Designing to Learn About Complex Systems
Complex systems are commonly found in natural and physical science. Understanding such systems is often difficult because they may be viewed from multiple perspectives and their analysis may conflict with or extend beyond the range of everyday experience. There are many complex structural, behavioral, and functional relations to understand as well. Design activities, which allow explorations of how systems work, can be an excellent way to help children acquire a deeper, more systemic understanding of such complex domains. We report on a design experiment in which 6th grade children learned about the human respiratory system by designing artificial lungs and building partial working models. Structure-behavior-function models are used as a framework for the cognitive analysis of the domain. The design activities helped students learn about the respiratory system. The design students indeed learned more than students receiving direct instruction. They learned to view the respiratory system more systemically. As expected, because of the short time they spent on the exercise, they understood more about structure than function and more about the functions of different parts of the respiratory system than its causal behaviors. This early Learning by Design experiment makes several important suggestions about successful learning from design activities: (a) the need to define design challenges functionally; (b) the importance of dynamic feedback; (c) the need for multiple iterations toward a solution; and most important; (d) thinking about design as a system of activities and allocating time so that the full system can be carried out, allowing its full set of affordances to be realized.
Official Publisher's Webpage (Taylor & Francis)
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Hmelo, C. E., Holton, D. L., & Kolodner, J. L. (2000). Designing to Learn About Complex Systems. Journal of the Learning Sciences, 9(3), 247–298. https://doi.org/10.1207/S15327809JLS0903_2
Design Thinking and the Learning Sciences: Theoretical, Practical, and Empirical Perspectives
Publisher: Routledge _eprint: https://doi.org/10.1207/S15327809JLS0903_2
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