Ranney, M. A., & Clark, D. (2016). Climate change conceptual change: Scientific information can transform attitudes. Topics in Cognitive Science, 8(1), 49-75.
Were you surprised, or even shocked, by the answer? If so, your reaction may bolster your support for policy actions to mitigate the effects of global warming. The above question and six more comprised one of two types of interventions used by Ranney & Clark (2016) to investigate, through seven experiments, how to increase participants’ global warming knowledge and support for efforts to staunch its effects.1 Based on previous studies demonstrating the importance of science literacy in society 2, Ranney and colleagues hypothesized that even small doses of critical information could change participants’ beliefs about the reality of global warming, regardless of their politics.
The researchers’ predictions challenged and disconfirmed an opposing view among some theorists that attitudes about global warming were overwhelmingly culturally motivated (e.g., through political or ideological beliefs) and therefore intractable to scientific evidence, a view that Ranney and colleagues referred to as stasis theory.2, 3 Disproving stasis theory carried theoretical merit and practical consequences for the researchers; in addition to demonstrating that scientific knowledge could overcome cultural biases, Ranney and colleagues recognized an imperative to improve the public understanding of the gravity of global warming.
The two classes of interventions differed in structure and content. Estimation-reveal interventions (as with the Glacier National Park question, above) used a quiz-like format to introduce participants to a small set of critical statistics about global warming. Mechanistic interventions, described below, presented the fundamental physical and chemical processes driving global warming via a one-page text or a longer high school curriculum. Both types of interventions were motivated by cognitive theory that proposes that strategically designed scientific information can aid decision-making and spark attitudinal change. And both interventions were successful in doing so.
The interventions were used in six pre-to-post-test experiments—in which participants answered the same knowledge and attitude questions before and after each intervention. Knowledge assessments tested participants’ understanding of the basic mechanisms of global warming. Attitudinal assessments measured participants’ acceptance of the reality of global warming, belief in its human (i.e., anthropogenic) causes, and support for public actions to mitigate its effects.
Strategically placed statistics shift beliefs
The experiments included delayed post-testing a week or more the after the interventions to assess longer-term retention of information. In some experiments, participants rated their levels of surprise in response to the intervention. Participants’ self-reported political and social leanings (rated on a 9-point scale ranging from extremely liberal to extremely conservative) allowed researchers to probe associations between attitudinal shifts and cultural values. Participants included science and psychology students at major U.S. state universities, and individuals recruited from public venues and crowd-sourced platforms.
In the estimation-reveal intervention, participants (high school students and members of the public) first estimated a key statistic about global warming, after which they learned the correct answer. This continued for each of a small set of (7) statistics. Estimates of the statistics were frequently so far off base that participants reported surprise or shock upon learning the correct statistic. Despite the brevity of this intervention — or perhaps partly because of it — the estimation-reveal intervention significantly changed participants’ acceptance of the reality of global warming, regardless of their self-reported political values.
Why might learning even a single, surprising statistic nudge a participant’s attitude about a social policy? According to a model of conceptual change proposed by Ranney and colleagues, an individual’s understanding of a social issue is rarely based entirely on facts, but is also likely to be formed by personal experiences, media opinions, misinformation, religious views, and other less-evidential sources. When asked to state a statistic related to a social topic, Ranney asserts, “It’s rare that someone remembers a specific statistic; instead, it’s more common for an individual to recall a set of personal experiences and anecdotal information related to the topic”.5
Discovering that one’s estimate is vastly different from its actual value can lead to surprise and shock. These emotions can aid changes in memory and beliefs because people pay more attention to unexpected than to expected information. Momentary incredulity can help change attitudes, as well. According to previous research by Ranney and colleagues, experiencing surprise at learning that the world is not as expected can motivate people to restructure even their fundamental beliefs.5 Additionally, the brevity of a single statistic may sharpen the wedge of doubt in one’s previous beliefs; previous work on decision-making by Ranney and Thagard (1988) proposed that when faced with a decision, individuals prefer evidence presented in a parsimonious — or streamlined — format.6
Mechanistic knowledge aids reasoning
Mechanistic explanations of the physical and chemical processes driving global warming were presented as interventions in a 400-word section of text and a (longer) high school curriculum. A summary of the main points of the mechanistic intervention is shown in 35 words1 below:
Earth transforms sunlight’s visible light energy into infrared light energy, which leaves Earth slowly because it is absorbed by greenhouse gases.When people produce greenhouse gases, energy leaves Earth even more slowly – raising Earth’s temperature.
