Toward Ontological Alignment: Coordinating Student Ideas with the Representational System of a Computational Modeling Unit for Science Learning

Abstract

Computational modeling tools present unique opportunities and challenges for student learning. Each tool has a representational system that impacts the kinds of explorations students engage in. Inquiry aligned with a tool’s representational system can support more productive engagement toward target learning goals. However, little research has examined how teachers can make visible the ways students’ ideas about a phenomenon can be expressed and explored within a tool’s representational system. In this paper, we elaborate on the construct of ontological alignment—that is, identifying and leveraging points of resonance between students’ existing ideas and the representational system of a tool. Using interaction analysis, we identify alignment practices adopted by a science teacher and her students in a computational agent-based modeling unit. Specifically, we describe three practices: (1) Elevating student ideas relevant to the tool’s representational system; (2) Exploring and testing links between students’ conceptual and computational models; and (3) Drawing on evidence resonant with the tool’s representational system to differentiate between theories. Finally, we discuss the pedagogical value of ontological alignment as a way to leverage students’ ideas in alignment with a tool’s representational system and suggest the presented practices as exemplary ways to support students’ computational modeling for science learning.