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How General Intelligence (G Factor) Is Determined

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

Verywell / Emily Roberts

• Measurement

General intelligence, also known as the general factor or g factor , refers to the existence of a broad mental capacity that influences performance on cognitive ability measures. Other terms such as intelligence, IQ , general cognitive ability, and general mental ability are also used interchangeably to mean the same thing as general intelligence.

This general mental ability is what underlies specific mental skills related to areas such as spatial, numerical, mechanical, and verbal abilities. The idea is that general intelligence influences performance on all cognitive tasks. So, general intelligence can be defined as a construct that is made up of different cognitive abilities. These abilities allow people to acquire knowledge and solve problems.

Spearman's Theory of General Intelligence

Psychologist Charles Spearman helped develop a statistical technique known as factor analysis, which allows researchers to use a number of different test items to measure common abilities. For example, researchers might find that people who score well on questions that measure vocabulary also perform better on questions related to reading comprehension.

In 1904, Spearman suggested that this g factor was responsible for overall performance on mental ability tests. He noted that while people certainly could and often did excel in certain areas, people who did well in one area tended also to do well in other areas.

Spearman's theory of general intelligence is known as the two-factor theory and states that general intelligence or "g" is correlated with specific abilities or "s" to some degree. All tasks on intelligence tests, whether related to verbal or mathematical abilities, were influenced by this underlying g factor.

General intelligence can be compared to athleticism. A person might be a very skilled runner, but this does not necessarily mean that they will also be an excellent figure skater.

However, because this person is athletic and fit, they will probably perform much better on other physical tasks than an individual who is less coordinated and more sedentary.

Types of General Intelligence

In the 1940s, Raymond Cattell theorized that there were two types of intelligence that affect human cognitive ability: fluid intelligence (Gf) and crystallized intelligence (Gc). Fluid intelligence refers to intelligence that we are born with and that we acquire through interacting with our environment. Crystalized intelligence is intelligence that we acquire through our culture.

Others suggest that there are more types of general intelligence, often referred to as the "g's of intelligence." Additional g's of intelligence include:

• General memory and learning (Gy)
• Broad visual perception (Gv)
• Broad auditory perception (Gu)
• Broad retrieval ability (Gr)
• Broad cognitive speediness (Gs)
• Reaction time (Gt)

Components of General Intelligence

There are several key components that are believed to make up general intelligence . These include:

• Fluid reasoning : This involves the ability to think flexibly and solve problems.
• Knowledge : This is a person's general understanding of a wide range of topics and can be equated with crystallized intelligence.
• Quantitative reasoning : This is an individual's capacity to solve problems that involve numbers.
• Visual-spatial processing : This relates to a person's abilities to interpret and manipulate visual information, such as putting together puzzles and copying complex shapes.
• Working memory : This involves the use of short-term memory such as being able to repeat a list of items.

How General Intelligence Is Measured

Many modern intelligence tests measure some of the cognitive factors that are thought to make up general intelligence. Such tests propose that intelligence can be measured and expressed by a single number, such as an IQ score.

The Stanford-Binet, which is one of the most popular intelligence tests , aims to measure the g factor. In addition to providing an overall score, the current version of the test also offers a number of score composites as well as subtest scores in ten different areas.

What Do IQ Test Scores Mean?

While scoring systems vary, the average score on many is 100 and the following labels are often used for different scoring ranges:

• 40 - 54 : Moderately impaired or delayed
• 55 - 69 : Mildly impaired or delayed
• 70 - 79 : Borderline impaired or delayed
• 80 - 89 : Low average intelligence
• 90 - 109 : Average
• 110 - 119 : High average
• 120 - 129 : Superior
• 130 - 144 : Gifted or very advanced
• 145 - 160 : Exceptionally gifted or highly advanced

Impact of General Intelligence

While the concept of intelligence is still the subject of debate within psychology, researchers believe that general intelligence is correlated with overall success in life.   Some of the effects that it may have on an individual's life include areas such as:

Academic Achievement

One of the most obvious effects of general intelligence is in the realm of academic performance. While intelligence plays a role in academics, there has been a great deal of debate over the extent to which it influences academic achievement.

Research has shown that there is a strong association between general mental ability and academic achievement, but it doesn't act on its own. Some research suggests that between 51% and 75% of achievement cannot be accounted for by the g factor alone.

This means that while general intelligence does affect how well kids do in school, other factors can play a major role.

Job Success

IQ scores have long been thought to correlate to career success. This is why psychological testing has become so prevalent for pre-employment screening and career placement. Many have questioned, however, whether a general mental ability was really more important than specific mental abilities.

A 2020 study published in the Journal of Applied Psychology concluded that both general intelligence and specific mental abilities play an important role in determining career success including income and job attainment.

The importance of the g factor for job success becomes greater as the complexity of the work increases. For occupations with a high degree of complexity, having a higher general intelligence becomes a greater asset.

Health and Longevity

The field of cognitive epidemiology looks at associations between general intelligence and health. Just as health can play a role in influencing intelligence , a person's intelligence may have an impact on their health. Studies have found that high-IQ individuals have a lower risk of:

• Coronary heart disease
• Hypertension
• Some cancers

Research has found that people who have higher general intelligence also tend to be healthier and live longer, although the reasons for this are not entirely clear.  

Research also suggests that people with higher intelligence scores also tend to earn higher incomes. However, it is important to note that other factors play a mediating role including education, occupation, and socioeconomic background.

While the g factor has a number of effects, other variables are also important. Factors such as socioeconomic status and emotional intelligence , for example, can interact with general intelligence and play a major part in determining a person's success.

Challenges of General Intelligence

The notion that intelligence could be measured and summarized by a single number on an IQ test was controversial, even during Spearman's time. IQ and intelligence testing have remained topics of debate ever since. While influential, the g factor is just one way of thinking about intelligence.

Thurstone's Primary Mental Abilities

Some psychologists, including L.L. Thurstone, challenged the concept of a g-factor. Thurstone instead identified a number of what he referred to as primary mental abilities :

• Associative memory
• Number facility
• Perceptual speed
• Spatial visualization
• Verbal comprehension

He suggested that all people possess these mental abilities, although to varying degrees. People could be low in some areas and high in others.

Gardner's Multiple Intelligences

More recently, psychologists such as Howard Gardner have argued against the notion that a single general intelligence can accurately capture all of human mental ability. Gardner instead proposed that multiple intelligences exist.

Each intelligence represents abilities in a certain domain such as visual-spatial intelligence, verbal-linguistic intelligence, and logical-mathematical intelligence.

Research today points to an underlying mental ability that contributes to performance on many cognitive tasks. IQ scores, which are designed to measure this general intelligence, are also thought to influence an individual's overall success in life.

However, while IQ can play a role in academic and life success , other factors such as childhood experiences, educational experiences, socioeconomic status, motivation , maturity, and personality also play a critical role in determining overall success.

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

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

Diane f. halpern.

1 Department of Psychology, Claremont McKenna College, Emerita, Altadena, CA 91001, USA

Dana S. Dunn

2 Department of Psychology, Moravian College, Bethlehem, PA 18018, USA; ude.naivarom@nnud

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.

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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9.1 Defining and Measuring Intelligence

Learning objectives.

• Define intelligence and list the different types of intelligences psychologists study.
• Summarize the characteristics of a scientifically valid intelligence test.
• Outline the biological and environmental determinants of intelligence.

Psychologists have long debated how to best conceptualize and measure intelligence (Sternberg, 2003). These questions include how many types of intelligence there are, the role of nature versus nurture in intelligence, how intelligence is represented in the brain, and the meaning of group differences in intelligence.

General (g) Versus Specific (s) Intelligences

In the early 1900s, the French psychologist Alfred Binet (1857–1914) and his colleague Henri Simon (1872–1961) began working in Paris to develop a measure that would differentiate students who were expected to be better learners from students who were expected to be slower learners. The goal was to help teachers better educate these two groups of students. Binet and Simon developed what most psychologists today regard as the first intelligence test, which consisted of a wide variety of questions that included the ability to name objects, define words, draw pictures, complete sentences, compare items, and construct sentences.

Binet and Simon (Binet, Simon, & Town, 1915; Siegler, 1992) believed that the questions they asked their students, even though they were on the surface dissimilar, all assessed the basic abilities to understand, reason, and make judgments. And it turned out that the correlations among these different types of measures were in fact all positive; students who got one item correct were more likely to also get other items correct, even though the questions themselves were very different.

On the basis of these results, the psychologist Charles Spearman (1863–1945) hypothesized that there must be a single underlying construct that all of these items measure. He called the construct that the different abilities and skills measured on intelligence tests have in common the general intelligence factor (g) . Virtually all psychologists now believe that there is a generalized intelligence factor, g, that relates to abstract thinking and that includes the abilities to acquire knowledge, to reason abstractly, to adapt to novel situations, and to benefit from instruction and experience (Gottfredson, 1997; Sternberg, 2003). People with higher general intelligence learn faster.

Soon after Binet and Simon introduced their test, the American psychologist Lewis Terman (1877–1956) developed an American version of Binet’s test that became known as the Stanford-Binet Intelligence Test . The Stanford-Binet is a measure of general intelligence made up of a wide variety of tasks including vocabulary, memory for pictures, naming of familiar objects, repeating sentences, and following commands.

Although there is general agreement among psychologists that g exists, there is also evidence for specific intelligence (s) , a measure of specific skills in narrow domains . One empirical result in support of the idea of s comes from intelligence tests themselves. Although the different types of questions do correlate with each other, some items correlate more highly with each other than do other items; they form clusters or clumps of intelligences.

One distinction is between fluid intelligence , which refers to the capacity to learn new ways of solving problems and performing activities, and crystallized intelligence , which refers to the accumulated knowledge of the world we have acquired throughout our lives (Salthouse, 2004). These intelligences must be different because crystallized intelligence increases with age—older adults are as good as or better than young people in solving crossword puzzles—whereas fluid intelligence tends to decrease with age (Horn, Donaldson, & Engstrom, 1981; Salthouse, 2004).

Other researchers have proposed even more types of intelligences. L. L. Thurstone (1938) proposed that there were seven clusters of primary mental abilities , made up of word fluency, verbal comprehension, spatial ability, perceptual speed, numerical ability, inductive reasoning, and memory. But even these dimensions tend to be at least somewhat correlated, showing again the importance of g.

One advocate of the idea of multiple intelligences is the psychologist Robert Sternberg. Sternberg has proposed a triarchic (three-part) theory of intelligence that proposes that people may display more or less analytical intelligence, creative intelligence, and practical intelligence . Sternberg (1985, 2003) argued that traditional intelligence tests assess analytical intelligence, the ability to answer problems with a single right answer, but that they do not well assess creativity (the ability to adapt to new situations and create new ideas) or practicality (e.g., the ability to write good memos or to effectively delegate responsibility).

