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Toward Better Beliefs
Abstract
Beliefs play a central role in our lives. They lie at the heart of what makes us human, they shape the organization and functioning of our minds, they define the boundaries of our culture, and they guide our motivation and behavior. Given their central importance, researchers across a number of disciplines have studied beliefs, leading to results and literatures that do not always interact. The Cognitive Science of Belief aims to integrate these disconnected lines of research to start a broader dialogue on the nature, role, and consequences of beliefs. It tackles timeless questions, as well as applications of beliefs that speak to current social issues. This multidisciplinary approach to beliefs will benefit graduate students and researchers in cognitive science, psychology, philosophy, political science, economics, and religious studies.
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Does one’s stance toward evidence evaluation and belief revision have relevance for actual beliefs? We investigate the role of endorsing an actively open-minded thinking style about evidence (AOT-E) on a wide range of beliefs, values, and opinions. Participants indicated the extent to which they think beliefs (Study 1) or opinions (Studies 2 and 3) ought to change according to evidence on an 8-item scale. Across three studies with 1,692 participants from two different sources (Mechanical Turk and Lucid for Academics), we find that our short AOT-E scale correlates negatively with beliefs about topics ranging from extrasensory perception, to respect for tradition, to abortion, to God; and positively with topics ranging from anthropogenic global warming to support for free speech on college campuses. More broadly, the belief that beliefs should change according to evidence was robustly associated with political liberalism, the rejection of traditional moral values, the acceptance of science, and skepticism about religious, paranormal, and conspiratorial claims. However, we also find that AOT-E is more strongly predictive for political liberals (Democrats) than conservatives (Republicans). We conclude that socio-cognitive theories of belief (both specific and general) should take into account people’s beliefs about when and how beliefs should change – that is, meta-beliefs – but that further work is required to understand how meta-beliefs about evidence interact with political ideology.
Twelve experiments examined ways of improving informal reasoning, as assesed by presenting students with accessible, current, and interesting social and political issues, eliciting reasoning about them, and scoring the reasoning for quality of argument. The experiments addressed: (1) the impact of established instructional programs that emphasized critical thinking (Experiments 1–4); (2) the impact of an investigator-designed high school level minicourse (Experiments 5–7); (3) the responsiveness of subjects to prompts that asked them to develop arguments more fully, and the relation of their responses to general intelligence (Experiments 8–10); (4) checks on the validity of the testing methodology (Experiments 11–12). Two of the established instructional programs had a beneficial effect. The minicourse had a particularly large effect on students’ attention to the other side of the case, the most neglected aspect of informal reasoning. The prompting studies showed that subjects could develop their arguments far more than they normally did. Finally, subjects with higher intelligence were actually somewhat more biased in their reasoning. In summary: people can reason much better than they typically do on the sorts of issues posed; people are not performing near the limits of their abilities; strategies and standards of good reasoning can improve reasoning; and education can develop students’ reasoning much further than education typically does.
When faced with a dilemma between believing what is supported by an impartial assessment of the evidence (e.g., that one's friend is guilty of a crime) and believing what would better fulfill a moral obligation (e.g., that the friend is innocent), people often believe in line with the latter. But is this how people think beliefs ought to be formed? We addressed this question across three studies and found that, across a diverse set of everyday situations, people treat moral considerations as legitimate grounds for believing propositions that are unsupported by objective, evidence-based reasoning. We further document two ways in which moral considerations affect how people evaluate others' beliefs. First, the moral value of a belief affects the evidential threshold required to believe, such that morally beneficial beliefs demand less evidence than morally risky beliefs. Second, people sometimes treat the moral value of a belief as an independent justification for belief, and on that basis, sometimes prescribe evidentially poor beliefs to others. Together these results show that, in the folk ethics of belief, morality can justify and demand motivated reasoning.
Observational learning can debias judgment and decision making. One-shot observational
learning-based training interventions (akin to “hot seating”) can produce reductions in cognitive biases in the laboratory (i.e., anchoring, representativeness, and social projection), and successfully teach a decision rule that increases advice taking in a weight on advice paradigm (i.e., the averaging principle). These interventions improve judgment, rule learning, and advice taking more than practice. We find observational learning-based interventions can be as effective as information-based interventions. Their effects are additive for advice taking, and for accuracy when advice is algorithmically optimized. As found in the organizational learning literature, explicit knowledge transferred through information appears to reduce the stickiness of tacit knowledge transferred through observational learning. Moreover, observational learning appears to be a unique debiasing training strategy, an addition to the four proposed by Fischhoff (1982). We also report new scales measuring individual differences in anchoring, representativeness heuristics, and social projection.
