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Designs for learning about climate change as a complex system |
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| Affiliation: | 1. The University of Sydney, Australia;2. ETH Zurich, Switzerland;3. Arizona State University, United States;1. CNRS, UMR 8240, LaPsyDÉ, France;2. Université Paris Descartes, Sorbonne Paris Cité, UMR 8240, LaPsyDÉ, France;3. Université de Caen Basse-Normandie, UMR 8240, LaPsyDÉ, France;4. Normandie Université, UMR 8240, LaPsyDÉ, France;5. Institut Universitaire de France, France;1. Leibniz-Institut für Wissensmedien, Tübingen, Germany;2. Department of Psychology, University of Freiburg, Germany;3. University of Tübingen, Germany;1. Faculty of Education, University of Erfurt, Postfach 900221, 99105 Erfurt, Germany;2. Department of Learning, Instruction, and Teacher Education, Faculty of Education, University of Haifa, 199 Abba Khoushy Ave., Mount Carmel, Haifa 3498838, Israel;3. Department of Psychology, Westfälische Wilhelms-Universität Münster, Fliednerstrasse 21, 48149 Muenster, Germany;1. Faculty of Educational Sciences, University of Helsinki, Finland;2. University of Tampere, Faculty of Education, Finland;3. Centre for Educational Assessment, University of Helsinki, Finland |
| Abstract: | This paper reports on a study in which students used agent-based computer models to learn about complex systems ideas of relevance to understanding climate change. The experimental condition used a Productive Failure (PF) learning design in which ninth grade students initially worked with agent-based computer models to solve challenge problems followed by teacher instruction about targeted climate and complexity ideas. In contrast, the comparison condition employed a Direct Instruction (DI) learning design in which the teacher instruction was provided initially, followed by the students working on the same computer models and challenge problems as the experimental group. The students in the PF group scored significantly higher on the post-test on measures of climate and complex systems explanatory knowledge and near and far knowledge transfer. Theoretical and practical implications of these findings are considered. |
| Keywords: | Complex systems Climate change Productive failure Agent-based models Transfer Direct instruction Science education |
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