hawaiian/Pacific Islander (AAHN). We discuss recommendations for effective IRE programming based on our evaluation and the features found to be particularly salient for AAHN women. The contribution of this work is in describing how a national initiative for IREs builds community and creates conditions known to support persistence of women in computer science. View details
    Preview abstract The exploreCS (eCSR) program is a university awards program created to support the design, development, and execution of research-focused workshops that provide opportunities for undergraduate women in Computer Science to learn more about research pathways and work on exploratory research problems. During the inaugural year of 2018-19, the program funded intensive research (IREs) workshops at fifteen universities across the nation, with 1,103 total student participants, 83% of whom were females, with a majority indicating Women of Color status. The intent of these workshops is to offer accessible research experiences to students who would not ordinarily participate in research, i.e. students from groups traditionally less exposed to computing (women, Women of Color, lower socio-economic status). The overall research questions guiding the study of the program are: does the program foster a sense of community, build skills, confidence and motivation among women to pursue computer science research; and, how do Women of Color experience this program? In this paper, we present findings from a mixed-methods study which demonstrate that IREs are effective at creating a positive research culture for undergraduate women. Factors that were found to be particularly salient for Women of Color are presented. View details
    Pre-College Computer Science Education: A Survey of the Field
    Paulo Blikstein
    Google LLC, Retrieved from https://goo.gl/gmS1Vm (2018), pp. 45
    Preview abstract Google commissioned this work to better understand the knowns and unknowns with regard to the state of the CSEd field in relation to our understanding of student learning and the research opportunities that exist or that might be created to ensure fruitful and sustained advancement for all students. With this goal in mind, this report summarizes an examination of literature reviews and articles and interviews conducted with a number of leading researchers in the field. View details
    Preview abstract As computer science (CS) education expands at the K-12 level, we must be careful to ensure that CS does not exacerbate existing equity gaps in education nor does it hinder efforts to diversify the field of CS. In this paper, we discuss structural and social barriers that influence Blacks, Hispanics, and girls, based on surveys of 1,672 students, 1,677 parents, 1,008 teachers, 9,805 principals, and 2,307 superintendents in the United States. We find that despite higher interest in CS among Black and Hispanic students and parents, structural barriers in access to computers and CS classes are greater for them than for White students. And while girls have the same access as boys, social barriers exist with girls reporting lower awareness of CS opportunities outside of classes, less encouragement from teachers and parents, and less exposure to CS role models in the media. It is critical for expanding CS opportunities to address these issues for each group. View details
    Preview abstract The barriers to diversity in computer science (CS) are complex, consisting of both structural and social barriers. In this paper, we focus on social perceptions for students in grades 7-12 in the U.S. Through surveys of nationally representative samples of 1,672 students, 1,677 parents, 1,008 teachers, 9,805 principals, and 2,307 superintendents, we built on qualitative work by Lewis, Anderson, and Yasuhara [1,2] to understand social beliefs around students’ fit and ability as well the external context, as related to students’ interest. We contribute a holistic perspective of pre-university students, confirming much research on gender differences in social perceptions in CS while identifying new findings for race/ethnicity, specifically Black and Hispanic students. As K-12 CS expands, these findings can inform differentiation strategies in equitably engaging K-12 students. View details
    Preview abstract Through surveys of 1,673 students, 1,685 parents, 1,013 teachers, 9,693 principals, and 1,865 superintendents across the United States, this study explores perceptions, access, and barriers to computer science education at the K–12 level. We found most respondents were unable to distinguish computer literacy activities from computer science, with female, Black, or Hispanic respondents even less likely to do so. Perceptions of who does computer science were narrow and stereotypical (White, male, smart), but there was high value and demand for computer science across all populations, particularly among parents. Results indicate discrepancies in access to technology and computer science. Over 75% of principals reported their school did not offer computer science with programming/coding, but Hispanic students reported lower exposure to computers at home and in school and Black students and low-income students reported less access to computer science learning in school. Hispanic students and female students were also less likely to have learned computer science or have confidence to learn computer science compared to their counterparts. Finally, we explored barriers to access and identified a harsh disconnect: parent and student demand for computer science education was high while administrators’ perceptions of this demand was low. Additionally, the most common barriers to offering computer science cited by principals and superintendents were the need to dedicate time to other courses and testing requirements and the lack of qualified teachers, with technology less common of a barrier. View details
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