Confronting Inequities in Computer Science Education: A Case for Critical Theory
How might we better address the pervasive inequities in CS education? While empirical efforts have advanced pedagogy, created innovative learning tools, and deepened our understanding of learner cognition, we are still failing many students. Disparities in who can access and who succeeds in CS persist. In this position paper I argue that we need to reconsider how we approach CS education research (CSER). Prior research discussions have focused on methodologies, but research designs are influenced by more than strategies and methods of data collection. They are also guided by philosophies of how the world works. Philosophical views dominant in CSER have served us well in answering questions such as which instructional approaches lead to greater achievement or how do alternative programming conceptions develop. However, confronting systemic problems that prevent some learners from being at the table might require a transformative research lens. I introduce critical theory as a means to put inequities and the voices of the marginalized at the fore of our research. This is demonstrated through the analysis of three examples: a narrative ethnographic analysis of the power differences in a researcher practitioner partnership serving Latinx youth; an auto ethnography of a Black scholar‚ journey into an IT career; and a survey study examining the relationship between interest, stereotypes and CS career intentions in students from minoritized groups. Lastly, I offer a call to action for increasing the use and acceptance of critical theory in our dissemination venues and professional development opportunities.
Confronting Inequities in Computer Science Education: A Case for Critical Theory
- Author Hubbard Cheuoua, Aleata
- Publication Title Proceedings Of The 52Nd ACM Technical Symposium On Computer Science Education
- Publication Year 2021
- BPC Focus Underrepresented Racial/Ethnic Groups, Black/African American Students, Latinx/Hispanic
- Methodology Survey, Program Evaluation
- Analytic Method Regression
- Institution Type NA
- DOI 10.1145/3408877.3432453
- URL https://doi.org/10.1145/3408877.3432453