is critical thinking a better model of intelligence

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Critical Thinking: A Model of Intelligence for Solving Real-World Problems

Affiliations.

1 Department of Psychology, Claremont McKenna College, Emerita, Altadena, CA 91001, USA.
2 Department of Psychology, Moravian College, Bethlehem, PA 18018, USA.
PMID: 33916939
PMCID: PMC8167750
DOI: 10.3390/jintelligence9020022

Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive biases, partisan thinking, reactance, or confirmation bias, among others. There are several newer theories that directly address the question about solving real-world problems. Prominent among them is Sternberg's adaptive intelligence with "adaptation to the environment" as the central premise, a construct that does not exist on standardized IQ tests. Similarly, some scholars argue that standardized tests of intelligence are not measures of rational thought-the sort of skill/ability that would be needed to address complex real-world problems. Other investigators advocate for critical thinking as a model of intelligence specifically designed for addressing real-world problems. Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem such as COVID-19, which we use as an example of contemporary problems that need a new approach.

Keywords: critical thinking; intelligence; real-world problems.

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Critical Thinking: A Model of Intelligence for Solving Real-world Problems

is critical thinking a better model of intelligence

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Halpern, D.F.; Dunn, D.S. Critical Thinking: A Model of Intelligence for Solving Real-World Problems. J. Intell. 2021 , 9 , 22. Halpern, D.F.; Dunn, D.S. Critical Thinking: A Model of Intelligence for Solving Real-World Problems. J. Intell. 2021, 9, 22. Copy

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Critical thinking, intelligence, and unsubstantiated beliefs: an integrative review.

1. Introduction

2. defining critical thinking and intelligence, 3. does critical thinking “go beyond” what is meant by intelligence, 4. dual-process theory measures and unsubstantiated beliefs, 5. assessing critical thinking and unsubstantiated beliefs, 6. dual-processing theory and research on unsubstantiated beliefs, 7. discussion, 8. conclusions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Bensley, D.A. Critical Thinking, Intelligence, and Unsubstantiated Beliefs: An Integrative Review. J. Intell. 2023 , 11 , 207. https://doi.org/10.3390/jintelligence11110207

Bensley DA. Critical Thinking, Intelligence, and Unsubstantiated Beliefs: An Integrative Review. Journal of Intelligence . 2023; 11(11):207. https://doi.org/10.3390/jintelligence11110207

Bensley, D. Alan. 2023. "Critical Thinking, Intelligence, and Unsubstantiated Beliefs: An Integrative Review" Journal of Intelligence 11, no. 11: 207. https://doi.org/10.3390/jintelligence11110207

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Critical Thinking, Intelligence, and Unsubstantiated Beliefs: An Integrative Review

Associated data.

This research did not involve collection of original data, and hence there are no new data to make available.

A review of the research shows that critical thinking is a more inclusive construct than intelligence, going beyond what general cognitive ability can account for. For instance, critical thinking can more completely account for many everyday outcomes, such as how thinkers reject false conspiracy theories, paranormal and pseudoscientific claims, psychological misconceptions, and other unsubstantiated claims. Deficiencies in the components of critical thinking (in specific reasoning skills, dispositions, and relevant knowledge) contribute to unsubstantiated belief endorsement in ways that go beyond what standardized intelligence tests test. Specifically, people who endorse unsubstantiated claims less tend to show better critical thinking skills, possess more relevant knowledge, and are more disposed to think critically. They tend to be more scientifically skeptical and possess a more rational–analytic cognitive style, while those who accept unsubstantiated claims more tend to be more cynical and adopt a more intuitive–experiential cognitive style. These findings suggest that for a fuller understanding of unsubstantiated beliefs, researchers and instructors should also assess specific reasoning skills, relevant knowledge, and dispositions which go beyond what intelligence tests test.

1. Introduction

Why do some people believe implausible claims, such as the QAnon conspiracy theory, that a cabal of liberals is kidnapping and trafficking many thousands of children each year, despite the lack of any credible supporting evidence? Are believers less intelligent than non-believers? Do they lack knowledge of such matters? Are they more gullible or less skeptical than non-believers? Or, more generally, are they failing to think critically?

Understanding the factors contributing to acceptance of unsubstantiated claims is important, not only to the development of theories of intelligence and critical thinking but also because many unsubstantiated beliefs are false, and some are even dangerous. Endorsing them can have a negative impact on an individual and society at large. For example, false beliefs about the COVID-19 pandemic, such as believing that 5G cell towers induced the spread of the COVID-19 virus, led some British citizens to set fire to 5G towers ( Jolley and Paterson 2020 ). Other believers in COVID-19 conspiracy theories endangered their own and their children’s lives when they refused to socially distance and be vaccinated with highly effective vaccines, despite the admonitions of scientific experts ( Bierwiaczonek et al. 2020 ). Further endangering the population at large, those who believe the false conspiracy theory that human-caused global warming is a hoax likely fail to respond adaptively to this serious global threat ( van der Linden 2015 ). Parents, who uncritically accept pseudoscientific claims, such as the false belief that facilitated communication is an effective treatment for childhood autism, may forego more effective treatments ( Lilienfeld 2007 ). Moreover, people in various parts of the world still persecute other people whom they believe are witches possessing supernatural powers. Likewise, many people still believe in demonic possession, which has been associated with mental disorders ( Nie and Olson 2016 ). Compounding the problems created by these various unsubstantiated beliefs, numerous studies now show that when someone accepts one of these types of unfounded claims, they tend to accept others as well; see Bensley et al. ( 2022 ) for a review.

Studying the factors that contribute to unfounded beliefs is important not only because of their real-world consequences but also because this can facilitate a better understanding of unfounded beliefs and how they are related to critical thinking and intelligence. This article focuses on important ways in which critical thinking and intelligence differ, especially in terms of how a comprehensive model of CT differs from the view of intelligence as general cognitive ability. I argue that this model of CT more fully accounts for how people can accurately decide if a claim is unsubstantiated than can views of intelligence, emphasizing general cognitive ability. In addition to general cognitive ability, thinking critically about unsubstantiated claims involves deployment of specific reasoning skills, dispositions related to CT, and specific knowledge, which go beyond the contribution of general cognitive ability.

Accordingly, this article begins with an examination of the constructs of critical thinking and intelligence. Then, it discusses theories proposing that to understand thinking in the real world requires going beyond general cognitive ability. Specifically, the focus is on factors related to critical thinking, such as specific reasoning skills, dispositions, metacognition, and relevant knowledge. I review research showing that that this alternative multidimensional view of CT can better account for individual differences in the tendency to endorse multiple types of unsubstantiated claims than can general cognitive ability alone.

2. Defining Critical Thinking and Intelligence

Critical thinking is an almost universally valued educational objective in the US and in many other countries which seek to improve it. In contrast, intelligence, although much valued, has often been viewed as a more stable characteristic and less amenable to improvement through specific short-term interventions, such as traditional instruction or more recently through practice on computer-implemented training programs. According to Wechsler’s influential definition, intelligence is a person’s “aggregate or global capacity to act purposefully, to think rationally, and to deal effectively with his environment” ( Wechsler 1944, p. 3 ).

Consistent with this definition, intelligence has long been associated with general cognitive or intellectual ability and the potential to learn and reason well. Intelligence (IQ) tests measure general cognitive abilities, such as knowledge of words, memory skills, analogical reasoning, speed of processing, and the ability to solve verbal and spatial problems. General intelligence or “g” is a composite of these abilities statistically derived from various cognitive subtests on IQ tests which are positively intercorrelated. There is considerable overlap between g and the concept of fluid intelligence (Gf) in the prominent Cattell–Horn–Carroll model ( McGrew 2009 ), which refers to “the ability to solve novel problems, the solution of which does not depend on previously acquired skills and knowledge,” and crystalized intelligence (Gc), which refers to experience, existing skills, and general knowledge ( Conway and Kovacs 2018, pp. 50–51 ). Although g or general intelligence is based on a higher order factor, inclusive of fluid and crystallized intelligence, it is technically not the same as general cognitive ability, a commonly used, related term. However, in this article, I use “general cognitive ability” and “cognitive ability” because they are the imprecise terms frequently used in the research reviewed.

Although IQ scores have been found to predict performance in basic real-world domains, such as academic performance and job success ( Gottfredson 2004 ), an enduring question for intelligence researchers has been whether g and intelligence tests predict the ability to adapt well in other real-world situations, which concerns the second part of Wechsler’s definition. So, in addition to the search for the underlying structure of intelligence, researchers have been perennially concerned with how general abilities associated with intelligence can be applied to help a person adapt to real-world situations. The issue is largely a question of how cognitive ability and intelligence can help people solve real-world problems and cope adaptively and succeed in dealing with various environmental demands ( Sternberg 2019 ).

Based on broad conceptual definitions of intelligence and critical thinking, both intelligence and CT should aid adaptive functioning in the real world, presumably because they both involve rational approaches. Their common association with rationality gives each term a positive connotation. However, complicating the definition of each of these is the fact that rationality also continues to have a variety of meanings. In this article, in agreement with Stanovich et al. ( 2018 ), rationality is defined in the normative sense, used in cognitive science, as the distance between a person’s response and some normative standard of optimal behavior. As such, degree of rationality falls on a continuous scale, not a categorical one.

Despite disagreements surrounding the conceptual definitions of intelligence, critical thinking, and rationality, a commonality in these terms is they are value-laden and normative. In the case of intelligence, people are judged based on norms from standardized intelligence tests, especially in academic settings. Although scores on CT tests seldom are, nor could be, used to judge individuals in this way, the normative and value-laden basis of CT is apparent in people’s informal judgements. They often judge others who have made poor decisions to be irrational or to have failed to think critically.

This value-laden aspect of CT is also apparent in formal definitions of CT. Halpern and Dunn ( 2021 ) defined critical thinking as “the use of those cognitive skills or strategies that increase the probability of a desirable outcome. It is used to describe thinking that is purposeful, reasoned, and goal-directed.” The positive conception of CT as helping a person adapt well to one’s environment is clearly implied in “desirable outcome”.

Robert Ennis ( 1987 ) has offered a simpler, yet useful definition of critical thinking that also has normative implications. According to Ennis, “critical thinking is reasonable, reflective thinking focused on deciding what to believe or do” ( Ennis 1987, p. 102 ). This definition implies that CT helps people know what to believe (a goal of epistemic rationality) and how to act (a goal of instrumental rationality). This is conveyed by associating “critical thinking” with the positive terms, “reasonable” and “reflective”. Dictionaries commonly define “reasonable” as “rational”, “logical”, “intelligent”, and “good”, all terms with positive connotations.

For critical thinkers, being reasonable involves using logical rules, standards of evidence, and other criteria that must be met for a product of thinking to be considered good. Critical thinkers use these to evaluate how strongly reasons or evidence supports one claim versus another, drawing conclusions which are supported by the highest quality evidence ( Bensley 2018 ). If no high-quality evidence is available for consideration, it would be unreasonable to draw a strong conclusion. Unfortunately, people’s beliefs are too often based on acceptance of unsubstantiated claims. This is a failure of CT, but is it also a failure of intelligence?

3. Does Critical Thinking “Go Beyond” What Is Meant by Intelligence?

Despite the conceptual overlap in intelligence and CT at a general level, one way that CT can be distinguished from the common view of intelligence as general cognitive ability is in terms of what each can account for. Although intelligence tests, especially measures of general cognitive ability, have reliably predicted academic and job performance, they may not be sufficient to predict other everyday outcomes for which CT measures have made successful predictions and have added to the variance accounted for in performance. For instance, replicating a study by Butler ( 2012 ), Butler et al. ( 2017 ) obtained a negative correlation ( r = −0.33) between scores on the Halpern Critical Thinking Appraisal (HCTA) and a measure of 134 negative, real-world outcomes, not expected to befall critical thinkers, such as engaging in unprotected sex or posting a message on social media which the person regretted. They found that higher HCTA scores not only predicted better life decisions, but also predicted better performance beyond a measure of general cognitive ability. These results suggest that CT can account for real-world outcomes and goes beyond general cognitive ability to account for additional variance.

Some theorists maintain that standardized intelligence tests do not capture the variety of abilities that people need to adapt well in the real world. For example, Gardner ( 1999 ), has proposed that additional forms of intelligence are needed, such as spatial, musical, and interpersonal intelligences in addition to linguistic and logical–mathematical intelligences, more typically associated with general cognitive ability and academic success. In other theorizing, Sternberg ( 1988 ) has proposed three additional types of intelligence: analytical, practical, and creative intelligence, to more fully capture the variety of intelligent abilities on which people differ. Critical thinking is considered part of analytical skills which involve evaluating the quality and applicability of ideas, products, and options ( Sternberg 2022 ). Regarding adaptive intelligence, Sternberg ( 2019 ) has emphasized how adaptive aspects of intelligence are needed to solve real-world problems both at the individual and species levels. According to Sternberg, core components of intelligence have evolved in humans, but intelligence takes different forms in different cultures, with each culture valuing its own skills for adaptation. Thus, the construct of intelligence must go beyond core cognitive ability to encompass the specific abilities needed for adaptive behavior in specific cultures and settings.

