Show Summary Details

Page of

Printed from Oxford Research Encyclopedias, Environmental Science. Under the terms of the licence agreement, an individual user may print out a single article for personal use (for details see Privacy Policy and Legal Notice).

date: 06 December 2023

Addressing Climate Change Through Educationfree

Addressing Climate Change Through Educationfree

  • Tamara Shapiro Ledley, Tamara Shapiro LedleyCenter for STEM Teaching and Learning, Technical Education Research Centers (TERC)
  • Juliette Rooney-VargaJuliette Rooney-VargaUniversity of Massachusetts, Lowell
  •  and Frank NiepoldFrank NiepoldNational Oceanic and Atmospheric Administration

Summary

The scientific community has made the urgent need to mitigate climate change clear and, with the ratification of the Paris Agreement under the United Nations Framework Convention on Climate Change, the international community has formally accepted ambitious mitigation goals. However, a wide gap remains between the aspirational emissions reduction goals of the Paris Agreement and the real-world pledges and actions of nations that are party to it. Closing that emissions gap can only be achieved if a similarly wide gap between scientific and societal understanding of climate change is also closed.

Several fundamental aspects of climate change make clear both the need for education and the opportunity it offers. First, addressing climate change will require action at all levels of society, including individuals, organizations, businesses, local, state, and national governments, and international bodies. It cannot be addressed by a few individuals with privileged access to information, but rather requires transfer of knowledge, both intellectually and affectively, to decision-makers and their constituents at all levels. Second, education is needed because, in the case of climate change, learning from experience is learning too late. The delay between decisions that cause climate change and their full societal impact can range from decades to millennia. As a result, learning from education, rather than experience, is necessary to avoid those impacts.

Climate change and sustainability represent complex, dynamic systems that demand a systems thinking approach. Systems thinking takes a holistic, long-term perspective that focuses on relationships between interacting parts, and how those relationships generate behavior over time. System dynamics includes formal mapping and modeling of systems, to improve understanding of the behavior of complex systems as well as how they respond to human or other interventions. Systems approaches are increasingly seen as critical to climate change education, as the human and natural systems involved in climate change epitomize a complex, dynamic problem that crosses disciplines and societal sectors.

A systems thinking approach can also be used to examine the potential for education to serve as a vehicle for societal change. In particular, education can enable society to benefit from climate change science by transferring scientific knowledge across societal sectors. Education plays a central role in several processes that can accelerate social change and climate change mitigation. Effective climate change education increases the number of informed and engaged citizens, building social will or pressure to shape policy, and building a workforce for a low-carbon economy. Indeed, several climate change education efforts to date have delivered gains in climate and energy knowledge, affect, and/or motivation. However, society still faces challenges in coordinating initiatives across audiences, managing and leveraging resources, and making effective investments at a scale that is commensurate with the climate change challenge. Education is needed to promote informed decision-making at all levels of society.

Subjects

  • Environmental Issues and Problems
  • Sustainability and Solutions

Education has no higher purpose than preparing people to lead personally fulfilling and responsible lives. For its part, science education—meaning education in science, mathematics, and technology—should help students to develop the understandings and habits of mind they need to become compassionate human beings able to think for themselves and to face life head on. It should equip them also to participate thoughtfully with fellow citizens in building and protecting a society that is open, decent, and vital. America's future—its ability to create a truly just society, to sustain its economic vitality, and to remain secure in a world torn by hostilities—depends more than ever on the character and quality of the education that the nation provides for all of its children.

Science for All Americans (Rutherford & Ahlgren, 1991, p. xiii)

Introduction

The scientific community has made the urgent need to mitigate climate change clear (IPCC, 2013, 2014a, 2014b, 2014c). The international community has formally accepted ambitious mitigation goals through its ratification of the Paris Agreement under the United Nations Framework Convention on Climate Change (UNFCCC), which states that warming should be limited to “well below” 2 ˚C and efforts should be pursued to hold it to 1.5˚C (UNFCCC, 2015). Yet, a formidable “emissions gap” (Figure 1) remains between the aspirational goals of the Paris Agreement and the real-world pledges and actions of nations that are party to it. Here, it is argued that closing the emissions gap can only be achieved if a similarly wide “education gap” between scientific and societal understanding of climate change is also closed. In other words, addressing climate change effectively will require transfer and use of knowledge—that is education, that enables informed decision making and action at all levels in society. In this context, education encompasses the many ways in which knowledge and skill are transferred from one person to another. This includes formal primary, secondary, tertiary, and adult education; professional development; worker training; and learning through informal means (i.e., through cultural and social experiences).

Figure 1. CO2 emissions scenarios (left) and temperature outcomes (right) commensurate with no major climate change mitigation policies (“No policy;” or RCP 8.5), the Nationally Determined Contributions (NDCs) pledged under the Paris Agreement; and limiting warming to 1.5 ˚C above preindustrial times. Emissions trajectories and outcomes were generated with the C-ROADS (Sterman et al., 2012, 2013) climate change policy simulator.

Social science research is also clear: acquiring knowledge about climate change does not necessarily move individuals to action (DeWaters & Powers, 2013; Schultz, Gouveia, Cameron, Tankha, Schmuck, & Franěk, 2005). Affective and social forces often influence risk perception and actions around climate change (e.g., Doherty & Webler, 2016; Kahan et al., 2012; Pidgeon & Fischhoff, 2011; Weber, 2006). Thus, knowledge must be paired with affect, beliefs, intentions, and motivation to enact change (Lombardi & Sinatra, 2012).

Several fundamental aspects of climate change make both the imperative and the opportunity that education offers clear. First, successful mitigation of climate change will require action at all levels of society—from individuals to organizations, local, state, and national governments, and international bodies. Second, in the case of climate change, learning from experience is learning too late. Because of inertia in the climate and human energy systems, decisions and actions have consequences that unfold over decades to centuries or longer. We are privileged to live in a time when science offers rigorously grounded projections of possible outcomes, providing an opportunity to learn from projections, rather than experience. Yet this privilege cannot be realized without translation of that knowledge, through education, into societal action.

Education is also central for achieving broader social goals that are interdependent with climate goals and that balance and integrate across economic, social, and environmental systems (United Nations General Assembly, 2015). These goals include access to affordable, reliable, sustainable, and modern energy for all; enabling sustained, inclusive, and sustainable economic opportunity; and full and productive employment for all. The crucial role played by education and training is recognized by the UNFCCC, the Paris Climate Change Agreement, and the Sustainable Development Goals of the United Nations.

Organizations, countries, and scientific institutions have made progress on climate change education, training, and international cooperation unrelated to these international agreements and goals. However, it is clear that there is a significant gap between the potential to support and accelerate effective societal responses to climate change challenges and opportunities and domestic and international programs, especially those that strengthen international cooperation to scale up education efforts that are already underway, as described by Article 6 of the UNFCCC (2015; and see Conference of the Parties, 2016).

Here, general themes and several specific examples of effective climate change education efforts are explored. While this article is informed primarily by climate change education and training activities in the United States, examples of international efforts are included (e.g., the World Climate simulation and the GLOBE Program), and the themes discussed are transferable internationally.

Climate Change and Society—The Problem

Taken together, scientific understanding of the causes and potential consequences of climate change provide a clear imperative for a rapid transition to a low carbon economy. Figure 1 contrasts three emissions scenarios and their expected global surface temperature rise over preindustrial times by 2100. These include: (a) no significant policy changes, “business-as-usual” or BAU (IPCC, 2014d), with an expected increase of ~4.5˚C by 2100; (b) the expected outcome of nations’ pledges, or Nationally Determined Contributions (NDC) to the UNFCCC Paris Agreement (UNFCCC, 2015) with an expected increase of ~3.5 ˚C by 2100 (Kintisch, 2015); and (c) an example of a trajectory expected to limit warming to ~1.5 ˚C. Both the BAU and NDC scenarios are expected to yield harmful consequences for human health, security, agricultural production, infrastructure, and biodiversity loss. For example, impacts expected by 2100 under BAU include a ~60% increase in the frequency of drought across the globe (Prudhomme et al., 2013); a 20% and 50% decline in the production of maize and wheat, respectively, in most of Central and South America, sub-Saharan Africa, and most of southeast Asia (Rosenzweig et al., 2013); and the possibility of multi-meter sea level rise by 2100 (Hansen et al., 2016). Both BAU and NDCs scenarios are likely to lead to mass migration of human populations from the Middle East and North Africa by mid- to late century due to air pollution from windblown desert dust that are expected to surpass human physiological tolerance (Lelieveld, Proestos, Hadjinicolaou, Tanarhte, Tyrlis, & Zittis, 2016). Both scenarios are also expected to lead to committed sea level rise of >13 m (Levermann et al., 2013) and committed warming of ~5˚C or more over centuries to millennia (Solomon et al., 2011). In addition, many climate change impacts are thought to be mediated by threshold processes, in which a small step in warming causes a large increase in risks if those thresholds are passed. Examples include public health impacts (Heal & Park, 2016; Kjellstrom, Briggs, Freyberg, Lemke, Otto, & Hyatt, 2016; USGCRP, 2016) and crop failure (Lesk, Rowhani, & Ramankutty, 2016; Schlenker & Roberts, 2009), which are both mediated by physiological thresholds.

Clearly, it would benefit society if decision makers across sectors learn about climate change impacts and their causes from scientific projections, rather than direct experience, and take action to avoid them. Feasible emissions scenarios that could meet the Paris Agreement goals diverge from the BAU and the NDC pathways within the next few years (e.g., Figure 1), well before the impacts described above are expected to occur. Thus to close the emissions gap, the education gap must also be closed, through the transfer of knowledge from science to society, in ways that address affective, social, and cultural forces that allow the building of the political will, behaviors, and technologies to enable informed emissions decisions.

