Applying a humanistic data science framework to curricular development and implementation: a forensic analysis of synergies and tensions across layers in middle school social studies

Purpose As data science education becomes more common in K-12 education, there is a need to teach students about the technical, sociopolitical, and ethical dimensions of data. The authors restrospectively apply a humanistic stance toward data science education to investigate middle school students’ engagements with data across the personal, cultural, and sociopolitical layers. The purpose of this article is to develop theory and knowledge toward sustainable data literacy education that foreground Indigenous perspectives in U.S. social studies curricula. To that end, the research questions focus on multiple stakeholders (e.g., students, teacher, Indigenous communities). Design/methodology/approach Drawing on a rich corpus of qualitative data, including reflective interviews with the students and teacher and student work, a forensic analysis of the designed and enacted curriculum was conducted, unpacking the personal, cultural, and sociopolitical layers of data, paying particular attention to synergies or tensions between the layers. Findings The findings reveal synergies between layers that foregrounded student agency and emphasized Indigenous perspectives alongside tensions between layers that disrupted student sensemaking and supported a deficit perspective of Indigenous communities. Originality/value The study extends prior work on data science education in social studies by operationalizing three layers of a humanistic stance toward data science to analyze students’ interactions across layers of data science in the unit, drawing attention to the implications of taken-for-granted tools of classroom data science and power structures and positioning within and outside of the classroom.