Designing at the Boundary: Exploring Teachers’ Integration of Data Science and Mathematics

• In Event: Supporting Teachers to Engage in Meaningful Data Literacy and Data Science Practices Across Disciplines

Abstract

Objectives
Calls to integrate statistics and data science into K–12 education are growing (e.g., Bargagliotti et al., 2021), but the particulars of how and what to integrate remain unclear (Jiang et al., 2022). Further complicating this, data science’s disciplinary boundaries are blurry – posing both challenges and opportunities, especially in mathematics classrooms where formal norms may conflict with the contextual and messy nature of data scientific work. Indeed, integrating STEM disciplines is an epistemically complex process (Lehrer & Schauble, 2021). This design-based study (Cobb et al., 2003) explores how four high school mathematics teachers worked to integrate data science into their teaching. We asked: To what extent did our data explorations integrate mathematics and data science disciplinary perspectives? How were disciplinary boundaries engaged with, resisted, or redefined?

Theoretical Framework
This study is informed by two strands of literature: integrated STEM and boundary crossing. We conceptualize STEM integration as boundary work, where disciplinary boundaries are positioned as sites of both opportunity and tension. Drawing on the concepts of boundary objects (Star & Griesemer, 1989) and boundary crossing (Akkerman & Bakker, 2011), we examine how different disciplinary practices interact and how teachers negotiate these boundaries in design. This framing allows us to treat interdisciplinary integration not as a merging of content, but as a site of negotiation across epistemic commitments and professional practices.

Methods
This study draws from a larger, multi-year research practice partnership with a professional development organization supporting experienced secondary mathematics teachers. We worked alongside teacher-participants to co-design and implement integrated mathematics and data investigations focused on local and relevant data contexts. Data sources included recordings of 25 design meetings, 16 lesson and classroom artifacts (including Jupyter notebooks, CODAP files, Desmos activities, student work), and three interviews with all four teachers. We constructed case summaries and engaged in iterative coding and memoing to analyze how disciplinary goals were navigated and negotiated during design and implementation.

Findings
Summarized in Table 9.1 below, we present three cases that reflect different configurations of how mathematics and data science were integrated: (1) data as a way to situate mathematics, (2) data in service of mathematics, and (3) data to recontextualize mathematics.

These configurations highlight the varied ways teachers navigated disciplinary boundaries in both design and enactment. Across cases, we observed that teachers made consequential instructional decisions about how prominently to position data science, and how tightly to couple it with mathematical goals. These findings suggest that disciplinary integration is deeply shaped by teacher interpretation, classroom interaction, and local context.

Significance
This study offers insight into how teachers navigate disciplinary boundaries through sustained professional development focused on integrating data science into mathematics instruction. Even with shared design goals, the depth and character of integration varied significantly across cases. Teachers engaged in extended cycles of design, enactment, and reflection, through which they negotiated what counted as valid mathematics or data work. These findings suggest that supporting integration requires more than new curricula, but opportunities for teachers to engage in the complex boundary work interdisciplinary teaching entails.

Authors

• Elizabeth Metts, Vanderbilt University

• Kate Chapman

• Ji Son, California State University - Los Angeles