Two other theories propose that other components be added to intelligent and rational thinking. Ackerman ( 2022 ) has emphasized the importance of acquiring domain-specific knowledge for engaging in intelligent functioning in the wide variety of tasks found in everyday life. Ackerman has argued that declarative, procedural, and tacit knowledge, as well as non-ability variables, are needed to better predict job performance and performance of other everyday activities. Taking another approach, Halpern and Dunn ( 2021 ) have proposed that critical thinking is essentially the adaptive application of intelligence for solving real-world problems. Elsewhere, Butler and Halpern ( 2019 ) have argued that dispositions such as open-mindedness are another aspect of CT and that domain-specific knowledge and specific CT skills are needed to solve real-world problems.

Examples are readily available for how CT goes beyond what IQ tests test to include specific rules for reasoning and relevant knowledge needed to execute real-world tasks. Take the example of scientific reasoning, which can be viewed as a specialized form of CT. Drawing a well-reasoned inductive conclusion about a theory or analyzing the quality of a research study both require that a thinker possess relevant specialized knowledge related to the question and specific reasoning skills for reasoning about scientific methodology. In contrast, IQ tests are deliberately designed to be nonspecialized in assessing Gc, broadly sampling vocabulary and general knowledge in order to be fair and unbiased ( Stanovich 2009 ). Specialized knowledge and reasoning skills are also needed in non-academic domains. Jurors must possess specialized knowledge to understand expert, forensic testimony and specific reasoning skills to interpret the law and make well-reasoned judgments about a defendant’s guilt or innocence.

Besides lacking specific reasoning skills and domain-relevant knowledge, people may fail to think critically because they are not disposed to use their reasoning skills to examine such claims and want to preserve their favored beliefs. Critical thinking dispositions are attitudes or traits that make it more likely that a person will think critically. Theorists have proposed numerous CT dispositions (e.g., Bensley 2018 ; Butler and Halpern 2019 ; Dwyer 2017 ; Ennis 1987 ). Some commonly identified CT dispositions especially relevant to this discussion are open-mindedness, skepticism, intellectual engagement, and the tendency to take a reflective, rational–analytic approach. Critical thinking dispositions are clearly value-laden and prescriptive. A good thinker should be open-minded, skeptical, reflective, intellectually engaged, and value a rational–analytic approach to inquiry. Conversely, corresponding negative dispositions, such as “close-mindedness” and “gullibility”, could obstruct CT.

Without the appropriate disposition, individuals will not use their reasoning skills to think critically about questions. For example, the brilliant mystery writer, Sir Arthur Conan Doyle, who was trained as a physician and created the hyper-reasonable detective Sherlock Holmes, was not disposed to think critically about some unsubstantiated claims. Conan Doyle was no doubt highly intelligent in cognitive ability terms, but he was not sufficiently skeptical (disposed to think critically) about spiritualism. He believed that he was talking to his dearly departed son though a medium, despite the warnings of his magician friend, Harry Houdini, who told him that mediums used trickery in their seances. Perhaps influenced by his Irish father’s belief in the “wee folk”, Conan Doyle also believed that fairies inhabited the English countryside, based on children’s photos, despite the advice of experts who said the photos could be faked. Nevertheless, he was skeptical of a new theory of tuberculosis proposed by Koch when he reported on it, despite his wife suffering from the disease. So, in professional capacities, Conan Doyle used his CT skills, but in certain other domains for which he was motivated to accept unsubstantiated claims, he failed to think critically, insufficiently disposed to skeptically challenge certain implausible claims.

This example makes two important points. Conan Doyle’s superior intelligence was not enough for him to reject implausible claims about the world. In general, motivated reasoning can lead people, even those considered highly intelligent, to accept claims with no good evidentiary support. The second important point is that we would not be able to adequately explain cases like this one, considering only the person’s intelligence or even their reasoning skills, without also considering the person’s disposition. General cognitive ability alone is not sufficient, and CT dispositions should also be considered.

Supporting this conclusion, Stanovich and West ( 1997 ) examined the influence of dispositions beyond the contribution of cognitive ability on a CT task. They gave college students an argument evaluation test in which participants first rated their agreement with several claims about real social and political issues made by a fictitious person. Then, they gave them evidence against each claim and finally asked them to rate the quality of a counterargument made by the same fictitious person. Participants’ ratings of the counterarguments were compared to the median ratings of expert judges on the quality of the rebuttals. Stanovich and West also administered a new measure of rational disposition called the Actively Open-minded Thinking (AOT) scale and the SAT as a proxy for cognitive ability. The AOT was a composite of items from several other scales that would be expected to measure CT disposition. They found that both SAT and AOT scores were significant predictors of higher argument analysis scores. Even after partialing out cognitive ability, actively open-minded thinking was significant. These results suggest that general cognitive ability alone was not sufficient to account for thinking critically about real-world issues and that CT disposition was needed to go beyond it.

Further examining the roles of CT dispositions and cognitive ability on reasoning, Stanovich and West ( 2008 ) studied myside bias, a bias in reasoning closely related to one-sided thinking and confirmation bias. A critical thinker would be expected to not show myside bias and instead fairly evaluate evidence on all sides of a question. Stanovich and West ( 2007 ) found that college students often showed myside bias when asked their opinions about real-world policy issues, such as those concerning the health risks of smoking and drinking alcohol. For example, compared to non-smokers, smokers judged the health risks of smoking to be lower. When they divided participants into higher versus lower cognitive ability groups based on SAT scores, the two groups showed little difference on myside bias. Moreover, on the hazards of drinking issue, participants who drank less had higher scores on the CT disposition measure.

Other research supports the need for both reasoning ability and CT disposition in predicting outcomes in the real world. Ren et al. ( 2020 ) found that CT disposition, as measured by a Chinese critical thinking disposition inventory, and a CT skill measure together contributed a significant amount of the variance in predicting academic performance beyond the contribution of cognitive ability alone, as measured by a test of fluid intelligence. Further supporting the claim that CT requires both cognitive ability and CT disposition, Ku and Ho ( 2010 ) found that a CT disposition measure significantly predicted scores on a CT test beyond the significant contribution of verbal intelligence in high school and college students from Hong Kong.

The contribution of dispositions to thinking is related to another way that CT goes beyond the application of general cognitive ability, i.e., by way of the motivation for reasoning. Assuming that all reasoning is motivated ( Kunda 1990 ), then CT is motivated, too, which is implicit within the Halpern and Dunn ( 2021 ) and Ennis ( 1987 ) definitions. Critical thinking is motivated in the sense of being purposeful and directed towards the goal of arriving at an accurate conclusion. For instance, corresponding to pursuit of the goal of accurate reasoning, the CT disposition of “truth-seeking” guides a person towards reaching the CT goal of arriving at an accurate conclusion.

Also, according to Kunda ( 1990 ), a second type of motivated reasoning can lead to faulty conclusions, often by directing a person towards the goal of maintaining favored beliefs and preconceptions, as in illusory correlation, belief perseverance, and confirmation bias. Corresponding to this second type, negative dispositions, such as close-mindedness and self-serving motives, can incline thinkers towards faulty conclusions. This is especially relevant in the present discussion because poorer reasoning, thinking errors, and the inappropriate use of heuristics are related to the endorsement of unsubstantiated claims, all of which are CT failures. The term “thinking errors” is a generic term referring to logical fallacies, informal reasoning fallacies, argumentation errors, and inappropriate uses of cognitive heuristics ( Bensley 2018 ). Heuristics are cognitive shortcuts, commonly used to simplify judgment tasks and reduce mental effort. Yet, when used inappropriately, heuristics often result in biased judgments.

Stanovich ( 2009 ) has argued that IQ tests do not test people’s use of heuristics, but heuristics have been found to be negatively correlated with CT performance ( West et al. 2008 ). In this same study, they found that college students’ cognitive ability, as measured by performance on the SAT, was not correlated with thinking biases associated with use of heuristics. Although Stanovich and West ( 2008 ) found that susceptibility to biases, such as the conjunction fallacy, framing effect, base-rate neglect, affect bias, and myside bias were all uncorrelated with cognitive ability (using SAT as a proxy), other types of thinking errors were correlated with SAT.

Likewise, two types of knowledge are related to the two forms of motivated reasoning. For instance, inaccurate knowledge, such as misconceptions, can derail reasoning from moving towards a correct conclusion, as in when a person reasons from false premises. In contrast, reasoning from accurate knowledge is more likely to produce an accurate conclusion. Taking into account inaccurate knowledge and thinking errors is important to understanding the endorsement of unsubstantiated claims because these are also related to negative dispositions, such as close-mindedness and cynicism, none of which are measured by intelligence tests.

Critical thinking questions are often situated in real-world examples or in simulations of them which are designed to detect thinking errors and bias. As described in Halpern and Butler ( 2018 ), an item like one on the “Halpern Critical Thinking Assessment” (HCTA) provides respondents with a mock newspaper story about research showing that first-graders who attended preschool were better able to learn how to read. Then the question asks if preschool should be made mandatory. A correct response to this item requires recognizing that correlation does not imply causation, that is, avoiding a common reasoning error people make in thinking about research implications in everyday life. Another CT skills test, “Analyzing Psychological Statements” (APS) assesses the ability to recognize thinking errors and apply argumentation skills and psychology to evaluate psychology-related examples and simulations of real-life situations ( Bensley 2021 ). For instance, besides identifying thinking errors in brief samples of thinking, questions ask respondents to distinguish arguments from non-arguments, find assumptions in arguments, evaluate kinds of evidence, and draw a conclusion from a brief psychological argument. An important implication of the studies just reviewed is that efforts to understand CT can be further informed by assessing thinking errors and biases, which, as the next discussion shows, are related to individual differences in thinking dispositions and cognitive style.

4. Dual-Process Theory Measures and Unsubstantiated Beliefs

Dual-process theory (DPT) and measures associated with it have been widely used in the study of the endorsement of unsubstantiated beliefs, especially as they relate to cognitive style. According to a cognitive style version of DPT, people have two modes of processing, a fast intuitive–experiential (I-E) style of processing and a slower, reflective, rational–analytic (R-A) style of processing. The intuitive cognitive style is associated with reliance on hunches, feelings, personal experience, and cognitive heuristics which simplify processing, while the R-A cognitive style is a reflective, rational–analytic style associated with more elaborate and effortful processing ( Bensley et al. 2022 ; Epstein 2008 ). As such, the rational–analytic cognitive style is consistent with CT dispositions, such as those promoting the effortful analysis of evidence, objective truth, and logical consistency. In fact, CT is sometimes referred to as “critical-analytic” thinking ( Byrnes and Dunbar 2014 ) and has been associated with analytical intelligence Sternberg ( 1988 ) and with rational thinking, as discussed before.

People use both modes of processing, but they show individual differences in which mode they tend to rely upon, although the intuitive–experiential mode is the default ( Bensley et al. 2022 ; Morgan 2016 ; Pacini and Epstein 1999 ), and they accept unsubstantiated claims differentially based on their predominate cognitive style ( Bensley et al. 2022 ; Epstein 2008 ). Specifically, individuals who rely more on an I-E cognitive style tend to endorse unsubstantiated claims more strongly, while individuals who rely more on a R-A cognitive style tend to endorse those claims less. Note, however, that other theorists view the two processes and cognitive styles somewhat differently, (e.g., Kahneman 2011 ; Stanovich et al. 2018 ).

Researchers have often assessed the contribution of these two cognitive styles to endorsement of unsubstantiated claims, using variants of three measures: the Cognitive Reflection Test (CRT) of Frederick ( 2005 ), the Rational–Experiential Inventory of Epstein and his colleagues ( Pacini and Epstein 1999 ), and the related Need for Cognition scale of Cacioppo and Petty ( 1982 ). The CRT is a performance-based test which asks participants to solve problems that appear to require simple mathematical calculations, but which actually require more reflection. People typically do poorly on the CRT, which is thought to indicate reliance on an intuitive cognitive style, while better performance is thought to indicate reliance on the slower, more deliberate, and reflective cognitive style. The positive correlation of the CRT with numeracy scores suggests it also has a cognitive skill component ( Patel et al. 2019 ). The Rational–Experiential Inventory (REI) of Pacini and Epstein ( 1999 ) contains one scale designed to measure an intuitive–experiential cognitive style and a second scale intended to measure a rational–analytic (R-A) style. The R-A scale was adapted from the Need for Cognition (NFC) scale of Cacioppo and Petty ( 1982 ), another scale associated with rational–analytic thinking and expected to be negatively correlated with unsubstantiated beliefs. The NFC was found to be related to open-mindedness and intellectual engagement, two CT dispositions ( Cacioppo et al. 1996 ).