Similarly, education is vital for climate change adaptation, or reducing vulnerability to impacts that are now inevitable even if emissions targets are met. For example, even if warming is limited to +2˚C by 2100, expected impacts include: upper temperature limits that surpass present-day extremes in many regions (Schleussner et al., 2016); sea level rise before 2100 of ~0.5 m; and committed sea level rise beyond the century to millennial timescales of 2–10 m (Levermann et al., 2013). Reducing vulnerability to inevitable impacts requires changes in infrastructure, policy, and behavior well before the impacts themselves occur. Once again, the role of education is critical in enabling informed decision-making based on projections of potential impacts, rather than relying on experience that will come too late.

In short, for individuals and society to effectively address climate change it is necessary that they have the ability to iteratively and effectively integrate scientific information about climate change into their own societal and cultural context and decision making.

Climate Change Science and Education: A Need to Integrate Across Disciplines

There has long been a desire to connect academic science to real-life situations (Hurd, 1998), not only to capture the interest of students but to enable those students to apply the knowledge and skills they gain to effectively contribute to society. From this is derived the definition of a scientifically literate person as one who can apply their understanding of science and the scientific process to solve problems and address societal issues. However, this transfer of knowledge and skills to practical situations outside of the context in which it is taught is not always achieved (Hurd, 1998). This is despite calls, such as from the U.S. National Science Foundation in 1970, for an increased focus on “the understanding of science and technology by those who are not and do not expect to be professional scientists and technologists” (National Science Foundation, 1970, p. III). The need for the educational system to serve not only future scientists but all citizens is reflected in the numerous science educational frameworks. For example, in the United States, the Next Generation Science Standards (NGSS) states “All students no matter what their future education and career path must have a solid K–12 science education in order to be prepared for college, careers, and citizenship” (NGSS Lead States, 2013b, p. 5). To address this need, students must see the interdisciplinary nature of climate science and its relevance in their lives.

Understanding climate change initially required the development of scientific research programs that bridged the traditional disciplinary boundaries of atmospheric science, oceanography, hydrology, geology, ecology, and environmental science to conduct interdisciplinary investigations to which all these fields could contribute. The interdisciplinary field of Earth system science grew out of this need in the late 1980s and early 1990s (Wainwright, 2009). More generally, an application-oriented perspective of science has led to a growth in collaborations across disciplinary boundaries to produce new fields of intellectual pursuit (van den Besselaar & Heimeriks, 2001) that are enriched by multiple disciplinary perspectives and analytical techniques.

The implications of climate change for society require further expansion, beyond the natural and physical sciences to include the social sciences, civic/government, humanities, and professional fields; moving beyond the interdisciplinary nature of Earth system science to the transdisciplinary nature of creating a society and a workforce prepared for shaping our collective future. Yet, academia and education remain divided into disciplinary departments, and scientists generally value deeper more narrowly focused research over broad interdisciplinary research (Bateman & Hess, 2015). This disciplinary approach has implications for faculty and research appointments, and for courses and degree programs that are aimed at preparing future scientists to continue that research. This remains a barrier to effective and efficient climate change education.

Systems Thinking: A Framework for Understanding and Addressing Climate Change

Systems thinking approaches offer a means to not only integrate across disciplinary boundaries, but also to understand the complex and dynamic nature of climate change. Growing recognition of the need to integrate knowledge from across disciplines has led to calls for systems thinking to be central to climate change and sustainability education (e.g., Barth, 2016; Claesson & Svanström, 2015; Hämäläinen, Luoma, & Saarinen, 2013; Iwaniec, Childers, VanLehn, & Wiek, 2014; Liu et al., 2015; Marcus, Coops, Ellis, & Robinson, 2015; Pruneau, Kerry, & Langis, 2016; Vincent, Bunn, & Sloane, 2013). Yet, the term systems thinking is often vaguely defined as a synonym for any holistic approach or consideration of interconnections. Here, systems thinking is referred to as a set of methods and practices for understanding the often non-intuitive behavior of complex dynamic systems, describing systems in terms of stocks, flows, delays, feedbacks, and non-linear behaviors (see definitions in Table 1). System dynamics extends systems thinking to include formal modeling, including: developing maps of dynamic systems that serve to elicit, share, and sharpen mental models; building models (including, but not necessarily limited to, quantitative computer models) that enable us to overcome our cognitive limitations in understanding dynamic complexity; and developing group or organizational processes to foster effective decision making and translation of insights into action (Sterman, 2000). Yet, in 2016 only 17 (out of >4,100) institutions of higher education in the United States offer courses in system dynamics (Systems Dynamics Society, 2016), and many of those are not explicitly tied to sustainability.

Table 1. Key Terms Used in Systems Thinking and System Dynamics

System

An interconnected set of elements that is coherently organized in a way that achieves something.

Systems thinking

A perspective and approach for solving problems that is centered on a whole-system level, including system elements and their inter-relationships. Contrasts with reductionist approaches that seek to understand problems by dissecting them into individual components.

System dynamics

Use of computer simulations to model systems and to explore or demonstrate how systems behave over time.

Simulation

An interactive representation of reality that is based on a model of a system.

Stock

System element that can be measured or quantified; accumulation of material or information.

Flow

Movement of material or information into or out of a stock.

Feedback loop

Closed chain of causal connections from a stock, through a set of decisions, rules, physical laws, or actions that are dependent on the level of the stock and back again through a flow to change the stock.

Reinforcing loop

Feedback loop in which the causal connections result in further change in the same direction as an initial action or change. Results in exponential growth or decay over time. Also referred to as a positive feedback loop, virtuous (or vicious) cycle, snowball effect, amplifying feedback.

Balancing loop

Feedback loop in which the causal connections result in dampening change in response to an initial action or change. Results in goal-seeking behavior over time. Also referred to as a negative feedback loop, stabilizing loop, diminishing feedback.

Source: Adapted from Meadows, D. H. (2008). Thinking in systems: A primer. White River Junction, VT: Chelsea Green.

The Challenges of Climate Change Education

Effective climate change education faces many challenges. In order for future members of the workforce and citizenry to be prepared to contribute to addressing the impacts and solving the problems resulting from climate change, they must have sufficient contact time with the science behind the causes (National Research Council, 2010a). In addition, they need to develop the skills to identify, gather, collect, and accurately discern the credibility of the information with reasoning skills; engage in discourse approaches that enable trust; analyze and draw conclusions from the information and data that they have gathered; develop solutions to problems based on those conclusions; and communicate their findings effectively to others.

However, in the United States these skills have been missing from earlier science frameworks and standards (National Research Council, 1996) and thus have not been included in students’ curriculum. This has been addressed in the Framework for K–12 Science Education (Framework) (National Research Council, 2012b) and the resulting NGSS (NGSS Lead States, 2013a) where the skills have been deeply integrated. The NGSS goes further to require that science be taught in a way that integrates three dimensions: disciplinary core ideas (content), science and engineering practices, and crosscutting concepts. This has resulted in Earth system and climate change science being deeply woven into the learning progressions from kindergarten to 12th grade. While not strictly adhering to the rigorous definitions of systems thinking concepts, this three-dimensional methodology of teaching science embraces the need for systems thinking approaches.

Similar recommendations for teaching and learning about climate change have also emerged from international evidence-based research (Anderson, 2013). These include:

Climate change literacy can be improved through sustained, active learning activities using integrated, cross-discipline curricula.

Active learning should be connected to local problem solving.

While climate change education should inform students about the scientific concepts and implications of climate change, it is also important to cultivate problem solving and critical thinking skills through framing messages to emphasize an individual’s capacity to achieve positive outcomes.

Problem solving-based education can increase the degree to which students behave in a sustainable manner if learners are presented with information and behavior change options whereby concrete gains can be made to reduce individual footprints.

It is important therefore to include measurement tools, such as carbon and ecological footprint calculators, with climate change education so that learners can track the changes they can make/are making/will make over time.

Narrative techniques, visual imagery (such as photographs) and persuasive texts are powerful tools.

Teacher education is essential for providing quality climate change education.

However, there are significant obstacles beyond what is included in standards and curriculum that are relevant worldwide, to helping students develop the needed knowledge, skills and action competence (Vaughter, 2016) to enable them to effectively address the transdisciplinary challenges presented by climate change. These include the cognitive challenges of complex dynamic systems; the social and cultural forces that impact learning about climate change; the affective forces that limit the willingness of individuals to learn about climate change; and the lack of professional development of teachers to build confidence and competence both in the content area and in the skills needed to support their students; and in the effect of cultural/political pressures and educators’ personal beliefs and values in their learning environments (Plutzer, Hannah, Rosenau, McCaffrey, Berbeco, & Reid, 2016).

Cognitive Challenges of Complex Dynamic Systems

Human cognitive capacity has been shown to be limited to processing the interactions of no more than two-to-three variables at a time (Halford, Baker, McCredden, & Bain, 2005). Climate change and our responses to it represent systems that are far beyond our capacity for mental simulation, leading to some of the most important misconceptions about how to effectively address climate change, such as:

The future climate will be similar to the climate of the recent past that we’re used to (Weber & Stern, 2011).

Climate change will be imperceptibly slow and gradual and will not directly affect me or those close to me (Leiserowitz, 2005, 2006; Leiserowitz, Smith, & Marlon, 2011; Maibach, Roser-Renouf, Weber, & Taylor, 2008; Weber, 2006).

Greenhouse gases dissipate out of the lower atmosphere, into space (Weber & Stern, 2011).

If emissions are stabilized, atmospheric concentrations of greenhouse gases will also stabilize (“stock-flow failure”) (Cronin, Gonzalez, & Sterman, 2009; Sterman & Sweeney, 2007).

