Model-Based Learning About Climate Change With Productive Failure: Preliminary Findings

• In Event: Technology-Supported Learning in K-12 Science

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 the scientific complexity of climate change. The experimental intervention in this study involves different design approaches for low-to-high structure and high-to-low structure problem-solving and learning activities involving model-based learning (MBL) about selected conceptual dimensions of climate change related to the carbon cycle and greenhouse gases. The theoretical framing of this research and methods are discussed and preliminary findings are reported.

Authors

• Michael J. Jacobson, The University of Sydney

• Lina Markauskaite, The University of Sydney

• Nick Kelly, The University of Sydney

• Paul G. Stokes, Hornsby Girls School