In a mixed‐methods study following 1551 adolescents from eight diverse schools across the US, a large majority demonstrated (a) strong norms of actively open‐minded thinking (AOT) and (b) a widespread capacity for AOT. Students from two public (government) schools, two private (public) schools, and two charter (academy) schools were followed for 18 months over the transition from middle school to high school, with data collected in each semester of the eighth grade and ninth grade year. The study included an unusually varied set of approaches to assess AOT values and habits, including a rating scale, two new multiple choice measures, teacher reports from three teachers per student, peer nomination, and interviews with subsets of the larger sample. These varied measures converged to reveal widespread openness to disagreement, desire for understanding, and pluralistic norms. In interviews, participants demonstrated AOT in three powerful ways: deep web search for ideas, epistemic empathy, and pluralistic thinking. Moreover, repeated administration of measures indicated moderate intertemporal reliability of this trait, with six‐month test‐retest correlations ranging from .27 to .59 depending on the measure. This research suggests that existing capacities for AOT could be more fruitfully leveraged and supported by educators, helping students to capitalise on their own values and intuitions as they develop into mature critical thinkers.
The primary objection to debiasing training interventions is a lack of evidence that they transfer to improve decision making in field settings, where reminders of bias are absent. We gave graduate students in three professional programs (N = 290) a one-shot training intervention that reduces confirmation bias in laboratory experiments. Natural variance in the training schedule assigned participants to receive training before or after solving an unannounced business case modeled on the decision to launch the Space Shuttle Challenger. We used case solutions to surreptitiously measure their susceptibility to confirmation bias. Trained participants were 29% less likely to choose the inferior hypothesis-confirming solution than untrained participants. Analysis of case write-ups suggests that a reduction in confirmatory hypothesis testing accounts for their improved decision making in the case. The results provide promising evidence that debiasing training effects transfer to field settings and can improve consequential decisions in professional and private life.
Online, social media communication is often ambiguous, and it can encourage speed and inattentiveness. We investigated whether Actively Open Minded Thinking (AOT), a dispositional willingness to seek out new or potentially threatening information, may help users avoid these pitfalls. In Study 1, we determined that correctly assessing social media authors’ traits was positively predicted by raters’ AOT. In Study 2, we used data-driven methods to devise a three-dimensional picture of online behaviors of people high or low in AOT, finding that AOT is associated with thoughtful, nuanced, idiosyncratic actions and with resisting the typically fast pace of online interactions. AOT may be an important factor in accurate, socially responsible online behavior. © 2018, Society for Judgment and Decision making. All rights reserved.
Delusion-prone individuals may be more likely to accept even delusion-irrelevant implausible ideas because of their tendency to engage in less analytic and less actively open-minded thinking. Consistent with this suggestion, two online studies with over 900 participants demonstrated that although delusion-prone individuals were no more
likely to believe true news headlines, they displayed an increased belief in “fake news” headlines, which often feature implausible content. Mediation analyses suggest that analytic cognitive style may partially explain these individuals’ increased willingness to believe fake news. Exploratory analyses showed that dogmatic individuals
and religious fundamentalists were also more likely to believe false (but not true) news, and that these relationships may be fully explained by analytic cognitive style. Our findings suggest that existing interventions that increase analytic and actively open-minded thinking might be leveraged to help reduce belief in fake news.
Addressing fake news requires a multidisciplinary effort
In recent years, public officials have shown a growing interest in using evidence from the behavioural sciences to promote policy goals. Much of the discussion of behaviourally informed approaches has focused on ‘nudges’; that is, non-fiscal and non-regulatory interventions that steer (nudge) people in a specific direction while preserving choice. Less attention has been paid to boosts, an alternative evidence-based class of non-fiscal and non-regulatory intervention. The goal of boosts is to make it easier for people to exercise their own agency in making choices. For instance, when people are at risk of making poor health, medical or financial choices, the policy-maker – rather than steering behaviour through nudging – can take action to foster or boost individuals’ own decision-making competences. Boosts range from interventions that require little time and cognitive effort on the individual's part to ones that require substantial amounts of training, effort and motivation. This article outlines six rules that policy-makers can apply in order to determine under which conditions boosts, relative to nudges, are the preferable form of non-fiscal and non-regulatory intervention. The objective is not to argue that boosts are better than nudges or vice versa, but to begin to spell out the two approaches’ respective conditions for success.
