U.S. PK-12 Superintendent and High School Principal Perceptions Toward Computer Science Education
Pages 3 - 12
Abstract
PK-12 district and school leaders play an important role in translating equitable computer science (CS) educational reform into practice. This study unpacks U.S. PK-12 superintendents' and high school principals' perceptions toward CS. Results reveal that both leaders express positive support for CS education but do not feel that other stakeholders in their school districts, like school board members, parents/guardians, and teachers, are equally supportive of CS. Perceptions were lowest for leaders in the Western U.S. and for leaders who oversee majority low-wealth students. The implications of these findings on CS education reform are discussed.
References
[1]
Code.org, CSTA, ECEP Alliance (2023). 2023 State of Computer Science Education: Retrieved from https://advocacy.code.org/stateofcs
[2]
A. Scott, F.K. Klein, F. McAlear, A. Martin, and Koshy, S. "The Leaky Tech Pipeline: A Comprehensive Framework for Understanding and Addressing the Lack of Diversity across the Tech Ecosystem." Kapor Center. 2022. https://www.kaporcenter.org/the-leaky-tech-pipeline/
[3]
Fletcher, C. L., & Warner, J. R. (2021). CAPE: A framework for assessing equity throughout the computer science education ecosystem. Communications of the ACM, 64(2), 23--25.
[4]
Gransbury, I., McGill, M. M., Thompson, A., Heckman, S., Rosato, J., & Delyser, L. A. (2023, March). Building upon the CAPE Framework for Broader Understanding of Capacity in K-12 CS Education. https://csedresearch.org/resources/extended-cape-codebook/
[5]
Parker, M. C., & Hendrickson, K. A. (2022). Capacity-related factors associated with computer science access and participation in Georgia public high schools. Policy Futures in Education, 14782103221081920.
[6]
Santo, R., DeLyser, L. A., & Ahn, J. (2020). Negotiating equity priorities within systems change: A case study of a district-level initiative to implement K12 computer science education. Computing in Science & Engineering, 22(5), 7--19.
[7]
Santo, R., DeLyser, L. A., Ahn, J., Pellicone, A., Aguiar, J., & Wortel-London, S. (2019a). Equity in the who, how and what of computer science education: K12 school district conceptualizations of equity in "CSforAll' initiatives. In 2019 research on equity and sustained participation in engineering, computing, and technology (RESPECT). IEEE, 1--8.
[8]
Google & Gallup (2020). Current perspectives and continuing challenges in computer science education U.S. K-12 schools. https://csedu.gallup.com/home.aspx
[9]
Hutchings Jr, G. C., & Brown, J. L. (2021). The current work of the American superintendent. The American Superintendent, 39--49.
[10]
Tienken, C. H. (2021). The evolution of the American school superintendent. The American Superintendent 2020 Decennial Study, 1.
[11]
Warner, J. R., Fletcher, C. L., Martin, N. D., & Baker, S. N. (2022). Applying the CAPE framework to measure equity and inform policy in computer science education. Policy Futures in Education. https://doi.org/10.1177/14782103221074467
[12]
Margolis, J., & Goode, J. (2016). Ten lessons for computer science for all. ACM Inroads, 7(4), 52--56.
[13]
Cohen, D. K., Spillane, J. P., & Peurach, D. J. (2018). The Dilemmas of Educational Reform. Educational Researcher, 47(3), 204--212. https://doi.org/10.3102/0013189X17743488
[14]
Johnson, C. C. (2013). Educational turbulence: The influence of macro and micro-policy on science education reform. Journal of Science Teacher Education, 24(4), 693--715.
[15]
Johnson, S. M., Marietta, G., Higgins, M. C., Mapp, K. L., & Grossman, A. S. (2014). Achieving coherence in district improvement: Managing the relationship between the central office and schools. Harvard Education Press.
[16]
Tate, C., Remold, J & Bienkowski, M. (2018). Pursuing the vision of CSforAll: views from the front lines. ACM Inroads, 9(3), 48--52.
[17]
Code.org (2021). 2021 state of computer science education: Accelerating action through advocacy. https://advocacy.code.org/2021_state_of_cs.pdf
[18]
Hung, M., Smith, W. A., Voss, M. W., Franklin, J. D., Gu, Y., & Bounsanga, J. (2020). Exploring student achievement gaps in school districts across the United States. Education and Urban Society, 52(2), 175--193.
[19]
Koshy, S., Martin, A., Hinton, L., Scott, A., Twarek, B., Davis, K. (2021). The Computer Science Teacher Landscape: Results of a Nationwide Teacher Survey. The Kapor Center. https://www.kaporcenter.org/wp-content/uploads/2021/05/KC21002_-CS-Teacher-Survey-Report_final.pdf
[20]
Jarvis, S. N., & Okonofua, J. A. (2020). School deferred: When bias affects school leaders. Social Psychological and Personality Science, 11(4), 492--498.