As Sternberg proposed, research has found that creativity is not highly correlated with analytical intelligence (Furnham & Bachtiar, 2008), and exceptionally creative scientists, artists, mathematicians, and engineers do not score higher on intelligence than do their less creative peers (Simonton, 2000). Furthermore, the brain areas that are associated with convergent thinking , thinking that is directed toward finding the correct answer to a given problem, are different from those associated with divergent thinking , the ability to generate many different ideas for or solutions to a single problem (Tarasova, Volf, & Razoumnikova, 2010). On the other hand, being creative often takes some of the basic abilities measured by g, including the abilities to learn from experience, to remember information, and to think abstractly (Bink & Marsh, 2000).

Test your divergent thinking. How many uses for a paper clip can you think of?

Dead Hochman – paper clips – CC BY 2.0.

Studies of creative people suggest at least five components that are likely to be important for creativity:

• Expertise . Creative people have carefully studied and know a lot about the topic that they are working in. Creativity comes with a lot of hard work (Ericsson, 1998; Weisberg, 2006).
• Imaginative thinking . Creative people often view a problem in a visual way, allowing them to see it from a new and different point of view.
• Risk taking . Creative people are willing to take on new but potentially risky approaches.
• Intrinsic interest . Creative people tend to work on projects because they love doing them, not because they are paid for them. In fact, research has found that people who are paid to be creative are often less creative than those who are not (Hennessey & Amabile, 2010).
• Working in a creative environment . Creativity is in part a social phenomenon. Simonton (1992) found that the most creative people were supported, aided, and challenged by other people working on similar projects.

The last aspect of the triarchic model, practical intelligence, refers primarily to intelligence that cannot be gained from books or formal learning. Practical intelligence represents a type of “street smarts” or “common sense” that is learned from life experiences. Although a number of tests have been devised to measure practical intelligence (Sternberg, Wagner, & Okagaki, 1993; Wagner & Sternberg, 1985), research has not found much evidence that practical intelligence is distinct from g or that it is predictive of success at any particular tasks (Gottfredson, 2003). Practical intelligence may include, at least in part, certain abilities that help people perform well at specific jobs, and these abilities may not always be highly correlated with general intelligence (Sternberg, Wagner, & Okagaki, 1993). On the other hand, these abilities or skills are very specific to particular occupations and thus do not seem to represent the broader idea of intelligence.

Another champion of the idea of multiple intelligences is the psychologist Howard Gardner (1983, 1999). Gardner argued that it would be evolutionarily functional for different people to have different talents and skills, and proposed that there are eight intelligences that can be differentiated from each other ( Table 9.1 “Howard Gardner’s Eight Specific Intelligences” ). Gardner noted that some evidence for multiple intelligences comes from the abilities of autistic savants , people who score low on intelligence tests overall but who nevertheless may have exceptional skills in a given domain, such as math, music, art, or in being able to recite statistics in a given sport (Treffert & Wallace, 2004).

Table 9.1 Howard Gardner’s Eight Specific Intelligences

Source: Adapted from Gardner, H. (1999). Intelligence reframed: Multiple intelligences for the 21st century . New York, NY: Basic Books.

Although intelligence is often conceptualized in a general way (as the g factor), there is a variety of specific skills that can be useful for particular tasks.

Nayu Kim – Playing piano – CC BY 2.0; Helgi Halldórsson – Run faster, Jump higher – CC BY-SA 2.0; Thomas Hawk – Bahamian Clown – CC BY-NC 2.0; Sudipta Mallick – painter – CC BY 2.0; Blondinrikard Fröberg – Torsten, math teacher – CC BY 2.0.

The idea of multiple intelligences has been influential in the field of education, and teachers have used these ideas to try to teach differently to different students. For instance, to teach math problems to students who have particularly good kinesthetic intelligence, a teacher might encourage the students to move their bodies or hands according to the numbers. On the other hand, some have argued that these “intelligences” sometimes seem more like “abilities” or “talents” rather than real intelligence. And there is no clear conclusion about how many intelligences there are. Are sense of humor, artistic skills, dramatic skills, and so forth also separate intelligences? Furthermore, and again demonstrating the underlying power of a single intelligence, the many different intelligences are in fact correlated and thus represent, in part, g (Brody, 2003).

Measuring Intelligence: Standardization and the Intelligence Quotient

The goal of most intelligence tests is to measure g, the general intelligence factor. Good intelligence tests are reliable , meaning that they are consistent over time, and also demonstrate construct validity , meaning that they actually measure intelligence rather than something else. Because intelligence is such an important individual difference dimension, psychologists have invested substantial effort in creating and improving measures of intelligence, and these tests are now the most accurate of all psychological tests. In fact, the ability to accurately assess intelligence is one of the most important contributions of psychology to everyday public life.

Intelligence changes with age. A 3-year-old who could accurately multiply 183 by 39 would certainly be intelligent, but a 25-year-old who could not do so would be seen as unintelligent. Thus understanding intelligence requires that we know the norms or standards in a given population of people at a given age. The standardization of a test involves giving it to a large number of people at different ages and computing the average score on the test at each age level .

It is important that intelligence tests be standardized on a regular basis, because the overall level of intelligence in a population may change over time. The Flynn effect refers to the observation that scores on intelligence tests worldwide have increased substantially over the past decades (Flynn, 1999). Although the increase varies somewhat from country to country, the average increase is about 3 IQ points every 10 years. There are many explanations for the Flynn effect, including better nutrition, increased access to information, and more familiarity with multiple-choice tests (Neisser, 1998). But whether people are actually getting smarter is debatable (Neisser, 1997).

Once the standardization has been accomplished, we have a picture of the average abilities of people at different ages and can calculate a person’s mental age , which is the age at which a person is performing intellectually . If we compare the mental age of a person to the person’s chronological age, the result is the intelligence quotient (IQ) , a measure of intelligence that is adjusted for age . A simple way to calculate IQ is by using the following formula:

IQ = mental age ÷ chronological age × 100.

Thus a 10-year-old child who does as well as the average 10-year-old child has an IQ of 100 (10 ÷ 10 × 100), whereas an 8-year-old child who does as well as the average 10-year-old child would have an IQ of 125 (10 ÷ 8 × 100). Most modern intelligence tests are based the relative position of a person’s score among people of the same age, rather than on the basis of this formula, but the idea of an intelligence “ratio” or “quotient” provides a good description of the score’s meaning.

A number of scales are based on the IQ. The Wechsler Adult lntelligence Scale (WAIS) is the most widely used intelligence test for adults (Watkins, Campbell, Nieberding, & Hallmark, 1995). The current version of the WAIS, the WAIS-IV, was standardized on 2,200 people ranging from 16 to 90 years of age. It consists of 15 different tasks, each designed to assess intelligence, including working memory, arithmetic ability, spatial ability, and general knowledge about the world (see Figure 9.4 “Sample Items From the Wechsler Adult Intelligence Scale (WAIS)” ). The WAIS-IV yields scores on four domains: verbal, perceptual, working memory, and processing speed. The reliability of the test is high (more than 0.95), and it shows substantial construct validity. The WAIS-IV is correlated highly with other IQ tests such as the Stanford-Binet, as well as with criteria of academic and life success, including college grades, measures of work performance, and occupational level. It also shows significant correlations with measures of everyday functioning among the mentally retarded.

The Wechsler scale has also been adapted for preschool children in the form of the Wechsler Primary and Preschool Scale of Intelligence (WPPSI-III) and for older children and adolescents in the form of the Wechsler Intelligence Scale for Children (WISC-IV) .

Figure 9.4 Sample Items From the Wechsler Adult Intelligence Scale (WAIS)

Source: Adapted from Thorndike, R. L., & Hagen, E. P. (1997). Cognitive Abilities Test (Form 5): Research handbook . Chicago, IL: Riverside Publishing.

The intelligence tests that you may be most familiar with are aptitude tests , which are designed to measure one’s ability to perform a given task, for instance, to do well in college or in postgraduate training. Most U.S. colleges and universities require students to take the Scholastic Assessment Test (SAT) or the American College Test (ACT), and postgraduate schools require the Graduate Record Examination (GRE), Medical College Admissions Test (MCAT), or the Law School Admission Test (LSAT). These tests are useful for selecting students because they predict success in the programs that they are designed for, particularly in the first year of the program (Kuncel, Hezlett, & Ones, 2010). These aptitude tests also measure, in part, intelligence. Frey and Detterman (2004) found that the SAT correlated highly (between about r = .7 and r = .8) with standard measures of intelligence.

Intelligence tests are also used by industrial and organizational psychologists in the process of personnel selection . Personnel selection is the use of structured tests to select people who are likely to perform well at given jobs (Schmidt & Hunter, 1998). The psychologists begin by conducting a job analysis in which they determine what knowledge, skills, abilities, and personal characteristics ( KSAPs ) are required for a given job. This is normally accomplished by surveying and/or interviewing current workers and their supervisors. Based on the results of the job analysis, the psychologists choose selection methods that are most likely to be predictive of job performance. Measures include tests of cognitive and physical ability and job knowledge tests, as well as measures of IQ and personality.

The Biology of Intelligence

The brain processes underlying intelligence are not completely understood, but current research has focused on four potential factors: brain size, sensory ability, speed and efficience of neural transmission, and working memory capacity.

There is at least some truth to the idea that smarter people have bigger brains. Studies that have measured brain volume using neuroimaging techniques find that larger brain size is correlated with intelligence (McDaniel, 2005), and intelligence has also been found to be correlated with the number of neurons in the brain and with the thickness of the cortex (Haier, 2004; Shaw et al., 2006). It is important to remember that these correlational findings do not mean that having more brain volume causes higher intelligence. It is possible that growing up in a stimulating environment that rewards thinking and learning may lead to greater brain growth (Garlick, 2003), and it is also possible that a third variable, such as better nutrition, causes both brain volume and intelligence.

Another possibility is that the brains of more intelligent people operate faster or more efficiently than the brains of the less intelligent. Some evidence supporting this idea comes from data showing that people who are more intelligent frequently show less brain activity (suggesting that they need to use less capacity) than those with lower intelligence when they work on a task (Haier, Siegel, Tang, & Abel, 1992). And the brains of more intelligent people also seem to run faster than the brains of the less intelligent. Research has found that the speed with which people can perform simple tasks—such as determining which of two lines is longer or pressing, as quickly as possible, one of eight buttons that is lighted—is predictive of intelligence (Deary, Der, & Ford, 2001). Intelligence scores also correlate at about r = .5 with measures of working memory (Ackerman, Beier, & Boyle, 2005), and working memory is now used as a measure of intelligence on many tests.

