Improving Public Misunderstanding of CO2 Accumulations

There exists much scientific evidence of how environmental emissions (e.g., CO2, SO2, and NOx) are contributing to the global warming and climate change phenomena, yet poor public understanding of, and engagement with, environmental accumulations is rampant. How can peoples understanding of environmental accumulations be improved? We argue that the adoption of the stock and flow perspective, which provides effective tools such as System Dynamics-based based Interactive Learning Environments (SDILEs) for education and engagement can address this challenge effectively. On the effectiveness of simulation-based education and training, prior research has shown that in the absence of a structured debriefing, subjects perform poorly. For instance, the decision makers, after they have the rich learning experiences with simulation-based decision support systems, face difficulty in clarifying some misconceptions about the task system (e.g., why decreasing the inflow of CO2 emissions did not stop the rise in CO2 accumulations). Also, there are many experiences that the decision-makers can have while learning with decision support systems. They initially have no way of knowing which are important and useful. Debriefing, which is an after-the-simulation-experience human-facilitated activity that allows the decision makers to share, evaluate and reflect on their decision making experiences with the SDILE, can provide this needed knowledge. The basic premise of an SDILE is that by understanding the structure of a system (e.g., the stocks and flows of our resource consumption system) one can manage the behavior of the system (e.g., the trajectory of environmental accumulations) the stock and flow thinking. The SDILEs promote experiential learning - learning by doing. With such a promising potential, the training with SDILEs should improve peoples decision making and learning in dynamic tasks. Our interest here in this investigation, therefore, is to empirically test the effectiveness of human debriefing-based SDILEs in improving peoples understanding of the basic dynamics of environmental emissions. Specifically, we will test the two hypotheses: (1) Subjects trained with a human debriefing-based SDILE or a standalone, automated SDILE will better understand the dynamics of environmental accumulations than those without any debriefing-based SDILE, and (2) subjects trained with a human debriefing-based SDILE will better understand the dynamics of environmental accumulations than those trained with a standalone, auto-scripted debriefing-based SDILE. To assess the effectiveness of debriefing-based SDILEs on subjects performance in environmental accumulation, a dynamic task, we will use the laboratory-experiment method. In our experiments, we will use a three-group pretest-treatment-posttest research design in which the intervention will be the two SDILEs (i.e. with and without human debriefing). Data for this study will be collected from voluntarily recruited participants at three international and one local site. Our SDILE will be a publically available web-based simulator. Our assessment of the impact of two interventions is aimed at improving the decision makers understanding of, and ability to apply, the basic principle of accumulation. Such an improved understanding about CO2 accumulation is expected to support the design and implementation of mitigation and adaptation strategies needed for our sustainable future.