Writing Data Stories is a social design-based research project to co-design and study data literacy units. The project encourages nondominant students to integrate everyday practices and scientific datasets by using storytelling and computational transformation to highlight personally and socially relevant issues. We present an analysis of one cycle of instruction where students pursued an unanticipated path of investigation—locating themselves on a map within a data analysis tool though the dataset lacked geographic information. A researcher initially considered this path to be unproductive, but changed focus as the teacher followed students’ lead and encouraged exploration of the map in subsequent classes. Using conceptions of third space, we examine the sequence through which teachers and students co-produced a reorganization of the activity, power relations, and curriculum toward expansive data reasoning. We contrast this productive reorganization with marginalization of other student practices, identifying implications for curricular design and classroom research.

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.