Humanizing Data Through Critical Ethnographic Narratives: Integrating Computer Science Project-Based Inquiry Across K-12 Disciplines (Poster 3)

• In Event: Formative Research and Pedagogical Approaches to Integrate Computational Thinking and Computer Science in a Residency

Abstract

Objectives or Purposes
We teach computer science (CS) to K-12 teachers earning a CS supplemental authorization. Our students as teachers come from diverse disciplines and work in urban Title I schools, serving predominantly Black and Brown students in historically low-income communities in Southern California. In solidarity with the communities we serve, we aspire for a critical and humanizing approach to data science, informed by critical race theory, critical studies, and abolitionist tools in computing education.
Inquiry Question: How do K-12 Teachers apply computing and computational thinking practices to critical issues in understanding data?
The Why: As Teacher educators, how do we support and encourage our students as K-12 teachers in reimagining computing education through humanizing and critical pedagogies? How might we transform our practice to further reimagine computing education?
Theories of Humanizing Framework
Because we are passionate and challenged to freedom dream and reimagine a humanizing and critical pedagogy in CS curriculum and classrooms, we lean on our humanizing framework consisting of several theories: (re)humanizing students situated in critical pedagogy (Freire, 1970/2018, Salazar, 2013), care and healing pedagogy (Ginwright, 2016, 2022; Noddings, 2005), culturally responsive/sustaining pedagogies (Davis et al., 2021, Gay, 2018; Ladson-Billings, 2014; Paris & Alim, 2014), and critical race theory (DeCuir & Dixson, 2004; Ladson-Billings, 2021; Solórzano, 1997; Yosso, 2005).
Methodological Approach
We approach our inquiry from Safir’s Levels of Data framework in which researchers shift away from collecting dehumanizing quantitative satellite data to gathering decolonizing and critical ethnographic street data (Safir & Dugan, 2021). Our positionalities and philosophy of computing education align with a decolonizing and critical ethnographic methodology in a case study which orients towards reconceptualizing inquiry for social and educational transformation in urban schools and communities (Calabrese Barton, 2001; Safir & Dugan, 2021).
Data Sources
The students in our CS pathway are pre-service and in-service teachers serving in urban Title 1 schools. Our inquiry focuses on a cohort of 24 students in the first of four computer science courses, Computational Thinking with Data Science. We delved deeply into our students’ assignments, including reflections and projects, that occurred between August and December 2023. Our inquiry focuses on a newly designed project for the course, Data Story: Humanizing Students with “Street Data” Inquiry Project (see Appendices A to C). We focused on five students’ projects to examine their dispositions and shifts in computing pedagogy and practices.
Results and Significance
The teachers selected their inquiry focus based on data that was humanizing and aligned with our program’s vision for transformative computing education for K-12 students. Their presentations exceeded our expectations by effectively addressing discourse and actions to dismantle racial and socio-political injustices through humanizing data and CS practices. We were also encouraged by their written reflections on the project, which revealed that they felt it positively impacted their philosophy and pedagogy in teaching CS. More significantly, we feel affirmed in our progress towards transforming CS education through this collaborative work with teachers.

Author

• Jane W. Kim, University of California - Los Angeles