Although intelligence is not located in a specific part of the brain, it is more prevalent in some brain areas than others. Duncan et al. (2000) administered a variety of intelligence tasks and observed the places in the cortex that were most active. Although different tests created different patterns of activation, as you can see in Figure 9.5 “Where Is Intelligence?” , these activated areas were primarily in the outer parts of the cortex, the area of the brain most involved in planning, executive control, and short-term memory.

Figure 9.5 Where Is Intelligence?

fMRI studies have found that the areas of the brain most related to intelligence are in the outer parts of the cortex.

Source: Adapted from Duncan, J., Seitz, R. J., Kolodny, J., Bor, D., Herzog, H., Ahmed, A.,…Emslie, H. (2000). A neural basis for general intelligence. Science, 289 (5478), 457–460.

Is Intelligence Nature or Nurture?

Intelligence has both genetic and environmental causes, and these have been systematically studied through a large number of twin and adoption studies (Neisser et al., 1996; Plomin, DeFries, Craig, & McGuffin, 2003). These studies have found that between 40% and 80% of the variability in IQ is due to genetics, meaning that overall genetics plays a bigger role than does environment in creating IQ differences among individuals (Plomin & Spinath, 2004). The IQs of identical twins correlate very highly ( r = .86), much higher than do the scores of fraternal twins who are less genetically similar ( r = .60). And the correlations between the IQs of parents and their biological children ( r = .42) is significantly greater than the correlation between parents and adopted children ( r = .19). The role of genetics gets stronger as children get older. The intelligence of very young children (less than 3 years old) does not predict adult intelligence, but by age 7 it does, and IQ scores remain very stable in adulthood (Deary, Whiteman, Starr, Whalley, & Fox, 2004).

But there is also evidence for the role of nurture, indicating that individuals are not born with fixed, unchangeable levels of intelligence. Twins raised together in the same home have more similar IQs than do twins who are raised in different homes, and fraternal twins have more similar IQs than do nontwin siblings, which is likely due to the fact that they are treated more similarly than are siblings.

The fact that intelligence becomes more stable as we get older provides evidence that early environmental experiences matter more than later ones. Environmental factors also explain a greater proportion of the variance in intelligence for children from lower-class households than they do for children from upper-class households (Turkheimer, Haley, Waldron, D’Onofrio, & Gottesman, 2003). This is because most upper-class households tend to provide a safe, nutritious, and supporting environment for children, whereas these factors are more variable in lower-class households.

Social and economic deprivation can adversely affect IQ. Children from households in poverty have lower IQs than do children from households with more resources even when other factors such as education, race, and parenting are controlled (Brooks-Gunn & Duncan, 1997). Poverty may lead to diets that are undernourishing or lacking in appropriate vitamins, and poor children may also be more likely to be exposed to toxins such as lead in drinking water, dust, or paint chips (Bellinger & Needleman, 2003). Both of these factors can slow brain development and reduce intelligence.

If impoverished environments can harm intelligence, we might wonder whether enriched environments can improve it. Government-funded after-school programs such as Head Start are designed to help children learn. Research has found that attending such programs may increase intelligence for a short time, but these increases rarely last after the programs end (McLoyd, 1998; Perkins & Grotzer, 1997). But other studies suggest that Head Start and similar programs may improve emotional intelligence and reduce the likelihood that children will drop out of school or be held back a grade (Reynolds, Temple, Robertson, & Mann 2001).

Intelligence is improved by education; the number of years a person has spent in school correlates at about r = .6 with IQ (Ceci, 1991). In part this correlation may be due to the fact that people with higher IQ scores enjoy taking classes more than people with low IQ scores, and they thus are more likely to stay in school. But education also has a causal effect on IQ. Comparisons between children who are almost exactly the same age but who just do or just do not make a deadline for entering school in a given school year show that those who enter school a year earlier have higher IQ than those who have to wait until the next year to begin school (Baltes & Reinert, 1969; Ceci & Williams, 1997). Children’s IQs tend to drop significantly during summer vacations (Huttenlocher, Levine, & Vevea, 1998), a finding that suggests that a longer school year, as is used in Europe and East Asia, is beneficial.

It is important to remember that the relative roles of nature and nurture can never be completely separated. A child who has higher than average intelligence will be treated differently than a child who has lower than average intelligence, and these differences in behaviors will likely amplify initial differences. This means that modest genetic differences can be multiplied into big differences over time.

Psychology in Everyday Life: Emotional Intelligence

Although most psychologists have considered intelligence a cognitive ability, people also use their emotions to help them solve problems and relate effectively to others. Emotional intelligence refers to the ability to accurately identify, assess, and understand emotions, as well as to effectively control one’s own emotions (Feldman-Barrett & Salovey, 2002; Mayer, Salovey, & Caruso, 2000).

The idea of emotional intelligence is seen in Howard Gardner’s interpersonal intelligence (the capacity to understand the emotions, intentions, motivations, and desires of other people) and intrapersonal intelligence (the capacity to understand oneself, including one’s emotions). Public interest in, and research on, emotional intellgence became widely prevalent following the publication of Daniel Goleman’s best-selling book, Emotional Intelligence: Why It Can Matter More Than IQ (Goleman, 1998).

There are a variety of measures of emotional intelligence (Mayer, Salovey, & Caruso, 2008; Petrides & Furnham, 2000). One popular measure, the Mayer-Salovey-Caruso Emotional Intelligence Test ( http://www.emotionaliq.org ), includes items about the ability to understand, experience, and manage emotions, such as these:

• What mood(s) might be helpful to feel when meeting in-laws for the very first time?
• Tom felt anxious and became a bit stressed when he thought about all the work he needed to do. When his supervisor brought him an additional project, he felt ____ (fill in the blank).

Contempt most closely combines which two emotions?

• anger and fear
• fear and surprise
• disgust and anger
• surprise and disgust

Debbie just came back from vacation. She was feeling peaceful and content. How well would each of the following actions help her preserve her good mood?

• Action 1: She started to make a list of things at home that she needed to do.
• Action 2: She began thinking about where and when she would go on her next vacation.
• Action 3: She decided it was best to ignore the feeling since it wouldn’t last anyway.

One problem with emotional intelligence tests is that they often do not show a great deal of reliability or construct validity (Føllesdal & Hagtvet, 2009).Although it has been found that people with higher emotional intelligence are also healthier (Martins, Ramalho, & Morin, 2010), findings are mixed about whether emotional intelligence predicts life success—for instance, job performance (Harms & Credé, 2010). Furthermore, other researchers have questioned the construct validity of the measures, arguing that emotional intelligence really measures knowledge about what emotions are, but not necessarily how to use those emotions (Brody, 2004), and that emotional intelligence is actually a personality trait, a part of g, or a skill that can be applied in some specific work situations—for instance, academic and work situations (Landy, 2005).

Although measures of the ability to understand, experience, and manage emotions may not predict effective behaviors, another important aspect of emotional intelligence— emotion regulation —does. Emotion regulation refers to the ability to control and productively use one’s emotions. Research has found that people who are better able to override their impulses to seek immediate gratification and who are less impulsive also have higher cognitive and social intelligence. They have better SAT scores, are rated by their friends as more socially adept, and cope with frustration and stress better than those with less skill at emotion regulation (Ayduk et al., 2000; Eigsti et al., 2006; Mischel & Ayduk, 2004).

Because emotional intelligence seems so important, many school systems have designed programs to teach it to their students. However, the effectiveness of these programs has not been rigorously tested, and we do not yet know whether emotional intelligence can be taught, or if learning it would improve the quality of people’s lives (Mayer & Cobb, 2000).

Key Takeaways

• Intelligence is the ability to think, to learn from experience, to solve problems, and to adapt to new situations. Intelligence is important because it has an impact on many human behaviors.
• Psychologists believe that there is a construct that accounts for the overall differences in intelligence among people, known as general intelligence (g).
• There is also evidence for specific intelligences (s), measures of specific skills in narrow domains, including creativity and practical intelligence.
• The intelligence quotient (IQ) is a measure of intelligence that is adjusted for age. The Wechsler Adult lntelligence Scale (WAIS) is the most widely used IQ test for adults.
• Brain volume, speed of neural transmission, and working memory capacity are related to IQ.
• Between 40% and 80% of the variability in IQ is due to genetics, meaning that overall genetics plays a bigger role than does environment in creating IQ differences among individuals.
• Intelligence is improved by education and may be hindered by environmental factors such as poverty.
• Emotional intelligence refers to the ability to identify, assess, manage, and control one’s emotions. People who are better able to regulate their behaviors and emotions are also more successful in their personal and social encounters.

Exercises and Critical Thinking

• Consider your own IQ. Are you smarter than the average person? What specific intelligences do you think you excel in?
• Did your parents try to improve your intelligence? Do you think their efforts were successful?
• Consider the meaning of the Flynn effect. Do you think people are really getting smarter?
• Give some examples of how emotional intelligence (or the lack of it) influences your everyday life and the lives of other people you know.

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Intelligence

IQ, Giftedness

Reviewed by Psychology Today Staff

Reading a road map upside-down, excelling at chess, and generating synonyms for "brilliant" may seem like three different skills. But each is thought to be a measurable indicator of general intelligence or "g," a construct that includes problem-solving ability, spatial manipulation, and language acquisition that is relatively stable across a person's lifetime.

IQ—or intelligence quotient—is the standard most widely used to assess general intelligence. IQ tests seek to measures a variety of intellectual skills that include verbal, non-verbal and spatial. Any person from any walk of life can be highly intelligent, and scoring high on one sub-test tends to correlate with high scores in other tests, though this is not always the case. IQ tests compare a person's performance with that of other people who are the same age—what’s known as a normative sample.

Research has shown that IQ is generally strongly correlated with positive life outcomes, including health and longevity, job performance, and adult income. It is also protective in ways that are not fully understood: People with high IQs seem to be at an advantage in coping with traumatic events—they are less likely to develop full-blown PTSD and more capable of overcoming it when they do—and may experience less rapid decline during the course of Alzheimer's Disease.

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There may be. Research suggest that people who are high in the personality trait of openness tended to be more mentally flexible and verbally fluent and more likely to take creative, unconventional approaches to solving problems. Extraverted people were also more likely to score higher on test of verbal fluency because they tended to talk more, and be less concerned about mistakes. And people higher in the trait of conscientiousness tend to perform better on memory tasks because they’re generally better organized and willing to work harder.

No, not even close. This pervasive pop-culture myth—one survey found that 50 percent of science teachers believed it was true—has no basis in reality. We use 100 percent of our brains every day, as is clearly shown by functional magnetic resonance imaging scans. Neurons only make up 10 percent of the cells in our brains but the other 90 percent work full-time, maintaining homeostasis, providing structural support, and removing pathogens. The source of the famous notion is pioneering psychologist William James, who once write that “we are making use of only a small part of our possible mental and physical resources,” and he was right—but our untapped potential has little to do with our brain cells.