The cognitive styles associated with DPT also relate to CT dispositions. Thinking critically requires that individuals be disposed to use their reasoning skills to reject unsubstantiated claims ( Bensley 2018 ) and that they be inclined to take a rational–analytic approach rather than relying on their intuitions and feelings. For instance, Bensley et al. ( 2014 ) found that students who endorsed more psychological misconceptions adopted a more intuitive cognitive style, were less disposed to take a rational–scientific approach to psychology, and scored lower on a psychological critical thinking skills test. Further supporting this connection, West et al. ( 2008 ) found that participants who tended to use cognitive heuristics more, thought to be related to intuitive processing and bias, scored lower on a critical thinking measure. As the Bensley et al. ( 2014 ) results suggest, in addition to assessing reasoning skills and dispositions, comprehensive CT assessment research should assess knowledge and unsubstantiated beliefs because these are related to failures of critical thinking.

5. Assessing Critical Thinking and Unsubstantiated Beliefs

Assessing endorsement of unsubstantiated claims provides another way to assess CT outcomes related to everyday thinking, which goes beyond what intelligence tests test ( Bensley and Lilienfeld 2020 ). From the perspective of the multi-dimensional model of CT, endorsement of unsubstantiated claims could result from deficiencies in a person’s CT reasoning skills, a lack of relevant knowledge, and in the engagement of inappropriate dispositions. Suppose an individual endorses an unsubstantiated claim, such as believing the conspiracy theory that human-caused global warming is a hoax. The person may lack the specific reasoning skills needed to critically evaluate the conspiracy. Lantian et al. ( 2020 ) found that scores on a CT skills test were negatively correlated with conspiracy theory beliefs. The person also must possess relevant scientific knowledge, such as knowing the facts that each year humans pump about 40 billion metric tons of carbon dioxide into the atmosphere and that carbon dioxide is a greenhouse gas which traps heat in the atmosphere. Or, the person may not be scientifically skeptical or too cynical or mistrustful of scientists or governmental officials.

Although endorsing unsubstantiated beliefs is clearly a failure of CT, problems arise in deciding which ones are unsubstantiated, especially when considering conspiracy theories. Typically, the claims which critical thinkers should reject as unsubstantiated are those which are not supported by objective evidence. But of the many conspiracies proposed, few are vigorously examined. Moreover, some conspiracy theories which authorities might initially deny turn out to be real, such as the MK-Ultra theory that the CIA was secretly conducting mind-control research on American citizens.

A way out of this quagmire is to define unsubstantiated beliefs on a continuum which depends on the quality of evidence. This has led to the definition of unsubstantiated claims as assertions which have not been supported by high-quality evidence ( Bensley 2023 ). Those which are supported have the kind of evidentiary support that critical thinkers are expected to value in drawing reasonable conclusions. Instead of insisting that a claim must be demonstrably false to be rejected, we adopt a more tentative acceptance or rejection of claims, based on how much good evidence supports them. Many claims are unsubstantiated because they have not yet been carefully examined and so totally lack support or they may be supported only by low quality evidence such as personal experience, anecdotes, or non-scientific authority. Other claims are more clearly unsubstantiated because they contradict the findings of high-quality research. A critical thinker should be highly skeptical of these.

Psychological misconceptions are one type of claim that can be more clearly unsubstantiated. Psychological misconceptions are commonsense psychological claims (folk theories) about the mind, brain, and behavior that are contradicted by the bulk of high-quality scientific research. Author developed the Test of Psychological Knowledge and Misconceptions (TOPKAM), a 40-item, forced-choice measure with each item posing a statement of a psychological misconception and the other response option stating the evidence-based alternative ( Bensley et al. 2014 ). They found that higher scores on the APS, the argument analysis test applying psychological concepts to analyze real-world examples, were associated with more correct answers on the TOPKAM. Other studies have found positive correlations between CT skills tests and other measures of psychological misconceptions ( McCutcheon et al. 1992 ; Kowalski and Taylor 2004 ). Bensley et al. ( 2014 ) also found that higher correct TOPKAM scores were positively correlated with scores on the Inventory of Thinking Dispositions in Psychology (ITDP) of Bensley ( 2021 ), a measure of the disposition to take a rational and scientific approach to psychology but were negatively correlated with an intuitive cognitive style.

Bensley et al. ( 2021 ) conducted a multidimensional study, assessing beginner psychology students starting a CT course on their endorsement of psychological misconceptions, recognition of thinking errors, CT dispositions, and metacognition, before and after CT instruction. Two classes received explicit instruction involving considerable practice in argument analysis and scientific reasoning skills, with one class receiving CT instruction focused more on recognizing psychological misconceptions and a second class focused more on recognizing various thinking errors. Bensley et al. assessed both classes before and after instruction on the TOPKAM and on the Test of Thinking Errors, a test of the ability to recognize in real-world examples 17 different types of thinking errors, such as confirmation bias, inappropriate use of the availability and representativeness heuristics, reasoning from ignorance/possibility, gambler’s fallacy, and hasty generalization ( Bensley et al. 2021 ). Correct TOPKAM and TOTE scores were positively correlated, and after CT instruction both were positively correlated with the APS, the CT test of argument analysis skills.

Bensley et al. found that after explicit instruction of CT skills, students improved significantly on both the TOPKAM and TOTE, but those focusing on recognizing misconceptions improved the most. Also, those students who improved the most on the TOTE scored higher on the REI rational–analytic scale and on the ITDP, while those improving the most on the TOTE scored higher on the ITDP. The students receiving explicit CT skill instruction in recognizing misconceptions also significantly improved the accuracy of their metacognitive monitoring in estimating their TOPKAM scores after instruction.

Given that before instruction neither class differed in GPA nor on the SAT, a proxy for general cognitive ability, CT instruction provided a good accounting for the improvement in recognition of thinking errors and misconceptions without recourse to intelligence. However, SAT scores were positively correlated with both TOTE scores and APS scores, suggesting that cognitive ability contributed to CT skill performance. These results replicated the earlier findings of Bensley and Spero ( 2014 ) showing that explicit CT instruction improved performance on both CT skills tests and metacognitive monitoring accuracy while controlling for SAT, which was positively correlated with the CT skills test performance.

Taken together, these findings suggest that cognitive ability contributes to performance on CT tasks but that CT instruction goes beyond it to further improve performance. As the results of Bensley et al. ( 2021 ) show, and as discussed next, thinking errors and bias from heuristics are CT failures that should also be assessed because they are related to endorsement of unsubstantiated beliefs and cognitive style.

6. Dual-Processing Theory and Research on Unsubstantiated Beliefs

Consistent with DPT, numerous other studies have obtained significant positive correlations between intuitive cognitive style and paranormal belief, often using the REI intuitive–experiential scale and the Revised Paranormal Belief Scale (RPBS) of Tobacyk ( 2004 ) (e.g., Genovese 2005 ; Irwin and Young 2002 ; Lindeman and Aarnio 2006 ; Pennycook et al. 2015 ; Rogers et al. 2018 ; Saher and Lindeman 2005 ). Studies have also found positive correlations between superstitious belief and intuitive cognitive style (e.g., Lindeman and Aarnio 2006 ; Maqsood et al. 2018 ). REI intuitive–experiential thinking style was also positively correlated with belief in complementary and alternative medicine ( Lindeman 2011 ), conspiracy theory belief ( Alper et al. 2020 ), and with endorsement of psychological misconceptions ( Bensley et al. 2014 ; Bensley et al. 2022 ).

Additional evidence for DPT has been found when REI R-A and NFC scores were negatively correlated with scores on measures of unsubstantiated beliefs, but studies correlating them with measures of paranormal belief and conspiracy theory belief have shown mixed results. Supporting a relationship, REI rational–analytic and NFC scores significantly and negatively predicted paranormal belief ( Lobato et al. 2014 ; Pennycook et al. 2012 ). Other studies have also obtained a negative correlation between NFC and paranormal belief ( Lindeman and Aarnio 2006 ; Rogers et al. 2018 ; Stahl and van Prooijen 2018 ), but both Genovese ( 2005 ) and Pennycook et al. ( 2015 ) found that NFC was not significantly correlated with paranormal belief. Swami et al. ( 2014 ) found that although REI R-A scores were negatively correlated with conspiracy theory belief, NFC scores were not.

Researchers often refer to people who are doubtful of paranormal and other unfounded claims as “skeptics” and so have tested whether measures related to skepticism are associated with less endorsement of unsubstantiated claims. They typically view skepticism as a stance towards unsubstantiated claims taken by rational people who reject them, (e.g., Lindeman and Aarnio 2006 ; Stahl and van Prooijen 2018 ), rather than as a disposition inclining a person to think critically about unsubstantiated beliefs ( Bensley 2018 ).

Fasce and Pico ( 2019 ) conducted one of the few studies using a measure related to skeptical disposition, the Critical Thinking Disposition Scale (CTDS) of Sosu ( 2013 ), in relation to endorsement of unsubstantiated claims. They found that scores on the CTDS were negatively correlated with scores on the RPBS but not significantly correlated with either a measure of pseudoscience or of conspiracy theory belief. However, the CRT was negatively correlated with both RPBS and the pseudoscience measure. Because Fasce and Pico ( 2019 ) did not examine correlations with the Reflective Skepticism subscale of the CTDS, its contribution apart from full-scale CTDS was not found.

To more directly test skepticism as a disposition, we recently assessed college students on how well three new measures predicted endorsement of psychological misconceptions, paranormal claims, and conspiracy theories ( Bensley et al. 2022 ). The dispositional measures included a measure of general skeptical attitude; a second measure, the Scientific Skepticism Scale (SSS), which focused more on waiting to accept claims until high-quality scientific evidence supported them; and a third measure, the Cynicism Scale (CS), which focused on doubting the sincerity of the motives of scientists and people in general. We found that although the general skepticism scale did not predict any of the unsubstantiated belief measures, SSS scores were a significant negative predictor of both paranormal belief and conspiracy theory belief. REI R-A scores were a less consistent negative predictor, while REI I-E scores were more consistent positive predictors, and surprisingly CS scores were the most consistent positive predictors of the unsubstantiated beliefs.

Researchers commonly assume that people who accept implausible, unsubstantiated claims are gullible or not sufficiently skeptical. For instance, van Prooijen ( 2019 ) has argued that conspiracy theory believers are more gullible (less skeptical) than non-believers and tend to accept unsubstantiated claims more than less gullible people. van Prooijen ( 2019 ) reviewed several studies supporting the claim that people who are more gullible tend to endorse conspiracy theories more. However, he did not report any studies in which a gullible disposition was directly measured.

Recently, we directly tested the gullibility hypothesis in relation to scientific skepticism ( Bensley et al. 2023 ) using the Gullibility Scale of Teunisse et al. ( 2019 ) on which people skeptical of the paranormal had been shown to have lower scores. We found that Gullibility Scale and the Cynicism Scale scores were positively correlated, and both were significant positive predictors of unsubstantiated beliefs, in general, consistent with an intuitive–experiential cognitive style. In contrast, we found that scores on the Cognitive Reflection Test, the Scientific Skepticism Scale, and the REI rational–analytic scale were all positively intercorrelated and significant negative predictors of unsubstantiated beliefs, in general, consistent with a rational–analytic/reflective cognitive style. Scientific skepticism scores negatively predicted general endorsement of unsubstantiated claims beyond the REI R-A scale, but neither the CTDS nor the CTDS Reflective Skepticism subscale were significant. These results replicated findings from the Bensley et al. ( 2023 ) study and supported an elaborated dual-process model of unsubstantiated belief. The SSS was not only a substantial negative predictor, it was also negatively correlated with the Gullibility Scale, as expected.

These results suggest that both CT-related dispositions and CT skills are related to endorsement of unsubstantiated beliefs. However, a measure of general cognitive ability or intelligence must be examined along with measures of CT and unsubstantiated beliefs to determine if CT goes beyond intelligence to predict unsubstantiated beliefs. In one of the few studies that also included a measure of cognitive ability, Stahl and van Prooijen ( 2018 ) found that dispositional characteristics helped account for acceptance of conspiracies and paranormal belief beyond cognitive ability. Using the Importance of Rationality Scale (IRS), a rational–analytic scale designed to measure skepticism towards unsubstantiated beliefs, Stahl and van Prooijen ( 2018 ) found that the IRS was negatively correlated with paranormal belief and belief in conspiracy theories. In separate hierarchical regressions, cognitive ability was the strongest negative predictor of both paranormal belief and of conspiracy belief, but IRS scores in combination with cognitive ability negatively predicted endorsement of paranormal belief but did not significantly predict conspiracy theory belief. These results provided partial support that that a measure of rational–analytic cognitive style related to skeptical disposition added to the variance accounted for beyond cognitive ability in negatively predicting unsubstantiated belief.

