Cultivating Identities of Care in the Science Classroom Using Complex Systems Data and Modeling

• In Event: Data Literacy in Context: Culturally Oriented and Place-Based Learning Through Data

Abstract

Systems thinking can be counterintuitive to everyday ways of knowing (Grotzer et al., 2019; Yoon et al., 2019). This can surface doubt around predicted patterns of emergence in complex systems data, especially as it relates to the current climate crisis and related community-based and justice-oriented solutions. Our study describes a three-year design-based research project in which we engaged high school biology students in complex systems modeling of two large- scale citizen science data sets (MARINe & Flu Near You) to understand the linkages between increasing temperatures and the rate and severity of disease outbreaks (Harvell et al., 2002). Our research questions asked, a) What computational inquiry practices support students’ sensemaking of large-scale climate data sets? and b) How can systems modeling practices help students identify community and place-based approaches for addressing the global climate crisis?
This study was part of a three-year design-based research project (DBR Collective, 2003) in which project-based curriculum units involving computational thinking (Weintrop et al., 2016) were codesigned in partnership with teachers, community members, and disciplinary experts in order to situate learning in local contexts. Through the lens of social practice theory (Wenger, 2000), we focused on sociomaterial arrangements and tools that positioned students as developing experts on the boundaries of multiple communities of practice, with a focus on how climate-related identities, computational tools, and terminology differ for learners across contexts (Penuel, 2014). We used qualitative methods (Merriam, 2009) and grounded theory (Strauss & Corbin, 1997) to analyze over 90 hours of classroom observations that included video data, ethnographic field notes, student artifacts and 30 hours of student interview data to surface the coordination of tools, practices, and discourses that supported students’ ability to locate the core causes of climate change, and to design just and place-based centered solutions for their communities.
Our initial findings showed that students approached climate data with uncertainty and viewed their lives as separate from the impacts of climate change. Through iterative design work, youth used authentic data and computational tools to construct geospatial and causal-loop models of climate-related disease outbreaks that situated case studies within broader socioecological and sociotechnical contexts of historic and powered human decision making. Systems models positioned students as a part of natural systems and enabled students to consider “whose needs are being served?” when designing for local climate action. Students shifted their understanding of disease outbreaks from one of technical understanding to one of care and responsibility for mitigating the impacts of the climate crisis on human and nonhuman communities through local action and ongoing research. As one student reflected on the role of data analysis and modeling through project work she shared, "We never knew how much we truly impacted sea stars, and other species. I now deeply care about the effects humans are having on the world and want to do something to change this.”

Authors

• Veronica Cassone McGowan, University of Washington Bothell

• Philip L. Bell, University of Washington