In the current study, a serious game was developed to address a training challenge: teaching players to recognize and mitigate their cognitive biases. Cognitive biases, which are human tendencies to commit systematic errors in thinking that lead to irrational judgments, are deeply ingrained and difficult to alter. This paper describes the theory-based approach we employed to create a game for the mitigation of cognitive biases – a challenging and abstract training topic. A cognitive bias framework that relates the target cognitive biases, their causes, and effective bias mitigation techniques was developed and incorporated into the game design. The resultant serious game, titled Missing: The Final Secret (hereinafter: Missing), pairs the most promising mitigation strategies with the primary causes of the targeted cognitive biases and incorporates them into game-play. Further, we present preliminary results from a game efficacy evaluation suggesting that Missing is an effective tool for training cognitive bias recognition and mitigation.
Actively open-minded thinking (AOT) is often used as a proxy for reflective thinking in research on reasoning and related fields. It is associated with less biased reasoning in many types of tasks. However, few studies have examined its psychometric properties and criterion validity. We developed a shortened, 17-item version of the AOT for quicker administration. AOT17 is highly correlated with the original 41-item scale and has highly similar relationships to other thinking dispositions, social competence and supernatural beliefs. Our analyses revealed that the AOT is not a unitary construct, but comprises four distinct dimensions, some of which concern attitudes towards knowledge, and others concern attitudes towards people. This factor structure was replicated in another data-set, and correlations with other measures in four data-sets (total N = 3345) support the criterion validity of these dimensions. Different dimensions were responsible for the AOT's relationships with other thinking dispositions.
In recent years, policy makers worldwide have begun to acknowledge the potential value of insights from psychology and behavioral economics into how people make decisions. These insights can inform the design of nonregulatory and nonmonetary policy interventions—as well as more traditional fiscal and coercive measures. To date, much of the discussion of behaviorally informed approaches has emphasized “nudges,” that is, interventions designed to steer people in a particular direction while preserving their freedom of choice. Yet behavioral science also provides support for a distinct kind of nonfiscal and noncoercive intervention, namely, “boosts.” The objective of boosts is to foster people’s competence to make their own choices—that is, to exercise their own agency. Building on this distinction, we further elaborate on how boosts are conceptually distinct from nudges: The two kinds of interventions differ with respect to (a) their immediate intervention targets, (b) their roots in different research programs, (c) the causal pathways through which they affect behavior, (d) their assumptions about human cognitive architecture, (e) the reversibility of their effects, (f) their programmatic ambitions, and (g) their normative implications. We discuss each of these dimensions, provide an initial taxonomy of boosts, and address some possible misconceptions.
Kahan and Corbin suggest that the cognitive capabilities that constitute actively open-minded thinking (AOT) are used in the defense of favored positions, thus leading to polarization concerning global warming. Such a conclusion is contrary to the definition of AOT. I suggest, and dispute, two ways in which such a result could be consistent with the definition: the scale that measures AOT is correlated with other traits that do increase polarization; or AOT may itself not be a general trait, so that conservatives do not apply it to global warming. A third, more plausible, explanation is that part of the main result is based on a floor effect, a statistical artifact. It is also possible that the effect of AOT is exerted primarily on political identification. The substantial correlation between AOT and political liberalism also helps us interpret prior conflicting results concerning politics and cognitive style, especially in view of the total absence of any correlation between politics and the Cognitive Reflection Test in the same data set.
Across consequential attributions of attitudes, ability, emotions, and morality, people make correspondent inferences. People infer stable personality characteristics from others’ behavior, even when that behavior is caused by situational factors. We examined the structure of correspondent inferences and report the development and validation of an instrument measuring individual differences in this correspondence bias (a Neglect of External Demands scale, or “NED”). The NED is internally consistent and distinct from scales and measures of intelligence, cognitive ability, cognitive reflection, general decision-making ability, preference for control, and attributional style. Individual differences in correspondence bias predict blaming people for harmful accidents, believing coerced confessions, correcting for job and task difficulty when making performance evaluations and incentive-compatible personnel selections, and separating market and fund performance when making incentive-compatible investments. Fortunately, the tendency to commit correspondence bias can be reduced. Making situational information easier to process debiases those most prone to correspondence bias.