No, a larger brain does not make a person more intelligent . Some studies have suggested, for example, that a larger brain may contribute as much as 6 percent boost to one’s intelligence, but this research has come into question, and some experts doubt that a larger brain would bring any advantages because it would necessarily demand greater energy consumption, potentially contributing a drag on a person’s resources. Considering all animals, including humans, there is a theory that the size of a creature’s brain relative the size of their body may confer a higher level of intelligence, though—and human brains constitute up a higher ratio of our body size than do the brains of many other animals.

The theory known as “the Flynn effect” maintains that average IQ scores have and will continue to rise over time, primarily due to changes in our environment—better diet and greater access to education and information, for example. But in recent years, IQ scores appear to declining —one-half to two points per decade—possibly a reflection of a decline in those same environmental factors.

In the early 1980s, Harvard researcher Howard Gardner proposed that, along with IQ, there may be multiple kinds of intelligence that people possess in varying quantities, including visual-spatial, logical-mathematical, and interpersonal (emotional) intelligence. According to this theory, someone high in interpersonal intelligence would likely excel at cooperating within a group, while someone with high levels of logical-mathematical intelligence would have a heightened capacity to understand numbers, patterns, and logic. But while the concept has gained much public attention — and is often used as part of personality or employment tests—many researchers dispute the idea of different intelligences and have criticized Gardner's theory, criteria, and research designs. For example, emotional intelligence cannot be reliably measured through testing as general intelligence can, the critics argue, and so it lacks the power to explain differences between people.

For more, see Emotional Intelligence .

A critical prerequisite for intellectual growth is the idea that one can gain mastery and improve on native ability. While one can indeed improve memory and problem-solving abilities over time via practice or environmental pressure, this does not mean that one is becoming "more" intelligent. IQ scores do not fluctuate markedly over the course of a person's lifetime, and they tend to consistently correlate with other tests, such as the SAT. Many supplements and computer programs are marketed as brain boosters, but there is little long-term evidence to support those claims.

One reason people attend, and stay in, school through high school, college, and beyond, is to become more intelligent. And while additional years of schooling should increase one’s store of general knowledge and career prospects, until recently research had not concluded that formal education also increased one’s IQ. But then a meta-analysis determined that each additional year of schooling appeared to raise IQ by one to five points. Exactly how schooling boosts IQ is not clear, though, nor is whether or how the effect accumulates over many years of education. But experts point to the study as a sign of a more crucial truth: that an individual’s intelligence can change over time.

The right ones seem to be able to. Successful players of games requiring strategy, creativity , and teamwork , research finds, tend to have a higher IQ than others. A similar connection between IQ and gaming success was not found in studies of first-person shooter-type games that rely on hand-eye coordination. But other studies find that playing certain games can actually help boost IQ. Studies that involved popular puzzle-based strategy games, particularly those involving complex, changing environments, led to gains in problem solving, spatial skills, and persistence. Significantly, such results were not found in studies of so-called “brain-training” games marketed as cognitive boosters.

A growing body of research supports the idea that exercise can help boost cognition, especially moderate-to-vigorous aerobic exercise. In one example, researchers found that, for older people, time spent in moderate-to-vigorous cardiovascular exercise was positively correlated with increases in “fluid” intelligence—processing speed, memory, and reasoning. In the same study, sedentary time was correlated with boosts in “crystallized” intelligence, such as vocabulary development. Light physical activity, however, provided little cognitive benefit.

Stimulants like methylphenidate ( Ritalin ) and mixed amphetamine salts ( Adderall ) deliver proven benefits for many people with ADHD. But the question of whether such stimulants could improve cognitive ability is highly controversial. Recent research, however, suggests that the drugs do not deliver any cognitive enhancement—aside from an increase in confidence , interest, and energy in people’s tasks. A boost in optimism when tackling a difficult assignment is not the same as a boost in intelligence, but it can help deliver better results by motivating people to deploy their existing cognitive resources more vigorously.

While most research finds very little difference in the mean IQ between men and women,  men are overrepresented at the tails of the distribution. This means that more men than women have scores that reflect severe retardation, and more men than women score in the profoundly gifted or "genius" range. Research shows that men are a lot more likely than women to overstate their intelligence. In one example, 71 percent of men claimed to be smarter than the average person, compared to just 59 percent of women.

There’s a persistent stereotype that people high in the trait of psychopathy are smarter than most others because they are skilled at both presenting a false façade to potential victims and at manipulating targets into doing what they want those people to do. But research shows that this is not the case. In fact, some studies find, psychopaths are generally less intelligent than others, particularly so when it comes to capabilities like recognizing emotions in others. So why do they seem so intelligent and devious? Researchers suggest that it’s because they constantly target people with schemes, to the point that even if their percentage of success is quite low, they do occasionally rope in a target.

No, but many become obsessed with the idea that they could be. Studies of narcissism have found that a belief in their intellectual superiority is often crucial to their identity . Narcissists of the type known as grandiose are highly likely to believe they are smarter than other people; some place an especially high value on IQ testing. Vulnerable narcissists, on the other hand, who tend to be more introverted, insecure, and neurotic , are not as likely to believe that they are smarter than others, but they are more likely than others to find taking intelligence tests to be highly stressful .

It has long been believed that left-handed people are smarter than right-handers, but research does not support the notion. In fact, a meta-analysis of studies including more than 20,000 people found that right-handers had a slightly higher IQ, on average, than left-handers, but the difference was not significant.

This is emerging as a core philosophical question as AI systems increase in power and humans become more concerned about how many aspects of work, decision-making , and even creative production could eventually be turned over to computer intelligence. But there are some tasks humans perform far better, such as image recognition, and humans can also be seen as more flexible and adaptive learners. Some argue that the human propensity to ask original questions sets us apart from machine intelligence, along with the ability to leverage others people’s intelligence while solving problems together.

The vast majority of people claim that they find intelligence to be among the most desirable traits in a potential romantic partner. As with other favorable traits, though, this appeal most strongly influences initial interest in a new partner. Once people begin dating, other factors like personality and conflict style play important roles in determining whether a couple will stay together. But for a certain group, intelligence is their primary erotic turn-on . Some research suggests that these individuals, known as sapiosexuals , may represent a distinct sexual orientation . Interestingly, whether one finds intelligence to be a turn-on does not seem to be determined by one’s own level of intelligence. But for sapiosexuals, looks and even gender may not be as vital a factor in sexual attraction as intelligence.

Generally, yes. Studies of adolescents found that more intelligent individuals were more well-liked by peers than others—although other research finds that more intelligent people tend to like fewer people than others, and to prefer being with other intelligent people. In the dating pool, smarter people may be at an advantage because others’ preference for being with smart people is strongest at the beginning of relationships.

Generally, it’s an advantage, although some research suggests that the most intelligent people may be at a disadvantage . When people were asked to consider whether they would want to date people in different percentiles of intelligence, the favorability rankings increased steadily from the 50th percentile to the 90th, at which point interest declined. This research is consistent with other findings that even the most appealing traits tend not be desired in the extreme.

In surveys, men and women both claim that they are at least as attracted to intelligence as they are to good looks. In practice, especially for men, that is not always the case. The idea that highly intelligent women may be at a disadvantage in the dating pool , research suggests, is no myth: Men tend to shy away from women who are clearly more intelligent than they are. (Women are less likely to have the same reaction to intelligent men.) Experts suggest that intelligent women avoid dumbing themselves down to attract a partner or going out of their way to support a partner’s ego, as in the end those strategies are likely to lead to unfulfilling relationships.

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Metacognition, or thinking about how they think, can help teens understand their strengths and weaknesses and the strategies that are most useful to them in specific situations.

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At any moment, someone’s aggravating behavior or our own bad luck can set us off on an emotional spiral that threatens to derail our entire day. Here’s how we can face our triggers with less reactivity so that we can get on with our lives.

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6 Thinking and Intelligence

What is the best way to solve a problem? How does a person who has never seen or touched snow in real life develop an understanding of the concept of snow? How do young children acquire the ability to learn language with no formal instruction? Psychologists who study thinking explore questions like these and are called cognitive psychologists.

Cognitive psychologists also study intelligence. What is intelligence, and how does it vary from person to person? Are “street smarts” a kind of intelligence, and if so, how do they relate to other types of intelligence? What does an IQ test really measure? These questions and more will be explored in this chapter as you study thinking and intelligence.

In other chapters, we discussed the cognitive processes of perception, learning, and memory. In this chapter, we will focus on high-level cognitive processes. As a part of this discussion, we will consider thinking and briefly explore the development and use of language. We will also discuss problem solving and creativity before ending with a discussion of how intelligence is measured and how our biology and environments interact to affect intelligence. After finishing this chapter, you will have a greater appreciation of the higher-level cognitive processes that contribute to our distinctiveness as a species.

Learning Objectives

By the end of this section, you will be able to:

• Describe cognition
• Distinguish concepts and prototypes
• Explain the difference between natural and artificial concepts
• Describe how schemata are organized and constructed

Imagine all of your thoughts as if they were physical entities, swirling rapidly inside your mind. How is it possible that the brain is able to move from one thought to the next in an organized, orderly fashion? The brain is endlessly perceiving, processing, planning, organizing, and remembering—it is always active. Yet, you don’t notice most of your brain’s activity as you move throughout your daily routine. This is only one facet of the complex processes involved in cognition. Simply put,  cognition  is thinking, and it encompasses the processes associated with perception, knowledge, problem solving, judgment, language, and memory. Scientists who study cognition are searching for ways to understand how we integrate, organize, and utilize our conscious cognitive experiences without being aware of all of the unconscious work that our brains are doing (for example, Kahneman, 2011).

Upon waking each morning, you begin thinking—contemplating the tasks that you must complete that day. In what order should you run your errands? Should you go to the bank, the cleaners, or the grocery store first? Can you get these things done before you head to class or will they need to wait until school is done? These thoughts are one example of cognition at work. Exceptionally complex, cognition is an essential feature of human consciousness, yet not all aspects of cognition are consciously experienced.

Cognitive psychology  is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem solving, in addition to other cognitive processes. Cognitive psychologists strive to determine and measure different types of intelligence, why some people are better at problem solving than others, and how emotional intelligence affects success in the workplace, among countless other topics. They also sometimes focus on how we organize thoughts and information gathered from our environments into meaningful categories of thought, which will be discussed later.

Concepts and Prototypes

The human nervous system is capable of handling endless streams of information. The senses serve as the interface between the mind and the external environment, receiving stimuli and translating it into nerve impulses that are transmitted to the brain. The brain then processes this information and uses the relevant pieces to create thoughts, which can then be expressed through language or stored in memory for future use. To make this process more complex, the brain does not gather information from external environments only. When thoughts are formed, the mind synthesizes information from emotions and memories ( Figure 7.2 ). Emotion and memory are powerful influences on both our thoughts and behaviors.