An appropriate response to climate change is “wait-and-see”—taking action to reduce emissions or invest in potentially expensive adaptation strategies does not make sense until the problem is clearly manifest (Sterman, 2012).

Many of these misconceptions stem from cognitive challenges posed by dynamic systems. For example, research has shown that most highly educated adults have difficulty inferring the behavior of even simple systems: accumulation of a stock in response to its inflows and outflows (Cronin et al., 2009; Sterman, 2008; Sweeney & Sterman, 2000). The concept of accumulation is frequently encountered in everyday human experience (e.g., a bathtub filling when the faucet is turned on and the drain is plugged). However, most people interpret stock-and-flow systems using a “correlation heuristic” in which stocks are incorrectly believed to behave in a manner that correlates with flows (Cronin et al., 2009). The correlation heuristic leads to “stock-flow failure” in dynamic decision-making (Cronin et al., 2009). For example, a common misconception in the context of climate change is that stabilizing CO2 emissions (a flow) would stabilize atmospheric CO2 concentrations (a stock) and, as a result, stabilize temperature (Sterman & Sweeney, 2007). Instead, anthropogenic emissions exceed terrestrial and marine sinks combined by a factor of two (Peters, Marland, Le Quéré, Boden, Canadell, & Raupach, 2012). Thus, atmospheric concentrations will continue to rise until emissions fall to the level of sinks. Despite this fundamental reality, most people fail to grasp the scale of action required to stabilize CO2 concentrations at levels deemed likely to meet international climate goals (e.g., Figure 1).

Delays are another common feature of complex systems that are non-intuitive and lead to misconceptions and failure to intervene effectively in systems (Sterman, 1994). Stocks create inherent delays due to the time required for accumulation or decline of a stock. For example, even if all CO2 emissions stopped immediately, excess CO2 would remain in the atmosphere for millennia (Solomon, Plattner, Knutti, & Friedingstein, 2009; Solomon et al., 2011). Similarly, additional delays are integral in stock-and-flow components of the climate system; for example, global surface air temperature responds relatively slowly to increased greenhouse gas concentrations because much of the heat is stored in the large ocean reservoir (Hansen, Sato, Kharecha, & von Schuckmann, 2011). With regards to sea level rise, the rate at which land-based ice melts into the oceans is constrained by ice sheet dynamics, creating a delay in the response of sea level to warming (Hansen et al., 2011). In human energy systems, delays are also numerous and causal chains are long. For example, even if science, and not political realities, were the primary guide to policy, action to mitigate global CO2 emissions would require scientific research, detection of changing greenhouse gas concentrations and temperature, analysis of potential impacts, communicating findings, analysis of economic and policy options, implementation of policies, building of new infrastructure, etcetera.

Evidence suggests that our failure to grasp the full effect of delays may also be due to our tendency to steeply discount costs and benefits of future events, with the greatest decrement occurring as an event is deferred beyond the immediate future (Loewenstein & Elster, 1992; Weber, 2006). Together, these failures lead to a fundamental misconception that the most prudent response to climate change is to wait until serious impacts are upon us before taking action to respond (Sterman, 2012). This misconception implicitly assumes that the climate is a simple system that responds rapidly and in a roughly linear fashion to our interventions, rather than a complex, dynamic system with multiple delays and non-linear behaviors (Sterman & Sweeney, 2007).

In addition to stocks, flows, and delays, complex systems are characterized by feedbacks. Once again, misperceptions about feedback loops lead to problems in understanding and predicting the responses of complex systems to interventions (Sterman, 2012). The climate and energy systems contain feedback loops that amplify change (reinforcing feedbacks) or, conversely, dampen it (balancing feedbacks). An example of a large-scale reinforcing feedback loop is the ice-albedo feedback (Hansen et al., 2011). In this feedback loop, warming causes sea ice to melt and decreases geographic extent. As sea ice is replaced with ocean water, the surface albedo, or reflectivity, declines. The darker ocean surface absorbs more sunlight which leads to additional warming and thus additional sea ice melt, closing the reinforcing feedback, and further amplifying warming in a vicious cycle. Other examples of large-scale reinforcing feedbacks in the climate system include collapse of the Amazon rainforest (van Nes, Hirota, Holmgren, & Scheffer, 2014), and the release of methane from a warming Arctic (Lenton, 2012).

Large-scale balancing feedbacks that dampen change are also present in the climate system. For example, CO2 fertilization feedback results from the stimulatory effect increased atmospheric CO2 has on photosynthesis, which in turn sequesters atmospheric CO2 (Pan et al., 2011). Other examples of large-scale balancing feedback loops include increased net photosynthesis due to longer growing seasons, and increased low-level clouds and albedo due to evaporation under warmer temperatures (Dessler, 2010). While these balancing feedbacks have moderated the impact of human-caused greenhouse gas emissions thus far, paleoclimate evidence indicates that during periods of warming, reinforcing feedbacks are likely to dominate (Friedrich, Timmermann, Tigchelaar, Elison Timm, & Ganopolski, 2016). Together, reinforcing and balancing feedbacks generate nonlinear behavior that is also non-intuitive. Feedback loops do not figure into the mental models of most people (Dörner, 1980, 1996), as people tend to think in single-strand causal series and extrapolate linearly (Sterman, 2012; Wagenaar & Sagaria, 1975).

Social and Cultural Forces That Impact Learning About Climate Change

Social forces have been shown to be powerful in shaping individuals’ understanding of climate change, related actions, and willingness to support climate and energy policy. For example, cultural worldview is predictive of climate change risk perception, with individuals shaping their beliefs to match predominant views held in their social group, whether those views are coherent with climate change science or not (Kahan et al., 2012). Thus, social context has a strong influence on how information about climate change is perceived and used. Similarly, the social identity of the messenger influences the efficacy of climate communication, with the most effective messengers being trusted individuals who share social group membership with their audience (Moser, 2010). Thus, a key to addressing a cultural worldview that does not accept the evidence of climate change science is research based pedagogy, a trusted messenger, and sufficient contact time (Lombardi, Sinatra, & Nussbaum, 2013).

The failure of climate change to activate our moral intuitions and associated responses is also influenced by social factors. In particular, people are inclined to treat individuals in other social groups worse than in-group members, especially if the harm inflicted on others is indirectly linked to their actions (Markowitz & Shariff, 2012). These tendencies are especially relevant to climate change for which the actions of well-off adults in developed nations will indirectly and disproportionately harm young people, future generations, the poor, and populations in developing nations, i.e., those in “other” social groups that are not the highest emitters. Lastly, social forces influence our willingness to take action on climate change, with motivation to take action being linked to membership in a group that is taking action together (Jackson, 2005). In general, fostering collective efficacy appears to be key for generating sustained effort and action (Bandura, 2000). Considering the quantitative insignificance of individual actions but tremendous potential of collective action and policy to address climate change, this response to climate action is especially cogent.

Affective Forces That Limit the Willingness of Individuals to Learn About Climate Change

The affective system plays an important role in evaluating uncertainty and risk (such as potential climate change impacts or mitigation), and is the primary motivator for action (Weber, 2006) and sustained commitment to difficult problems (Pidgeon & Fischhoff, 2011). While the affective system enables rapid responses, analytic reasoning requires us to learn procedures for decision-making and apply them through conscious awareness and control. Importantly, these two processing systems work together: analytic reasoning is not effective unless guided by emotion and affect, and, if the responses of the two systems are in conflict, the affective system almost always prevails (Damasio, 1994). Thus, emotion is integral to our thinking, perceptions, and behavior (Pidgeon & Fischhoff, 2011). Similarly, social context, such as that provided in simulation role-playing games, can play an important role in amplifying or attenuating our perception of and responses to risk (Pidgeon & Fischhoff, 2011).

Lack of Teacher and Informal Educator Preparation to Teach About Climate Change

In the United States, climate change and energy comprise a significant component (over 30% of the biological, physical and earth-space topics) of the 2012 Framework and the 2013 NGSS. In addition the NGSS requires that the learning of science be achieved through the doing of science and have the “ability to apply a practice to content knowledge” (NGSS Lead States, 2013b). Yet, current teachers were trained prior to these new standards and are frequently not equipped to teach or support their students’ learning, especially on climate change and related subjects (Plutzer et al., 2016). Building teachers’ content knowledge about climate change and effective societal response as well as their ability to implement this new vision for science and engineering learning requires a significant and sustained professional development effort to support millions of teachers in states adopting these new standards.

However, in the United States, across more than 15,000 school districts, there are currently only a small number of professional development programs, and they are generally limited in both content and skills taught. These professional development programs also often lack a transdisciplinary systems thinking framework that addresses the social and civic aspects of the impacts of and responses to climate change that would make the materials and skills relevant to students. The scale of the challenge become exponential when you consider education plays a fundamental role internationally for the implementation of the Paris climate change agreement (197 signatory countries) and for the United Nation’s Sustainable Development Goals.

Similar challenges and opportunities exist in informal education. Informal education has been shown to play a major role in STEM education (National Research Council, 2010b) and can likewise play a critical role in building climate literacy and engagement. Informal education can also serve to bring diverse organizations and programs together, aligning informal education efforts directly with climate change mitigation and action. For example, the San Francisco Bay Area Climate Collaborative aligns evidence-based informal education programs with initiatives to accelerate clean technology markets and community-based mitigation. Like formal education, challenges and needs faced by informal initiatives include capacity and time, educational resources, support on designing for behavior change, and evaluation models (Institute of the Golden Gate, 2014).

A Systems View of the Role of Education in Addressing Climate Change

The potential for education to be a powerful force in addressing climate change stems from its own role in social systems. Education is critical for science and technology based changes in individual behavior, workforce development and training, policy support, and policy- and decision-making. In the development of this article, a systems thinking tool referred to as causal loop diagramming, was used to better understand many of these dynamic interactions and the central role education and training play in fostering and implementing change (Figure 2 and Table 2).