In another study that included a measure of cognitive ability, Cavojova et al. ( 2019 ) examined how CT-related dispositions and the Scientific Reasoning Scale (SRS) were related to a measure of paranormal, pseudoscientific, and conspiracy theory beliefs. The SRS of Drummond and Fischhoff ( 2017 ) likely measures CT skill in that it measures the ability to evaluate scientific research and evidence. As expected, the unsubstantiated belief measure was negatively correlated with the SRS and a cognitive ability measure, similar to Raven’s Progressive Matrices. Unsubstantiated beliefs were positively correlated with dogmatism (the opposite of open-mindedness) but not with REI rational–analytic cognitive style. The SRS was a significant negative predictor of both unsubstantiated belief and susceptibility to bias beyond the contribution of cognitive ability, but neither dogmatism nor analytic thinking were significant predictors. Nevertheless, this study provides some support that a measure related to CT reasoning skill accounts for variance in unsubstantiated belief beyond cognitive ability.

The failure of this study to show a correlation between rational–analytic cognitive style and unsubstantiated beliefs, when some other studies have found significant correlations with it and related measures, has implications for the multidimensional assessment of unsubstantiated beliefs. One implication is that the REI rational–analytic scale may not be a strong predictor of unsubstantiated beliefs. In fact, we have recently found that the Scientific Skepticism Scale was a stronger negative predictor ( Bensley et al. 2022 ; Bensley et al. 2023 ), which also suggests that other measures related to rational–analytic thinking styles should be examined. This could help triangulate the contribution of self-report cognitive style measures to endorsement of unsubstantiated claims, recognizing that the use of self-report measures has a checkered history in psychological research. A second implication is that once again, measures of critical thinking skill and cognitive ability were negative predictors of unsubstantiated belief and so they, too, should be included in future assessments of unsubstantiated beliefs.

7. Discussion

This review provided different lines of evidence supporting the claim that CT goes beyond cognitive ability in accounting for certain real-world outcomes. Participants who think critically reported fewer problems in everyday functioning, not expected to befall critical thinkers. People who endorsed unsubstantiated claims less showed better CT skills, more accurate domain-specific knowledge, less susceptibility to thinking errors and bias, and were more disposed to think critically. More specifically, they tended to be more scientifically skeptical and adopt a more rational–analytic cognitive style. In contrast, those who endorsed them more tended to be more cynical and adopt an intuitive–experiential cognitive style. These characteristics go beyond what standardized intelligence tests test. In some studies, the CT measures accounted for additional variance beyond the variance contributed by general cognitive ability.

That is not to say that measures of general cognitive ability are not useful. As noted by Gottfredson ( 2004 ), “g” is a highly successful predictor of academic and job performance. More is known about g and Gf than about many other psychological constructs. On average, g is closely related to Gf, which is highly correlated with working memory ( r = 0.70) and can be as high as r = 0.77 ( r 2 = 0.60) based on a correlated two-factor model ( Gignac 2014 ). Because modern working memory theory is, itself, a powerful theory ( Chai et al. 2018 ), this lends construct validity to the fluid intelligence construct. Although cognitive scientists have clearly made progress in understanding the executive processes underlying intelligence, they have not yet identified the specific cognitive components of intelligence ( Sternberg 2022 ). Moreover, theorists have acknowledged that intelligence must also include components beyond g, including domain-specific knowledge ( Ackerman 2022 ; Conway and Kovacs 2018 ) which are not yet clearly understood,

This review also pointed to limitations in the research that should be addressed. So far, not only have few studies of unsubstantiated beliefs included measures of intelligence, but they have also often used proxies for intelligence test scores, such as SAT scores. Future studies, besides using more and better measures of intelligence, could benefit from inclusion of more specifically focused measures, such as measures of Gf and Gc. Also, more research should be carried out to develop additional high-quality measures of CT, including ones that assess specific reasoning skills and knowledge relevant to thinking about a subject, which could help resolve perennial questions about the domain-general versus domain-specific nature of intelligence and CT. Overall, the results of this review encourage taking a multidimensional approach to investigating the complex constructs of intelligence, CT, and unsubstantiated belief. Supporting these recommendations were results of studies in which the improvement accrued from explicit CT skill instruction could be more fully understood when CT skills, relevant knowledge, CT dispositions, metacognitive monitoring accuracy, and a proxy for intelligence were used.

8. Conclusions

Critical thinking, broadly conceived, offers ways to understand real-world outcomes of thinking beyond what general cognitive ability can provide and intelligence tests test. A multi-dimensional view of CT which includes specific reasoning and metacognitive skills, CT dispositions, and relevant knowledge can add to our understanding of why some people endorse unsubstantiated claims more than others do, going beyond what intelligence tests test. Although general cognitive ability and domain-general knowledge often contribute to performance on CT tasks, thinking critically about real-world questions also involves applying rules, criteria, and knowledge which are specific to the question under consideration, as well as the appropriate dispositions and cognitive styles for deploying these.

Despite the advantages of taking this multidimensional approach to CT in helping us to more fully understand everyday thinking and irrationality, it presents challenges for researchers and instructors. It implies the need to assess and instruct multidimensionally, including not only measures of reasoning skills but also addressing thinking errors and biases, dispositions, the knowledge relevant to a task, and the accuracy of metacognitive judgments. As noted by Dwyer ( 2023 ), adopting a more complex conceptualization of CT beyond just skills is needed, but it presents challenges for those seeking to improve students’ CT. Nevertheless, the research reviewed suggests that taking this multidimensional approach to CT can enhance our understanding of the endorsement of unsubstantiated claims beyond what standardized intelligence tests contribute. More research is needed to resolve remaining controversies and to develop evidence-based applications of the findings.

Funding Statement

This research received no external funding.

Institutional Review Board Statement

This research involved no new testing of participants and hence did not require Institutional Review Board approval.

Informed Consent Statement

This research involved no new testing of participants and hence did not require an Informed Consent Statement.

Data Availability Statement

Conflicts of interest.

The author declares no conflict of interest.

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

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DOI: 10.1017/9781316817049.013
Corpus ID: 149308385

Is critical thinking a better model of intelligence

D. Halpern , Heather Butler
Published 2018
Psychology, Philosophy

8 Citations

Analysis of the contribution of critical thinking and psychological well-being to academic performance, an account of the relationship between critical thinking and fluid intelligence in considering executive functions, critical thinking, intelligence, and unsubstantiated beliefs: an integrative review, critical thinking in ethical and neutral settings in gifted children and non-gifted children, critical thinking in algerian secondary school efl classes: expectations and reality, critical thinking: a model of intelligence for solving real-world problems, intelligence and reasoning, spearman’s g found in 31 non-western nations: strong evidence that g is a universal phenomenon, 24 references, the rationality quotient: toward a test of rational thinking, the halpern critical thinking assessment : towards a dutch appraisal of critical thinking, teaching critical thinking to promote learning, crimes and the bell curve: the role of people with high, average, and low intelligence, halpern critical thinking assessment, situation assessment as an ignored factor in the behavioral consistency paradigm underlying the validity of personnel selection procedures., halpern critical thinking assessment predicts real-world outcomes of critical thinking, the halpern critical thinking assessment and real-world outcomes: cross-national applications, operation ara: a computerized learning game that teaches critical thinking and scientific reasoning, learning gains for core concepts in a serious game on scientific reasoning, related papers.

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Paul-Elder Critical Thinking Framework

Critical thinking is that mode of thinking – about any subject, content, or problem — in which the thinker improves the quality of his or her thinking by skillfully taking charge of the structures inherent in thinking and imposing intellectual standards upon them. (Paul and Elder, 2001). The Paul-Elder framework has three components:

The elements of thought (reasoning)
The intellectual standards that should be applied to the elements of reasoning
The intellectual traits associated with a cultivated critical thinker that result from the consistent and disciplined application of the intellectual standards to the elements of thought

Graphic Representation of Paul-Elder Critical Thinking Framework

According to Paul and Elder (1997), there are two essential dimensions of thinking that students need to master in order to learn how to upgrade their thinking. They need to be able to identify the "parts" of their thinking, and they need to be able to assess their use of these parts of thinking.

Elements of Thought (reasoning)

The "parts" or elements of thinking are as follows:

All reasoning has a purpose
All reasoning is an attempt to figure something out, to settle some question, to solve some problem
All reasoning is based on assumptions
All reasoning is done from some point of view
All reasoning is based on data, information and evidence
All reasoning is expressed through, and shaped by, concepts and ideas
All reasoning contains inferences or interpretations by which we draw conclusions and give meaning to data
All reasoning leads somewhere or has implications and consequences

Universal Intellectual Standards

The intellectual standards that are to these elements are used to determine the quality of reasoning. Good critical thinking requires having a command of these standards. According to Paul and Elder (1997 ,2006), the ultimate goal is for the standards of reasoning to become infused in all thinking so as to become the guide to better and better reasoning. The intellectual standards include:

Intellectual Traits

Consistent application of the standards of thinking to the elements of thinking result in the development of intellectual traits of:

Intellectual Humility
Intellectual Courage
Intellectual Empathy
Intellectual Autonomy
Intellectual Integrity
Intellectual Perseverance
Confidence in Reason
Fair-mindedness

Characteristics of a Well-Cultivated Critical Thinker

Habitual utilization of the intellectual traits produce a well-cultivated critical thinker who is able to:

Raise vital questions and problems, formulating them clearly and precisely
Gather and assess relevant information, using abstract ideas to interpret it effectively
Come to well-reasoned conclusions and solutions, testing them against relevant criteria and standards;
Think open-mindedly within alternative systems of thought, recognizing and assessing, as need be, their assumptions, implications, and practical consequences; and
Communicate effectively with others in figuring out solutions to complex problems

Paul, R. and Elder, L. (2010). The Miniature Guide to Critical Thinking Concepts and Tools. Dillon Beach: Foundation for Critical Thinking Press.

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The Importance of Critical Thinking in Intelligence Analysis

By James Hess, Ph.D. | 04/13/2021

Intelligence analysts are charged with a difficult and challenging mission – to analyze current threats and to predict future threats. The good thing is that there is help in this mission, a discipline known as critical thinking.

Critical thinking is defined as “disciplined thinking that is clear, rational, open-minded, and informed by evidence.” One might think that given their position and training, intelligence analysts are natural critical thinkers. To a certain extent, that is correct, but critical thinking is difficult and requires a lot of practice to do it well.

The Two Schools of Thought About Critical Thinking

While critical thinking has developed considerably over the past decade, there are still two predominate schools of thought about this discipline. The first is The Foundation for Critical Thinking , founded by Drs. Richard Paul and Linda Elder. They have been studying and evaluating critical thinking processes for many years.

They represent the first school of thought: that critical thinking is a “process for taking charge of and responsibility for one’s thinking.” This process provides methods for how to think through problems by using techniques such as flexible and agile thinking, questioning assumptions, and criterion-based judgment.

Paul and Elder represent a holistic approach to applying critical thinking to our thought processes. In turn, these techniques inform the thought process by enabling improved analysis through their critical thinking framework: elements of thought, intellectual standards, and intellectual traits .

The other predominate school of thought for critical thinking is represented by former dean of the College of Arts and Sciences at Santa Clara University and provost of Loyola University Chicago, Dr. Peter Facione. His seminal work, “ Critical Thinking: What It Is and Why It Counts ” is the result of three decades of research.

Facione argues that domain-specific application of cognitive skills produces more effective critical thinking. This means that critical thinking can provide significant improvement of one’s thinking when it is applied to processes and procedures within a discipline; that is, specificity of thought rather than improving general thought.

Facione identified six cognitive skills that can be applied to any discipline to improve critical thinking. They are:

Interpretation
Explanation
Self-regulation

During my Ph.D. work, I developed a process that applied Facione’s six cognitive skills to intelligence analysis. I called this process Critical Thinking Applied to Intelligence Analysis Process (CTIAP). The overall concept of CTIAP is that by developing a critical thinking framework and applying it to intelligence analysis, intelligence reporting can be evaluated more efficiently and effectively. In return, this could result in improved analysis and assessments.

After developing this process, I tested its effectiveness in my dissertation, “Improving intelligence in a counterinsurgency or counterterrorism environment through the application of a critical thinking-based framework.” My findings concluded that, indeed, analysis and assessments can be improved through the application of CTIAP.

American Military University currently offers two classes at both the undergraduate and graduate levels in intelligence analysis – INTL 402 and INTL 508. In both classes, students are taught critical thinking approaches. They can also pursue their own evaluation of critical thinking frameworks applied to intelligence analysis in the Bachelor’s Senior Seminar in Intelligence Studies, the Master’s Capstone or the Doctorate of Strategic Intelligence (DSI) .

