Model-based learning about climate change with productive failure: preliminary findings

Jacobson, Michael J. and Markauskaite, Lina and Kelly, Nick and Stokes, Paul G. (2012) Model-based learning about climate change with productive failure: preliminary findings. In: American Educational Research Association Annual Meeting (AERA 2012): Non Satis Scire: To Know Is Not Enough, 13-17 Apr 2012, Vancouver, BC. Canada.

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Abstract

This paper reports on research being conducted as part of a four year funded project in Australia that involves the use of agent-based computer models to help students learn about climate change. The intervention in this study involved different sequences of structure provided as part of pedagogical guidance for problem solving and learning activities with agent based models. Thirty-three grade nine students in an all girls' school in Australia participated in the study that used two NetLogo models of greenhouse gases and the carbon cycle. There were significant findings of learning gains from pretest to post test by all students, and qualitative observations and teacher interviews suggest that the students were highly engaged and enjoyed learning with the agent-based computer models. Implications and future research plans are discussed.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: This publication is copyright. It may be reproduced in whole or in part for the purposes of study, research, or review, but is subject to the inclusion of an acknowledgment of the source.
Faculty / Department / School: Historic - Faculty of Education
Date Deposited: 23 Sep 2014 05:01
Last Modified: 06 Feb 2017 06:03
Uncontrolled Keywords: model based learning; model-based netlogo; agent-based; climate change; carbon cycle; greenhouse gas
Fields of Research : 04 Earth Sciences > 0401 Atmospheric Sciences > 040104 Climate Change Processes
13 Education > 1303 Specialist Studies in Education > 130306 Educational Technology and Computing
13 Education > 1303 Specialist Studies in Education > 130309 Learning Sciences
Socio-Economic Objective: C Society > 93 Education and Training > 9301 Learner and Learning > 930101 Learner and Learning Achievement
URI: http://eprints.usq.edu.au/id/eprint/25576

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