Figure 2. Causal loop diagram depicting the role of education in addressing climate change. Arrows between variables indicate that the variable from which the arrow originates causes a change in the variable at which it terminates. A + (−) indicates that the two variables change in the same (opposite) directions. Circle arrows surrounding an R or B identify feedback loops represented by the collection of variables and arrows surrounding them, with an R (B) indicating a reinforcing (balancing) feedback loop. Clarification of what each variable encompasses is in Table 2. Feedback loops are illustrated individually in Figure 3.

Causal loop diagrams provide a means to crystallize and share mental models of complex systems and to capture hypotheses about the underlying causes and feedbacks that drive dynamics. Causal relationships between system variables (stocks and flows) are depicted with arrows from a cause to an effect. The polarities (depicted in Figures 2 and 3 as a “+” or “−”) of causal links are used to indicate whether cause and effect change in the same (+) or opposite (−) direction. Reinforcing and balancing feedbacks (Table 1) are indicated by circular arrows around the letters R and B, respectively (e.g., Figure 1). Importantly, reinforcing feedbacks amplify change. In other words, a change in one system variable feeds back through the causal links to further amplify that change, leading to growth or decline. Conversely, balancing feedbacks dampen change, exhibiting goal-seeking or stabilizing behavior.

Table 2. Variables in the Causal Loop Diagram Depicting the Role of Education in Addressing Climate Change (Figures 2 & 3)

Variable

What the variable encompasses

Climate change/Sustainability science

Scientific data and knowledge that assess the state of the climate system (including each of its components), how it is changing, and what is causing the changes. Projects scenarios for these changes, and demonstrates how the intersection of natural process and man’s activities can provide the knowledge and support to accelerate transformations to a sustainable world. Additionally, the science and engineering of energy efficiency, sustainable transportation, and renewable power technologies are advanced and the knowledge to integrate and optimize energy systems is provided.

Climate/sustainability education and training

All types of education, training, and retraining for the entire range of audiences including K–12, higher education, informal education, policy and decision makers, professionals, job retraining, and all who need to incorporate the impacts of climate change in their decisions.

Climate/energy active people

People who have developed a concern about the changing climate and are taking actions, of any kind, that will help mitigate climate change and/or adapt to the change.

Climate/energy informed people

People who have developed a concern about the changing climate and have actively sought information or formal education to better understand the issues and possibly how to address them.

Transition-ready workforce

Students and citizens who have prepared themselves for careers in areas that can contribute to mitigation and/or adaption to climate change. This can involve student training for future careers or the retraining of the current workforce to fill current positions that address mitigation and/or adaptation.

Policy support for transition

Refers to the public/individual support for the adaptation of policies that will address the impacts of climate change.

Climate Change mitigation and adaptation

Human interventions to reduce the sources of greenhouse gases or enhance the sinks that remove them from the atmosphere. Initiatives and measures to reduce the vulnerability of natural and human

systems against actual or expected climate change effects. (USGCRP, 2009)

Demand for transition-ready workforce

Demand for workers and professionals for the workforce that can contribute to the enactment of policies that create the Clean-Energy and resilience workforce.

Climate change damage

Short and long-term changes impacted by the implementation or lack of implementation of effective mitigation and adaptation strategies.

Learning from impacts

Responding to damage related to climate change by seeking education to understand the impact and to learn how to adapt to the damage and prepare for future destructive events. Seeking education through this balancing loop is generally too late to effectively address the problems.

Note: See Figures 2 and 3.

The variable “Climate/sustainability education and training” mediates transfer of knowledge about the causes and consequences of “Climate change/sustainability science” from scientific research to society (Figure 2). This enables a pathway to inform people about the potential impacts and causes of climate change, “Climate/energy informed people,” and delivers gains in literacy and an ability to apply their understanding to address real-world problems. Prior research has linked climate change understanding and risk perception to support for policies and intent to take action against climate change (Lee, Markowitz, Howe, Ko, & Leiserowitz, 2015; Rath & Rooney-Varga, 2015) leading to an increase in “Climate/energy active people.” As effective education and training related to climate change increases, the “Transition-ready workforce” is able to implement new policies or programs, and “Climate/energy informed people” and “Climate/energy active people” become larger segments of communities. Finally, the “Transition-ready workforce,” “Climate/energy informed people” and “Climate/energy active people” create “Social will and pressure” for transitions that lead to effective mitigation policies. The reinforcing feedback loops of “Learning for Action,” “Workforce Building,” and “Social Will and Pressure” offer a means to accelerate the social transformation required for the transition to low carbon economies and resilient communities (Figure 2). Because education plays a central role in all of the reinforcing feedback loops, there is an opportunity for leverage: Growing the diverse and mutually reinforcing climate change education programs could have far-reaching consequences for society’s ability to rapidly address and respond to a changing climate.

In the “Learning for Action” reinforcing feedback loop (Figure 2 and Figure 3A) “Climate/sustainability education and training” is the foundation to increasing the number of “Climate/energy informed people” and “Climate/energy active people.” In turn, “Climate/energy active people” support more education and training investments as demonstrated by Yale’s Six Americas research (Leiserowitz, Maibach, & Roser-Renouf, 2010). Education leads to “Climate/energy informed people” who understand the implications of unmitigated climate change and the possibilities of a transition to a low-carbon society. The more informed and engaged people are, the more likely they are to become active in the areas of climate change and energy transition. Actively involved people want to learn more and will seek additional “Climate/sustainability education and training” to do so and will encourage others to do so as well, closing the reinforcing feedback loop “Learning for Action.”

Figure 3. Causal loop diagram depicting the role of education in addressing climate change with feedback loops highlighted. A, Learning for action reinforcing feedback loop (highlighted in green); B, Workforce building reinforcing feedback loop (highlighted in red); C, Social will and pressure reinforcing feedback loop (highlighted in blue); D, Impacts motivate education balancing feedback loop (highlighted in purple).

In the “Workforce Building” reinforcing feedback loop (Figures 2 and 3B) the role of “Climate/sustainability education and training” is a key input into the future workforce required to transition our energy systems based on climate mitigation policies. This occurs directly, as people are engaged in education and training to enable them to enter the “Transition ready workforce” and indirectly, as people become “Climate/energy informed people,” which leads to becoming part of the “Transition ready workforce.” People who are in that workforce see direct benefits of policies that support a transition to a low carbon society and therefore provide “Policy support for transition.” Climate change mitigation policies then grow, leading to greater “Demand for transition-ready workforce,” which, in turn, stimulates “Climate/sustainability education and training” efforts.

The “Social Will and Pressure” reinforcing loop (Figures 2 and 3C) intersects with the “Learning for Action” reinforcing loop through the branch that leads from “Climate/sustainability education and training” to “Climate/energy informed people” and “Climate/energy active people,” as well as a “Transition-ready workforce.” “Climate/energy informed people” understand the implications of unmitigated climate change and how a transition to a low-carbon society can be beneficial. They are more likely to be supportive of action to address climate change; as a result, they will actively provide “Policy support for transition” across sectors (businesses, other organizations, and different levels of government) that mitigate and adapt to climate change, including education policies. For example, those who negotiated the UNFCCC Paris Agreement on Climate Change (United Nations Framework Convention on Climate Change, 2015) included Article 12, which recognizes the central role of education and obligates participating nations to enhance and report on their climate change education efforts. Conversely, in communities where science topics, like climate change, are perceived as societally controversial, barriers to advancement of climate science education reform are created, significantly limiting progress and delaying knowledge and skill building (Colston & Ivey, 2015).

The “Impacts motivate education” balancing loop (Figures 2 and 3D) indicates that direct experiences with the damage resulting from climate change leads to additional “Climate/sustainability education and training,” which leads to increases in “Climate/energy informed people,” “Climate/energy active people,” and a “Transition-ready workforce,” and thus, an increase in “Policy support for transition” for addressing the impacts of climate change (e.g., New York City’s climate policy efforts increased directly after Superstorm Sandy). The resulting policies that address climate change reduce emissions; and human forcing, often after a substantial delay (years to centuries or more), reduces climate impacts. The “Impacts motivate education” loop emphasizes that, especially given the long delays inherent in many climate change impacts, a reactive approach will lead to greater damage. However, through its link to “Climate/sustainability education and training,” the “Impacts motivate education” loop also feeds into the “Workforce Building,” “Learning for Action,” “Social Will and Pressure” reinforcing feedback loops.

There is another avenue by which support for policies to address the impacts of climate change can grow. A separate “Adapting to Impacts” balancing loop (Figure 4) illustrates that, as devastating impacts occur, people, from experience, become more informed about the impacts of climate change, and are thus supportive of policies to adapt to those impacts. Education is not part of this loop, so recognition of the causes of climate change and the need to mitigate against future climate change are not a consideration in the policies supported. As with the “Impacts Motivate Education” balancing loop (Figures 2 and 3D), the long delays between the emission of greenhouse gases and the extensive societal impacts mean that simply reacting to impacts will still result in extensive damage from climate change.

Figure 4. Adapting to impacts balancing feedback loop. This does not include education, and the response is too late to effectively address climate change impacts.

In short, education is central to effectively addressing both the causes and the impacts of climate change. The causal loop diagrams depicted in Figures 24 clearly show conceptually the complexity of addressing climate change impacts. What is also apparent is that it requires all of society, as culturally and demographically diverse as it is, to participate in effective climate change mitigation and adaptation efforts.

