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Designing for Equity in Education Via Computational Thinking: A Case Study

Published: 07 March 2024 Publication History

Abstract

CADRE (Catalyst for Actively Designing and Researching Equity) is a Researcher-Practitioner Partnership (RPP) that empowers in-service K-12 educators to learn and leverage Computational Thinking (CT) to design for equity in their classrooms, schools, and districts. We cast equity gaps as bugs in education and focus on helping educators debug the system with CT-based tools, methods, and strategies such as user-centered design, system abstraction, and iteration. In this paper, we first describe how educators were taught CT and provide an example of how they applied these skills in practice. We then highlight the results of the qualitative case study of 34 educators where we found that CT helped CADRE participants gain a better understanding of the equity gaps their students faced and improve their instructional practices within their locus of control. Implications for future research are also discussed.

References

[1]
Duchesneau, N. Social, emotional, and academic development through an equity lens. The Education Trust, Wasington DC, 2020.
[2]
Hammond, Z. Culturally Responsive Teaching and the Brain. Corwin, Thousand Oaks, CA, 2015.
[3]
National Equity Project Educational Equity: A Definition. National Equity Project, Oakland, CA, n.d. https://www.nationalequityproject.org/education-equity-definition
[4]
Santamaria, L. J. Culturally responsive differentiated instruction: Narrowing gaps between best pedagogical practices benefiting all learners. Teachers College Record, 111, 1 (2009), 214--247.
[5]
Delpit, L. Multiplication is for White People: Raising Expectations for Other People's Children. The New Press, New York, NY, 2012
[6]
Ladson-Billings, G. But that's just good teaching! The case for culturally relevant pedagogy. Theory into Practice, 34, 3 (1995), 159--165.
[7]
United States Government Accountability Office K-12 Education Discipline Disparities for Black Students, Boys, and Students with Disabilities (GAO-18--258). US Government Accountability Office, Wasington DC, 2018.
[8]
Carter, P. L., Skiba, R., Arredondo, M. I. and Pollock, M. You can't fix what you don't look at: Acknowleding race in addressing racial discipline disparities. Urban Education, 52, 2 (2017), 207--235.
[9]
Milner IV, H. R. Beyond the test score: Explaining opportunity gaps in educational practice. Journal of Black Studies, 43, 6 (2012), 693--718.
[10]
Gray, D. L., Hope, E. C. and Matthews, J. S. Black and belonging at school: A case for interpersonal, instructional, and institutional opportunity structures. Educational Psychologist, 53, 2 (2017), 97--113.
[11]
Gershenson, S., Holt, S. B. and Papageorge, N. W. Who believes in me? The effect of student-teacher demographic match on teacher expectations. Economics of Education Review, 52, 2016 (2016), 209--224.
[12]
Blackwell, L. S., Trzesniewski, K. H. and Dweck, C. S. Implicit theories of intelligence predict achievement across an adolescent transition: A longitudinal study and an intervention. Child Development, 78, 1 (2007), 246--263.
[13]
Irwin, V., Wang, K., Tezil, J., Filbey, A., Jung, J., Bullock Mann, F., Dilig, R. and Parker, S. Report on the Condition of Education 2023 (NCES 2023--144). US Department of Education Institute of Education Sciences National Center for Education Statistics, Wasington DC, 2023.
[14]
Goodwin, B. The Road Less Traveled: Changing Schools from the Inside Out. McREL International, Denver, CO, 2015.
[15]
Safir, S. and Dugan, J. Street Data: A Next Generation Model for Equity, Pedagogy, and School Transformation. Corwin Press, Thousand Oaks, CA, 2021.
[16]
Shute, V. J., Sun, C. and Asbell-Clarke, J. Demystifying Computational Thinking. Educational Research Review, 22 (2017), 142--158.
[17]
Voskoglou, M. G. and Buckley, S. Problem Solving and Computers in a Learning Environment. Egyptian Computer Science Journal, 36, 4 (2012), 28--46.
[18]
Wing, J. M. Computational Thinking. Communications of the ACM, 49, 3 (2006), 33--35.
[19]
Barr, D., Harrison, J. and Conery, L. Computational Thinking: A Digital Age Skill for Everyone. Learning & Leading with Technology, 38, 6 (2011), 20--23.
[20]
Bower, M., Wood, L. N., Lai, J. W. M., Howe, C., Lister, R., Mason, R., Highfield, K. and Veal, J. Improving the Computational Thinking Pedagogical Capabilities of School Teachers. Australian Journal of Teacher Education, 42, 3 (2017), 53--72.
[21]
Dong, Y., Catete, V., Jocius, R., Lytle, N., Barnes, T., Albert, J., Joshi, D., Robinson, R. and Andrews, A. PRADA: A Practical Model for Integrating Computational Thinking in K-12 Education. Minnesota, MN, 2019.
[22]
Grover, S. and Pea, R. Computational Thinking in K--12: A Review of the State of the Field. Educational Researcher, 42, 1 (2013), 38--43.
[23]
Grover, S. and Pea, R. Computational Thinking: A Competency Whose Time Has Come. Computer Science Education: Perspectives on Teaching and Learning in School, S. Sentance, E. Barendsen and C. Schulte, Eds., New York, New York, Bloomsbury Publishing, 2018, pp. 20--38.
[24]
Harangus, K. and Kátai, Z. Computational Thinking in Secondary and Higher Education. Procedia Manufacturing, 46, (615--622).
[25]
Haseski, U., U. Defining a New 21st Century Skill-Computational Thinking: Concepts and Trends. International Education Studies, 11, 4 (2018), 29--42.
[26]
Settle, A., Hwang, S. and Jones, J. A Framework for Computational Thinking across the Curriculum. Ankara, Turkey, 2010.
[27]
Yadav, A., Hong, H. and Stephenson, C. Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. TechTrends, 60 (2016), 565--568.
[28]
Yadav, A., Stephenson, C. and Hong, H. Computational thinking for teacher education. Communications of the ACM, 60, 4 (2017), 55--62.
[29]
Darling-Hammond, L., Hyler, M. E. and Gardner, M. Effective Teacher Professional Development. Learning Policy Institute, Palo Alto, CA, 2017.
[30]
Nelsestuen, K. and Smith, J. Empathy Interviews. The Learning Professional, 41, 5 (2020), 59--62.
[31]
Saldana, J. The Coding Manual for Qualitative Researchers. Sage Publications, Thousand Oaks, CA, 2009.
[32]
Hill, C. E., Thompson, B. J. and Williams, E. N. A guide to conducting consensual qualitative research. The Counseling Psychologist, 25, 4 (1997), 517--572.
[33]
Leavy, P. L. The Oxford Handbook of Qualitative Research. Oxford University Press, New York, NY, 2014.
[34]
Garson, G. D. Case study research in public administration and public policy: Standards and strategies. Journal of Public Affairs Education, 8, 3 (2002), 209--216.
[35]
Baxter, P. and Jack, S. Qualitative case study methodology: Study design and implementation for novice researchers. The Qualitative Report, 13, 4 (2008), 544--559.

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cover image ACM Conferences
SIGCSE 2024: Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1
March 2024
1583 pages
ISBN:9798400704239
DOI:10.1145/3626252
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 07 March 2024

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Author Tags

  1. computational thinking
  2. csforall
  3. gender and diversity
  4. high school teacher development
  5. k-12 instruction
  6. learning environment
  7. professional practice

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