Mechanistic knowledge explains the underlying processes that give rise to observable phenomena. Cognitive scientists consider mechanistic knowledge to be a powerful thinking tool because it permits individuals to generate ideas that can be tested and evaluated.7 For example, anyone who understands and accepts Ranney & Clark’s mechanistic explanation of global warming is likely to acknowledge its human sources. Incorporating this explanation into one’s understanding of climate change begs the question: “If greenhouse gases increase Earth’s temperature, and if humans produce greenhouse gases, how can the human role in global warming be ignored?“
How does mechanistic knowledge differ from other sorts of information about global warming? Ranney and colleagues surveyed visitors to a San Diego public park about their understanding of global warming before introducing the instructional interventions. Essentially none of the participants understood its most basic mechanisms; only 12% mentioned the role of atmospheric gases and only 3% specifically mentioned greenhouse gases. Many participants mentioned global warming’s temporal precursors, such as over-industrialization, or its effects––such as increasing mean global temperatures, rising sea levels––rather than describing its fundamental cause.
Across all studies, participants demonstrated virtually no knowledge of the physical and chemical mechanisms of global warming at pre-test. However, both types of interventions yielded noteworthy gains in participants’ knowledge and acceptance of the reality of global warming.
Across the several pertinent experiments, mechanistic interventions resulted in a median increase (on the immediate post-test) of 41% of possible gains in knowledge; at delayed post-testing (a week to a month after the intervention), participants had retained a median increase of 28% of possible gains in knowledge. These results held regardless of participants’ self-reported liberal-conservative values. Across both types of the brief interventions (mechanism and statistics), the median immediate post-test gain in acceptance of global warming was 14% of the possible gain; after 4-to 34-day delays, the median post-test gain in acceptance was 9% of what was possible. (see Joslyn & Demnitz, 2021, for a replication.8)
The estimation-reveal intervention was the single kind of intervention in two experiments, but to different ends. In one estimation-reveal experiment, participants received correct feedback on their estimates of seven key (i.e., representative) global statistics (i.e., the same questions linked to this post). This intervention succeeded in significantly increasing participants’ acceptance of, and concern about, global warming––with no evidence of polarization of participants’ attitudes toward global warming. The second estimation-reveal experiment provided participants with misleading statistics about global warming to investigate how this could reduce participants’ acceptance of global warming. As predicted, participants’ acceptance of the human causes of climate change dropped significantly with such misleading information; however, new work has shown that intermingling representative and misleading statistics yields an increase in global warming acceptance,9 because the contrast between such item-types allows people to find the “wheat in the chafe.”
An immediate educational public-outreach outcome of these experiments was How Global Warming Works, a free website that adapted the instructional interventions to (a) brief animations and (b) an interactive estimation-reveal interface. Transcripts of animation content (and other texts) are available online, and the mechanistic videos are available with German, Czech, and Mandarin Chinese narrations/graphics.10 New information on the website offers compelling graphs –– contrasting the stock market’s historic changes with Earth’s historic temperature changes –– that also increase global warming acceptance.3 (HowGlobalWarmingWorks.org’s materials have been used in many classrooms throughout the U.S. and world, and the site has spawned over one million page views.)