Critical Thinking is Useful in All Aspects of Life

Critical thinking can be useful in all aspects of life. Regardless if one defers to Paul and Elder’s critical thinking model or Facione’s domain-specific applications of critical thinking, studying and applying these cognitive skills can be useful for any process. Intelligence analysis is challenging, albeit critically important, and leveraging critical thinking skills can improve the most seasoned of analysts.

jh3421-pci-SSGS_James-Hess_Faculty-Photo-1 Photo

Dr. James Hess is a professor of intelligence and terrorism studies with American Public University. He holds an associate degree in intelligence operations studies from Cochise College, a bachelor’s degree in general studies from Northwestern State University, and a master’s degree in liberal arts from Louisiana State University.

Dr. Hess also earned a Ph.D. from Louisiana State University, where he studied improving analytical methodologies in counterinsurgency and counter-terrorism environments. He is also a fellow and affiliated faculty with the University of Arizona’s Center for Middle Eastern Studies where he researches Islamic jurisprudence and its impact on terrorism.

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Critical Thinking: A Model of Intelligence for Solving Real-World Problems

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1. Introduction

The editors of this Special Issue asked authors to respond to a deceptively simple statement: “How Intelligence Can Be a Solution to Consequential World Problems.” This statement holds many complexities, including how intelligence is defined and which theories are designed to address real-world problems.

2. The Problem with Using Standardized IQ Measures for Real-World Problems

For the most part, we identify high intelligence as having a high score on a standardized test of intelligence. Like any test score, IQ can only reflect what is on the given test. Most contemporary standardized measures of intelligence include vocabulary, working memory, spatial skills, analogies, processing speed, and puzzle-like elements (e.g., Wechsler Adult Intelligence Scale Fourth Edition; see (Drozdick et al. 2012)). Measures of IQ correlate with many important outcomes, including academic performance (Kretzschmar et al. 2016), job-related skills (Hunter and Schmidt 1996), reduced likelihood of criminal behavior (Burhan et al. 2014), and for those with exceptionally high IQs, obtaining a doctorate and publishing scholarly articles (McCabe et al. 2020). Gottfredson (1997, p. 81) summarized these effects when she said the “predictive validity of g is ubiquitous.” More recent research using longitudinal data, found that general mental abilities and specific abilities are good predictors of several work variables including job prestige, and income (Lang and Kell 2020). Although assessments of IQ are useful in many contexts, having a high IQ does not protect against falling for common cognitive fallacies (e.g., blind spot bias, reactance, anecdotal reasoning), relying on biased and blatantly one-sided information sources, failing to consider information that does not conform to one’s preferred view of reality (confirmation bias), resisting pressure to think and act in a certain way, among others. This point was clearly articulated by Stanovich (2009, p. 3) when he stated that,” IQ tests measure only a small set of the thinking abilities that people need.”

3. Which Theories of Intelligence Are Relevant to the Question?

Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. For example, Grossmann et al. (2013) cite many studies in which IQ scores have not predicted well-being, including life satisfaction and longevity. Using a stratified random sample of Americans, these investigators found that wise reasoning is associated with life satisfaction, and that “there was no association between intelligence and well-being” (p. 944). (critical thinking [CT] is often referred to as “wise reasoning” or “rational thinking,”). Similar results were reported by Wirthwein and Rost (2011) who compared life satisfaction in several domains for gifted adults and adults of average intelligence. There were no differences in any of the measures of subjective well-being, except for leisure, which was significantly lower for the gifted adults. Additional research in a series of experiments by Stanovich and West (2008) found that participants with high cognitive ability were as likely as others to endorse positions that are consistent with their biases, and they were equally likely to prefer one-sided arguments over those that provided a balanced argument. There are several newer theories that directly address the question about solving real-world problems. Prominent among them is Sternberg’s adaptive intelligence with “adaptation to the environment” as the central premise, a construct that does not exist on standardized IQ tests (e.g., Sternberg 2019). Similarly, Stanovich and West (2014) argue that standardized tests of intelligence are not measures of rational thought—the sort of skill/ability that would be needed to address complex real-world problems. Halpern and Butler (2020) advocate for CT as a useful model of intelligence for addressing real-world problems because it was designed for this purpose. Although there is much overlap among these more recent theories, often using different terms for similar concepts, we use Halpern and Butler’s conceptualization to make our point: Yes, intelligence (i.e., CT) can be enhanced and used for solving a real-world problem like COVID-19.

4. Critical Thinking as an Applied Model for Intelligence

One definition of intelligence that directly addresses the question about intelligence and real-world problem solving comes from Nickerson (2020, p. 205): “the ability to learn, to reason well, to solve novel problems, and to deal effectively with novel problems—often unpredictable—that confront one in daily life.” Using this definition, the question of whether intelligent thinking can solve a world problem like the novel coronavirus is a resounding “yes” because solutions to real-world novel problems are part of his definition. This is a popular idea in the general public. For example, over 1000 business managers and hiring executives said that they want employees who can think critically based on the belief that CT skills will help them solve work-related problems (Hart Research Associates 2018).

We define CT as the use of those cognitive skills or strategies that increase the probability of a desirable outcome. It is used to describe thinking that is purposeful, reasoned, and goal directed--the kind of thinking involved in solving problems, formulating inferences, calculating likelihoods, and making decisions, when the thinker is using skills that are thoughtful and effective for the particular context and type of thinking task. International surveys conducted by the OECD (2019, p. 16) established “key information-processing competencies” that are “highly transferable, in that they are relevant to many social contexts and work situations; and ‘learnable’ and therefore subject to the influence of policy.” One of these skills is problem solving, which is one subset of CT skills.

The CT model of intelligence is comprised of two components: (1) understanding information at a deep, meaningful level and (2) appropriate use of CT skills. The underlying idea is that CT skills can be identified, taught, and learned, and when they are recognized and applied in novel settings, the individual is demonstrating intelligent thought. CT skills include judging the credibility of an information source, making cost–benefit calculations, recognizing regression to the mean, understanding the limits of extrapolation, muting reactance responses, using analogical reasoning, rating the strength of reasons that support and fail to support a conclusion, and recognizing hindsight bias or confirmation bias, among others. Critical thinkers use these skills appropriately, without prompting, and usually with conscious intent in a variety of settings.

One of the key concepts in this model is that CT skills transfer in appropriate situations. Thus, assessments using situational judgments are needed to assess whether particular skills have transferred to a novel situation where it is appropriate. In an assessment created by the first author (Halpern 2018), short paragraphs provide information about 20 different everyday scenarios (e.g., A speaker at the meeting of your local school board reported that when drug use rises, grades decline; so schools need to enforce a “war on drugs” to improve student grades); participants provide two response formats for every scenario: (a) constructed responses where they respond with short written responses, followed by (b) forced choice responses (e.g., multiple choice, rating or ranking of alternatives) for the same situations.

There is a large and growing empirical literature to support the assertion that CT skills can be learned and will transfer (when taught for transfer). See for example, Holmes et al. (2015), who wrote in the prestigious Proceedings of the National Academy of Sciences , that there was “significant and sustained improvement in students’ critical thinking behavior” (p. 11,199) for students who received CT instruction. Abrami et al. (2015, para. 1) concluded from a meta-analysis that “there are effective strategies for teaching CT skills, both generic and content specific, and CT dispositions, at all educational levels and across all disciplinary areas.” Abrami et al. (2008, para. 1), included 341 effect sizes in a meta-analysis. They wrote: “findings make it clear that improvement in students’ CT skills and dispositions cannot be a matter of implicit expectation.” A strong test of whether CT skills can be used for real-word problems comes from research by Butler et al. (2017). Community adults and college students (N = 244) completed several scales including an assessment of CT, an intelligence test, and an inventory of real-life events. Both CT scores and intelligence scores predicted individual outcomes on the inventory of real-life events, but CT was a stronger predictor.

Heijltjes et al. (2015, p. 487) randomly assigned participants to either a CT instruction group or one of six other control conditions. They found that “only participants assigned to CT instruction improved their reasoning skills.” Similarly, when Halpern et al. (2012) used random assignment of participants to either a learning group where they were taught scientific reasoning skills using a game format or a control condition (which also used computerized learning and was similar in length), participants in the scientific skills learning group showed higher proportional learning gains than students who did not play the game. As the body of additional supportive research is too large to report here, interested readers can find additional lists of CT skills and support for the assertion that these skills can be learned and will transfer in Halpern and Dunn (Forthcoming). There is a clear need for more high-quality research on the application and transfer of CT and its relationship to IQ.

5. Pandemics: COVID-19 as a Consequential Real-World Problem

A pandemic occurs when a disease runs rampant over an entire country or even the world. Pandemics have occurred throughout history: At the time of writing this article, COVID-19 is a world-wide pandemic whose actual death rate is unknown but estimated with projections of several million over the course of 2021 and beyond (Mega 2020). Although vaccines are available, it will take some time to inoculate most or much of the world’s population. Since March 2020, national and international health agencies have created a list of actions that can slow and hopefully stop the spread of COVID (e.g., wearing face masks, practicing social distancing, avoiding group gatherings), yet many people in the United States and other countries have resisted their advice.

Could instruction in CT encourage more people to accept and comply with simple life-saving measures? There are many possible reasons to believe that by increasing citizens’ CT abilities, this problematic trend can be reversed for, at least, some unknown percentage of the population. We recognize the long history of social and cognitive research showing that changing attitudes and behaviors is difficult, and it would be unrealistic to expect that individuals with extreme beliefs supported by their social group and consistent with their political ideologies are likely to change. For example, an Iranian cleric and an orthodox rabbi both claimed (separately) that the COVID-19 vaccine can make people gay (Marr 2021). These unfounded opinions are based on deeply held prejudicial beliefs that we expect to be resistant to CT. We are targeting those individuals who beliefs are less extreme and may be based on reasonable reservations, such as concern about the hasty development of the vaccine and the lack of long-term data on its effects. There should be some unknown proportion of individuals who can change their COVID-19-related beliefs and actions with appropriate instruction in CT. CT can be a (partial) antidote for the chaos of the modern world with armies of bots creating content on social media, political and other forces deliberately attempting to confuse issues, and almost all media labeled “fake news” by social influencers (i.e., people with followers that sometimes run to millions on various social media). Here, are some CT skills that could be helpful in getting more people to think more critically about pandemic-related issues.

Reasoning by Analogy and Judging the Credibility of the Source of Information

Early communications about the ability of masks to prevent the spread of COVID from national health agencies were not consistent. In many regions of the world, the benefits of wearing masks incited prolonged and acrimonious debates (Tang 2020). However, after the initial confusion, virtually all of the global and national health organizations (e.g., WHO, National Health Service in the U. K., U. S. Centers for Disease Control and Prevention) endorse masks as a way to slow the spread of COVID (Cheng et al. 2020; Chu et al. 2020). However, as we know, some people do not trust governmental agencies and often cite the conflicting information that was originally given as a reason for not wearing a mask. There are varied reasons for refusing to wear a mask, but the one most often cited is that it is against civil liberties (Smith 2020). Reasoning by analogy is an appropriate CT skill for evaluating this belief (and a key skill in legal thinking). It might be useful to cite some of the many laws that already regulate our behavior such as, requiring health inspections for restaurants, setting speed limits, mandating seat belts when riding in a car, and establishing the age at which someone can consume alcohol. Individuals would be asked to consider how the mandate to wear a mask compares to these and other regulatory laws.

Another reason why some people resist the measures suggested by virtually every health agency concerns questions about whom to believe. Could training in CT change the beliefs and actions of even a small percentage of those opposed to wearing masks? Such training would include considering the following questions with practice across a wide domain of knowledge: (a) Does the source have sufficient expertise? (b) Is the expertise recent and relevant? (c) Is there a potential for gain by the information source, such as financial gain? (d) What would the ideal information source be and how close is the current source to the ideal? (e) Does the information source offer evidence that what they are recommending is likely to be correct? (f) Have you traced URLs to determine if the information in front of you really came from the alleged source?, etc. Of course, not everyone will respond in the same way to each question, so there is little likelihood that we would all think alike, but these questions provide a framework for evaluating credibility. Donovan et al. (2015) were successful using a similar approach to improve dynamic decision-making by asking participants to reflect on questions that relate to the decision. Imagine the effect of rigorous large-scale education in CT from elementary through secondary schools, as well as at the university-level. As stated above, empirical evidence has shown that people can become better thinkers with appropriate instruction in CT. With training, could we encourage some portion of the population to become more astute at judging the credibility of a source of information? It is an experiment worth trying.