Efforts to Integrate and Leverage Climate Change Education Activities

With the central role that education and training plays in addressing climate change across society, to what extent has society been able to build this educational capacity? In the United States, both federal agencies and private foundations have worked in parallel to expand support for a wide range of research and development investments to advance climate change education, build public awareness of the impacts of climate change, and engage communities on the climate change issue. These investments are partially described in the Tri-Agency Climate Education (TrACE) Collection (McDougal, Martin, Givens, Yue, Wilson, & Karsten, 2012) that integrates efforts by the National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), and the National Science Foundation (NSF); the National Research Council’s Roundtable on Climate Change Education (CCE) (National Research Council, 2011a; National Research Council, 2012a), and the 2014 U. S. Climate Action Report to the UNFCCC (United States State Department, 2014).

Despite some of the protracted political and business efforts to undermine communication of the scientific consensus (mostly in the United States) on climate change (Oreskes & Conway, 2011), public awareness and concern is gradually increasing (Gallup Poll, 2016; Wike, 2016). Numerous educational case studies offer a glimpse into some of the programs that have achieved positive, and in some cases, significant on-the-ground results (Flora, Saphir, Lappe, Roser-Renouf, Maibach, & Leiserowitz, 2014; Lombardi et al., 2013; National Research Council, 2011b, 2012a; Spitzer, 2014). For example, the Alliance for Climate Education (ACE) has reached more than 1.6 million students in the United States alone, with a multimedia presentation that delivered gains in young people’s beliefs, involvement, and behavior to address climate change (Flora et al., 2014). Similarly, informal climate education efforts at museums and aquaria, such as the U.S.-based National Network for Ocean and Climate Change Interpretation (NNOCCI), leverage evidence-based approaches in informal learning, climate literacy, cognitive and social psychology, community building, and diffusion of innovation (Spitzer, 2014). With all the programmatic successes to date, larger societal success in addressing climate change challenges and opportunities hinge on wider comprehensive and coordinated educational investments across various audiences, managing and leveraging resources, and scaling or replicating effective efforts to meet the threats society faces (Ledley, Gold, Niepold, & McCaffrey, 2014).

Social and political scientists have demonstrated that success on effectively addressing climate change challenges and opportunities does not initially require a new prescriptive, top-down approach. Rather, community engagement in improved assessment of existing activities and resources, stronger coordination of efforts like the NSF funded Climate Change Education Partnership Alliance, http://ccepalliance.org/; the Climate Literacy and Energy Awareness Network (CLEAN), http://cleanet.org/clean/community/index.html; and the National Network for Ocean and Climate Change Interpretation (NNOCCI), http://climateinterpreter.org/about/projects/NNOCCI; and enhanced collaboration across communities of practice (Wenger, 1998) to support a wide range of stakeholders. For example, one community of practice, the CLEAN Network, has identified the importance of a coordinated effort to synthesize strategies (Ledley et al., 2014, 2016). This climate literacy collective impact effort seeks to promote the coordination, collaboration, and leveraging of successful climate change education efforts through an overarching shared common agenda, shared measures of progress, mutually reinforcing activities, continuous communication, and a coordinating backbone support organization (Hanleybrown et al., 2012; Kania & Kramer, 2011). While the CLEAN Network has achieved some success as a rudimentary coordinating backbone support organization, lack of sufficient funding limits its ability to fully develop and implement all aspects of collective impact.

Further discussions within the CLEAN Network recognized the need to focus this kind of coordination at the regional/metropolitan area scale (Ledley et al., 2016). At this scale the specific impacts of climate change that need to be addressed are relevant to people, making it more likely that they will engage in climate change education programs and support policies to mitigate and adapt to climate change.

Further work needs to be done to develop, test, and implement coordinated climate change regional/metropolitan area mitigation and adaptation efforts that include broad robust education activities. Examples of successful efforts in the United States thus far include the Climate Youth Summits; the Bay Area Climate Literacy Impact Collaborative; and College and Universities Climate Leadership. These efforts focus on increasing the resilience of social and ecological systems and/or building the capacity of the transition-ready workforce. There is an opportunity to draw on the best practices from across programs and to work collectively to enhance climate-related community decision making. Starting in 2012 at the Climate and Energy Literacy Summit (McCaffrey, Berbeco, & Scott, 2013), a series of six summits of the climate change education stakeholders illustrates that current programs and organizations are poised to be part of a coordinated network of networks solution framework (Ledley et al., 2014) and are primed to engage people in this new community resilience and low carbon transition strategy.

Internationally, nations agreed to achieve the shared goal to avoid dangerous climate change which explicitly includes education and training through both Article 6 of the UNFCCC (1992) treaty and Article 12 of the Paris Agreement (UNFCCC, 2015). Governments are working toward this by promoting and facilitating at the “national and, as appropriate, subregional and regional levels” in six priority action areas: education, training, public access to information, public awareness, public participation, and international cooperation. These efforts are working to effectively focus the enormous capacity of a nation’s educational systems to support these commitments; however many nations have limited resources and, as a result, organizations like the CLEAN Network have formed to compliment national initiatives. To coordinate this emerging international community of effective practice in climate and energy literacy, a new effort, similar to the CLEAN Network, was recently launched. In November 2016, at the Conference of the Parties (COP) 22 meeting in Marrakesh Morocco, the UNFCCC approved a special Education, Communication, and Outreach Stakholders (ECOS, originally ECONGO) community that is a system of networks to develop capacity in support of Article 6 Climate Education and Training of the UNFCCC (GLOCHA, 2016). The CLEAN Network represents the U.S. community in this international ECOS effort.

Examples of Successful Climate Change Education Efforts: Simulation-Based Games and the GLOBE Program

While a comprehensive review of climate change education projects is beyond the scope of this article, two approaches that integrate systems thinking and “learning-by-doing” pedagogical approaches that have international reach are presented in more detail here. These include simulation-based games, which represent a nascent but promising approach to combine systems thinking; experiential, social, and affective learning, such as World Climate (Sterman et al., 2014); and the GLOBE Program, an international effort that uses place-based approaches and focuses on the interacting components in Earth systems

Simulation-Based Role-Playing Games: An Opportunity to Bring Systems Thinking into Active Climate Change Education

There is a growing opportunity to address climate change education and communication barriers through tools that rely on active learning, that are social, engaging (and even fun), and that are grounded in rigorous science. An increasing number of decision-support computer models are being developed, intended to make complex technical problems accessible to non-experts in an interactive format (e.g., Hu, Johnston, Hemphill, Krishnamurthy, & Vinze, 2012). At the same time, the use of scenario planning, role-playing games, and active learning approaches are gaining ground in policy and education spheres (Mayer, 2009). Simulation-based role-playing games bring these approaches together and can provide powerful learning experiences. They offer the potential to compress time and reality, create experiences without requiring the “real thing,” explore the consequences of our decisions that often unfold over decades, and open affective and social learning pathways.

We refer to “simulation-based role-playing games” as serious games that incorporate computer simulations of complex physical-technical systems, as well as the “softer,” but often equally complex social dynamics, through role-playing. These games are not new—they have been integral to the field of system dynamics since the 1960s. However, they are not widely used and are only recently gaining ground in climate change education and communication. Indeed, they may be ideally suited for understanding and responding to climate change—a long-term, complex problem that is itself dependent on both physical-technical systems and human social dynamics, and for which experiential, affective, and social learning are especially important.

World Climate: A Simulation-Based Game That Enhances Learning and Motivation

The World Climate simulation game offers an example of an educational resource that integrates a system dynamics computer model with role-play that is international in scope. In World Climate, participants take on the roles of delegates to the international climate negotiations and are challenged to create a successful global agreement that limits warming to well below 2 ˚C over preindustrial levels (Sterman et al., 2014). Their negotiations are framed by current scientific understanding in real-time through an interactive system dynamics computer model, C-ROADS (Sterman et al., 2012, 2013), which is also used for real-world climate policy analysis within the highest levels of government, the UN, the private sector, and nongovernmental organizations, as well as by citizens and students around the world. The simulation is typically a two- to three-hour face-to-face event with anywhere from 10 to 50 participants; most of which is a “multi-logue” with participants in dialogue with each other. Evaluation of learning outcomes using pre- and post-World Climate surveys has shown that the simulation delivers statistically significant shifts in climate change knowledge, affect, desire to learn more, and intent to take action on climate change (Rath & Rooney-Varga, 2015). Gains in knowledge and affect were linked, as were gains in affect and intent to act. In other words, the simulation enables people to learn for themselves and generates an intrinsic affective response, both of which have the potential to motivate action informed by science. At the time of writing, more than 29,500 people in 69 countries have experienced World Climate, and it has been designated for promotion to all high school teachers in Germany and France.

Why Simulations?

Interactive simulations offer a means to expand “systems literacy” by enabling users to interactively explore the dynamics of complex systems and come to their own conclusions about how systems work (Landriscina, 2009). Simulations are defined as interactive representations of a real-world system (Enciso, 2001; Landriscina, 2009). By relieving us from strenuous calculations, they free cognitive capacity for conceptual learning and development of new mental models (Kopainsky & Sawicka, 2011). Correcting fundamental misconceptions about the climate and energy systems must clearly be one goal of climate change education, communication, and decision support, especially as causal thinking about climate change has been linked to support for policies to address it. For example, support for policies to reduce CO2 emissions was higher among individuals who correctly understood CO2 as the main cause of climate change (Bostrom et al., 2012). Simulations enable iterative experimentation when it would otherwise be costly, risky, or, as in the case of the climate and energy systems, impossible. Thus, simulations provide an opportunity to engage learners in a process that mirrors scientific discovery by posing hypotheses, conducting experiments, determining outcomes, and adjusting one’s understanding of the world accordingly (Saunders & Powell, 1998; Sterman, 1994). They also enable learners to explore the dynamics of complex systems and build mental models about how systems work (Landriscina, 2009).

Why Games?

