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Technology, Knowledge and Learning

, Volume 19, Issue 1–2, pp 19–52 | Cite as

On the Embedded Complementarity of Agent-Based and Aggregate Reasoning in Students’ Developing Understanding of Dynamic Systems

  • Walter M. Stroup
  • Uri Wilensky
Article
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Abstract

Placed in the larger context of broadening the engagement with systems dynamics and complexity theory in school-aged learning and teaching, this paper is intended to introduce, situate, and illustrate—with results from the use of network supported participatory simulations in classrooms—a stance we call ‘embedded complementarity’ as an account of the relations between two major forms of systems-related learning and reasoning. The two forms of systems reasoning discussed are called ‘aggregate’ and ‘agent-based.’ These forms of reasoning are presented as distinct yet we also outline how there are forms of complementarity, between and within these approaches, useful in analyzing complex dynamic systems. We then explore specific ways in which the embedded complementarity stance can be used to analyze how learner understandings progress in science, technology, engineering, and mathematics-related participatory simulations supported by the HubNet (Wilensky and Stroup 1999c) learning environment developed with support from the National Science Foundation. We found that the learners used and built on the interdependence of agent and aggregate forms of reasoning in ways consistent with the discussion of embedded complementarity outlined in the early parts of the paper.

Keywords

Dynamic systems Complexity theory Agent-based modeling Aggregate modeling Participatory simulations NetLogo HubNet 
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Notes

Acknowledgments

We would like to acknowledge the considerable contributions of Dor Abrahamson, Sarah Davis and Andrew Hurford to the activity design, data collection, coding, and analyses contributing to the development of this paper. We would also like to thank Bruce Sherin and Richard Noss for their steadfast support and helpful comments. We are particularly grateful to Michelle Wilkerson-Jerde for her remarkably thorough, insightful, and deeply engaged comments and suggestions regarding early iterations of this paper. Funding from the National Science Foundation, Grant 126227 titled Integrated Simulation and Modeling Environment Project, made this work possible. Texas Instruments also provided significant material support for aspects of this work. The views expressed herein are those of the authors and do not necessarily reflect those of the funding institutions.

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© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.The University of Texas at AustinAustinUSA
  2. 2.Northwestern UniversityEvanstonUSA

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