Data are available at https://doi.org/10.1287/mnsc.2016.2668 .
This paper was accepted by Yuval Rottenstreich, judgment and decision making.
The heuristics-and-biases research program highlights reasons for expecting people to be poor intuitive forecasters. This article tests the power of a cognitive-debiasing training module (“CHAMPS KNOW”) to improve probability judgments in a four-year series of geopolitical forecasting tournaments sponsored by the U.S. intelligence community. Although the training lasted less than one hour, it consistently improved accuracy (Brier scores) by 6 to 11% over the control condition. Cognitive ability and practice also made largely independent contributions to predictive accuracy. Given the brevity of the training tutorials and the heterogeneity of the problems posed, the observed effects are likely to be lower-bound estimates of what could be achieved by more intensive interventions. Future work should isolate which prongs of the multipronged CHAMPS KNOW training were most effective in improving judgment on which categories of problems.
We report on findings from a qualitative study of Australian scientists whose work brings them into contact with the public. This research sought to understand how a school science curriculum could better represent the work of scientists today. We discuss the views expressed by our participant scientists about the importance of openness and open-mindedness in their work, including their engagement with the public. They described openness as an important characteristic of science. Our participants also see open-mindedness on the part of both scientists and members of the public as important for productive relationships. They see the development of such relationships as an essential facet of their work. The views expressed by these scientists provide a provocative insight into the ways in which contemporary scientists see their work and relationships with their communities. Their perspectives have important implications for approaches to teaching science in schools.
Although ethics is an essential component of undergraduate medical education, research suggests that current medical ethics curricula face considerable challenges in improving students' ethical reasoning. This article discusses these challenges and introduces a promising new mode of graduate and professional ethics instruction for overcoming them. We begin by describing common ethics curricula, focusing in particular on established problems with current approaches. Next, we describe a novel method of ethics education and assessment for medical students that we have devised: the Medical Ethics Bowl (MEB). Finally, we suggest the pedagogical advantages of the MEB when compared to other ethics curricula.
From failures of intelligence analysis to misguided beliefs about vaccinations, biased judgment and decision making contributes to problems in policy, business, medicine, law, education, and private life. Early attempts to reduce decision biases with training met with little success, leading scientists and policy makers to focus on debiasing by using incentives and changes in the presentation and elicitation of decisions. We report the results of two longitudinal experiments that found medium to large effects of one-shot debiasing training interventions. Participants received a single training intervention, played a computer game or watched an instructional video, which addressed biases critical to intelligence analysis (in Experiment 1: bias blind spot, confirmation bias, and fundamental attribution error; in Experiment 2: anchoring, representativeness, and social projection). Both kinds of interventions produced medium to large debiasing effects immediately (games ≥ −31.94% and videos ≥ −18.60%) that persisted at least 2 months later (games ≥ −23.57% and videos ≥ −19.20%). Games that provided personalized feedback and practice produced larger effects than did videos. Debiasing effects were domain general: bias reduction occurred across problems in different contexts, and problem formats that were taught and not taught in the interventions. The results suggest that a single training intervention can improve decision making. We suggest its use alongside improved incentives, information presentation, and nudges to reduce costly errors associated with biased judgments and
decisions.
Averaging estimates is an effective way to improve accuracy when combining expert judgments, integrating group members' judgments, or using advice to modify personal judgments. If the estimates of two judges ever fall on different sides of the truth, which we term bracketing, averaging must outperform the average judge for convex loss functions, such as mean absolute deviation (MAD). We hypothesized that people often hold incorrect beliefs about averaging, falsely concluding that the average of two judges' estimates would be no more accurate than the average judge. The experiments confirmed that this misconception was common across a range of tasks that involved reasoning from summary data (Experiment 1), from specific instances (Experiment 2), and conceptually (Experiment 3). However, this misconception decreased as observed or assumed bracketing rate increased (all three studies) and when bracketing was made more transparent (Experiment 2). Experiment 4 showed that flawed inferential rules and poor extensional reasoning abilities contributed to the misconception. We conclude by describing how people may face few opportunities to learn the benefits of averaging and how misappreciating averaging contributes to poor intuitive strategies for combining estimates.