6. Making Cost—Benefit Assessments for Actions That Would Slow the Spread of COVID-19

Historical records show that refusal to wear a mask during a pandemic is not a new reaction. The epidemic of 1918 also included mandates to wear masks, which drew public backlash. Then, as now, many people refused, even when they were told that it was a symbol of “wartime patriotism” because the 1918 pandemic occurred during World War I (Lovelace 2020). CT instruction would include instruction in why and how to compute cost–benefit analyses. Estimates of “lives saved” by wearing a mask can be made meaningful with graphical displays that allow more people to understand large numbers. Gigerenzer (2020) found that people can understand risk ratios in medicine when the numbers are presented as frequencies instead of probabilities. If this information were used when presenting the likelihood of illness and death from COVID-19, could we increase the numbers of people who understand the severity of this disease? Small scale studies by Gigerenzer have shown that it is possible.

Analyzing Arguments to Determine Degree of Support for a Conclusion

The process of analyzing arguments requires that individuals rate the strength of support for and against a conclusion. By engaging in this practice, they must consider evidence and reasoning that may run counter to a preferred outcome. Kozyreva et al. (2020) call the deliberate failure to consider both supporting and conflicting data “deliberate ignorance”—avoiding or failing to consider information that could be useful in decision-making because it may collide with an existing belief. When applied to COVID-19, people would have to decide if the evidence for and against wearing a face mask is a reasonable way to stop the spread of this disease, and if they conclude that it is not, what are the costs and benefits of not wearing masks at a time when governmental health organizations are making them mandatory in public spaces? Again, we wonder if rigorous and systematic instruction in argument analysis would result in more positive attitudes and behaviors that relate to wearing a mask or other real-world problems. We believe that it is an experiment worth doing.

7. Conclusions

We believe that teaching CT is a worthwhile approach for educating the general public in order to improve reasoning and motivate actions to address, avert, or ameliorate real-world problems like the COVID-19 pandemic. Evidence suggests that CT can guide intelligent responses to societal and global problems. We are NOT claiming that CT skills will be a universal solution for the many real-world problems that we confront in contemporary society, or that everyone will substitute CT for other decision-making practices, but we do believe that systematic education in CT can help many people become better thinkers, and we believe that this is an important step toward creating a society that values and practices routine CT. The challenges are great, but the tools to tackle them are available, if we are willing to use them.

Author Contributions

Conceptualization, D.F.H. and D.S.D.; resources, D.F.H.; data curation, writing—original draft preparation, D.F.H.; writing—review and editing, D.F.H. and D.S.D. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Institutional Review Board Statement

No IRB Review.

Informed Consent Statement

No Informed Consent.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive biases, partisan thinking, reactance, or confirmation bias, among others. There are several newer theories that directly address the question about solving real-world problems. Prominent among them is Sternberg’s adaptive intelligence with “adaptation to the environment” as the central premise, a construct that does not exist on standardized IQ tests. Similarly, some scholars argue that standardized tests of intelligence are not measures of rational thought—the sort of skill/ability that would be needed to address complex real-world problems. Other investigators advocate for critical thinking as a model of intelligence specifically designed for addressing real-world problems. Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem such as COVID-19, which we use as an example of contemporary problems that need a new approach.

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What Is Intelligence In Psychology

Charlotte Ruhl

Research Assistant & Psychology Graduate

BA (Hons) Psychology, Harvard University

Charlotte Ruhl, a psychology graduate from Harvard College, boasts over six years of research experience in clinical and social psychology. During her tenure at Harvard, she contributed to the Decision Science Lab, administering numerous studies in behavioral economics and social psychology.

Learn about our Editorial Process

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Intelligence in psychology refers to the mental capacity to learn from experiences, adapt to new situations, understand and handle abstract concepts, and use knowledge to manipulate one’s environment. It includes skills such as problem-solving, critical thinking, learning quickly, and understanding complex ideas.

Key Takeaways

Defining and classifying intelligence is extremely complicated. Theories of intelligence range from having one general intelligence (g) to certain primary mental abilities and multiple category-specific intelligences.
Following the creation of the Binet-Simon scale in the early 1900s, intelligence tests, now referred to as intelligence quotient (IQ) tests, are the most widely-known and used measure for determining an individual’s intelligence.
Although these tests are generally reliable and valid tools, they have flaws as they lack cultural specificity and can evoke stereotype threats and self-fulfilling prophecies.
IQ scores are normally distributed , meaning that 95% of the population has IQ scores between 70 and 130. However, some extreme examples exist of people with scores far exceeding 130 or far below 70.

Academic training with education and knowledge learning tiny person concept. School, college or university class course for cognitive process and smart professional skills program vector illustration

What Is Intelligence?

It might seem useless to define such a simple word. After all, we have all heard this word hundreds of times and probably have a general understanding of its meaning.

However, the concept of intelligence has been a widely debated topic among members of the psychology community for decades.

Intelligence has been defined in many ways: higher level abilities (such as abstract reasoning, mental representation, problem solving, and decision making), the ability to learn, emotional knowledge, creativity, and adaptation to meet the demands of the environment effectively.

Psychologist Robert Sternberg defined intelligence as “the mental abilities necessary for adaptation to, as well as shaping and selection of, any environmental context (1997, p. 1).

History of Intelligence

The study of human intelligence dates back to the late 1800s when Sir Francis Galton (the cousin of Charles Darwin) became one of the first to study intelligence.

Galton was interested in the concept of a gifted individual, so he created a lab to measure reaction times and other physical characteristics to test his hypothesis that intelligence is a general mental ability producing biological evolution (hello, Darwin!).

Galton theorized that because quickness and other physical attributes were evolutionarily advantageous, they would also provide a good indication of general mental ability (Jensen, 1982).

Thus, Galton operationalized intelligence as reaction time.

Operationalization is an important process in research that involves defining an unmeasurable phenomenon (such as intelligence) in measurable terms (such as reaction time), allowing the concept to be studied empirically (Crowthre-Heyck, 2005).

Galton’s study of intelligence in the laboratory setting and his theorization of the heritability of intelligence paved the way for decades of future research and debate in this field.

Theories of Intelligence

Some researchers argue that intelligence is a general ability, whereas others make the assertion that intelligence comprises specific skills and talents. Psychologists contend that intelligence is genetic, or inherited, and others claim that it is largely influenced by the surrounding environment.

As a result, psychologists have developed several contrasting theories of intelligence as well as individual tests that attempt to measure this very concept.

Spearman’s General Intelligence (g)

General intelligence, also known as g factor, refers to a general mental ability that, according to Spearman, underlies multiple specific skills, including verbal, spatial, numerical, and mechanical.

Charles Spearman, an English psychologist, established the two-factor theory of intelligence back in 1904 (Spearman, 1904). To arrive at this theory, Spearman used a technique known as factor analysis.

Factor analysis is a procedure through which the correlation of related variables is evaluated to find an underlying factor that explains this correlation.

In the case of intelligence, Spearman noticed that those who did well in one area of intelligence tests (for example, mathematics) also did well in other areas (such as distinguishing pitch; Kalat, 2014).

In other words, there was a strong correlation between performing well in math and music, and Spearman then attributed this relationship to a central factor, that of general intelligence (g).

Spearman concluded that there is a single g-factor that represents an individual’s general intelligence across multiple abilities and that a second factor, s, refers to an individual’s specific ability in one particular area (Spearman, as cited in Thomson, 1947).

General Intelligence and Specific Abilities

Together, these two main factors compose Spearman’s two-factor theory.

Thurstone’s Primary Mental Abilities

Thurstone (1938) challenged the concept of a g-factor. After analyzing data from 56 different tests of mental abilities, he identified a number of primary mental abilities that comprise intelligence as opposed to one general factor.

The seven primary mental abilities in Thurstone’s model are verbal comprehension, verbal fluency, number facility, spatial visualization, perceptual speed, memory, and inductive reasoning (Thurstone, as cited in Sternberg, 2003).

Description
Word Fluency	Ability to use words quickly and fluency in performing such tasks as rhyming, solving anagrams, and doing crossword puzzles.
Verbal Comprehension	Ability to understand the meaning of words, concepts, and ideas.
Numerical Ability	Ability to use numbers to quickly compute answers to problems.
Spatial Visualization	Ability to visualize and manipulate patterns and forms in space.
Perceptual Speed	Ability to grasp perceptual details quickly and accurately and to determine similarities and differences between stimuli.
Memory	Ability to recall information such as lists or words, mathematical formulas, and definitions.
Inductive Reasoning	Ability to derive general rules and principles from the presented information.

Although Thurstone did not reject Spearman’s idea of general intelligence altogether, he instead theorized that intelligence consists of both general ability and a number of specific abilities, paving the way for future research that examined the different forms of intelligence.

Gardner’s Multiple Intelligences

Following the work of Thurstone, American psychologist Howard Gardner built off the idea that there are multiple forms of intelligence.

He proposed that there is no single intelligence, but rather distinct, independent multiple intelligences exist, each representing unique skills and talents relevant to a certain category.

Gardner (1983, 1987) initially proposed seven multiple intelligences : linguistic, logical-mathematical, spatial, musical, bodily-kinesthetic, interpersonal, and intrapersonal, and he has since added naturalist intelligence.

Gardner holds that most activities (such as dancing) will involve a combination of these multiple intelligences (such as spatial and bodily-kinesthetic intelligences). He also suggests that these multiple intelligences can help us understand concepts beyond intelligence, such as creativity and leadership .

And although this theory has widely captured the attention of the psychology community and the greater public, it does have its faults.

There have been few empirical studies that actually test this theory, and this theory does not account for other types of intelligence beyond the ones Gardner lists (Sternberg, 2003).

Triarchic Theory of Intelligence

Just two years later, in 1985, Robert Sternberg proposed a three-category theory of intelligence, integrating components that were lacking in Gardner’s theory. This theory is based on the definition of intelligence as the ability to achieve success based on your personal standards and your sociocultural context.

According to the triarchic theory, intelligence has three aspects: analytical, creative, and practical (Sternberg, 1985).

Analytical intelligence , also referred to as componential intelligence, refers to intelligence that is applied to analyze or evaluate problems and arrive at solutions. This is what a traditional IQ test measures.

Creative intelligence is the ability to go beyond what is given to create novel and interesting ideas. This type of intelligence involves imagination, innovation, and problem-solving.

Practical intelligence is the ability that individuals use to solve problems faced in daily life when a person finds the best fit between themselves and the demands of the environment.

Adapting to the demands of the environment involves either utilizing knowledge gained from experience to purposefully change oneself to suit the environment (adaptation), changing the environment to suit oneself (shaping), or finding a new environment in which to work (selection).

Other Types of Intelligence

After examining the popular competing theories of intelligence, it becomes clear that there are many different forms of this seemingly simple concept.

On the one hand, Spearman claims that intelligence is generalizable across many different areas of life, and on the other hand, psychologists such as Thurstone, Gardener, and Sternberg hold that intelligence is like a tree with many different branches, each representing a specific form of intelligence.

To make matters even more interesting, let’s throw a few more types of intelligence into the mix!

Emotional Intelligence

Emotional Intelligence is the “ability to monitor one’s own and other people’s emotions, to discriminate between different emotions and label them appropriately, and to use emotional information to guide thinking and behavior” (Salovey and Mayer, 1990).

Emotional intelligence is important in our everyday lives, seeing as we experience one emotion or another nearly every second of our lives. You may not associate emotions and intelligence with one another, but in reality, they are very related.

Emotional intelligence refers to the ability to recognize the meanings of emotions and to reason and problem-solve on the basis of them (Mayer, Caruso, & Salovey, 1999). The four key components of emotional Intelligence are (i) self-awareness, (ii) self-management, (iii) social awareness, and (iv) relationship management.

Emotional and Social Intelligence Leadership Competencies

In other words, if you are high in emotional intelligence, you can accurately perceive emotions in yourself and others (such as reading facial expressions), use emotions to help facilitate thinking, understand the meaning behind your emotions (why are you feeling this way?), and know how to manage your emotions (Salovey & Mayer, 1990).

Fluid vs. Crystallized Intelligence

Raymond Cattell (1963) first proposed the concepts of fluid and crystallized intelligence and further developed the theory with John Horn.

Fluid intelligence is the ability to problem solve in novel situations without referencing prior knowledge, but rather through the use of logic and abstract thinking. Fluid intelligence can be applied to any novel problem because no specific prior knowledge is required (Cattell, 1963). As you grow older fluid increases and then starts to decrease in the late 20s.

Crystallized intelligence refers to the use of previously-acquired knowledge, such as specific facts learned in school or specific motor skills or muscle memory (Cattell, 1963). As you grow older and accumulate knowledge, crystallized intelligence increases.

graph showing fluid and crystalized intelligence across the lifespan

The Cattell-Horn (1966) theory of fluid and crystallized intelligence suggests that intelligence is composed of a number of different abilities that interact and work together to produce overall individual intelligence.