In order to organize this staggering amount of information, the mind has developed a “file cabinet” of sorts in the mind. The different files stored in the file cabinet are called concepts.  Concepts  are categories or groupings of linguistic information, images, ideas, or memories, such as life experiences. Concepts are, in many ways, big ideas that are generated by observing details, and categorizing and combining these details into cognitive structures. You use concepts to see the relationships among the different elements of your experiences and to keep the information in your mind organized and accessible.

Concepts are informed by our semantic memory (you will learn more about semantic memory in a later chapter) and are present in every aspect of our lives; however, one of the easiest places to notice concepts is inside a classroom, where they are discussed explicitly. When you study United States history, for example, you learn about more than just individual events that have happened in America’s past. You absorb a large quantity of information by listening to and participating in discussions, examining maps, and reading first-hand accounts of people’s lives. Your brain analyzes these details and develops an overall understanding of American history. In the process, your brain gathers details that inform and refine your understanding of related concepts like democracy, power, and freedom.

Concepts can be complex and abstract, like justice, or more concrete, like types of birds. In psychology, for example, Piaget’s stages of development are abstract concepts. Some concepts, like tolerance, are agreed upon by many people because they have been used in various ways over many years. Other concepts, like the characteristics of your ideal friend or your family’s birthday traditions, are personal and individualized. In this way, concepts touch every aspect of our lives, from our many daily routines to the guiding principles behind the way governments function.

Another technique used by your brain to organize information is the identification of prototypes for the concepts you have developed. A  prototype  is the best example or representation of a concept. For example, what comes to your mind when you think of a dog? Most likely your early experiences with dogs will shape what you imagine. If your first pet was a Golden Retriever, there is a good chance that this would be your prototype for the category of dogs.

Natural and Artificial Concepts

In psychology, concepts can be divided into two categories, natural and artificial.  Natural concepts  are created “naturally” through your experiences and can be developed from either direct or indirect experiences. For example, if you live in Essex Junction, Vermont, you have probably had a lot of direct experience with snow. You’ve watched it fall from the sky, you’ve seen lightly falling snow that barely covers the windshield of your car, and you’ve shoveled out 18 inches of fluffy white snow as you’ve thought, “This is perfect for skiing.” You’ve thrown snowballs at your best friend and gone sledding down the steepest hill in town. In short, you know snow. You know what it looks like, smells like, tastes like, and feels like. If, however, you’ve lived your whole life on the island of Saint Vincent in the Caribbean, you may never have actually seen snow, much less tasted, smelled, or touched it. You know snow from the indirect experience of seeing pictures of falling snow—or from watching films that feature snow as part of the setting. Either way, snow is a natural concept because you can construct an understanding of it through direct observations, experiences with snow, or indirect knowledge (such as from films or books) ( Figure 7.3 ).

An  artificial concept , on the other hand, is a concept that is defined by a specific set of characteristics. Various properties of geometric shapes, like squares and triangles, serve as useful examples of artificial concepts. A triangle always has three angles and three sides. A square always has four equal sides and four right angles. Mathematical formulas, like the equation for area (length × width), are artificial concepts defined by specific sets of characteristics that are always the same. Artificial concepts can enhance the understanding of a topic by building on one another. For example, before learning the concept of “area of a square” (and the formula to find it), you must understand what a square is. Once the concept of “area of a square” is understood, an understanding of area for other geometric shapes can be built upon the original understanding of area. The use of artificial concepts to define an idea is crucial to communicating with others and engaging in complex thought. According to Goldstone and Kersten (2003), concepts act as building blocks and can be connected in countless combinations to create complex thoughts.

A  schema  is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.

There are several types of schemata. A  role schema  makes assumptions about how individuals in certain roles will behave (Callero, 1994). For example, imagine you meet someone who introduces himself as a firefighter. When this happens, your brain automatically activates the “firefighter schema” and begins making assumptions that this person is brave, selfless, and community-oriented. Despite not knowing this person, already you have unknowingly made judgments about him. Schemata also help you fill in gaps in the information you receive from the world around you. While schemata allow for more efficient information processing, there can be problems with schemata, regardless of whether they are accurate: Perhaps this particular firefighter is not brave, he just works as a firefighter to pay the bills while studying to become a children’s librarian.

An  event schema , also known as a  cognitive script , is a set of behaviors that can feel like a routine. Think about what you do when you walk into an elevator ( Figure 7.4 ). First, the doors open and you wait to let exiting passengers leave the elevator car. Then, you step into the elevator and turn around to face the doors, looking for the correct button to push. You never face the back of the elevator, do you? And when you’re riding in a crowded elevator and you can’t face the front, it feels uncomfortable, doesn’t it? Interestingly, event schemata can vary widely among different cultures and countries. For example, while it is quite common for people to greet one another with a handshake in the United States, in Tibet, you greet someone by sticking your tongue out at them, and in Belize, you bump fists (Cairns Regional Council, n.d.)

Because event schemata are automatic, they can be difficult to change. Imagine that you are driving home from work or school. This event schema involves getting in the car, shutting the door, and buckling your seatbelt before putting the key in the ignition. You might perform this script two or three times each day. As you drive home, you hear your phone’s ring tone. Typically, the event schema that occurs when you hear your phone ringing involves locating the phone and answering it or responding to your latest text message. So without thinking, you reach for your phone, which could be in your pocket, in your bag, or on the passenger seat of the car. This powerful event schema is informed by your pattern of behavior and the pleasurable stimulation that a phone call or text message gives your brain. Because it is a schema, it is extremely challenging for us to stop reaching for the phone, even though we know that we endanger our own lives and the lives of others while we do it (Neyfakh, 2013) ( Figure 7.5 ).

Remember the elevator? It feels almost impossible to walk in and  not  face the door. Our powerful event schema dictates our behavior in the elevator, and it is no different with our phones. Current research suggests that it is the habit, or event schema, of checking our phones in many different situations that make refraining from checking them while driving especially difficult (Bayer & Campbell, 2012). Because texting and driving has become a dangerous epidemic in recent years, psychologists are looking at ways to help people interrupt the “phone schema” while driving. Event schemata like these are the reason why many habits are difficult to break once they have been acquired. As we continue to examine thinking, keep in mind how powerful the forces of concepts and schemata are to our understanding of the world.

• Define language and demonstrate familiarity with the components of language
• Understand the development of language
• Explain the relationship between language and thinking

Language  is a communication system that involves using words and systematic rules to organize those words to transmit information from one individual to another. While language is a form of communication, not all communication is language. Many species communicate with one another through their postures, movements, odors, or vocalizations. This communication is crucial for species that need to interact and develop social relationships with their conspecifics. However, many people have asserted that it is language that makes humans unique among all of the animal species (Corballis & Suddendorf, 2007; Tomasello & Rakoczy, 2003). This section will focus on what distinguishes language as a special form of communication, how the use of language develops, and how language affects the way we think.

Components of Language

Language, be it spoken, signed, or written, has specific components: a lexicon and grammar.  Lexicon  refers to the words of a given language. Thus, lexicon is a language’s vocabulary.  Grammar  refers to the set of rules that are used to convey meaning through the use of the lexicon (Fernández & Cairns, 2011). For instance, English grammar dictates that most verbs receive an “-ed” at the end to indicate past tense.

Words are formed by combining the various phonemes that make up the language. A  phoneme  (e.g., the sounds “ah” vs. “eh”) is a basic sound unit of a given language, and different languages have different sets of phonemes. Phonemes are combined to form  morphemes , which are the smallest units of language that convey some type of meaning (e.g., “I” is both a phoneme and a morpheme). We use semantics and syntax to construct language. Semantics and syntax are part of a language’s grammar.  Semantics  refers to the process by which we derive meaning from morphemes and words.  Syntax  refers to the way words are organized into sentences (Chomsky, 1965; Fernández & Cairns, 2011).

We apply the rules of grammar to organize the lexicon in novel and creative ways, which allow us to communicate information about both concrete and abstract concepts. We can talk about our immediate and observable surroundings as well as the surface of unseen planets. We can share our innermost thoughts, our plans for the future, and debate the value of a college education. We can provide detailed instructions for cooking a meal, fixing a car, or building a fire. Through our use of words and language, we are able to form, organize, and express ideas, schema, and artificial concepts.

Language Development

Given the remarkable complexity of a language, one might expect that mastering a language would be an especially arduous task; indeed, for those of us trying to learn a second language as adults, this might seem to be true. However, young children master language very quickly with relative ease. B. F.  Skinner  (1957) proposed that language is learned through reinforcement. Noam  Chomsky  (1965) criticized this behaviorist approach, asserting instead that the mechanisms underlying language acquisition are biologically determined. The use of language develops in the absence of formal instruction and appears to follow a very similar pattern in children from vastly different cultures and backgrounds. It would seem, therefore, that we are born with a biological predisposition to acquire a language (Chomsky, 1965; Fernández & Cairns, 2011). Moreover, it appears that there is a critical period for language acquisition, such that this proficiency at acquiring language is maximal early in life; generally, as people age, the ease with which they acquire and master new languages diminishes (Johnson & Newport, 1989; Lenneberg, 1967; Singleton, 1995).

Children begin to learn about language from a very early age ( Table 7.1 ). In fact, it appears that this is occurring even before we are born. Newborns show a preference for their mother’s voice and appear to be able to discriminate between the language spoken by their mother and other languages. Babies are also attuned to the languages being used around them and show preferences for videos of faces that are moving in synchrony with the audio of spoken language versus videos that do not synchronize with the audio (Blossom & Morgan, 2006; Pickens, 1994; Spelke & Cortelyou, 1981).

DIG DEEPER: The Case of Genie

In the fall of 1970, a social worker in the Los Angeles area found a 13-year-old girl who was being raised in extremely neglectful and abusive conditions. The girl, who came to be known as Genie, had lived most of her life tied to a potty chair or confined to a crib in a small room that was kept closed with the curtains drawn. For a little over a decade, Genie had virtually no social interaction and no access to the outside world. As a result of these conditions, Genie was unable to stand up, chew solid food, or speak (Fromkin, Krashen, Curtiss, Rigler, & Rigler, 1974; Rymer, 1993). The police took Genie into protective custody.

Genie’s abilities improved dramatically following her removal from her abusive environment, and early on, it appeared she was acquiring language—much later than would be predicted by critical period hypotheses that had been posited at the time (Fromkin et al., 1974). Genie managed to amass an impressive vocabulary in a relatively short amount of time. However, she never developed a mastery of the grammatical aspects of language (Curtiss, 1981). Perhaps being deprived of the opportunity to learn language during a critical period impeded Genie’s ability to fully acquire and use language.

You may recall that each language has its own set of phonemes that are used to generate morphemes, words, and so on. Babies can discriminate among the sounds that make up a language (for example, they can tell the difference between the “s” in vision and the “ss” in fission); early on, they can differentiate between the sounds of all human languages, even those that do not occur in the languages that are used in their environments. However, by the time that they are about 1 year old, they can only discriminate among those phonemes that are used in the language or languages in their environments (Jensen, 2011; Werker & Lalonde, 1988; Werker & Tees, 1984).