While simulations offer powerful tools for exploring the dynamics of physical-technical systems, combining them with role-playing games offers a means of incorporating the social, emotional, and sometimes irrational behavior of real people and the often messy, chaotic, and unpredictable process of human negotiation and decision making (Mayer, 2009). The use of games to learn about complex systems that combine social and physical components is ancient, with the earliest known examples being war games originating in China around 3000 bce (Feinstein, Mann, & Corsun, 2002). In the 1960’s, Meadows (Meadows, 1999) pioneered the use of role-playing games framed by system dynamics models to foster accessibility and interaction with models. By immersing participants in a complex social system that interacts with the physical-technical system, they can gain first-hand knowledge of social drivers of decision making. Games can motivate and guide interaction with simulations by compelling participants to learn how the system works through discovery, competition, and pleasure (Mendler de Suarez, Suarez, & Bachofen, 2012). The social dynamics of games are also complex systems, incorporating feedbacks, non-linearities, delays, uncertainty, and unanticipated side effects (Mendler de Suarez et al., 2012). They offer a simulated setting that is free from real-world constraints, empowering us to make decisions and experience making those decisions, without experiencing their real-world consequences. Unlike the real world, games enable us to learn from iteration, without accumulating the repercussions of failed decisions. At the same time, they offer the potential for generating innovative, systemic solutions, through experience of systemic change.

Unlike low-tech or no-tech games, in which complexity is limited by cognitive load, incorporating computer simulations into games raises the complexity and amount of information that can be accessed and provides a reality check grounded in science, while also making it possible to move bi-directionally in time, playing out different possible futures (Mayer, 2009). Simulation games are an effective means to elicit and expose faulty mental models, creating the disequilibrium that learners experience when they cannot incorporate new information into existing schemas or mental models, which, in turn, motivates construction of new mental models (Piaget, 1972).

Simulation role-playing games offer an opportunity to access social learning pathways and may offer a means to overcome many of the social barriers in climate change communication:

Social cognition. Games create a shared social experience, providing an opportunity for updating beliefs within a social context rather than individually. They can cultivate shared understanding and collective intelligence (Mendler de Suarez et al., 2012). Further research is needed to determine whether these social experiences can overcome the barriers to climate change communication by cultural worldviews (Kahan et al., 2012).

The role of the messenger. Games are multi-logues with no back seats (Mendler de Suarez et al., 2012), not one-way communication with a messenger and an audience. Furthermore, simulation-based games convey information about physical technical systems through discovery and exploration of simulations rather than through information delivery. While games may be guided by a facilitator, the role of messenger is fulfilled primarily by the participants themselves. Perhaps equally important, participants gain experience being the messenger, or learning through teaching others, as well as gaining first-hand experience communicating about climate change.

The social “other,” bounded rationality, and activating moral responses. Role-playing games give players an opportunity to become part of a simulated social group that they may not, in reality, identify with, enabling them to temporarily view the system from the perspective of a different social group and expanding their “bounded rationality.” People take on membership in social groups and their associated in-group biases even when groups are created based on arbitrary or nonexistent characteristics (Tajfel, Billig, Bundy, & Flament, 1971). An enticing possibility is that of activating moral responses to climate change through simulated identification with “other” social groups, including those that are expected to disproportionately suffer climate change impacts (e.g., populations in developing nations, future generations, the poor, etc.)

Global Learning and Observations to Benefit the Environment (GLOBE)

The GLOBE Program is an international science and education program that provides students and the public worldwide with the opportunity to participate in data collection and the scientific process, and to contribute meaningfully to our understanding of the Earth system and global environment. The international GLOBE network has grown since 1995 to include representatives from over 110 participating countries and over 100 U.S. partners coordinating GLOBE activities that are integrated into their local and regional communities.

Students have a difficult time understanding a system of interacting components where each component impacts and is affected by the others, but in many cases those interactions can’t be seen. Teachers can begin to help students develop this understanding by having them explore these interactions in a context they are familiar with. An example of how this can be done is seen in a series of Earth science activities that appear in the GLOBE Teachers Guide (Ledley et al., 2003) and in the EarthLabs Earth System Science module (Ledley, Haddad, Bardar, Ellins, McNeal, & Libarkin, 2012).

In the GLOBE Earth systems activities students first learn about the different components of the Earth system and explore their local site for those components and the connections between them. They visit and photograph this site, identify and describe the various components of the Earth system within the context of the local environment, and consider the impact of changes in one component of the Earth system on the others. Students are then asked to identify the interconnections they observed or inferred, and consider how energy and matter are transferred between different components of the Earth system. For students to realize that some processes in the local environment are more important than others, students are asked to create a simplified diagram of their site that highlights the most important interactions that define their local environment. This place-based approach results in highly localized responses with expected answers being different for the wide range of environments within which students live.

Once students have explored the connections between the various components of the Earth system in their own local environment, visually and through discussions with their teacher and peers, they move on to explore those connections with observational data gathered by students as part of the GLOBE program. Students access and graph data collected during the spring and summer, a time of warming. The variables examined include the monthly averaged surface air temperature, daily precipitation accumulation, soil moisture at 10 cm below the surface, and soil moisture 90 cm below the surface. By examining this data and through facilitated class discussions, students discover the relationship between these variables over time.

In later activities, students build on their developing understanding of the connections between the components of the Earth system in the local context by exploring Earth system science in the larger regional and global scales. Educational research using systems assessments before and after completing the EarthLabs Earth System Science module indicated that use of the module significantly increased students understanding of systems (McNeal et al., 2014) suggesting that the approach of initiating instruction about Earth systems in contexts that are familiar can help overcome the cognitive challenges students have with understanding complex dynamic systems.

Conclusion

While the Paris Agreement has laid out ambitious climate goals, a wide gap remains between those goas and emissions reductions needed to achieve them (Kintisch, 2015; Rogelj et al., 2016). This article argues that the emissions gap cannot be closed without also closing the education gap—that is, the gap between the science and society’s understanding of climate change, the threats it poses, and the energy transition it demands. It is recognized that education for action requires more than scientific literacy; it must integrate concepts and dynamics across disciplines and in ways that address affective, social, and cultural forces—a challenge that can be met through systems thinking and system dynamics. Using a systems thinking approach, the potential for education to serve as a vehicle for rapid societal change is examined. As shown in Figures 2 and 3, education not only enables society to benefit from the projections climate change science has offered us but also plays a central role in several reinforcing feedback loops that can accelerate the growth of climate-informed decision-making at all levels, the social will and support for action, and the building of a transition-ready workforce. Many effective climate change education efforts have been successful in increasing climate and energy literacy and community capacity building. However, society still face challenges in coordinating initiatives across various audiences, managing and leveraging resources, and sustaining and scaling the effective programs to meet the challenges and opportunities posed by a changing climate. Education and training at all levels of society can promote and ensure strong and enduring government, business, and civic leadership and informed decision making by individuals, community leaders, office holders, and engaged citizens.