For example, if you are taking a hard math test, you rely on your crystallized intelligence to process the numbers and meaning of the questions, but you may use fluid intelligence to work through the novel problem and arrive at the correct solution. It is also possible that fluid intelligence can become crystallized intelligence.

The novel solutions you create when relying on fluid intelligence can, over time, develop into crystallized intelligence after they are incorporated into long-term memory.

This illustrates some of the ways in which different forms of intelligence overlap and interact with one another, revealing its dynamic nature.

Intelligence Testing

Binet-simon scale.

During the early 1900s, the French government enlisted the help of psychologist Alfred Binet to understand which children were going to be slower learners and thus required more assistance in the classroom (Binet et al., 1912).

As a result, he and his colleague, Theodore Simon, began to develop a specific set of questions that focused on areas such as memory and problem-solving skills.

They tested these questions on groups of students aged three to twelve to help standardize the measure (Binet et al., 1912). Binet realized that some children were able to answer advanced questions that their older peers were able to answer.

As a result, he created the concept of mental age, or how well an individual performs intellectually relative to the average performance at that age (Cherry, 2020).

Ultimately, Binet finalized the scale, known as the Binet-Simon scale, that became the basis for the intelligence tests still used today.

The Binet-Simon scale of 1905 comprised 30 items designed to measure judgment, comprehension, and reasoning, which Binet deemed the key characteristics of intelligence.

Stanford-Binet Intelligence Scale

When the Binet-Simon scale made its way over to the United States, Stanford psychologist Lewis Terman adapted the test for American students and published the Stanford-Binet Intelligence Scale in 1916 (Cherry, 2020).

The Stanford-Binet Scale is a contemporary assessment that measures intelligence according to five features of cognitive ability,

including fluid reasoning, knowledge, quantitative reasoning, visual-spatial processing, and working memory. Both verbal and nonverbal responses are measured.

This test used a single number, referred to as the intelligence quotient (IQ), to indicate an individual’s score.

The average score for the test is 100, and any score from 90 to 109 is considered to be in the average intelligence range. Scores from 110 to 119 are considered to be High Average. Superior scores range from 120 to 129 and anything over 130 is considered Very Superior.

To calculate IQ, the student’s mental age is divided by his or her actual (or chronological) age, and this result is multiplied by 100. If your mental age is equal to your chronological age, you will have an IQ of 100, or average. If your mental age is 12, but your chronological age is only 10, you will have an above-average IQ of 120.

WISC and WAIS

Just as theories of intelligence build off one another, intelligence tests do too. After Terman created Stanford-Binet test, American psychologist David Wechsler developed a new tool due to his dissatisfaction with the limitations of the Stanford-Binet test (Cherry, 2020).

Like Thurstone, Gardner, and Sternberg, Wechsler believed intelligence involved many different mental abilities and felt that the Stanford-Binet scale too closely reflected the idea of one general intelligence.

Because of this, Wechsler created the Wechsler Intelligence Scale for Children (WISC) and the Wechsler Adult Intelligence Scale (WAIS) in 1955, with the most up-to-date version being the WAIS-IV (Cherry, 2020).

The Wechsler Intelligence Scale for Children (WISC), developed by David Wechsler, is an IQ test designed to measure intelligence and cognitive ability in children between the ages of 6 and 16. It is currently in its fourth edition (WISC-V) released in 2014 by Pearson.

Above Image: WISC-IV Sample Test Question

The Wechsler Adult Intelligence Scale (WAIS) is an IQ test designed to measure cognitive ability in adults and older adolescents, including

verbal comprehension, perceptual reasoning, working memory, and processing speed.

The latest version of the Wechsler Adult Intelligence Scale (WAIS-IV) was standardized on 2,200 healthy people between the ages of 16 and 90 years (Brooks et al., 2011).

The standardization of a test involves giving it to a large number of people of different ages to compute the average score on the test at each age level.

The overall IQ score combines the test takers’ performance in all four categories (Cherry, 2020). And rather than calculating this number based on mental and chronological age, the WAIS compares the individual’s score to the average score at that level, as calculated by the standardization process.

The Flynn Effect

It is important to regularly standardize an intelligence test because the overall level of intelligence in a population may change over time.

This phenomenon is known as the Flynn effect (named after its discoverer, New Zealand researcher James Flynn) which refers to the observation that scores on intelligence tests worldwide increase from decade to decade (Flynn, 1984).

Aptitude vs. Achievement Tests

Other tests, such as aptitude and achievement tests, are designed to measure intellectual capability. Achievement tests measure what content a student has already learned (such as a unit test in history or a final math exam), whereas an aptitude test measures a student’s potential or ability to learn (Anastasi, 1984).

Although this may sound similar to an IQ test, aptitude tests typically measure abilities in very specific areas.

Criticism of Intelligence Testing

Criticisms have ranged from the claim that IQ tests are biased in favor of white, middle-class people. Negative stereotypes about a person’s ethnicity, gender, or age may cause the person to suffer stereotype threat, a burden of doubt about his or her own abilities, which can create anxiety that result in lower scores.

Reliability and Construct Validity

Although you may be wondering if you take an intelligence test multiple times will you improve your score and whether these tests even measure intelligence in the first place, research provides reassurance that these tests are both very reliable and have high construct validity.

Reliability simply means that they are consistent over time. In other words, if you take a test at two different points in time, there will be very little change in performance or, in the case of intelligence tests, IQ scores.

Although this isn’t a perfect science, and your score might slightly fluctuate when taking the same test on different occasions or different tests at the same age, IQ tests demonstrate relatively high reliability (Tuma & Appelbaum, 1980).

Additionally, intelligence tests also reveal strong construct validity , meaning that they are, in fact, measuring intelligence rather than something else.

Researchers have spent hours on end developing, standardizing, and adapting these tests to best fit the current times. But that is also not to say that these tests are completely flawless.

Research documents errors with the specific scoring of tests and interpretation of the multiple scores (since typically, an individual will receive an overall IQ score accompanied by several category-specific scores), and some studies question the actual validity, reliability, and utility for individual clinical use of these tests (Canivez, 2013).

Additionally, intelligence scores are created to reflect different theories of intelligence, so the interpretations may be heavily based on the theory upon which the test is based (Canivez, 2013).

Cultural Specificity

There are issues with intelligence tests beyond looking at them in a vacuum. These tests were created by Western psychologists who created such tools to measure euro-centric values.

However, it is important to recognize that the majority of the world’s population does not reside in Europe or North America, and as a result, the cultural specificity of these tests is crucial.

Different cultures hold different values and even have different perceptions of intelligence, so is it fair to have one universal marker of this increasingly complex concept?

For example, a 1992 study found that Kenyan parents defined intelligence as the ability to do without being told what needed to be done around the homestead (Harkness et al., 1992), and, given the American and European emphasis on speed, some Ugandans define intelligent people as being slow in thought and action (Wober, 1974).

Together, these examples illustrate the flexibility of defining intelligence, making capturing this concept in a single test, let alone a single number even more challenging. And even within the U.S., do perceptions of intelligence differ?

An example is in San Jose, California, where Latino, Asian, and Anglo parents had varying definitions of intelligence. The teachers’ understanding of intelligence was more similar to that of the Asian and Anglo communities, and this similarity predicted the child’s performance in school (Okagaki & Sternberg, 1993).

That is, students whose families had more similar understandings of intelligence were doing better in the classroom.

Intelligence takes many forms, ranging from country to country and culture to culture. Although IQ tests might have high reliability and validity, understanding the role of culture is as, if not more, important in forming the bigger picture of an individual’s intelligence.

IQ tests may accurately measure academic intelligence, but more research must be done to discern whether they truly measure practical intelligence or even just general intelligence in all cultures.

Social and Environmental Factors

Another important part of the puzzle to consider is the social and environmental context in which an individual lives and the IQ test-related biases that develop as a result.

These might help explain why some individuals have lower scores than others. For example, the threat of social exclusion can greatly decrease the expression of intelligence.

A 2002 study gave participants an IQ test and a personality inventory, and some were randomly chosen to receive feedback from the inventory indicating that they were “the sort of people who would end up alone in life” (Baumeister et al., 2002).

After a second test, those who were told they would be loveless and friendless in the future answered significantly fewer questions than they did on the earlier test.

These findings can translate into the real world where not only the threat of social exclusion can decrease the expression of intelligence but also a perceived threat to physical safety.

In other words, a child’s poor academic performance can be attributed to the disadvantaged, potentially unsafe communities in which they grow up.

Stereotype Threat

Stereotype threat is a phenomenon in which people feel at risk of conforming to stereotypes about their social group. Negative stereotypes can also create anxiety that results in lower scores.

In one study, Black and White college students were given part of the verbal section from the Graduate Record Exam (GRE), but in the stereotype threat condition, they told students the test diagnosed intellectual ability, thus potentially making the stereotype that Blacks are less intelligent than Whites salient.

The results of this study revealed that in the stereotype threat condition, Blacks performed worse than Whites, but in the no stereotype threat condition, Blacks and Whites performed equally well (Steele & Aronson, 1995).

And even just recording your race can also result in worsened performance. Stereotype threat is a real threat and can be detrimental to an individual’s performance on these tests.

Self-Fulfilling Prophecy

Stereotype threat is closely related to the concept of a self-fulfilling prophecy in which an individual’s expectations about another person can result in the other person acting in ways that conform to that very expectation.

In one experiment, students in a California elementary school were given an IQ test, after which their teachers were given the names of students who would become “intellectual bloomers” that year based on the results of the test (Rosenthal & Jacobson, 1968).

At the end of the study, the students were tested again with the same IQ test, and those labeled as “intellectual bloomers” significantly increased their scores.

This illustrates that teachers may subconsciously behave in ways that encourage the success of certain students, thus influencing their achievement (Rosenthal & Jacobson, 1968), and provides another example of small variables that can play a role in an individual’s intelligence score and the development of their intelligence.

This is all to say that it is important to consider the less visible factors that play a role in determining someone’s intelligence. While an IQ score has many benefits in measuring intelligence, it is critical to consider that just because someone has a lower score does not necessarily mean they are lower in intelligence.

There are many factors that can worsen performance on these tests, and the tests themselves might not even be accurately measuring the very concept they are intended to.

Extremes of Intelligence

IQ scores are generally normally distributed (Moore et al., 2013). That is, roughly 95% of the population has IQ scores between 70 and 130. But what about the other 5%?

Individuals who fall outside this range represent the extremes of intelligence.

Those who have an IQ above 130 are considered to be gifted (Lally & French, 2018), such as Christopher Langan, an American horse rancher, who has an IQ score around 200 (Gladwell, 2008).

Those individuals who have scores below 70 do so because of an intellectual disability marked by substantial developmental delays, including motor, cognitive, and speech delays (De Light, 2012).

Some of the time, these disabilities are the product of genetic mutations.

Down syndrome, for example, resulting from extra genetic material from or a complete extra copy of the 21st chromosome, is a common genetic cause of an intellectual disability (Breslin, 2014). As such, many individuals with Down Syndrome have below-average IQ scores (Breslin, 2014).

Savant syndrome is another example of extreme intelligence. Despite having significant mental disabilities, these individuals demonstrate certain abilities in some fields that are far above average, such as incredible memorization, rapid mathematical or calendar calculation ability, or advanced musical talent (Treffert, 2009).

The fact that these individuals who may be lacking in certain areas such as social interaction and communication make up for it in other remarkable areas further illustrates the complexity of intelligence and what this concept means today, as well as how we must consider all individuals when determining how to perceive, measure, and recognize intelligence in our society.

Intelligence Today

Today, intelligence is generally understood as the ability to understand and adapt to the environment by using inherited abilities and learned knowledge.

Many new intelligence tests have arisen, such as the University of California Matrix Reasoning Task (Pahor et al., 2019), that can be taken online and in very little time, and new methods of scoring these tests have been developed too (Sansone et al., 2014).

Admission into university and graduate schools relies on specific aptitude and achievement tests, such as the SAT, ACT, and the LSAT – these tests have become a huge part of our lives.

Humans are incredibly intelligent beings and rely on our intellectual abilities daily. Although intelligence can be defined and measured in countless ways, our overall intelligence as a species makes us incredibly unique and has allowed us to thrive for generations on end.

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Theories of Intelligence in Psychology

Learn How to Define and Test Intelligence

What is Intelligence?
Foundational Theories

Other Types of Intelligence

Intelligence (iq) testing, frequently asked questions.

Intelligence is one of the most talked-about subjects in psychology , but no standard definition exists. Some researchers have suggested that intelligence is a single, general ability. Other theories of intelligence hold that intelligence encompasses a range of aptitudes, skills, and talents.

How Do We Define Intelligence?

