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Engaging the Tensions Between Data and Experience: Writing Data Stories With Story Builder (Poster 5)

Sun, April 16, 2:50 to 4:20pm CDT (2:50 to 4:20pm CDT), InterContinental Chicago Magnificent Mile, Floor: 3rd Floor, King Arthur Court

Abstract

There is growing interest in supporting K-12 students’ engagement with data along multiple conceptual and social dimensions (Philip et al., 2013; Ridgway, 2015). We have developed several middle school units that bring together science, data, and social-historical inquiry through storytelling. More specifically, we support students in exploring how data and science intersect with issues of marginalization, privilege, and advocacy through the construction of multimedia data stories. Our goal is to highlight how specific personal and community experiences shine light on what is revealed, hidden, or otherwise embedded within public scientific datasets.
The theoretical basis for our work is syncretism, a design approach that brings together everyday and scientific practices that are generally in tension in order to explore how those tensions reveal different histories, values, and power relations (Gutiérrez, 2014). In our project, syncretism motivates a more specific design principle for computational data work: engaging the tensions between data as a social and scientific text on one hand, and students’ own personal and community experiences on the other, through storytelling.
This principle offers a way to deeply integrate technical and social dimensions of data work by drawing on students’ own repertoires of practice and experiences within society (Wilkerson & Polman, 2019; Lee et al., 2021). We have observed students question why price or preparation time–features that are important to many families’ meal decision making–are not included in datasets about food and nutrition (Lee et al., 2022). We have seen them critique existing AQI maps, whose granular geographic and temporal resolution make it difficult to predict health risks for youth who move across space and time. Exposing and engaging these tensions between data and experience requires a careful balance. Data and computing skills such as understanding measurements, merging and transforming datasets, or disaggregating observations are needed to more deeply understand how patterns in data might connect with certain experiences or communities. At the same time, social and historical analysis is needed to understand how context, history, and perspective affect how datasets are constructed, what questions those datasets can address, and what might be underlying causes for patterns.
To support this design, we have worked with educators to co-develop curriculum units, DIY frameworks for teachers, and Story Builder, a new plug-in within the Common Online Data Analysis Platform (“CODAP”; Finzer & Damelin, 2015) that captures collections of graphs, maps, tables, text, images, videos, websites, and other components “moments” of a data story (Blinded, 2021). This makes transparent how and why data, personal, and community knowledge each informed and shaped students’ data investigations and findings. Our goal in promoting this work is to support students in becoming historical actors (Gutiérrez et al., 2019) who recognize injustice as not merely an individual experience but rather part of systemic oppression and who imagine and work toward a more just society. In our presentation for this session, we will share the (free, open source) Story Builder plug-in, curricular and activity support for writing data stories, and multiple examples of student-created data stories.

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