Masterarbeit, 2017
48 Seiten, Note: 1,5
1 Introduction
2 Theoretical background
2.1 The carbon cycle
2.2 The climate system
2.3 Climate change
2.4 Public beliefs about climate change
2.5 Stock-flow processes
2.6 Aim of this study and hypotheses
3 Method
3.1 Participants
3.2 Task description
4 Results
4.1 Preliminary analyses
4.2 Results regarding demographic variables
4.2.1 Ordinal data
4.2.2 Binary data
4.3 Results regarding the hypotheses
4.4 Qualitative analysis
5 Discussion
6 Conclusion
This thesis examines the relationship between performance in a stock-flow experiment and the depth of information processing regarding climate change. The primary research question is whether emphasizing the dangers of climate change enhances the depth of information processing and, consequently, improves participant performance in managing complex climate-related stock-flow structures.
2.5 Stock-flow processes
Several studies show that people do not have any intuitive feeling of stocks and flows – the process of accumulation (Cronin, Gonzalez & Sterman, 2009; Dutt & Gonzalez, 2009; Dutt & Gonzalez, 2013; Moxnes & Saysel, 2009; Newell, Kary, Moore & Gonzalez, 2015; Sterman, 2008; Sterman & Booth Sweeny, 2007). Even highly educated laypeople have difficulties solving stock flow tasks correctly. In stock flow relationships there is one stock, one inflow to the stock and one outflow from the stock. So the level of the stock at a certain point of time is the previous level plus the difference between inflow and outflow. The stock falls when the inflow is less than the outflow and rises when the inflow is exceeding the outflow. It remains stable when inflow and outflow are equal. Instead of taking this relationship into account people often rely on a pattern matching heuristic where outputs are correlated with inputs (Cronin et al., 2009; Dutt & Gonzalez, 2009; Dutt & Gonzalez, 2013; Moxnes & Saysel, 2009; Newell et al., 2015; Sterman, 2008; Sterman & Booth Sweeny, 2007). They assume that the accumulating variable (the stock) should “look” like the inflow while disregarding the outflow (pattern matching). This allows for quick problem solving in simple linear systems, but fails at more complex ones. With stock flow structures the stock can continue to rise even if the inflow falls as long as the inflow exceeds the outflow. Pattern matching would falsely suggest that the stock must fall, because the inflow is falling. Chen (2011) explains the robust nature of pattern matching with static mental models that ignore change over time. Stock-flow relationships are dynamic in that the difference between inflow and outflow defines not the level of the stock but its change at a particular point of time.
1 Introduction: Provides an overview of climate change politics, the necessity of public understanding, and the role of mental models in decision-making.
2 Theoretical background: Establishes the scientific basis of the carbon cycle, climate systems, and explains the cognitive challenges inherent in stock-flow reasoning.
3 Method: Details the experimental survey design, participant demographics, and the manipulation of information framing.
4 Results: Presents the statistical findings regarding participant performance, demographic influence, and qualitative insights into decision-making logic.
5 Discussion: Interprets the findings in the context of cognitive psychology and human inability to grasp complex accumulating systems.
6 Conclusion: Summarizes the implications of these findings for climate communication and the urgent need for better methods to bridge the gap between scientific knowledge and public action.
Climate change, accumulation, mental models, global warming, information processing, correlation heuristic, stock-flow reasoning, cognitive bias, decision-making, systematic processing, heuristic processing, pattern matching.
The thesis focuses on how individuals understand the accumulation processes (stocks and flows) within the context of the climate system and why they often struggle with these concepts.
The study covers climate change science, cognitive psychology related to stock-flow reasoning, public perception of environmental risks, and information processing models.
The goal is to determine if priming participants with information about the dangers of climate change increases the depth of their information processing, thereby improving their ability to solve stock-flow tasks.
A quantitative online survey experiment was conducted where 116 German-speaking participants were divided into groups and tasked with estimating emission and removal rates to stabilize CO2 levels.
The main body reviews the carbon cycle, the climate system, human cognitive limitations in understanding feedback loops, and experimental results evaluating participant decision-making.
Key terms include climate change, mental models, information processing, accumulation, and pattern matching.
Participants incorrectly assume that the output (stock level) should always move in the same direction as the input (emissions), leading them to ignore the influence of outflow (natural removal) on the system.
No, the hypothesis was rejected; participants who read the text highlighting the dangers of climate change did not perform significantly better than those who did not.
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