Confirmation bias, as the term is typically used in the psychological literature, connotes the seeking or interpreting of evidence in ways that are partial to existing beliefs, expectations, or a hypothesis in hand. The author reviews evidence of such a bias in a variety of guises and gives examples of its operation in several practical contexts. Possible explanations are considered, and the question of its utility or disutility is discussed.
Policymakers have recently embraced Behavioral Economics as an alternative approach which recognizes the limits and consequences of human decision-making. Early applications of BE (“nudges”) produced notable successes and helped to set the stage for more aggressive applications aimed at the deeper causes of policy problems. We contend that policies that aspire to simplify products and incentives, rather than choice environments, aggressively protect consumers from behavioral exploitation, and leverage BE to enhance the design and implementation of traditional policy instruments offer solutions commensurate with contemporary challenges. Case studies in health insurance, privacy, and climate change illustrate the application of these ideas.
People exhibit a bias blind spot: they are less likely to detect bias in themselves than in others. We report the development and validation of an instrument to measure individual differences in the propensity to exhibit the bias blind spot that is unidimensional, internally consistent, has high test-retest reliability, and is discriminated from measures of intelligence, decision-making ability, and personality traits related to self-esteem, self-enhancement, and self-presentation. The scale is predictive of the extent to which people judge their abilities to be better than average for easy tasks and worse than average for difficult tasks, ignore the advice of others, and are responsive to an intervention designed to mitigate a different judgmental bias. These results suggest that the bias blind spot is a distinct metabias resulting from naïve realism rather than other forms of egocentric cognition, and has unique effects on judgment and behavior.
This paper was accepted by Yuval Rottenstreich, judgment and decision making.
This article extends psychological methods and concepts into a domain that is as profoundly consequential
as it is poorly understood: intelligence analysis. We report findings from a geopolitical forecasting
tournament that assessed the accuracy of more than 150,000 forecasts of 743 participants on 199 events
occurring over 2 years. Participants were above average in intelligence and political knowledge relative
to the general population. Individual differences in performance emerged, and forecasting skills were
surprisingly consistent over time. Key predictors were (a) dispositional variables of cognitive ability,
political knowledge, and open-mindedness; (b) situational variables of training in probabilistic reasoning
and participation in collaborative teams that shared information and discussed rationales (Mellers, Ungar,
et al., 2014); and (c) behavioral variables of deliberation time and frequency of belief updating. We
developed a profile of the best forecasters; they were better at inductive reasoning, pattern detection,
cognitive flexibility, and open-mindedness. They had greater understanding of geopolitics, training in
probabilistic reasoning, and opportunities to succeed in cognitively enriched team environments. Last but
not least, they viewed forecasting as a skill that required deliberate practice, sustained effort, and constant
monitoring of current affairs.
The Cognitive Reflection Test (CRT) is thought to correlate with measures of utilitarian moral judgment because it measures system-2 correction of an initial intuitive response. And some theories of moral judgment hold that the same thing often happens when people arrive a utilitarian judgments. We find, however, that CRT-type items (using logic as well as arithmetic) can work just as well when they do not have obvious intuitive answers at predicting utilitarian moral judgment, assessed with self-report questionnaires as well as with hypothetical scenarios, and also at predicting a measure of actively open-minded thinking (AOT). Moreover, long response times, as well as high accuracy, also predict moral judgment and other outcomes. The CRT might thus be considered a test of reflection-impulsivity (RI). However, RI is only part of AOT, because RI is concerned only with the amount of thinking, not its direction. Tests of AOT also predict utilitarian moral judgments. Individual differences in AOT and moral judgments are both strongly (negatively) associated with belief that morality comes from God and cannot be understood through thought. The correlation of CRT and utilitarian judgment, when found, is thus likely due to the (imperfect) correlation of AOT and CRT. Intuition in these domains is thus not necessarily something that people overcome through additional thinking, but rather what they rely on when they do not think very much.
There is growing concern amongst policy makers, managers and academic researchers over the role that social media plays in spreading misinformation, widely described as ‘Fake News’. However, research to date has mainly focussed on the implications of fake news for political communication and debate. There has been less focus on the implications of social media misinformation upon marketing and consumers. Given the key role of social media as a communication platform, there is a gap in our understanding of fake news through a consumer lens. We address this gap by conducting an interdisciplinary systematic review of the relevant literature. Through critical evaluation and synthesis of the literature, we identify five themes that explain the fake news phenomenon: the dissemination process, spreading channel features, outcomes, fabricated legitimacy and attitudes. Finally, we propose a theoretical framework that highlights themes’ relationships and research propositions to guide future research in this area.