Suggested Readings

References

  • Anderson, A. (2013) Climate change education for mitigation and adaptation. Journal of Education for Sustainable Development, 6(2), 191–206.
  • Bandura, A. (2000). Exercise of human agency through collective efficacy. Current Directions in Psychological Science, 9(3), 75–78.
  • Barth, M. (2016). Teaching and learning in sustainability science. In B. J. M. De Vries (Ed.), Sustainability Science (pp. 325–333). Springer, New York: Cambridge University Press.
  • Bateman, T. S., & Hess, A. M. (2015). Different personal propensities among scientists relate to deeper vs broader knowledge contributions. Proceedings of the National Academy of Sciences, 112(12), 3653–3658.
  • Bostrom, A., O’Connor, R. E., Böhm, G., Hanss, D., Bodi, O., Ekström, F., Halder, P., Jeschke, S., Mack, B., & Qu, M., Rosentrater, L. D., & Sandve, A. (2012). Causal thinking and support for climate change policies: International survey findings. Global Environmental Change, 22(1), 210–222.
  • Claesson, A. N., & Svanström, M. (2015). Developing systems thinking for sustainable development in engineering education. The 7th International Conference on Engineering Education for Sustainable Development, Vancouver, Canada.
  • Colston, N. M., & Ivey, T. A. (2015). (un)Doing the next generation science standards: Climate change education actor-network. Journal of Education Policy, 30(6), 773–795.
  • Cronin, M. A., Gonzalez, C., & Sterman, J. D. (2009). Why don’t well-educated adults understand accumulation? A challenge to researchers, educators, and citizens. Organizational Behavior and Human Decision Processes. 108(1), 116–130.
  • Damasio, A. R. (1994). Descartes’ error: Emotion, reason, and the human brain. New York: Avon.
  • Dessler, A. E. (2010). A determination of the cloud feedback from climate variations over the past decade. Science, 330(6010), 1523–1527.
  • DeWaters, J., & Powers, S. (2013). Establishing measurement criteria for an energy literacy questionnaire. The Journal of Environmental Education, 44(1), 38–55.
  • Doherty, K. L., & Webler, T. N. (2016). Social norms and efficacy beliefs drive the alarmed segment’s public-sphere climate actions. Nature Climate Change, 6, 879–884.
  • Dörner, D. (1980). On the difficulties people have dealing with complexity. Simulations and Games, 11, 87–106.
  • Dörner, D. (1996). The logic of failure. New York: Metropolitan Books/Henry Holt.
  • Enciso, R. Z. (2001). Simulation games: A learning tool. Paper presented at the Proceedings of the International Simulation and Gaming Association Conference, Bari, Italy.
  • Feinstein, A. H., Mann, S.H., & Corsun, D. L. (2002). Computer simulation, games, and roleplay: Drawing lines of demarcation. Developments in Business Simulation and Experiential Learning, 29, 58–65,
  • Flora, J. A., Saphir, M., Lappe, M., Roser-Renouf, C., Maibach, E. W., & Leiserowitz, A. A. (2014). Evaluation of a national high school entertainment education program: The Alliance for Climate Education. Climatic Change, 127(3), 419–434.
  • Friedrich, T., Timmermann, A., Tigchelaar, M., Elison Timm, O., & Ganopolski, A. (2016). Nonlinear climate sensitivity and its implications for future greenhouse warming. Science Advances, 2(11).
  • Halford, G. S., Baker, R., McCredden, J. E., & Bain, J. D. (2005). How many variables can humans process? Psychological Science, 16(1), 70–76.
  • Hämäläinen, R. P., Luoma, J., & Saarinen, E. (2013). On the importance of behavioral operational research: The case of understanding and communicating about dynamic systems. European Journal of Operational Research, 228(3), 623–634.
  • Hanleybrown, F., Kania, J., & Kramer, M. (2012). Channeling change: Making collective impact work. Stanford Social Innovation Review, 8.
  • Hansen, J., Sato, M., Hearty, P., Ruedy, R., Kelley, M., Masson-Delmotte, V., et al. (2016). Ice melt, sea level rise, and superstorms: Evidence from paleoclimate data, climate modeling, and modern observations that 2 °C global warming could be dangerous. Atmospheric Chemistry and Physics, 16(6), 3761–3812.
  • Hansen, J., Sato, M., Kharecha, P., & von Schuckmann, K. (2011). Earth’s energy imbalance and implications. Atmospheric Chemistry and Physics, 11(24), 13421–13449.
  • Heal, G., & Park, J. (2016). Temperature stress and the direct impact of climate change: A review of an emerging literature. Review of Environmental Economics and Policy, 10(2), 347–362.
  • Hu, Q., Johnston, E., Hemphill, L., Krishnamurthy, R., & Vinze, A. (2012). Exploring the role of interactive computer simulations in public administration education. Journal of Public Affairs Education, 18(3), 513–530.
  • Hurd, P. D. (1998). Scientific literacy: New minds for a changing world. Science Education, 82, 407–416.
  • Institute of the Golden Gate. (2014). Bay Area Climate Change Education Needs Assessment Report.
  • IPCC (Ed.). (2013). Climate change 2013: The physical science basis: Working Group I contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, U.K.: Cambridge University Press.
  • IPCC (Ed.). (2014a). Climate change 2014: Impacts, adaptation, and vulnerability. Part B: Regional aspects. Contribution fro Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, U.K.: Cambridge University Press.
  • IPCC (Ed.). (2014b). Climate change 2014: Impacts, adaptation, and vulnerability. Part A: Global and sectoral aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, U.K.: Cambridge University Press.
  • IPCC (Ed.). (2014c). Climate change 2014: Mitigation of climate change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, U.K.: Cambridge University Press.
  • IPCC (Ed.). (2014d). Climate change 2014: Synthesis report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Geneva, Switzerland: IPCC.
  • Iwaniec, D. M., Childers, D. L., VanLehn, K., & Wiek, A. (2014). Studying, teaching, and applying sustainability visions using systems modeling. Sustainability, 6(7), 4452–4469.
  • Kahan, D. M., Peters, E., Wittlin, M., Slovic, P., Ouellette, L. L., Braman, D., et al. (2012). The polarizing impact of science literacy and numeracy on perceived climate change risks. Nature Climate Change, 2(10), 732–735.
  • Kania, J., & Kramer, M. (2011). Collective impact. Stanford Social Innovation Review, 9(1), 36–41.
  • Kintisch, E. (2015). After Paris: The rocky road ahead. Science, 350(6264), 1018–1019.
  • Kjellstrom, T., Briggs, D., Freyberg, C., Lemke, B., Otto, M., & Hyatt, O. (2016). Heat, human performance, and occupational health: A key issue for the assessment of global climate change impacts. Annual Review of Public Health, 37(1), 97–112.
  • Kopainsky, B., & Sawicka, A. (2011). Simulator-supported descriptions of complex dynamic problems: Experimental results on task performance and system understanding. System Dynamics Review, 27(2), 142–172.
  • Landriscina, F. (2009). Simulation and learning: The role of mental models. Journal of e-Learning and Knowledge Society, 5(2), 23–32.
  • Ledley, T. S., Allen, J., Sparrow, E., Gordon, L., Gordin, D., Shear, L., et al. (2003). Earth as a system. GLOBE Teachers Guide.
  • Ledley, T. S., Gold, A., Niepold, F., & McCaffrey, M. (2014). Moving toward collective impact in climate change literacy: The climate literacy and energy awareness network (CLEAN). Journal of Geoscience Education, 62(3), 307–318.
  • Ledley, T. S., Haddad, N., Bardar, E., Ellins, K., McNeal, K., & Libarkin, J. (2012). An Earth System Science laboratory module to facilitate teaching about climate change. The Earth Scientist, 28(3), 19–24.
  • Ledley, T. S., Niepold, F., Bozuwa, J., Davis, A., Fraser, J., Kretser, J., et al. (2016). A CLEAN Network initiative: Accelerating transition to post carbon and resilient communities through education and engagement. Paper presented at the American Geophysical Union Fall Meeting, San Francisco, CA.
  • Lee, T. M., Markowitz, E. M., Howe, P. D., Ko, C.-Y., & Leiserowitz, A. A. (2015). Predictors of public climate change awareness and risk perception around the world. Nature Climate Change, 5(11), 1014–1020.
  • Leiserowitz, A. (2005). American risk perceptions: Is climate change dangerous? Risk Analysis, 25(6), 1433–1442.
  • Leiserowitz, A. (2006). Climate change risk perception and policy preferences: The role of affect, imagery, and values. Climatic Change, 77(1), 45–72.
  • Leiserowitz, A., Maibach, E., & Roser-Renouf, C. (2010). Global warming’s six Americas, January 2010 Yale Project on Climate Change Communication.
  • Leiserowitz, A., Smith, N., & Marlon, J. R. (2011). American teens’ knowledge of climate change. Yale Program on Climate Change Communication.
  • Lelieveld, J., Proestos, Y., Hadjinicolaou, P., Tanarhte, M., Tyrlis, E., & Zittis, G. (2016). Strongly increasing heat extremes in the Middle East and North Africa (MENA) in the 21st century. Climatic Change, 137(1), 245–260.
  • Lenton, T. M. (2012). Arctic climate tipping points. AMBIO, 41(1), 10–22.
  • Lesk, C., Rowhani, P., & Ramankutty, N. (2016). Influence of extreme weather disasters on global crop production. Nature, 529(7584), 84–87.
  • Levermann, A., Clark, P. U., Marzeion, B., Milne, G. A., Pollard, D., Radic, V., et al. (2013). The multimillennial sea-level commitment of global warming. Proceedings of the National Academy of Sciences, 110(34), 13745–13750.
  • Liu, J., Mooney, H., Hull, V., Davis, S. J., Gaskell, J., Hertel, T., et al. (2015). Systems Integration for global sustainability. Science, 347(6225).
  • Loewenstein, G., & Elster, J. (Eds.). (1992). Choice over time. New York: Russell SAGE.
  • Lombardi, D., & Sinatra, G. M. (2012). College students’ perceptions about the plausibility of human-induced climate change. Research in Science Education, 42(2), 201–217.
  • Lombardi, D., Sinatra, G. M., & Nussbaum, E. M. (2013). Plausibility reappraisals and shifts in middle school students’ climate change conceptions. Learning and Instruction, 27, 50–62.
  • Maibach, E., Roser-Renouf, C., Weber, D., & Taylor, M. (2008). What are Americans thinking and doing about global warming? Results of a national household survey: January 2008. George Mason University Center for Climate Change Communication.
  • Marcus, J., Coops, N. C., Ellis, S., & Robinson, J. (2015). Embedding sustainability learning pathways across the university. Current Opinion in Environmental Sustainability, 16, 7–13.
  • Markowitz, E. M., & Shariff, A. F. (2012). Climate change and moral judgement. Nature Climate Change. 2, 243–247.
  • Mayer, I. S. (2009). The gaming of policy and the politics of gaming: A review. Simulation and gaming, 40(6), 825–862.
  • McCaffrey, M., Berbeco, M., & Scott, E. (2013). Toward a climate & energy literate society. Recommendations from the Climate and Energy Literacy Summit, December 7–9, 2012, Berkeley, CA.
