Agent-based Programming and Modeling in Elementary Science: Aesthetic Experience, Disciplined Interpretation, and Heterogeneity

Abstract

Modeling is the central representational and epistemic practice of science (Giere, 1984; Nersessian, 2008) and likewise an essential practice for K12 science learners (Lehrer, 2009; NRC, 2007, 2012). However, images of scientific practice in elementary classrooms rarely cast opportunities for students to realize the personal, interpretive, and deeply heterogeneous nature of the production of scientific knowledge through modeling. As computational modeling is also now regarded as a key practice for settings of K12 science education (NRC, 2012), science educators and learning scientists grapple with the challenges of integrating computational modeling within the broader contexts of science learning. In these three studies, I investigate the specific genre of agent-based computational modeling for science learning in Grades 4 - 6 and identify forms of experience that can help us understand how programming can become a complementary representational form in kinematics learning sequences. I first propose a framework for thinking about children’s computational modeling work as a form of Deweyan (1934/2005) aesthetic experience, with a focus on initially disengaged learners. In the second study, I argue that the integration of computation supported learners’ development of “disciplined interpretation” in modeling, and that students’ work was progressively deepened as the subjective nature of the experience of modeling was increasingly available and valued, rather than deemphasized. In the third paper, I describe how computational abstractions were grounded and contextualized in the lifeworld of two classrooms. Scientific computing using agent-based modeling was deeply heterogeneous in terms of teachers’ and learners’ use of the environment and the ways that learners and teachers operated in the “mangle” (Pickering, 1995) among theories, instruments, investigations, and computing and brought these into contact with one another. I also discuss how such phenomenological images of computational modeling in classrooms and scientific practice can help us better design computational modeling environments and activity systems for classroom integration in K-12 science.