What is intelligence? Can it be increased by teaching? If so, how, and what difference would an increase make? Before we can answer these questions, we need to clarify them. Jonathan Baron argues that when we do so we find that intelligence has much to do with rational thinking, and that the skills involved in rational thinking are in fact teachable, at least to some extent. Rationality and Intelligence develops and justifies a prescriptive theory of rational thinking in terms of utility theory and the theory of rational life plans. The prescriptive theory, buttressed by other assumptions, suggests that people generally think too little and in a way that is insufficiently critical of the initial possibilities that occur to them. However these biases can be - and sometimes are - corrected by education.
The Adaptive Decision Maker argues that people use a variety of strategies to make judgments and choices. The authors introduce a model that shows how decision makers balance effort and accuracy considerations and predicts which strategy a person will use in a given situation. A series of experiments testing the model are presented, and the authors analyse how the model can lead to improved decisions and opportunities for further research.
Research on moral judgment has been dominated by rationalist models, in which moral judgment is thought to be caused by moral reasoning. The author gives 4 reasons for considering the hypothesis that moral reasoning does not cause moral judgment; rather, moral reasoning is usually a post hoc construction, generated after a judgment has been reached. The social intuitionist model is presented as an alternative to rationalist models. The model is a social model in that it deemphasizes the private reasoning done by individuals and emphasizes instead the importance of social and cultural influences. The model is an intuitionist model in that it states that moral judgment is generally the result of quick, automatic evaluations (intuitions). The model is more consistent than rationalist models with recent findings in social, cultural, evolutionary, and biological psychology, as well as in anthropology and primatology.
Ethics bowl is an academic competition combining a valuable and distinctive educational experience with the excitement and fun of a competitive game. Section “Format, Procedures, and Rules of the APPE-IEB” describes the format, procedures, and rules of the Association for Practical and Professional Ethics Intercollegiate Ethics Bowl (APPE-IEB). Section “Brief History of the APPE-IEB (Association for Practical and Professional Ethics Intercollegiate Ethics Bowl)” summarizes the APPE-IEB’s origin and development. Section “Basic Educational Objectives and of the APPE-IEB” identifies and analyzes the APPE-IEB’s basic educational objectives, making apparent the close coincidence of these objectives with those of ethics across the curriculum. Finally, Sect. “Is the APPE-IEB Too Competitive?” discusses the apparent tension between the APPE-IEB’s basic educational objectives and its utilization of the desire for competitive success as a motivator.
Following the 2016 US presidential election, many have expressed concern about the effects of false stories ("fake news"), circulated largely through social media. We discuss the economics of fake news and present new data on its consumption prior to the election. Drawing on web browsing data, archives of fact-checking websites, and results from a new online survey, we find: 1) social media was an important but not dominant source of election news, with 14 percent of Americans calling social media their "most important" source; 2) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared 8 million times; 3) the average American adult saw on the order of one or perhaps several fake news stories in the months around the election, with just over half of those who recalled seeing them believing them; and 4) people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks.
This dissertation investigates people’s ability to search for and use alternative reasons while making probabilistic judgments, with the goals of devising and testing (1) a new actively open-minded thinking (AOT) measure that assesses thinking behavior by looking at people’s ability to generate alternative reasons/contradicting evidence, and (2) a short online module to train people in actively open-minded thinking. In Chapter 1 we assessed individual differences in actively open-minded thinking on probabilistic judgment tasks by using both belief and behavioral measures. In the first three studies subjects made probabilistic judgments in three-choice almanac questions, while in the fourth study subjects made point and confidence interval estimates for numerical almanac questions. Compared to the low scoring subjects, subjects who score high on the new behavioral AOT measure were more likely to have more accurate probability judgments when they did not know the correct answer to the question. Higher scores on the behavioral actively open-minded thinking measure were also associated with lower overconfidence. In Chapter 2 we tested the effectiveness of making subjects consider alternative reasons and a one-hour long online training module in AOT. Studies 4 and 5 tested whether making subjects consider alternative reasons would improve their accuracy and decrease their overconfidence. In Study 4 we observed that this intervention was successful in increasing the number of alternative reasons and subjects’ accuracy when subjects did not know the correct answer. There was also a slight decrease in overconfidence as a result of this intervention. Study 5, which used point estimate questions, did not show any benefits of the intervention in accuracy or overconfidence. Studies 6 and 7 tested the effectiveness of new online AOT training modules we designed for adults. The training module in Study 6 did not show any improvement in subjects’ accuracy, but the training condition in Study 7 increased subjects’ accuracy scores when subjects did not know the correct answer. We observed some effect of the training on subjects’ overconfidence such that going through the training decreased subjects’ unwarranted confidence. Chapter 3 discusses the relation between the behavioral and belief measures of AOT, their effects on accuracy and overconfidence. We specifically argue that while the belief measure of AOT assesses general AOT tendencies, the behavioral measure of AOT assesses task specific AOT behavior. The results show that considering alternative reasons increases subjects’ accuracy by lowering their overconfidence. We finally discuss our results from training adult population in AOT and suggest potential testing scenarios for our training module.