  • McDougall, C., Martin, A., Givens, S. M., Yue, S., Wilson, C. E., & Karsten, J. L. (2012). The Tri-Agency Climate Education (TrACE) Catalog: Promoting collaboration, effective practice, and a robust portfolio by sharing educational resources developed across NASA, NOAA, & NSF climate education initiatives. Paper presented at the American Geophysical Union, Fall Meeting, San Francisco, CA.
  • McNeal, K. S., Libarkin, J., Ledley, T. S., Haddad, N., Bardar, E., et al. (2014). The role of research in online curriculum development: The case of the EarthLabs climate change curriculum. Journal of Geoscience Education, 62, 560–577.
  • Meadows, D. L. (1999). Learning to be simple: My odyssey with games. Simulation and Gaming, 30(3), 342–351.
  • Meadows, D. H. (2008). Thinking in systems: A primer. White River Junction, VT: Chelsea Green.
  • Mendler de Suarez, J., Suarez, P., & Bachofen, C. (Eds.). (2012). Games for a new climate: Experiencing the complexity of future risks. Task Force Report, Nov 2012. The Frederick S. Pardee Center for the Study of the Longer-Range Future. Boston University.
  • Moser, S. C. (2010). Communicating climate change: History, challenges, process, and future directions. Wiley Interdisciplinary Reviews: Climate Change, 1(1), 31–53.
  • National Research Council. (1996). National Science Education Standards. Washington, DC: National Academy Press.
  • National Research Council. (2010a). Education and communication. In National Research Council (Ed.), Informing an effective response to climate change (pp. 251–282). Washington, DC: National Academies Press.
  • National Research Council. (2010b). Surrounded by science: Learning science in informal environments. Washington, DC: The National Academies Press.
  • National Research Council. (2011a). America’s climate choices. Washington, DC: The National Academies Press.
  • National Research Council. (2011b). Climate change education: Goals, audiences, and strategies: A workshop summary. Washington, DC: The National Academies Press.
  • National Research Council. (2012a). Climate change education: Formal settings, K14: A workshop summary. Washington, DC: The National Academies Press.
  • National Research Council. (2012b). A framework for K12 science education:Practices, crosscutting concepts, and core ideas, Washington, DC: The National Academies Press.
  • National Science Foundation (U.S.). (1970). Science education: The task ahead for the National Science Foundation, report. Washington, DC: The Committee.
  • NGSS Lead States (2013a). Next generation science standards: For states, by states. Next Generation Science Standards.
  • NGSS Lead States (2013b). Appendix A: Conceptual shifts in the next generation science standards. Next Generation Science Standards: For States, By States.
  • Oreskes, N., & Conway, E. M. (2011). Merchants of doubt: How a handful of scientists obscured the truth on issues from tobacco smoke to global warming. New York: Bloomsbury Press.
  • Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A., et al. (2011). A large and persistent carbon sink in the world’s forests. Science, 333(6045), 988–993.
  • Peters, G. P., Marland, G., Le Quéré, C., Boden, T., Canadell, J. G., & Raupach, M. R. (2012). Rapid growth in CO2 emissions after the 2008–2009 global financial crisis. Nature Climate Change, 2(1), 2–4.
  • Piaget, J. (1972). Psychology and epistemology: Towards a theory of knowledge. Harmondsworth, U.K.: Penguin.
  • Pidgeon, N., & Fischhoff, B. (2011). The role of social and decision sciences in communicating uncertain climate risks. Nature Climate Change, 1(1), 35–41.
  • Plutzer, E., Hannah, A. L., Rosenau, J., McCaffrey, M. S., Berbeco, M., & Reid, A. H. (2016). Mixed messages: How climate is taught in america’s schools. Oakland, CA: National Center for Science Education,
  • Prudhomme, C., Giuntoli, I., Robinson, E. L., Clark, D. B., Arnell, N. W., Dankers, R., et al. (2013). Hydrological droughts in the 21st century, hotspots, and uncertainties from a global multimodel ensemble experiment. Proceedings of the National Academy of Sciences, 111(9), 3262–3267.
  • Pruneau, D., Kerry, J., & Langis, J. (2016). New competences to develop in students to help them get involved in sustainable development while they learn through inquiry methods. In Z. Smyrnaiou & M. Riopel (Eds.), New Developments in Science and Technology Education (pp. 153–161). Cham, Switzerland: Springer International.
  • Rath, K., & Rooney-Varga, J. N. (2015). The World Climate Exercise: Is (Stimulated) Experience Our Best Teacher?, Paper presented at the American Geophysical Union Meeting, San Francisco, CA.
  • Rogelj, J., den Elzen, M., Höhne, N., Fransen, T., Fekete, H., Winkler, H., et al. (2016). Paris Agreement climate proposals need a boost to keep warming well below 2 °C. Nature, 534(7609), 631–639.
  • Rosenzweig, C., Elliott, J., Deryng, D., Ruane, A. C., Müller, C., Arneth, A., et al. (2013). Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proceedings of the National Academy of Sciences, 111(9), 3268–3273.
  • Rutherford, F. J., & Ahlgren, A. (1991). Science for all Americans. Washington, DC: AAAS, Oxford University Press.
  • Saunders, D., & Powell, T. (1998). Developing a European media simulation through new information and communication technologies: The TENSAL project. In J. Rolfe, D. Saunders, & T. Powell (Eds.), The international simulation and gaming research yearbook: Simulations and games for emergency and crisis management (pp. 75–86). London: Biddles.
  • Schlenker, W., & Roberts, M. J. (2009). Nonlinear temperature effects indicate severe damages to U.S. crop yields under climate change. Proceedings of the National Academy of Sciences, 106(37), 15594–15598.
  • Schleussner, C. F., Lissner, T. K., Fischer, E. M., Wohland, J., Perrette, M., Golly, A., et al. (2016). Differential climate impacts for policy-relevant limits to global warming: the case of 1.5 ° C and 2 ° C. Earth System Dynamics, 7(2), 327–351.
  • Schultz, P. W., Gouveia, V. V., Cameron, L. D., Tankha, G., Schmuck, P., & Franěk, M. (2005). Values and their relationship to environmental concern and conservation behavior. Journal of Cross-Cultural Psychology, 36(4), 457–475.
  • Solomon, S., Battisti, D. S., Doney, S. C., Hayhoe, K., Held, I., Lettenmaier, D. P., et al. (2011). Climate stabilization targets: Emissions, concentrations, and impacts over decades to millennia. Washington, DC: National Academy Press.
  • Solomon, S., Plattner, G. K., Knutti, R., & Friedingstein, P. (2009). Irreversible climate change due to carbon dioxide emissions. Proceedings of the National Academy of Sciences, 106(6), 1704–1709.
  • Spitzer, W. (2014). Shaping the public dialogue on climate change. In D. Dalbotten, G. Roehrig, & P. Hamilton (Eds.), Future earth: Advancing civic understanding of the Anthropocene (pp. 89–97): Hoboken, NJ: John Wiley & Sons.
  • Sterman, J. D. (1994). Learning in and about complex systems. System Dynamics Review, 10(2–3), 291–330.
  • Sterman, J. D. (2000). Business Dynamics: Systems thinking and modeling for a complex world. Boston: McGraw-Hill Education.
  • Sterman, J. D. (2008). Risk communication on climate: Mental models and mass balance. Science, 322(5901), 532–533.
  • Sterman, J. D. (2012). Sustaining sustainability: Creating a systems science in a fragmented academy and polarized world. In M. Weinstein & R. E. Turner (Eds.), Sustainability science: The emerging paradigm and the urban environment. New York: Springer.
  • Sterman, J. D., & Sweeney, L.B. (2007). Understanding public complacency about climate change: Adults’ mental models of climate change violate conservation of matter. Climatic Change, 80(3), 213–238.
  • Sterman, J., Fiddaman, T., Franck, T., Jones, A., McCauley, S., Rice, P., et al. (2012). Climate interactive: The C-ROADS climate policy model. Systems Dynamics Review, 28(3), 295–305.
  • Sterman, J., Fiddaman, T., Franck, T., Jones, A., McCauley, S., Rice, P., et al. (2013). Sustainability science: The emerging paradigm and the urban environment. Environmental Modeling and Software. New York: Springer.
  • Sterman, J., Franck, T., Fiddaman, T., Jones, A., McCauley, S., Rice, P., et al. (2014). World climate: A Role-play simulation of climate negotiations. Simulation and Gaming, 46(3–4), 348–382.
  • Sweeney, L. B., & Sterman, J. D. (2000). Bathtub dynamics: Initial results of a systems thinking inventory. System Dynamics Review, 16(4), 249–286.
  • Tajfel, H., Billig, M. G., Bundy, R. P., & Flament, C. (1971). Social categorization and intergroup behaviour. European Journal of Social Psychology, 1(2), 149–178.
  • United Nations Framework Convention on Climate Change (1992). Article 6: Education, training, and public awareness. United Nations Framework Convention on Climate Change.
  • United Nations framework convention on climate change. (2015) Paris Agreement.
  • United Nations General Assembly. (2015). Transforming our world: The 2030 agenda for sustainable development, A/RES/70/1. New York, NY: United Nations.
  • United States State Department. (2014). United States climate action report 2014.
  • USGCRP (2016). The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment. In A., Crimmins, J. Balbus, J. L. Gamble, C. B. Beard, J. E. Bell, D. Dodgen, et al. (Eds.), Washington, DC: U.S. Global Change Research Program.
  • van den Besselaar, P., & Heimeriks, G. (2001). Disciplinary, multidisciplinary, interdisciplinary: Concepts and indicators. Paper presented at the 8th Conference on Scientometrics and Informetrics—ISSI2001, Syndey, Australia.
  • van Nes, E. H., Hirota, M., Holmgren, M., & Scheffer, M. (2014). Tipping points in tropical tree cover: linking theory to data. Global Change Biology, 20(3), 1016–1021.
  • Vaughter, P., (2016). Climate change education: From critical thinking to critical action, Policy Brief, 4, United Nations University, Institute for the Advanced Study of Sustainability.
  • Vincent, S., Bunn, S., & Sloane, L. (2013). Interdisciplinary environmental and sustainability education on the nation’s campuses 2012: Curriculum design. The National Council for Science and the Environment, Washington, DC.
  • Wagenaar, W. A., & Sagaria, S. D. (1975). Misperception of exponential growth. Perception and Pychophysics, 18(6), 416–422.
  • Wainwright, J. (2009). Earth-System Science. In N. Castree, D. Demeritt, D. Liverman, & B. Rhodes (Eds.), A companion to environmental geography (pp. 145–167). Oxford: Wiley-Blackwell.
  • Weber, E. (2006). Experience-based and description-based perceptions of long-term risk: Why global warming does not scare us (yet). Climatic Change, 77(1), 103–120.
  • Weber, E. U., & Stern, P. C. (2011). Public understanding of climate change in the United States. American Psychologist, 66(4), 315–328.
  • Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge, U.K.: Cambridge University Press.
  • Wike, R. (2016). What the world thinks about climate change in 7 charts. Pew Research Center.