Thinking Like a Wolf, a Sheep, or a Firefly: Learning Biology Through Constructing and Testing Computational Theories
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Cognition & Instruction 24 (2):171-209 (2006)
Biological phenomena can be investigated at multiple levels, from the molecular to the cellular to the organismic to the ecological. In typical biology instruction, these levels have been segregated. Yet, it is by examining the connections between such levels that many phenomena in biology, and complex systems in general, are best explained. We describe a computation-based approach that enables students to investigate the connections between different biological levels. Using agent-based, embodied modeling tools, students model the microrules underlying a biological phenomenon and observe the resultant aggregate dynamics. We describe 2 cases in which this approach was used. In both cases, students framed hypotheses, constructed multiagent models that incorporate these hypotheses, and tested these by running their models and observing the outcomes. Contrasting these cases against traditionally used, classical equation-based approaches, we argue that the embodied modeling approach connects more directly to students’ experience, enables extended investigations as well as deeper understanding, and enables “advanced” topics to be productively introduced into the high school curriculum.
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Michael Weisberg & Kenneth Reisman (2008). The Robust Volterra Principle. Philosophy of Science 75 (1):106-131.
Michelene T. H. Chi, Rod D. Roscoe, James D. Slotta, Marguerite Roy & Catherine C. Chase (2012). Misconceived Causal Explanations for Emergent Processes. Cognitive Science 36 (1):1-61.
Sanjay Chandrasekharan & Nancy J. Nersessian (2015). Building Cognition: The Construction of Computational Representations for Scientific Discovery. Cognitive Science 39 (8):1727-1763.
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