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Data science has increasingly integrated sociocritical theories and approaches, helping youth to not only learn data science but also relate data to their everyday and sociohistorical lives. Our project, Writing Data Stories, furthers these efforts by exploring sociocritical data literacies in a large-scale classroom enactment. We examine trends in middle school science student groups’ (n=11) data participation and sociocritical participation, showing how these forms of participation ebb and flow across a 21-day unit. We then present focal group case studies to further unpack how participation shifted over time and suggest what factors contributed to these shifts. We found that data participation was affected by the tools at students’ disposal, and sociocritical participation was shaped by the questions groups asked of each other and the data. These findings suggest that special attention to tools and guiding questions is critical when designing for sociocritical data literacy in middle school science contexts. 

We report on a curriculum development project in which students explore environmental racism through data. Recognizing that quantitative data alone is insufficient to understand the sociohistorical contexts of racism, we draw from syncretic approaches to learning that put everyday experiences and qualitative evidence into direct conversation with quantitative datasets through storytelling. Through two focal cases, we demonstrate how one student leveraged personal experience to engage in deep integrative analysis of data, while another with fewer perceived personal connections to environmental racism focused more specifically on patterns, with less structural or racial analysis. Implications of the analysis include the need to carefully attend to the use of quantitative data related to race and to scaffold the integration of other sources of information with quantitative data sets. 

There is growing interest in how to better prepare K–12 students to work with data. In this article, we assert that these discussions of teaching and learning must attend to the human dimensions of data work. Specifically, we draw from several established lines of research to argue that practices involving the creation and manipulation of data are shaped by a combination of personal experiences, cultural tools and practices, and political concerns. We demonstrate through two examples how our proposed humanistic stance highlights ways that efforts to make data personally relevant for youth also necessarily implicate cultural and sociopolitical dimensions that affect the design and learning opportunities in data-rich learning environments. We offer an interdisciplinary framework based on literature from multiple bodies of educational research to inform design, teaching and research for more effective, responsible, and inclusive student learning experiences with and about data. 

I've already deposited this and this record is a duplicate. I apparently can't move on with the project report unless I submit a duplicate for some reason. 

The ability to interpret, evaluate, and make data-based decisions is critical in the age of big data. Normative scripts around the use of data position them as a privileged epistemic form conferring authority through objectivity that can serve as a lever for effecting change. However, humans and materials shape how data are created and used which can reinscribe existing power relations in society at large (Van Wart, Lanouette & Parikh, 2020). Thus, research is needed on how learners can be supported to engage in critical data literacies through sociocultural perspectives. As a field intimately concerned with data-based reasoning, social justice, and design, the learning sciences is well-positioned to contribute to such an effort. This symposium brings together scholars to present theoretical frameworks and empirical studies on the design of learning spaces for critical data literacies. This collection supports a larger discussion around existing tensions, additional design considerations, and new methodologies. 

The projects in this interactive poster symposium explore ways of engaging learners with social justice issues through the design and study of data literacy interventions. These interventions span classroom to museum contexts, and environmental to social sciences domains. Together, they illustrate research and practice approaches for engaging learners with data to promote emancipatory activity.