In summary, Ranney & Clark (2016) demonstrated that two kinds of interventions (statistics and physical-chemical mechanisms) motivated by different aspects of cognitive theory can bolster global warming knowledge to a level more consistent with the scientific consensus. In each experiment, knowledge gains were associated with greater acceptance of global warming and increased support for personal and public actions to protect the environment. There was no evidence of polarization in any experiments, discounting the idea that cultural biases dominate the reasoning tools inherent in basic science literacy. Ranney et al. (e.g., 2019, 2021, etc.) have continued this line of work to show that ten kinds of briefly-presented information (i.e., eight more than discussed by Ranney & Clark, 2016) increase individuals’ acceptance/concern about global warming.3,11,12
1. Ranney, M. A., & Clark, D. (2016). Climate change conceptual change: Scientific information can transform attitudes. Topics in Cognitive Science, 8(1), 49-75.
2. Clark, D., Ranney, M. A., & Felipe, J. (2013). Knowledge helps: Mechanistic information and numeric evidence as cognitive levers to overcome stasis and build public consensus on climate change. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.) Proceedings of 35th Annual Meeting of the Cognitive Science Society (pp. 2070- 2075). Austin, TX: Cognitive Science Society.
3. Ranney, M.A., Shonman, M., Fricke, K., Lamprey, L. N., & Kumar, P. & (2019). Information that boosts normative global warming acceptance without polarization: Toward J. S. Mill’s political ethology of national character. In D. A. Wilkenfeld & R. Samuels (Eds.) Advances in experimental philosophy of science (pp. 61-96). (In Bloomsbury’s Advances in Experimental Philosophy series.) New York: Bloomsbury.
4. Ranney, M. A., Munnich, E. L., & Lamprey, L. N. (2016). Increased wisdom from the ashes of ignorance and surprise: Numerically-driven inferencing, global warming, and other exemplar realms. In B. H. Ross (Ed.), The psychology of learning and motivation, 65, 129-182. New York: Elsevier. https://escholarship.org/content/qt0744s5g6/qt0744s5g6.pdf
5. Munnich, E. L., Ranney, M. A., Nelson, J. M., Garcia de Osuna, J. M., & Brazil, N. B. (2003). Policy shift through Numerically-Driven Inferencing: An EPIC experiment about when base rates matter. In R. Alterman & D. Kirsh (Eds.), Proceedings of the Twenty-Fifth Annual Conference of the Cognitive Science Society (pp. 834-839). Mahwah, NJ: Erlbaum.
6. Ranney, M., & Thagard, P. (1988). Explanatory coherence and belief revision in naive physics. Proceedings of the Tenth Annual Conference of the Cognitive Science Society (pp. 426-432). Hillsdale, NJ: Erlbaum. https://convinceme.com/downloads/papers/RanneyThagard-CS1988.pdf
7. Krist, C., Schwarz, C. V., & Reiser, B. J. (2019). Identifying essential epistemic heuristics for guiding mechanistic reasoning in science learning. Journal of the Learning Sciences, 28(2), 160-205.
9. Velautham, L., & Ranney, M. A. (2020). Global warming, nationalism, and reasoning with numbers: Toward techniques to promote the public’s critical thinking about statistics. In S. Denison., M. Mack, Y. Xu, & B.C. Armstrong (Eds.). Proceedings of the 42nd Annual Conference of the Cognitive Science Society (pp. 1834-1840). Cognitive Science Society.
8. Joslyn S., & Demnitz, R. (2021). Explaining how long CO2 stays in the atmosphere: Does it change attitudes toward climate change? Journal of Experimental Psychology: Applied, 27(3), 473-484.
10. Ranney, M. A., & Lamprey, L. N. (Eds.). (2013-present). How Global Warming Works [Website and web-pages]. Available at http://www.HowGlobalWarmingWorks.org.
11. Ranney, M.A., & Velautham, L. (2021). Climate change cognition and education: Given no silver bullet for denial, diverse information-hunks increase global warming acceptance. Current Opinion in Behavioral Sciences, 42, 139-146.
12. Velautham, L., Ranney, M. A., Brow, Q. S. (2019). Communicating climate change oceanically: Sea level rise information increases mitigation, inundation, and global warming acceptance. Frontiers in Communication, 4, 1-17.