Developing Data Arguments: The Case of a Professional Learning Community of Secondary Mathematics Teachers

• In Event: Data Science Education: Re-Envisioning for 21st Century Teaching, Learning, and Research

Abstract

Argumentation is common across STEM disciplines and has typically been studied using Toulmin’s (1969) model. School mathematics often relies on deductive reasoning whereas statistics and data science commonly rely on inductive reasoning (Abelson, 1995;Cobb & Moore, 1997;Weiland, 2017). There are well documented challenges to getting argumentation taught in mathematics classrooms (Campbell et al., 2020). These issues create a need for supporting mathematics teachers, who are increasingly asked to teach data science, in creating data-based arguments. This research is guided by the question: How does a Professional Learning Community (PLC) of secondary mathematics teachers support each other in the development of data argument practices?

We draw from sociopolitical theories of learning. We view our PLC as a community of practice (Lave & Wenger, 1991) with learners becoming attuned to the affordances and constraints of the community through cycles of reflection and action. Drawing from perspectives in critical literacy (Freire, 1970), we view every member as an expert, just in different areas, so who is positioned as a more knowledgeable other changes and all knowledge is respected and valued equally. We draw from research in science education focused on data arguments (Berland & Reiser, 2009;Berland & McNeill, 2010) as involving claims, evidences, and reasoning and position it as part of the data investigative process (Lee et al., 2022) and a key component of writing the world with data for critical data literacies (Louie, 2022;Weiland, 2017).

We take a qualitative case study approach (Stake, 2000) where the case is the PLC drawing from individual and group data points including participant end-of-day survey responses, artifacts created while engaging in data investigations, and field notes from the research team. The PLC is part of a design research project (Cobb et al., 2003) where building community is an explicit design principle. We focus on three days of a summer PLC meeting with 16 secondary mathematics teachers focused on creating data arguments in investigations. We used inductive qualitative coding of survey responses to create themes related to how the community served to support participants' learning and then triangulated across other data sources.

We found three themes in how the community supported one another in learning. One theme was the community supported learning through creating space for dialogue to develop and refine their understanding. A second theme was the process of co-creating products such as questions, hypothesis, claims, evidence, and reasoning helped them learn data argumentation practices. A third theme was the community supported learning through sharing resources for doing and teaching data science, which provided the clearest evidence of equal contribution and value across community members. The research team shared research-based resources and designed resources based on teacher’s requests and the teachers shared resources from their experiences teaching. We see evidence that taking a community building approach to teacher education, which is not common, could be productive for supporting the development of mathematics teachers data practices by creating a sustainable, non-hierarchical community on common learning goals as opposed to the typical short term facilitator teaches teachers model.

Authors

• Travis Weiland, University of North Carolina - Charlotte

• Caitlin Ireland, University of North Carolina - Charlotte

• Laura Shelton, University of Houston

• Mandana Delavari, University of Houston