This study explores how high school computer science (CS) course enrollment differs by student background through an intersectional lens. I use statewide data from North Carolina that contains longitudinal student-level background and course-taking information from 2005–2006 to the 2018–2019 school year and estimate linear probability models predicting course taking. The results suggest three findings: overall CS enrollment increases seem to be disproportionately driven by particular student groups; both between-school differences and within-school factors appear to explain CS enrollment gaps between student groups; and students who are both female and a member of specific racial groups or being identified as having a disability or LEP status are likely to face overlapping inequities. To my knowledge, this study is the first to use large-scale longitudinal student-level data and an intersectional lens to investigate how CS enrollment varies by student background at the high school level, especially in the context of North Carolina. This study sheds light on the different types of patterns and magnitudes of inequities that diverse student groups face, particularly potential overlapping inequities related to multiple intersecting identities, guiding areas that both current and new policies should target to achieve equity in CS education, which is a challenge that is relevant both within and outside of the United States.
AndrewsSMorrisL (2020) Diversity in CS: race and gender among CS majors in 2015 vs 2020. The Stanford Daily, 8 August 2020.
2.
Ashford-HanserdSSinghSMuonekeA, et al. (2021) Teachers’ perceptions of barriers influencing African American and Hispanic students with disabilities’ participation in K-12 computer science education. In: 2021 Conference on Research in Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT), Philadelphia, PA, USA, 23–27 May 2021, pp. 1–4.
3.
Babes-VromanMJuniewiczILucarelliB, et al. (2017) Exploring gender diversity in CS at a large public R1 research university. In: Proceedings of the 2017 ACM SIGCSE technical symposium on computer science education, Seattle, WA, USA, 8–11 May 2017, pp. 51–56.
4.
BauerGRChurchillSMMahendranM, et al. (2021) Intersectionality in quantitative research: a systematic review of its emergence and applications of theory and methods. SSM - Population Health14: 100798.
5.
BrunoPLewisCM (2021) Equity in high school computer science: beyond access. Policy Futures in Education1–21. DOI: 10.1177/14782103211063002.
6.
BrunoPLewisCM (2022) Computer science trends and trade-offs in California high schools. Educational Administration Quarterly58(3): 386–418.
7.
CastilloWGillbornD (2023) How to “QuantCrit:” Practices and Questions for Education Data Researchers and Users. Providence, RI: Annenberg Institute at Brown University, 22–546.
8.
CheongYFPajaresFObermanPS (2004) Motivation and academic help-seeking in high school computer science. Computer Science Education14(1): 3–19.
9.
CheryanSPlautVCDaviesPG, et al. (2009) Ambient belonging: how stereotypical cues impact gender participation in computer science. Journal of Personality and Social Psychology97(6): 1045–1060.
10.
CheryanSDruryBJVichayapaiM (2013) Enduring influence of stereotypical computer science role models on women’s academic aspirations. Psychology of Women Quarterly37(1): 72–79.
Codiroli McmasterNCookR (2019) The contribution of intersectionality to quantitative research into educational inequalities. The Review of Education7(2): 271–292.
13.
ColeER (2009) Intersectionality and research in psychology. American Psychologist64(3): 170–180.
14.
CorlettSMavinS (2014) Intersectionality, identity and identity work: shared tenets and future research agendas for gender and identity studies. Gender in Management: International Journal29(5): 258–276.
15.
CrenshawK (1989) Demarginalizing the intersection of race and sex: a Black feminist critique of antidiscrimination doctrine. Feminist Theory and Antiracist Politics University of Chicago Legal Forum1989(1): 8:139–8:167, Available at: https://chicagounbound.uchicago.edu/uclf/vol1989/iss1/8
FlapanJKnudsonJHandjojoC, et al. (2023) Power surge: how a multistakeholder coalition promotes equity in computer science education policy. Policy Futures in Education1–18. DOI: 10.1177/14782103231183485.
18.
FletcherCLWarnerJR (2021) CAPE: a framework for assessing equity throughout the computer science education ecosystem. Communications of the ACM64(2): 23–25.
19.
HappeLBuhnovaBKoziolekA, et al. (2021) Effective measures to foster girls’ interest in secondary computer science education: a literature review. Education and Information Technologies26: 2811–2829.
