Commitments, Convergence, and Modeling in Middle School Science

• In Event: Thinking Across Representations: Designing to Leverage Material and Computational Investigations for Science Learning

Abstract

Objectives. We explore tensions between heterogeneity (Roseberry et al., 2010) and convergence (NSF, 2019) in science classrooms. Science relies on heterogeneity, including diversity in students’ ideas, languages, and representational practices (Author, 2016; Lehrer, 2009; Manz & Suárez, 2018). Convergence, “the merging of ideas, approaches, and technologies from widely diverse fields of knowledge” has also been positioned by the US National Science Foundation as central to science (2019). While “the merging of ideas and approaches” can spur discovery, driving toward consensus can also suppress diversity. We ask, how can science classrooms value diversity in students’ thinking while facilitating convergence?

Theoretical framework. Research demonstrates affordances of students creating and using multiple representations for science learning (e.g., Ainsworth, Tytler, & Prain, 2020; Parnafes & diSessa, 2004), yet less is known about how to help students connect models in a way that preserves representational and conceptual diversity. Convergence as unification (e.g., a consensus model) can hinder heterogeneity, because focusing on a final form model can suppress diverse contributions to and interpretations of the model (Duschl, 2008). Studies of science offer another image of convergence: resonance between models (Latour, 1999; Lehrer, 2009). Professional scientists are motivated to create, maintain, and link resonant models in response to sometimes-conflicting commitments (e.g., accuracy, ethics; Latour, 1999; Nersessian, 2017). In this paper, we explore students’ commitments for modeling – their sense of purpose in constructing or using multiple models. We propose that commitments that emerge during modeling could be used to make sense of multiple models (across and within phenomena).

Methods and data. Data were collected during a six-cycle design study (Cobb et al., 2003) aiming to integrate computational modeling into an NGSS-aligned ecology unit (NGSS Lead States, 2013). During the 9-week unit, students design a biosphere to determine guppies’ survival needs and build computational models to study guppies’ ecosystems (Table 1). We collected whole class data and data from 5-6 focal students per cycle (33 total), including all student work and video recordings of class sessions, to trace commitments that emerged and shaped modeling practices. We also collected video/audio recordings of focal students interacting with their peers and computers and conducted interviews with focal students to understand how students perceived models as related to each other and used models as representations for reasoning about ecosystems.

Results and significance. Commitments surfaced in students’ modeling, including accuracy, ethics, control, and visibility, shaping how they used and valued models for understanding ecosystems (see Table 2 - frequency, Table 3 - examples). Still, commitments were not fully stable or socially shared. Within a modeling activity, students differently expressed, valued, and addressed commitments. Also, individual students related to commitments differently throughout the unit. Therefore, commitments were not attached to specific models, model types, or students, and they did not settle into a hierarchy that dictated future modeling choices. Although commitments were differently expressed, valued, and addressed, they offered a ground for connecting and comparing models. Thus, discourse related to commitments shows promise for facilitating convergence while preserving heterogeneity in student thinking.

Authors

• Ashlyn Pierson, The Ohio State University

• Corey Brady, Vanderbilt University

• Doug Clark, University of Calgary

• Pratim Sengupta, University of Calgary