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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.
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Ontological Alignment: Investigating the Role of the Teacher in Supporting Computational Modeling in Science Classrooms
Though the medium of computational modeling presents unique opportunities and challenges for science learning, little research examines how teachers can effectively support students in this work. To address this gap, we investigate how an experienced 6th grade teacher guides her students through programming computational, agent-based models of diffusion. Using interaction analysis of whole-class videos, we define a construct we call ontological alignment in which the teacher facilitates discourse to surface, highlight, connect and seek supporting or contradictory evidence for student ideas in ways that align with the level of analysis available in the modeling tool. We identify two practices reflecting this construct; the teacher 1. primes students to orient to interactions between particles and 2. strategically selects evidence to help discern between student theories. We discuss the pedagogical value of ontological alignment and suggest the identified practices as exemplary for supporting students’ learning through computational modeling.
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- Award ID(s):
- 2010413
- PAR ID:
- 10424610
- Editor(s):
- Blikstein, P.; Brennan, K; Kiziko, R.; van Aalst, J.
- Date Published:
- Journal Name:
- Proceedings of the 2023 Annual Meeting of the International Society for the Learning Sciences
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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