After the first few months of life, babies enter what is known as the babbling stage, during which time they tend to produce single syllables that are repeated over and over. As time passes, more variations appear in the syllables that they produce. During this time, it is unlikely that the babies are trying to communicate; they are just as likely to babble when they are alone as when they are with their caregivers (Fernández & Cairns, 2011). Interestingly, babies who are raised in environments in which sign language is used will also begin to show babbling in the gestures of their hands during this stage (Petitto, Holowka, Sergio, Levy, & Ostry, 2004).

Generally, a child’s first word is uttered sometime between the ages of 1 year to 18 months, and for the next few months, the child will remain in the “one word” stage of language development. During this time, children know a number of words, but they only produce one-word utterances. The child’s early vocabulary is limited to familiar objects or events, often nouns. Although children in this stage only make one-word utterances, these words often carry larger meaning (Fernández & Cairns, 2011). So, for example, a child saying “cookie” could be identifying a cookie or asking for a cookie.

As a child’s lexicon grows, she begins to utter simple sentences and to acquire new vocabulary at a very rapid pace. In addition, children begin to demonstrate a clear understanding of the specific rules that apply to their language(s). Even the mistakes that children sometimes make provide evidence of just how much they understand about those rules. This is sometimes seen in the form of  overgeneralization . In this context, overgeneralization refers to an extension of a language rule to an exception to the rule. For example, in English, it is usually the case that an “s” is added to the end of a word to indicate plurality. For example, we speak of one dog versus two dogs. Young children will overgeneralize this rule to cases that are exceptions to the “add an s to the end of the word” rule and say things like “those two gooses” or “three mouses.” Clearly, the rules of the language are understood, even if the exceptions to the rules are still being learned (Moskowitz, 1978).

Language and Thought

When we speak one language, we agree that words are representations of ideas, people, places, and events. The given language that children learn is connected to their culture and surroundings. But can words themselves shape the way we think about things? Psychologists have long investigated the question of whether language shapes thoughts and actions, or whether our thoughts and beliefs shape our language. Two researchers, Edward Sapir and Benjamin Lee Whorf began this investigation in the 1940s. They wanted to understand how the language habits of a community encourage members of that community to interpret language in a particular manner (Sapir, 1941/1964). Sapir and Whorf proposed that language determines thought. For example, in some languages, there are many different words for love. However, in English, we use the word love for all types of love. Does this affect how we think about love depending on the language that we speak (Whorf, 1956)? Researchers have since identified this view as too absolute, pointing out a lack of empiricism behind what Sapir and Whorf proposed (Abler, 2013; Boroditsky, 2011; van Troyer, 1994). Today, psychologists continue to study and debate the relationship between language and thought.

• Describe problem solving strategies
• Define algorithm and heuristic
• Explain some common roadblocks to effective problem solving and decision making

People face problems every day—usually, multiple problems throughout the day. Sometimes these problems are straightforward: To double a recipe for pizza dough, for example, all that is required is that each ingredient in the recipe is doubled. Sometimes, however, the problems we encounter are more complex. For example, say you have a work deadline, and you must mail a printed copy of a report to your supervisor by the end of the business day. The report is time-sensitive and must be sent overnight. You finished the report last night, but your printer will not work today. What should you do? First, you need to identify the problem and then apply a strategy for solving the problem.

Problem-Solving Strategies

When you are presented with a problem—whether it is a complex mathematical problem or a broken printer, how do you solve it? Before finding a solution to the problem, the problem must first be clearly identified. After that, one of many problem solving strategies can be applied, hopefully resulting in a solution.

A  problem-solving strategy  is a plan of action used to find a solution. Different strategies have different action plans associated with them ( Table 7.2 ). For example, a well-known strategy is  trial and error . The old adage, “If at first, you don’t succeed, try, try again” describes trial and error. In terms of your broken printer, you could try checking the ink levels, and if that doesn’t work, you could check to make sure the paper tray isn’t jammed. Or maybe the printer isn’t actually connected to your laptop. When using trial and error, you would continue to try different solutions until you solved your problem. Although trial and error is not typically one of the most time-efficient strategies, it is a commonly used one.

Another type of strategy is an algorithm. An  algorithm  is a problem-solving formula that provides you with step-by-step instructions used to achieve a desired outcome (Kahneman, 2011). You can think of an algorithm as a recipe with highly detailed instructions that produce the same result every time they are performed. Algorithms are used frequently in our everyday lives, especially in computer science. When you run a search on the Internet, search engines like Google use algorithms to decide which entries will appear first in your list of results. Facebook also uses algorithms to decide which posts to display on your newsfeed. Can you identify other situations in which algorithms are used?

A heuristic is another type of problem solving strategy. While an algorithm must be followed exactly to produce a correct result, a  heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. A “rule of thumb” is an example of a heuristic. Such a rule saves the person time and energy when making a decision, but despite its time-saving characteristics, it is not always the best method for making a rational decision. Different types of heuristics are used in different types of situations, but the impulse to use a heuristic occurs when one of the five conditions is met (Pratkanis, 1989):

• When one is faced with too much information
• When the time to make a decision is limited
• When the decision to be made is unimportant
• When there is access to very little information to use in making the decision
• When an appropriate heuristic happens to come to mind in the same moment

Working backward is a useful heuristic in which you begin solving the problem by focusing on the end result. Consider this example: You live in Washington, D.C., and have been invited to a wedding at 4 PM on Saturday in Philadelphia. Knowing that Interstate 95 tends to back up any day of the week, you need to plan your route and time your departure accordingly. If you want to be at the wedding service by 3:30 PM, and it takes 2.5 hours to get to Philadelphia without traffic, what time should you leave your house? You use the working backward heuristic to plan the events of your day on a regular basis, probably without even thinking about it.

Another useful heuristic is the practice of accomplishing a large goal or task by breaking it into a series of smaller steps. Students often use this common method to complete a large research project or a long essay for school. For example, students typically brainstorm, develop a thesis or main topic, research the chosen topic, organize their information into an outline, write a rough draft, revise and edit the rough draft, develop a final draft, organize the references list, and proofread their work before turning in the project. The large task becomes less overwhelming when it is broken down into a series of small steps.

EVERYDAY CONNECTION: Solving Puzzles

Problem-solving abilities can improve with practice. Many people challenge themselves every day with puzzles and other mental exercises to sharpen their problem-solving skills. Sudoku puzzles appear daily in most newspapers. Typically, a sudoku puzzle is a 9×9 grid. The simple sudoku below ( Figure 7.7 ) is a 4×4 grid. To solve the puzzle, fill in the empty boxes with a single digit: 1, 2, 3, or 4. Here are the rules: The numbers must total 10 in each bolded box, each row, and each column; however, each digit can only appear once in a bolded box, row, and column. Time yourself as you solve this puzzle and compare your time with a classmate.

Here is another popular type of puzzle ( Figure 7.8 ) that challenges your spatial reasoning skills. Connect all nine dots with four connecting straight lines without lifting your pencil from the paper:

Take a look at the “Puzzling Scales” logic puzzle below ( Figure 7.9 ). Sam Loyd, a well-known puzzle master, created and refined countless puzzles throughout his lifetime (Cyclopedia of Puzzles, n.d.).

Not all problems are successfully solved, however. What challenges stop us from successfully solving a problem? Albert Einstein once said, “Insanity is doing the same thing over and over again and expecting a different result.” Imagine a person in a room that has four doorways. One doorway that has always been open in the past is now locked. The person, accustomed to exiting the room by that particular doorway, keeps trying to get out through the same doorway even though the other three doorways are open. The person is stuck—but she just needs to go to another doorway, instead of trying to get out through the locked doorway. A  mental set  is where you persist in approaching a problem in a way that has worked in the past but is clearly not working now.

Functional fixedness  is a type of mental set where you cannot perceive an object being used for something other than what it was designed for. Duncker (1945) conducted foundational research on functional fixedness. He created an experiment in which participants were given a candle, a book of matches, and a box of thumbtacks. They were instructed to use those items to attach the candle to the wall so that it did not drip wax onto the table below. Participants had to use functional fixedness to solve the problem ( Figure 7.10 ). During the  Apollo 13  mission to the moon, NASA engineers at Mission Control had to overcome functional fixedness to save the lives of the astronauts aboard the spacecraft. An explosion in a module of the spacecraft damaged multiple systems. The astronauts were in danger of being poisoned by rising levels of carbon dioxide because of problems with the carbon dioxide filters. The engineers found a way for the astronauts to use spare plastic bags, tape, and air hoses to create a makeshift air filter, which saved the lives of the astronauts.

Researchers have investigated whether functional fixedness is affected by culture. In one experiment, individuals from the Shuar group in Ecuador were asked to use an object for a purpose other than that for which the object was originally intended. For example, the participants were told a story about a bear and a rabbit that were separated by a river and asked to select among various objects, including a spoon, a cup, erasers, and so on, to help the animals. The spoon was the only object long enough to span the imaginary river, but if the spoon was presented in a way that reflected its normal usage, it took participants longer to choose the spoon to solve the problem. (German & Barrett, 2005). The researchers wanted to know if exposure to highly specialized tools, as occurs with individuals in industrialized nations, affects their ability to transcend functional fixedness. It was determined that functional fixedness is experienced in both industrialized and nonindustrialized cultures (German & Barrett, 2005).

In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. Sometimes, however, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the $2,000 home? Why would the realtor show you the run-down houses and the nice house? The realtor may be challenging your anchoring bias. An  anchoring bias  occurs when you focus on one piece of information when making a decision or solving a problem. In this case, you’re so focused on the amount of money you are willing to spend that you may not recognize what kinds of houses are available at that price point.

The  confirmation bias  is the tendency to focus on information that confirms your existing beliefs. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis.  Hindsight bias  leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did.  Representative bias describes a faulty way of thinking, in which you unintentionally stereotype someone or something; for example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.

Finally, the  availability heuristic  is a heuristic in which you make a decision based on an example, information, or recent experience that is that readily available to you, even though it may not be the best example to inform your decision .  Biases tend to “preserve that which is already established—to maintain our preexisting knowledge, beliefs, attitudes, and hypotheses” (Aronson, 1995; Kahneman, 2011). These biases are summarized in  Table 7.3 .

Were you able to determine how many marbles are needed to balance the scales in  Figure 7.9 ? You need nine. Were you able to solve the problems in  Figure 7.7  and  Figure 7.8 ? Here are the answers ( Figure 7.11 ).