Despite substantial interest in the subject, there still isn't a consensus among experts about the components of intelligence or whether accurate measurements of intelligence are even possible.

Although contemporary definitions of intelligence vary considerably, experts generally agree that intelligence involves mental abilities such as logic, reasoning, problem-solving , and planning. Specifically, current definitions tend to suggest that intelligence is the ability to:

Learn from experience : The acquisition , retention, and use of knowledge is an essential component of intelligence.
Recognize problems : To use knowledge, people first must identify the problems it might address.
Solve problems : People must then use what they have learned to come up with solutions to problems.

Research on intelligence plays a significant role in many areas, including educational program funding, job applicant screening, and testing to identify children who need additional academic help.

Main Theories of Intelligence in Psychology

Given the intense interest in the concept of intelligence, some of the field's greatest minds have explored it from numerous angles. Following are some of the major theories of intelligence that have emerged in the last 100 years.

Major Types of Intelligence Theories

General intelligence
Primary mental abilities
Multiple intelligences
The triarchic approach to intelligence

General Intelligence

British psychologist Charles Spearman (1863–1945) described the concept of general intelligence , or the "g factor." After using factor analysis to examine mental aptitude tests, Spearman concluded that scores on these tests were remarkably similar.

People who performed well on one cognitive test tended to perform well on other tests, while those who scored poorly on one test tended to score poorly on others. He concluded that intelligence is a general cognitive ability that researchers can measure and express numerically.

Primary Mental Abilities

Psychologist Louis L. Thurstone (1887–1955) focused on seven primary mental abilities rather than a single, general ability. These include:

Associative memory : The ability to memorize and recall
Numerical ability : The ability to solve mathematical problems
Perceptual speed : The ability to see differences and similarities among objects
Reasoning : The ability to find rules
Spatial visualization : The ability to visualize relationships
Verbal comprehension : The ability to define and understand words
Word fluency : The ability to produce words rapidly

Multiple Intelligences

Among more recent ideas about intelligence is Howard Gardner's theory of multiple intelligences . He proposed that traditional IQ testing does not fully and accurately depict a person's abilities. He proposed eight different intelligences based on skills and abilities that are valued in various cultures:

Bodily-kinesthetic intelligence : The ability to control body movements and handle objects skillfully
Interpersonal intelligence : The capacity to detect and respond appropriately to the moods, motivations, and desires of others
Intrapersonal intelligence : The capacity to be self-aware and in tune with inner feelings, values, beliefs, and thinking processes
Logical-mathematical intelligence : The ability to think conceptually and abstractly, as well as discern logical or numerical patterns
Musical intelligence : The ability to produce and appreciate rhythm, pitch, and timbre
Naturalistic intelligence : The ability to recognize and categorize animals, plants, and other objects in nature
Verbal-linguistic intelligence : Well-developed verbal skills and sensitivity to the sounds, meanings, and rhythms of words
Visual-spatial intelligence : The capacity to think in images and visualize accurately and abstractly

What Kind of Intelligence Do You Have?

If you'd like to know more about your intelligence style, try our fast and free quiz to learn more about what makes you tick.

The Triarchic Approach to Intelligence

Psychologist Robert Sternberg defined intelligence as "mental activity directed toward purposive adaptation to, selection, and shaping of real-world environments relevant to one's life."

Although he agreed with Gardner that intelligence is much broader than a single, general ability, he suggested that some of Gardner's types of intelligence are better viewed as individual talents. Sternberg proposed the concept of "successful intelligence," which involves three factors:

Analytical intelligence : The ability to evaluate information and solve problems
Creative intelligence : The ability to come up with new ideas
Practical intelligence : The ability to adapt to a changing environment

Of course, there are many other theories on the types of intelligence humans possess.

Fluid vs. Crystallized Intelligence

Psychologist Raymon Cattell, along with his student John Horn, created the theory of fluid vs. crystallized intelligence . Fluid intelligence involves the ability to solve new problems without relying on knowledge from previous experiences.

According to the theory, a person's fluid intelligence declines as they get older. Crystallized intelligence, on the other hand, increases with age—this type of intelligence is based on concrete facts and experiences.

Emotional Intelligence

Emotional intelligence (sometimes called EQ) was initially coined by psychologist Daniel Goleman. It refers to a person's ability to regulate emotions and use their emotions to relate to others. Signs of emotional intelligence include strong self-awareness , empathy , embracing change, and managing emotions in difficult situations.

Efforts to quantify intelligence took a significant leap forward when German psychologist William Stern first coined the term "intelligence quotient" (IQ) in the early 20th century.

Psychologist Alfred Binet developed the very first intelligence tests to help the French government identify schoolchildren who needed extra academic assistance.

Binet was the first to introduce the concept of mental age: a set of abilities that children of a certain age possess.

Since then, intelligence testing has emerged as a widely used tool, which has led to many other tests of skill and aptitude.

However, IQ testing continues to spur debate over its use, cultural biases, influences on intelligence, and even the very way we define intelligence.

How Psychologists and Psychiatrists Measure Intelligence

Experts use a variety of standardized tests to measure intelligence. Some are aptitude tests administered in a group setting, such as the Scholastic Assessment Test (SAT) and the American College Test (ACT). Others are IQ tests given to individuals.

IQ test scores average around 100. Most children with intellectual disabilities (85%) score between 55 and 70. Severe disabilities usually correspond to still lower scores.

The following is a brief history of IQ tests as they were developed:

Binet-Simon intelligence scale : This was the first IQ test ever made and was developed in 1905 by Alfred Binet and Theodore Simon.
Stanford-Binet IQ test : This was psychologist Lewis Terman's adaptation of the Binet-Simon test. Scores are based on a person's mental age divided by their chronological age (mental age/chronological age x 100).
Wechsler Adult Intelligence Scale (WAIS) : This was the first intelligence test for adults, developed by David Wechsler in 1939. It was the first to use standardized normal distribution in scoring and is commonly used today. It is divided into verbal and performance measures. Like most modern tests, it scores on a bell curve.

Other tests that psychologists and psychiatrists use today include the Woodcock-Johnson Tests of Cognitive Abilities, the Kaufman Assessment Battery for Children, the Cognitive Assessment System, and the Differential Ability Scale.

Questions About IQ Testing

The study of the human mind is complex, in part because the most important tool in the effort is the same as the subject itself.

As humans, researchers bring not only their knowledge and expertise but also their biases, experiences, cultural backgrounds, and beliefs to the table; like all scientific experts, they must combat their own humanness to strive for objectivity.

In addition, there's the sheer complexity of the human mind and the challenges of measuring a trait with so many conflicting definitions and nuances. No single standard for intelligence or its quantification exists as yet.

It's no surprise, then, that important questions about intelligence and IQ testing remain unanswered, at least in part. Some of these include:

Are intelligence tests biased?
Is intelligence a single ability, or does it involve multiple skills and abilities?
Is intelligence inherited, or does the environment play a more significant role?
What do intelligence scores predict, if anything?

To explore these questions, psychologists continue to research the nature, influences, and effects of intelligence. Their ongoing findings resonate across society, from education and the workplace to medical and behavioral diagnostic and therapeutic approaches.

Final Thoughts

Despite considerable debate, no definitive conceptualization of intelligence has emerged in the field of psychology. Today, psychologists often account for the many theoretical viewpoints when discussing intelligence and acknowledge that the debate is ongoing.

Early theories of intelligence focused on logic, problem-solving abilities, and critical thinking skills. In 1920, Edward Thorndike postulated three kinds of intelligence: social, mechanical, and abstract. Building on this, contemporary theories such as that proposed by Harvard psychologist Howard Gardner tend to break intelligence into separate categories (e.g., emotional, musical, spatial, etc.).

Emotional intelligence (EI or EQ) is the ability to perceive, control, and evaluate emotions. Some researchers suggest that emotional intelligence can be learned and strengthened; others claim it's an inborn characteristic. Generally, EI is measured by self-report and ability tests.

Fluid intelligence is the ability to apply logic and think flexibly. Raymond Cattell defined fluid intelligence as "the ability to perceive relationships independent of previous specific practice or instruction concerning those relationships."

Intelligence develops and changes throughout life, generally peaking in midlife . A study published in Psychological Science suggested that certain elements of fluid intelligence peak as late as 40.

Jaarsveld S, Lachmann T. Intelligence and creativity in problem solving: The importance of test features in cognition research . Front Psychol . 2017;8. doi:10.3389/fpsyg.2017.00134

Spearman C. "General intelligence," objectively determined and measured . The American Journal of Psychology . 1904;15(2):201. doi:10.2307/1412107

Thurstone LL. Primary Mental Abilities . University of Chicago Press; 1938.

Gardner H. Frames of Mind: The Theory of Multiple Intelligences . Basic Books; 2011.

Sternberg RJ. Beyond IQ: A Triarchic Theory of Human Intelligence . CUP Archive; 1985.

Horn JL, Cattell RB. Refinement and test of the theory of fluid and crystallized general intelligences . Journal of Educational Psychology . 1966;57(5):253-270. doi:10.1037/h0023816

Ghisletta P, Rabbitt P, Lunn M, Lindenberger U. Two thirds of the age-based changes in fluid and crystallized intelligence, perceptual speed, and memory in adulthood are shared . Intelligence . 2012;40(3):260-268. doi:10.1016/j.intell.2012.02.008

Barbey AK. Network neuroscience theory of human intelligence . Trends Cogn Sci (Regul Ed) . 2018;22(1):8-20. doi:10.1016/j.tics.2017.10.001

Drigas AS, Papoutsi C. A new layered model on emotional intelligence . Behav Sci (Basel). 2018;8(5):45. doi:10.3390/bs8050045

Nicolas S, Andrieu B, Croizet JC, Sanitioso RB, Burman JT. Sick? Or slow? On the origins of intelligence as a psychological object . Intelligence . 2013;41(5):699-711. doi:10.1016/j.intell.2013.08.006

HealthyChildren.org. Children with intellectual disabilities . American Academy of Pediatrics.

Richardson K, Norgate SH. Does IQ really predict job performance? Applied Developmental Science . 2015;19(3):153-169. doi:10.1080/10888691.2014.983635

Hartshorne JK, Germine LT. When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span . Psychol Sci . 2015;26(4):433-443. doi:10.1177/0956797614567339

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

COMMENTS

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Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive biases, partisan thinking, reactance, or confirmation bias, among others. There are several newer ...
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Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive biases, partisan thinking, reactance, or confirmation bias, among others. There are several newer ...
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Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem like Covid-19, which we use as an example of contemporary problems that need a new approach ...
[PDF] Critical Thinking: A Model of Intelligence for Solving Real-World
Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem such as COVID-19, which the authors use as an example of contemporary problems that need a new approach. Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many ...
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Halpern and Butler (2020) advocate for critical thinking as a better model of intelligence for addressing real-world problems than those that are based on psychometric properties of general intelligence. Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem like Covid-19, which we use as an ...
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PDF Critical Thinking: A Model of Intelligence for Solving Real-World ...
Other investigators advocate for critical thinking as a model of intelligence specifically designed for addressing real-world problems. Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem such as COVID-19, which we use as an example of contemporary problems that need a new approach.
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Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem such as COVID-19, which the authors use as an example of contemporary problems that need a new approach. Expand. 38.
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Critical Thinking as an Applied Model for Intelligence One definition of intelligence that directly addresses the question about intelligence and real-world problem solving comes from Nickerson (2020, p. 205): "the ability to learn, to reason well, to solve novel problems, and to deal effectively with novel problems—often unpredictable ...
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Interpersonal intelligence: The capacity to detect and respond appropriately to the moods, motivations, and desires of others. Intrapersonal intelligence: The capacity to be self-aware and in tune with inner feelings, values, beliefs, and thinking processes. Logical-mathematical intelligence: The ability to think conceptually and abstractly, as ...

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Critical Thinking, Intelligence, and Unsubstantiated Beliefs: An Integrative Review

1. Introduction

2. Defining Critical Thinking and Intelligence

3. Does Critical Thinking “Go Beyond” What Is Meant by Intelligence?

4. Dual-Process Theory Measures and Unsubstantiated Beliefs

5. Assessing Critical Thinking and Unsubstantiated Beliefs

6. Dual-Processing Theory and Research on Unsubstantiated Beliefs

7. Discussion

8. Conclusions

Funding Statement

Institutional Review Board Statement

Informed Consent Statement

Data Availability Statement

Is critical thinking a better model of intelligence

8 Citations

Ideas to Action (i2a)

Elements of Thought (reasoning)

Universal Intellectual Standards

Intellectual Traits

Characteristics of a Well-Cultivated Critical Thinker

The Importance of Critical Thinking in Intelligence Analysis

The Two Schools of Thought About Critical Thinking

Critical Thinking is Useful in All Aspects of Life

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Critical Thinking: A Model of Intelligence for Solving Real-World Problems

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