20.
HubwieserPGiannakosMNBergesM, et al. (2015) A global snapshot of computer science education in K-12 schools. In: Proceedings of the 2015 ITiCSE Conference on Working Group Reports, Vilnius, Lithuania, 4–8 July 2015, pp. 65–83.
21.
JacksonJFLCharlestonLJGilbertJE, et al. (2013) Changing attitudes about computing science at historically Black colleges and universities: benefits of an intervention program designed for undergraduates. Journal of African American Studies17(2): 162–173.
22.
JacobSMontoyaJWarschauerM (2022) Exploring the intersectional development of computer science identities in young Latinas. Teachers College Record124(5): 166–185.
23.
JacobSGillenBOjeda-RamirezS, et al. (2024) Intersectional factors that influence K-2 students’ computer science learning. In: Proceedings of the 2024 on RESPECT Annual Conference, Atlanta, GA, USA, 16–17 May 2024, pp. 21–29.
KempPEWongBBerryMG (2019) Female performance and participation in computer science: a national picture. ACM Transactions on Computing Education20(1): 1–28.
LewisCMAndersonREYasuharaK (2016) “I don’t code all day”: fitting in computer science when the stereotypes don’t fit. In: Proceedings of the 2016 ACM Conference on International Computing Education Research, Melbourne, VIC, Australia, 08–12 September 2016, pp. 23–32.
28.
LewisCBrunoPRaygozaJ, et al. (2019) Alignment of goals and perceptions of computing predicts students’ sense of belonging in computing. In: Proceedings of the 2019 ACM Conference on International Computing Education Research, Toronto, ON, Canada, 12–14 August 2019, pp. 11–19.
29.
LiuJConradCBlazarD (2024) Computer Science for All? the Impact of High School Computer Science Courses on College Majors and Earnings. Providence, RI: Annenberg Institute at Brown University, 24–904.
30.
LunnSZahediLRossM, et al. (2021) Exploration of intersectionality and computer science demographics: understanding the historical context of shifts in participation. ACM Transactions on Computing Education21(2): 1–30.
31.
MarshallSLGroomsAA (2022) Industry’s push for computer science education: is computer science really for all?Policy Futures in Education1–22. DOI: 10.1177/14782103211045601.
32.
MasterACheryanSMeltzoffAN (2016) Computing whether she belongs: stereotypes undermine girls’ interest and sense of belonging in computer science. Journal of Educational Psychology108(3): 424–437.
33.
MaukMWillettRCoulterN (2020) The can-do girl goes to coding camp: a discourse analysis of news reports on coding initiatives designed for girls. Learning, Media and Technology45(4): 395–408.
34.
MichelmoreKDynarskiS (2017) The gap within the gap: using longitudinal data to understand income differences in educational outcomes. AERA Open3(1): 1–18.
35.
MickelsonRAMikkelsenIDorodchiM, et al. (2024) Inspiring and preparing underserved middle school students for computer science: a descriptive case study of the UNC Charlotte/Wilson STEM Academy Partnership. School Community Journal34(1): 127–158, Available at: https://www.adi.org/journal/SS2024/MickelsonEtAl.pdf
36.
MooneyCBeckerBA (2020) Sense of belonging: the intersectionality of self-identified minority status and gender in undergraduate computer science students. In: United Kingdom & Ireland Computing Education Research conference, Glasgow, United Kingdom, 3–4 September 2020, pp. 24–30.
37.
National Center for Education Statistics (2023) Digest of Education Statistics: Bachelor’s Degrees Conferred by Postsecondary Institutions, by Race/Ethnicity and Field of Study: Academic Years 2020-21 and 2021-22. Available at: https://nces.ed.gov/programs/digest/d23/tables/dt23_322.50.asp (accessed 29 January 2024).
National Science Foundation (2023) Diversity and STEM - Women, Minorities, and Persons with Disabilities. Available at: https://ncses.nsf.gov/pubs/nsf23315/ (accessed 14 February 2024).
PapastephanouMZembylasMBostadI, et al. (2022) Philosophy of education in a new key: education for justice now. Educational Philosophy and Theory54(8): 1083–1098.
