Alleviating misconceptions about Earth's climate: evidence of behavioral learning in stock‐and‐flow simulations. (31st January 2019)

• Record Type: Journal Article
• Authors: Kumar, Medha; Dutt, Varun
• Is Part Of: System dynamics review. Volume 34:Number 4(2018)
• Page Start: 503
• Page End: 526
• Publication Date: 2019-01-31
• Subjects: Engineering -- Mathematical models -- Periodicals; Dynamics -- Periodicals; System analysis -- Periodicals; Ingénierie -- Modèles mathématiques -- Périodiques; Dynamique -- Périodiques; Systèmes, Analyse de -- Périodiques; 003
• DOI: 10.1002/sdr.1612
• Languages: English
• ISSNs: 0883-7066

Abstract

Abstract: Stock‐and‐flow simulation tools, which provide experiences of cause‐and‐effect relationships, are likely to be effective ways to overcome climate misconceptions. However, little is known about the ability of simulation tools to enable the transfer of system dynamics knowledge to subsequent tasks. The primary objective of this research was to use stronger transfer problems in simulation tools and to test the resulting transfer of knowledge. In an experiment, 120 participants were randomly assigned to problems that varied in the use of a stock‐and‐flow simulation tool, Dynamic Climate Change Simulator (DCCS); and, a subsequent paper‐and‐pencil Climate Stabilization (CS) task. Climate misconceptions reduced significantly in the following CS task across problems where the stock behavior was either identical or different between DCCS and CS tasks. Playing DCCS helped people to transfer their system dynamics knowledge to the CS task. We discuss the advantages of using stock‐and‐flow simulation tools for climate education and policy research. © 2019 System Dynamics Society