Scientific Modeling and Translanguaging: Supporting Productive Science Discourse

• In Event: Translanguaging and Disciplinary Literacies

Abstract

Objectives. This paper addresses two forces shaping science education. First, a new wave of reform emphasizes science practices (e.g., NGSS Lead States, 2013). Second, broadening participation to include bilingual students is urgent, because students classified as English learners (ELs) are the fastest growing subset of the U.S. student population (National Center for Education Statistics, 2019). In this paper, we use a syncretic approach (Gutiérrez & Jurow, 2016) to blend scientific modeling with translanguaging, leveraging linguistic diversity in service of inquiry.

Theoretical framework. Translanguaging practices can support rigorous engagement in STEM by increasing students’ access to representational resources (e.g., Moschkovich, 2015). Furthermore, similarities between linguistic and scientific practices can be leveraged synergistically (Hudicourt-Barnes, 2003). In this paper, we build on this research by identifying structural similarities between modeling and translanguaging. Parallels exist because both practices are used for bridging boundaries by creating and conveying ideas with representations (Galison, 1997; García & Kleyn, 2016).

Methods and data. In a design study conducted in a 6th grade STEM classroom as part of a 9-week ecology unit, we explored how students leveraged modeling and translanguaging, focusing two syncretic practices: translating as a part of modeling and using language and conversation as metaphors for multimodal modeling. We used conjecture mapping (Sandoval, 2014) to specify elements of our design and how they contribute to desired outcomes (Figure 1). We consider science discourse “productive” when it supports the development of scientific knowledge, practices, and community (Lehrer & Schauble, 2015). We conjecture that integrating modeling and translanguaging can contribute to productive science discourse by helping students leverage multilingual and multimodal resources to: understand complex phenomena, express ideas, and legitimize diverse linguistic and representational practices. We collected classroom video and student artifacts, which were analyzed using inductive coding and constant-comparative analysis (Charmaz, 2006; Strauss & Corbin, 1990).

Results and significance. This paper advances theory by describing how a syncretic approach integrating modeling and translanguaging supports productive science discourse. In the full paper, we trace pathways through the conjecture map (Figure 1). Here, we illustrate one pathway: while translating as a part of modeling, students created and selected among representations, contributing to productive science discourse. During the unit, the teacher (Ms. S) created opportunities for students to reflect on the creation and meaning of class terms. For example, Ms. S noticed that language had not emerged to describe a pattern in the computational model’s graph when the ecosystem was stable. When asked to describe the pattern, students mimicked the shape of the graph with a gesture. As this phenomenon became central to students’ discourse, Ms. S asked students to nominate English, Spanish, and invented terms to describe the pattern, legitimizing resources beyond English. Luis offered English, Spanish, and invented terms: “We did fluctuate, balanciado, and we also made up a word. It’s from balanced and graph. It’s a balagraph.” These examples demonstrate the wealth of resources that students brought to interpreting and describing the pattern; students drew on their full repertoires to enrich their understanding of the phenomenon.

Authors

• Ashlyn Pierson, The Ohio State University

• Doug Clark, University of Calgary

• Corey Brady, Vanderbilt University