Argumentation, a key epistemic practice in science, engages students in socially constructing knowledge claims using evidence. However, teachers need support in integrating argumentation into classroom instruction. We examined teachers’ enactments of an educative science curriculum and their curricular decision making for argumentation. Ten middle school teachers enacted lessons that focused on both the structure of an argument and argumentation as a dialogic process. For each teacher, we analyzed videotapes of two lessons and follow-up interviews. Across the teachers, we observed a wide range in teachers’ enactments. In some instances, teachers’ instructional practices aligned with the underlying epistemic goals, while in other cases the structural aspects were oversimplified and discourse norms followed more traditional teacher-led patterns. To support classroom instruction to move beyond pseudoargumentation, we found three main influences on teachers’ curricular decision making in classes with higher quality argumentation: (1) teachers’ understanding of argumentation as an epistemic practice (rather than surface level features), (2) teachers as critically reflective curriculum users, and (3) teachers problematizing their prior teaching experiences. As a field, we need to think critically about how to design teacher education experiences to discourage the relabeling of teaching with reform-oriented terms, such as argumentation, and instead support instructional transformation.
Political debates often suffer from vague-verbiage predictions that make it difficult to assess accuracy and improve policy. A tournament sponsored by the U.S. intelligence community revealed ways in which forecasters can better use probability estimates to make predictions—even for seemingly “unique” events—and showed that tournaments are a useful tool for generating knowledge. Drawing on the literature about the effects of accountability, the authors suggest that tournaments may hold even greater potential as tools for depolarizing political debates and resolving policy disputes.
This research note presents evidence that political polarization over the reality of human-caused climate change increases in tandem with individuals’ scores on a standard measure of actively open-minded thinking. This finding is at odds with the position that attributes political conflict over facts to a personality trait of closed-mindedness associated with political conservatism.
In this article, we report on a serious game development approach, characterized by combining theory-based design with an iterative development strategy guided by experimental test and evaluation. We describe two serious games that teach the mitigation of cognitive biases (human tendencies to commit systematic errors in thinking that lead to irrational judgments). Cognitive biases tend to be deeply ingrained and early attempts to reduce biases with training have met with little success. We address this training challenge using bias mitigation theory derived from the literature and an instructional framework to establish the educational content of each game. The mitigation effects of the games were measured through multiple experiment cycles, and multiple play-testing campaigns were conducted to inform instructional model and game design revisions. The final game versions achieved a medium-to-large training effect following a single play session.
This paper describes the ‘ordinary science intelligence’ scale (OSI_2.0). Designed for use in the empirical study of risk perception and science communication, OSI_2.0 comprises items intended to measure a latent capacity to recognize and make use of valid scientific evidence in everyday decision-making. The derivation of the items, the relationship of them to the knowledge and skills OSI requires, and the psychometric properties of the scale are examined. Evidence of the external validity of OSI_2.0 is also presented. Finally, the utility of OSI_2.0 is briefly illustrated by its use to assess standard survey items on evolution and global warming: when administered to members of a US general population sample, these items are more convincingly viewed as indicators of one or another latent cultural identity than as indicators of science comprehension.