43.
ParkerMCHendricksonKA (2022) Capacity-related factors associated with computer science access and participation in Georgia public high schools. Policy Futures in Education1–25. DOI: 10.1177/14782103221081920.
44.
PaytonFCBuschA (2020) Examining undergraduate computer science participation in North Carolina. Communications of the ACM63(8): 60–68.
RankinYAThomasJOEreteS (2021) Real talk: saturated sites of violence in CS education. In: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, Virtual Event, USA, 13–20 March 2021, pp. 802–808.
47.
ReaderJJandrićPPetersMA, et al. (2021) Enchantment-disenchantment-re-enchantment: postdigital relationships between science, philosophy, and religion. Postdigital Science and Education3: 934–965.
48.
RossMHazariZSonnertG, et al. (2020) The intersection of being Black and being a woman: examining the effect of social computing relationships on computer science career choice. ACM Transactions on Computing Education20(2): 9:1–9:15.
49.
SalehiSWangKDToorawaR, et al. (2020) Can majoring in computer science improve general problem-solving skills? In: Proceedings of the 51st ACM Technical Symposium on Computer Science Education, Portland, OR, USA, 11–14 March 2020, pp. 156–161.
50.
SaxLJNewhouseKNSGoodeJ, et al. (2022) Can computing be diversified on “principles” alone? Exploring the role of AP Computer Science courses in students’ major and career intentions. ACM Transactions on Computing Education22(2): 1–26.
51.
SelwynN (2004) Reconsidering political and popular understandings of the digital divide. New Media & Society6(3): 341–362.
52.
SelwynN (2021) Education and Technology: Key Issues and Debates. London: Bloomsbury Publishing.
53.
SelwynNGorardSWilliamsS (2001) Digital divide or digital opportunity? The role of technology in overcoming social exclusion in U.S. Education. Educational Policy15(2): 258–277.
54.
StewartGArndtSBesleyT, et al. (2017) Antipodean theory for educational research. Open Review of Educational Research4(1): 61–74.
55.
SthapitSThomasMBrockJ, et al. (2024) Cracking the cultural code: understanding the cultural barriers for Asian international CS students in the US. In: Proceedings of the 55th ACM Technical Symposium on Computer Science Education,Portland, OR, USA, 20–23 March 2024, pp. 1830–1831.
56.
SzlaviAHansenMFHusnesSH, et al. (2023) Intersectionality in computer science: a systematic literature review. In: 2023 IEEE/ACM 4th Workshop on Gender Equity, Diversity, and Inclusion in Software Engineering (GEICSE), Melbourne, Australia, 2023, pp. 9–16.
57.
TorbeyR (2023) Inequities of enrollment: a quantitative analysis of participation in high school computer science coursework across a 4-year period. In: Proceedings of the 2023 ACM Conference on International Computing Education Research, Chicago, IL, USA, 7–11 August 2023, pp. 344–355.
58.
UNESCO (2015) A Complex Formula: Girls and Women in Science, Technology, Engineering and Mathematics in Asia. Paris: United Nations Educational, Scientific and Cultural Organization.
WangJHongHRavitzJ, et al. (2016) Landscape of K-12 computer science education in the US: perceptions, access, and barriers. In: Proceedings of the 47th ACM Technical Symposium on Computing Science Education, Memphis, TN, USA, 2–5 March 2016, pp. 645–650.
63.
WarnerJRChildsJFletcherCL, et al. (2021) Quantifying disparities in computing education: access, participation, and intersectionality. In: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, Virtual Event, USA, 13–20 March 2021, pp. 619–625.
64.
WarnerJRFletcherCLMartinND, et al. (2022) Applying the CAPE framework to measure equity and inform policy in computer science education. Policy Futures in Education1–19. DOI: 10.1177/14782103221074467.
65.
WilliamsKCLDillonECarterS, et al. (2023) CS=Me: exploring factors that shape Black women’s CS identity at the intersections of race and gender. ACM Transactions on Computing Education24(2): 21:1–21:20.
66.
ZdawczykCVarmaK (2023) Engaging girls in computer science: gender differences in attitudes and beliefs about learning scratch and python. Computer Science Education33(4): 600–620.