• Define intelligence
• Explain the triarchic theory of intelligence
• Identify the difference between intelligence theories
• Explain emotional intelligence
• Define creativity

Classifying Intelligence

What exactly is intelligence? The way that researchers have defined the concept of intelligence has been modified many times since the birth of psychology. British psychologist Charles Spearman believed intelligence consisted of one general factor, called  g , which could be measured and compared among individuals. Spearman focused on the commonalities among various intellectual abilities and de-emphasized what made each unique. Long before modern psychology developed, however, ancient philosophers, such as Aristotle, held a similar view (Cianciolo & Sternberg, 2004).

Other psychologists believe that instead of a single factor, intelligence is a collection of distinct abilities. In the 1940s, Raymond Cattell proposed a theory of intelligence that divided general intelligence into two components: crystallized intelligence and fluid intelligence (Cattell, 1963). Crystallized intelligence  is characterized as acquired knowledge and the ability to retrieve it. When you learn, remember, and recall information, you are using crystallized intelligence. You use crystallized intelligence all the time in your coursework by demonstrating that you have mastered the information covered in the course.  Fluid intelligence  encompasses the ability to see complex relationships and solve problems. Navigating your way home after being detoured onto an unfamiliar route because of road construction would draw upon your fluid intelligence. Fluid intelligence helps you tackle complex, abstract challenges in your daily life, whereas crystallized intelligence helps you overcome concrete, straightforward problems (Cattell, 1963).

Other theorists and psychologists believe that intelligence should be defined in more practical terms. For example, what types of behaviors help you get ahead in life? Which skills promote success? Think about this for a moment. Being able to recite all 45 presidents of the United States in order is an excellent party trick, but will knowing this make you a better person?

Robert Sternberg developed another theory of intelligence, which he titled the  triarchic theory of intelligence  because it sees intelligence as comprised of three parts (Sternberg, 1988): practical, creative, and analytical intelligence ( Figure 7.12 ).

Practical intelligence , as proposed by Sternberg, is sometimes compared to “street smarts.” Being practical means you find solutions that work in your everyday life by applying knowledge based on your experiences. This type of intelligence appears to be separate from the traditional understanding of IQ; individuals who score high in practical intelligence may or may not have comparable scores in creative and analytical intelligence (Sternberg, 1988).

Analytical intelligence is closely aligned with academic problem solving and computations. Sternberg says that analytical intelligence is demonstrated by an ability to analyze, evaluate, judge, compare, and contrast. When reading a classic novel for a literature class, for example, it is usually necessary to compare the motives of the main characters of the book or analyze the historical context of the story. In a science course such as anatomy, you must study the processes by which the body uses various minerals in different human systems. In developing an understanding of this topic, you are using analytical intelligence. When solving a challenging math problem, you would apply analytical intelligence to analyze different aspects of the problem and then solve it section by section.

Creative intelligence  is marked by inventing or imagining a solution to a problem or situation. Creativity in this realm can include finding a novel solution to an unexpected problem or producing a beautiful work of art or a well-developed short story. Imagine for a moment that you are camping in the woods with some friends and realize that you’ve forgotten your camp coffee pot. The person in your group who figures out a way to successfully brew coffee for everyone would be credited as having higher creative intelligence.

Multiple Intelligences Theory  was developed by Howard Gardner, a Harvard psychologist and former student of Erik Erikson. Gardner’s theory, which has been refined for more than 30 years, is a more recent development among theories of intelligence. In Gardner’s theory, each person possesses at least eight intelligences. Among these eight intelligences, a person typically excels in some and falters in others (Gardner, 1983).  Table 7.4  describes each type of intelligence.

Gardner’s theory is relatively new and needs additional research to better establish empirical support. At the same time, his ideas challenge the traditional idea of intelligence to include a wider variety of abilities, although it has been suggested that Gardner simply relabeled what other theorists called “cognitive styles” as “intelligences” (Morgan, 1996). Furthermore, developing traditional measures of Gardner’s intelligences is extremely difficult (Furnham, 2009; Gardner & Moran, 2006; Klein, 1997).

Gardner’s inter- and intrapersonal intelligences are often combined into a single type: emotional intelligence.  Emotional intelligence  encompasses the ability to understand the emotions of yourself and others, show empathy, understand social relationships and cues, and regulate your own emotions and respond in culturally appropriate ways (Parker, Saklofske, & Stough, 2009). People with high emotional intelligence typically have well-developed social skills. Some researchers, including Daniel Goleman, the author of  Emotional Intelligence: Why It Can Matter More than IQ , argue that emotional intelligence is a better predictor of success than traditional intelligence (Goleman, 1995). However, emotional intelligence has been widely debated, with researchers pointing out inconsistencies in how it is defined and described, as well as questioning results of studies on a subject that is difficult to measure and study empirically (Locke, 2005; Mayer, Salovey, & Caruso, 2004)

The most comprehensive theory of intelligence to date is the Cattell-Horn-Carroll (CHC) theory of cognitive abilities (Schneider & McGrew, 2018). In this theory, abilities are related and arranged in a hierarchy with general abilities at the top, broad abilities in the middle, and narrow (specific) abilities at the bottom. The narrow abilities are the only ones that can be directly measured; however, they are integrated within the other abilities. At the general level is general intelligence. Next, the broad level consists of general abilities such as fluid reasoning, short-term memory, and processing speed. Finally, as the hierarchy continues, the narrow level includes specific forms of cognitive abilities. For example, short-term memory would further break down into memory span and working memory capacity.

Intelligence can also have different meanings and values in different cultures. If you live on a small island, where most people get their food by fishing from boats, it would be important to know how to fish and how to repair a boat. If you were an exceptional angler, your peers would probably consider you intelligent. If you were also skilled at repairing boats, your intelligence might be known across the whole island. Think about your own family’s culture. What values are important for Latinx families? Italian families? In Irish families, hospitality and telling an entertaining story are marks of the culture. If you are a skilled storyteller, other members of Irish culture are likely to consider you intelligent.

Some cultures place a high value on working together as a collective. In these cultures, the importance of the group supersedes the importance of individual achievement. When you visit such a culture, how well you relate to the values of that culture exemplifies your  cultural intelligence , sometimes referred to as cultural competence.

Creativity  is the ability to generate, create, or discover new ideas, solutions, and possibilities. Very creative people often have intense knowledge about something, work on it for years, look at novel solutions, seek out the advice and help of other experts, and take risks. Although creativity is often associated with the arts, it is actually a vital form of intelligence that drives people in many disciplines to discover something new. Creativity can be found in every area of life, from the way you decorate your residence to a new way of understanding how a cell works.

Creativity is often assessed as a function of one’s ability to engage in  divergent thinking . Divergent thinking can be described as thinking “outside the box;” it allows an individual to arrive at unique, multiple solutions to a given problem. In contrast,  convergent thinking describes the ability to provide a correct or well-established answer or solution to a problem (Cropley, 2006; Gilford, 1967)

• Explain how intelligence tests are developed
• Describe the history of the use of IQ tests
• Describe the purposes and benefits of intelligence testing

While you’re likely familiar with the term “IQ” and associate it with the idea of intelligence, what does IQ really mean? IQ stands for  intelligence quotient  and describes a score earned on a test designed to measure intelligence. You’ve already learned that there are many ways psychologists describe intelligence (or more aptly, intelligences). Similarly, IQ tests—the tools designed to measure intelligence—have been the subject of debate throughout their development and use.

When might an IQ test be used? What do we learn from the results, and how might people use this information? While there are certainly many benefits to intelligence testing, it is important to also note the limitations and controversies surrounding these tests. For example, IQ tests have sometimes been used as arguments in support of insidious purposes, such as the eugenics movement (Severson, 2011). The infamous Supreme Court Case,  Buck v. Bell , legalized the forced sterilization of some people deemed “feeble-minded” through this type of testing, resulting in about 65,000 sterilizations ( Buck v. Bell , 274 U.S. 200; Ko, 2016). Today, only professionals trained in psychology can administer IQ tests, and the purchase of most tests requires an advanced degree in psychology. Other professionals in the field, such as social workers and psychiatrists, cannot administer IQ tests. In this section, we will explore what intelligence tests measure, how they are scored, and how they were developed.

Measuring Intelligence

It seems that the human understanding of intelligence is somewhat limited when we focus on traditional or academic-type intelligence. How then, can intelligence be measured? And when we measure intelligence, how do we ensure that we capture what we’re really trying to measure (in other words, that IQ tests function as valid measures of intelligence)? In the following paragraphs, we will explore the how intelligence tests were developed and the history of their use.

The IQ test has been synonymous with intelligence for over a century. In the late 1800s, Sir Francis Galton developed the first broad test of intelligence (Flanagan & Kaufman, 2004). Although he was not a psychologist, his contributions to the concepts of intelligence testing are still felt today (Gordon, 1995). Reliable intelligence testing (you may recall from earlier chapters that reliability refers to a test’s ability to produce consistent results) began in earnest during the early 1900s with a researcher named Alfred Binet ( Figure 7.13 ). Binet was asked by the French government to develop an intelligence test to use on children to determine which ones might have difficulty in school; it included many verbally based tasks. American researchers soon realized the value of such testing. Louis Terman, a Stanford professor, modified Binet’s work by standardizing the administration of the test and tested thousands of different-aged children to establish an average score for each age. As a result, the test was normed and standardized, which means that the test was administered consistently to a large enough representative sample of the population that the range of scores resulted in a bell curve (bell curves will be discussed later).  Standardization  means that the manner of administration, scoring, and interpretation of results is consistent.  Norming  involves giving a test to a large population so data can be collected comparing groups, such as age groups. The resulting data provide norms, or referential scores, by which to interpret future scores. Norms are not expectations of what a given group  should  know but a demonstration of what that group  does  know. Norming and standardizing the test ensures that new scores are reliable. This new version of the test was called the Stanford-Binet Intelligence Scale (Terman, 1916). Remarkably, an updated version of this test is still widely used today.

In 1939, David Wechsler, a psychologist who spent part of his career working with World War I veterans, developed a new IQ test in the United States. Wechsler combined several subtests from other intelligence tests used between 1880 and World War I. These subtests tapped into a variety of verbal and nonverbal skills because Wechsler believed that intelligence encompassed “the global capacity of a person to act purposefully, to think rationally, and to deal effectively with his environment” (Wechsler, 1958, p. 7). He named the test the Wechsler-Bellevue Intelligence Scale (Wechsler, 1981). This combination of subtests became one of the most extensively used intelligence tests in the history of psychology. Although its name was later changed to the Wechsler Adult Intelligence Scale (WAIS) and has been revised several times, the aims of the test remain virtually unchanged since its inception (Boake, 2002). Today, there are three intelligence tests credited to Wechsler, the Wechsler Adult Intelligence Scale-fourth edition (WAIS-IV), the Wechsler Intelligence Scale for Children (WISC-V), and the Wechsler Preschool and Primary Scale of Intelligence—IV (WPPSI-IV) (Wechsler, 2012). These tests are used widely in schools and communities throughout the United States, and they are periodically normed and standardized as a means of recalibration. As a part of the recalibration process, the WISC-V was given to thousands of children across the country, and children taking the test today are compared with their same-age peers ( Figure 7.13 ).