Of this article's seven experiments, the first five demonstrate that virtually no Americans know the basic global warming mechanism. Fortunately, Experiments 2-5 found that 2-45 min of physical-chemical climate instruction durably increased such understandings. This mechanistic learning, or merely receiving seven highly germane statistical facts (Experiment 6), also increased climate-change acceptance-across the liberal-conservative spectrum. However, Experiment 7's misleading statistics decreased such acceptance (and dramatically, knowledge-confidence). These readily available attitudinal and conceptual changes through scientific information disconfirm what we term "stasis theory"-which some researchers and many laypeople varyingly maintain. Stasis theory subsumes the claim that informing people (particularly Americans) about climate science may be largely futile or even counterproductive-a view that appears historically naïve, suffers from range restrictions (e.g., near-zero mechanistic knowledge), and/or misinterprets some polarization and (noncausal) correlational data. Our studies evidenced no polarizations. Finally, we introduce HowGlobalWarmingWorks.org-a website designed to directly enhance public "climate-change cognition."
This book attempts to resolve the Great Rationality Debate in cognitive science-the debate about how much irrationality to ascribe to human cognition. It shows how the insights of dual-process theory and evolutionary psychology can be combined to explain why humans are sometimes irrational even though they possess remarkably adaptive cognitive machinery. The book argues that to characterize fully differences in rational thinking, we need to replace dual-process theories with tripartite models of cognition. Using a unique individual differences approach, it shows that the traditional second system (System 2) of dual-process theory must be further divided into the reflective mind and the algorithmic mind. Distinguishing them gives a better appreciation of the significant differences in their key functions: the key function of the reflective mind is to detect the need to interrupt autonomous processing and to begin simulation activities, whereas that of the algorithmic mind is to sustain the processing of decoupled secondary representations in cognitive simulation. The book then uses this algorithmic/reflective distinction to develop a taxonomy of cognitive errors made on tasks in the heuristics and biases literature. It presents the empirical data to show that the tendency to make these thinking errors is not highly related to intelligence. Using a tripartite model of cognition, the book shows how, when both are properly defined, rationality is a more encompassing construct than intelligence, and that IQ tests fail to assess individual differences in rational thought. It then goes on to discuss the types of thinking processes that would be measured if rational thinking were to be assessed as IQ has been.
The concept of actively open-minded thinking (AOT) provides standards for evaluation of thinking, which apply both to our own thinking and to the thinking of others. AOT is important for good citizenship for three reasons: it provides a prescription for individual thinking about political decisions; it serves as a social norm (when others agree); and, perhaps most importantly, it provides a standard for knowing which sources to trust, including politicians and pundits. I provide a current account of AOT as a general prescriptive theory that defines a standard or norm for all thinking, with emphasis on its role in the judgment of the thinking of others, and in maintaining appropriate confidence. I also contrast AOT with other standards. AOT does not assume that more thinking is always better, and it implies that low confidence in the results of thinking is often warranted and beneficial. I discuss the measurement of AOT and its relation to politics. Finally, I report two preliminary studies of AOT in judgments of others thoughts, and the role of confidence.
This study investigated the asserted differences in reasoning between adults and second, fourth, and sixth graders in a manipulation-of-variables task using common everyday situations. It is proposed that hypothesis-testing skills used in this task do not necessarily develop from an understanding of the logic of classes. These skills may develop through experience in manipulating elements in those naturally occurring situations where it is desirable to eliminate negative outcomes or reproduce positive outcomes. Subjects were given 8 multivariate stories with different outcomes, either good or bad, and asked to choose a test to determine which element caused the outcome. Subjects were expected to choose a test systematically on the basis of sensible considerations of the outcome value of any situation, not on purely logical grounds. For all age groups the general pattern of responses was the same. A logical disconfirming test (vary only the hypothesized variable) was preferred in bad-outcome situations, and a logically inappropriate confirming test (repeat the hypothesized variable in a different context) was preferred in good-outcome stories. The main developmental trend was a shift in choice of strategy to eliminate the hypothesized variable in bad-outcome stories. There was no relation between children's performance on class-inclusion problems and their story-problem solutions. These results are discussed in terms of "sensible" reasoning and problem-solving skills.
This paper introduces the Intercollegiate Ethics Bowl (IEB) as a means of promoting active learning in the realm of marketing ethics. The cases discussed in the competition are based on current ethical issues and require students to provide a coherent analysis of what are generally complex, ambiguous, and highly viewpoint dependent issues. The goal is for students to approach the intellectual controversy in such a manner that they are able to arrive at the best reasoned judgment possible. Using an active learning technique consistent with constructive controversy theory, the generation of deliberate discourse is believed to enhance students' moral development.