[21]
Kowalski, T. J., & Brunner, C. C. (2011). The school superintendent: Roles, challenges, and issues. Sage handbook of educational leadership: Advances in theory, research, and practice.
[22]
Levin, S., Scott, C., Yang, M., Leung, M., & Bradley, K. (2020). Supporting a Strong, Stable Principal Workforce: What Matters and What Can Be Done. Research Report. Learning Policy Institute.
[23]
Joseph, S. (2023). A Call for Black Superintendents to Document Their Experiences Through Autoethnography. Urban Education, 58(6), 1415--1434. https://doi.org/10.1177/00420859231153414
[24]
Proctor, C., Bigman, M., & Blikstein, P. (2019, February). Defining and designing computer science education in a k12 public school district. In Proceedings of the 50th ACM technical symposium on computer science education (pp. 314--320).
[25]
Vakil, S. (2018). Ethics, identity, and political vision: Toward a justice-centered approach to equity in computer science education. Harvard Educational Review, 88(1), 26--52.
[26]
Kania, J., Kramer, M., & Senge, P. (2018). The water of systems change. FSG. https://www.fsg.org/publications/water_of_systems_change
[27]
DiStefano, C., Zhu, M., & Mindrila, D. (2009). Understanding and using factor scores: Considerations for the applied researcher. Practical Assessment, Research, and Evaluation, 14(1), 20.
[28]
Watkins, M. W. (2018). Exploratory factor analysis: A guide to best practice. Journal of Black Psychology, 44(3), 219--246.
[29]
Sax, L. J., Newhouse, K. N., Goode, J., Nakajima, T. M., Skorodinsky, M., & Sendowski, M. (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 Education (TOCE), 22(2), 1--26.
[30]
NCES (2024). Locale Definitions. Retrieved from https://nces.ed.gov/surveys/annualreports/topical-studies/locale/definitions
[31]
Costello, A.B. & Osbourne, J. (2005). Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. Practical Assessment, Research, and Evaluation, 10(10), 1--9.
[32]
Batterton, K. A., & Hale, K. N. (2017). The Likert scale what it is and how to use it. Phalanx, 50(2), 32--39.
[33]
van Buuren S, Groothuis-Oudshoorn K (2011). "mice: Multivariate Imputation by Chained Equations in R." Journal of Statistical Software, 45(3), 1--67.
[34]
Schafer JL. Multiple imputation: a primer. Statistical Methods in Medical Research. 1999;8(1):3--15.
[35]
Schreiber, J. B. (2021). Issues and recommendations for exploratory factor analysis and principal component analysis. Research in Social and Administrative Pharmacy, 17(5), 1004--1011.
[36]
Osbourne, J.W. (2015). What is Rotating in Exploratory Factor Analysis? Practical Assessment, Research, and Evaluation, 20(20), 1--7.
[37]
Diaz-Ramirez LG, Lee SJ, Smith AK, Gan S, Boscardin WJ. A Novel Method for Identifying a Parsimonious and Accurate Predictive Model for Multiple Clinical Outcomes. Comput Methods Programs Biomed. 2021 Jun.
[38]
Mercer, A. W., Kreuter, F., Keeter, S., & Stuart, E. A. (2017). Theory and practice in nonprobability surveys: parallels between causal inference and survey inference. Public Opinion Quarterly, 81(S1), 250--271.
Index Terms
- U.S. PK-12 Superintendent and High School Principal Perceptions Toward Computer Science Education
Recommendations
Teacher Perceptions of Equity in High School Computer Science Classrooms
Effective and equitable CS teaching is contingent on teachers’ robust understanding of equity issues in CS classrooms. To this end, this study examined high school teachers’ perceptions of equity during their participation in a CS teacher certificate ...
Changing perceptions of computer science and computational thinking among high school teachers
Interest in specific college majors begins in high school. The influence of high school math and science teachers is important, both for high school preparation of future computer science undergraduates, and for the understanding and interest in ...
Defining and Designing Computer Science Education in a K12 Public School District
SIGCSE '19: Proceedings of the 50th ACM Technical Symposium on Computer Science EducationComputer science is poised to become a core discipline in K12 education, however there are unresolved tensions between the definitions and purposes of computer science and public education. This study's goal is to explore how logistical and conceptual ...
Comments
Information & Contributors
Information
Published In
May 2024
321 pages
ISBN:9798400706264
DOI:10.1145/3653666
- General Chair:
- Tamara Pearson,
- Program Chairs:
- Carla Strickland,
- Maya Israel
Copyright © 2024 Owner/Author.
This work is licensed under a Creative Commons Attribution International 4.0 License.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 16 May 2024
Check for updates
Author Tags
Qualifiers
- Research-article
Conference
RESPECT 2024
Sponsor:
RESPECT 2024: Conference for Research on Equitable and Sustained Participation in Engineering, Computing, and Technology
May 16 - 17, 2024
GA, Atlanta, USA
Upcoming Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 116Total Downloads
- Downloads (Last 12 months)116
- Downloads (Last 6 weeks)15
Reflects downloads up to 05 Jan 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in