A Framework for Exploring Self, Community, Histories, and Futures Through Data

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

Abstract

“Big data” describe complex socio-scientific systems that connect to geographical, social, environmental, and demographic features of students’ lives and identities (Donoho, 2017; Philip et al., 2013; 2016). How these systems are described, classified, and interpreted reflect the perspectives and values of those who construct the data set (D’Ignazio & Klien, 2020); these may differ significantly from those of students, reinforcing dominant narratives and marginalizing others. At the core of this project is an exploration of how we might help students to “think more carefully about the process by which anecdote is transformed into data and information” (Silver, 2014, para. 33) as an integral part of engaging in and communicating the results of data analysis.
We situate our work broadly within the growing literature on heterogenous reasoning; specifically syncretic literacy (Gutierrez, 2008). Syncretic literacy challenges common conceptualizations of learning as a progression from informal experience—including students’ everyday experiences and place-based knowledge—toward formality (as in the quote above, a movement from “anecdote” to “data”). Instead, we seek to elevate and place these knowledges in direct conversation, to engage learners in deep conceptual learning as well as an understanding of how power structures and inequities operate within, and might be challenged within, formal disciplines (Gutiérrez & Jurow, 2016).
Specifically, we will share a pedagogical framework that has emerged over two years of iterative co-design with teachers of curriculum units, including ones focused on place-based approaches to climate change and environmental justice. The framework was crystallized as pedagogical limitations related to COVID-19 shelter-in-place orders required educators to move toward shorter data engagements including brief “data talks.” It includes: (1) Making sense of trends and relationships observed in a data set or visualization; (2) Building personal connections by considering how students’ lives and communities are impacted or reflected by the patterns found in data; (3) Reflecting on the context and history of the data, how it was collected, by whom (including what gets “counted” or not), what might be missing/hidden, and what questions the data can and cannot answer; (4) Envisioning future uses and adaptations of the data to expand the investigation and explore different perspectives.
Our poster will focus on enactments of this sequence as they unfold across videos, youth and teacher-generated artifacts, transcripts, and observational field notes from two study contexts. The first context includes two week-long youth workshops being conducted this summer focused on data, advocacy, and environmental justice in an urban environment in the western U.S. During the workshops, the framework was used to guide students’ analyses of data-focused case studies of community environmental activism, as well as students’ construction of environmental justice “data stories” that explore health and environmental data about their communities. The second context features semi-structured clinical interviews with teachers and students as they interact with visualizations and analyze data sets using the framework as an explicit guide. Analysis is ongoing and will focus on the extent and processes by which the framework encourages syncretic data literacy as characterized by heterogeneity of experiential and data reasoning.

Authors

• Michelle Hoda Wilkerson, University of California - Berkeley

• David Stokes, North Carolina State University

• Hollylynne Stohl Lee, North Carolina State University

• Emily V. Reigh, Stanford University

• Meg Elena Escudé, University of California, Berkeley

• Edward Rivero, University of California - Berkeley

• Kris D. Gutiérrez, University of California - Berkeley