The Climate Action Simulation
Name
1046878119890643.pdf
Description
Published version
Size
795.86 KB
Format
Adobe PDF
Checksum (MD5)
38f9b1831d396ab53fccc15f83ba0099
Author(s)
Rooney-Varga, Juliette N
Kapmeier, Florian
Sterman, John D
Jones, Andrew P
Putko, Michele
Rath, Kenneth
Date Issued
2020
Journal
Simulation and Gaming
Publisher
SAGE Publications
Version
Final published version
Abstract
© The Author(s) 2019. Background. We describe and provide an initial evaluation of the Climate Action Simulation, a simulation-based role-playing game that enables participants to learn for themselves about the response of the climate-energy system to potential policies and actions. Participants gain an understanding of the scale and urgency of climate action, the impact of different policies and actions, and the dynamics and interactions of different policy choices. Intervention. The Climate Action Simulation combines an interactive computer model, En-ROADS, with a role-play in which participants make decisions about energy and climate policy. They learn about the dynamics of the climate and energy systems as they discover how En-ROADS responds to their own climate-energy decisions. Methods. We evaluated learning outcomes from the Climate Action Simulation using pre- and post-simulation surveys as well as a focus group. Results. Analysis of survey results showed that the Climate Action Simulation increases participants’ knowledge about the scale of emissions reductions and policies and actions needed to address climate change. Their personal and emotional engagement with climate change also grew. Focus group participants were overwhelmingly positive about the Climate Action Simulation, saying it left them feeling empowered to make a positive difference in addressing the climate challenge. Discussion and Conclusions. Initial evaluation results indicate that the Climate Action Simulation offers an engaging experience that delivers gains in knowledge about the climate and energy systems, while also opening affective and social learning pathways.
MIT Department
Sloan School of Management
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Terms of Use
Creative Commons Attribution NonCommercial License 4.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1177/1046878119890643