The WISC-V is composed of 14 subtests, which comprise five indices, which then render an IQ score. The five indices are Verbal Comprehension, Visual Spatial, Fluid Reasoning, Working Memory, and Processing Speed. When the test is complete, individuals receive a score for each of the five indices and a Full Scale IQ score. The method of scoring reflects the understanding that intelligence is comprised of multiple abilities in several cognitive realms and focuses on the mental processes that the child used to arrive at his or her answers to each test item.

Interestingly, the periodic recalibrations have led to an interesting observation known as the Flynn effect. Named after James Flynn, who was among the first to describe this trend, the  Flynn effect  refers to the observation that each generation has a significantly higher IQ than the last. Flynn himself argues, however, that increased IQ scores do not necessarily mean that younger generations are more intelligent per se (Flynn, Shaughnessy, & Fulgham, 2012).

Ultimately, we are still left with the question of how valid intelligence tests are. Certainly, the most modern versions of these tests tap into more than verbal competencies, yet the specific skills that should be assessed in IQ testing, the degree to which any test can truly measure an individual’s intelligence, and the use of the results of IQ tests are still issues of debate (Gresham & Witt, 1997; Flynn, Shaughnessy, & Fulgham, 2012; Richardson, 2002; Schlinger, 2003).

The Bell Curve

The results of intelligence tests follow the bell curve, a graph in the general shape of a bell. When the bell curve is used in psychological testing, the graph demonstrates a normal distribution of a trait, in this case, intelligence, in the human population. Many human traits naturally follow the bell curve. For example, if you lined up all your female schoolmates according to height, it is likely that a large cluster of them would be the average height for an American woman: 5’4”–5’6”. This cluster would fall in the center of the bell curve, representing the average height for American women ( Figure 7.14 ). There would be fewer women who stand closer to 4’11”. The same would be true for women of above-average height: those who stand closer to 5’11”. The trick to finding a bell curve in nature is to use a large sample size. Without a large sample size, it is less likely that the bell curve will represent the wider population. A  representative sample  is a subset of the population that accurately represents the general population. If, for example, you measured the height of the women in your classroom only, you might not actually have a representative sample. Perhaps the women’s basketball team wanted to take this course together, and they are all in your class. Because basketball players tend to be taller than average, the women in your class may not be a good representative sample of the population of American women. But if your sample included all the women at your school, it is likely that their heights would form a natural bell curve.

The same principles apply to intelligence test scores. Individuals earn a score called an intelligence quotient (IQ). Over the years, different types of IQ tests have evolved, but the way scores are interpreted remains the same. The average IQ score on an IQ test is 100. Standard deviations  describe how data are dispersed in a population and give context to large data sets. The bell curve uses the standard deviation to show how all scores are dispersed from the average score ( Figure 7.15 ). In modern IQ testing, one standard deviation is 15 points. So a score of 85 would be described as “one standard deviation below the mean.” How would you describe a score of 115 and a score of 70? Any IQ score that falls within one standard deviation above and below the mean (between 85 and 115) is considered average, and 68% of the population has IQ scores in this range. An IQ score of 130 or above is considered a superior level.

Only 2.2% of the population has an IQ score below 70 (American Psychological Association [APA], 2013). A score of 70 or below indicates significant cognitive delays. When these are combined with major deficits in adaptive functioning, a person is diagnosed with having an intellectual disability (American Association on Intellectual and Developmental Disabilities, 2013). Formerly known as mental retardation, the accepted term now is intellectual disability, and it has four subtypes: mild, moderate, severe, and profound ( Table 7.5 ).  The Diagnostic and Statistical Manual of Psychological Disorders  lists criteria for each subgroup (APA, 2013).

On the other end of the intelligence spectrum are those individuals whose IQs fall into the highest ranges. Consistent with the bell curve, about 2% of the population falls into this category. People are considered gifted if they have an IQ score of 130 or higher, or superior intelligence in a particular area. Long ago, popular belief suggested that people of high intelligence were maladjusted. This idea was disproven through a groundbreaking study of gifted children. In 1921, Lewis Terman began a longitudinal study of over 1500 children with IQs over 135 (Terman, 1925). His findings showed that these children became well-educated, successful adults who were, in fact, well-adjusted (Terman & Oden, 1947). Additionally, Terman’s study showed that the subjects were above average in physical build and attractiveness, dispelling an earlier popular notion that highly intelligent people were “weaklings.” Some people with very high IQs elect to join Mensa, an organization dedicated to identifying, researching, and fostering intelligence. Members must have an IQ score in the top 2% of the population, and they may be required to pass other exams in their application to join the group.

DIG DEEPER: What’s in a Name? 

In the past, individuals with IQ scores below 70 and significant adaptive and social functioning delays were diagnosed with mental retardation. When this diagnosis was first named, the title held no social stigma. In time, however, the degrading word “retard” sprang from this diagnostic term. “Retard” was frequently used as a taunt, especially among young people, until the words “mentally retarded” and “retard” became an insult. As such, the DSM-5 now labels this diagnosis as “intellectual disability.” Many states once had a Department of Mental Retardation to serve those diagnosed with such cognitive delays, but most have changed their name to the Department of Developmental Disabilities or something similar in language.

Erin Johnson’s younger brother Matthew has Down syndrome. She wrote this piece about what her brother taught her about the meaning of intelligence:

His whole life, learning has been hard. Entirely possible – just different. He has always excelled with technology – typing his thoughts was more effective than writing them or speaking them. Nothing says “leave me alone” quite like a text that reads, “Do Not Call Me Right Now.” He is fully capable of reading books up to about a third-grade level, but he didn’t love it and used to always ask others to read to him. That all changed when his nephew came along, because he willingly reads to him, and it is the most heart-swelling, smile-inducing experience I have ever had the pleasure of witnessing.

When it comes down to it, Matt can learn. He does learn. It just takes longer, and he has to work harder for it, which if we’re being honest, is not a lot of fun. He is extremely gifted in learning things he takes an interest in, and those things often seem a bit “strange” to others. But no matter. It just proves my point – he  can  learn. That does not mean he will learn at the same pace, or even to the same level. It also, unfortunately, does not mean he will be allotted the same opportunities to learn as many others.

Here’s the scoop. We are all wired with innate abilities to retain and apply our learning and natural curiosities and passions that fuel our desire to learn. But our abilities and curiosities may not be the same.

The world doesn’t work this way though, especially not for my brother and his counterparts. Have him read aloud a book about skunks, and you may not get a whole lot from him. But have him tell you about skunks straight out of his memory, and hold onto your hats. He can hack the school’s iPad system, but he can’t tell you how he did it. He can write out every direction for a drive to our grandparents’ home in Florida, but he can’t drive.

Society is quick to deem him disabled and use demeaning language like the r-word to describe him, but in reality, we haven’t necessarily given him opportunities to showcase the learning he can do. In my case, I can escape the need to memorize how to change the oil in my car without anyone assuming I can’t do it, or calling me names when they find out I can’t. But Matthew can’t get through a day at his job without someone assuming he needs help. He is bright. Brighter than most anyone would assume. Maybe we need to redefine what is smart.

My brother doesn’t fit in the narrow schema of intelligence that is accepted in our society. But intelligence is far more than being able to solve 525 x 62 or properly introduce yourself to another. Why can’t we assume the intelligence of someone who can recite all of a character’s lines in a movie or remember my birthday a year after I told him/her a single time? Why is it we allow a person’s diagnosis or appearance to make us not just wonder if, but entirely doubt that they are capable? Maybe we need to cut away the sides of the box we have created for people so everyone can fit.

My brother can learn. It may not be what you know. It may be knowledge you would deem unimportant. It may not follow a traditional learning trajectory. But the fact remains – he can learn. Everyone can learn. And even though it is harder for him and harder for others still, he is not a “retard.” Nobody is.

When you use the r-word, you are insinuating that an individual, whether someone with a disability or not, is unintelligent, foolish, and purposeless. This in turn tells a person with a disability that they too are unintelligent, foolish, and purposeless. Because the word was historically used to describe individuals with disabilities and twisted from its original meaning to fit a cruel new context, it is forevermore associated with people like my brother. No matter how a person looks or learns or behaves, the r-word is never a fitting term. It’s time we waved it goodbye.

Why Measure Intelligence?

The value of IQ testing is most evident in educational or clinical settings. Children who seem to be experiencing learning difficulties or severe behavioral problems can be tested to ascertain whether the child’s difficulties can be partly attributed to an IQ score that is significantly different from the mean for her age group. Without IQ testing—or another measure of intelligence—children and adults needing extra support might not be identified effectively. In addition, IQ testing is used in courts to determine whether a defendant has special or extenuating circumstances that preclude him from participating in some way in a trial. People also use IQ testing results to seek disability benefits from the Social Security Administration.

• Describe how genetics and environment affect intelligence
• Explain the relationship between IQ scores and socioeconomic status
• Describe the difference between a learning disability and a developmental disorder

High Intelligence: Nature or Nurture?

Where does high intelligence come from? Some researchers believe that intelligence is a trait inherited from a person’s parents. Scientists who research this topic typically use twin studies to determine the  heritability  of intelligence. The Minnesota Study of Twins Reared Apart is one of the most well-known twin studies. In this investigation, researchers found that identical twins raised together and identical twins raised apart exhibit a higher correlation between their IQ scores than siblings or fraternal twins raised together (Bouchard, Lykken, McGue, Segal, & Tellegen, 1990). The findings from this study reveal a genetic component to intelligence ( Figure 7.15 ). At the same time, other psychologists believe that intelligence is shaped by a child’s developmental environment. If parents were to provide their children with intellectual stimuli from before they are born, it is likely that they would absorb the benefits of that stimulation, and it would be reflected in intelligence levels.

The reality is that aspects of each idea are probably correct. In fact, one study suggests that although genetics seem to be in control of the level of intelligence, the environmental influences provide both stability and change to trigger manifestation of cognitive abilities (Bartels, Rietveld, Van Baal, & Boomsma, 2002). Certainly, there are behaviors that support the development of intelligence, but the genetic component of high intelligence should not be ignored. As with all heritable traits, however, it is not always possible to isolate how and when high intelligence is passed on to the next generation.

Range of Reaction  is the theory that each person responds to the environment in a unique way based on his or her genetic makeup. According to this idea, your genetic potential is a fixed quantity, but whether you reach your full intellectual potential is dependent upon the environmental stimulation you experience, especially in childhood. Think about this scenario: A couple adopts a child who has average genetic intellectual potential. They raise her in an extremely stimulating environment. What will happen to the couple’s new daughter? It is likely that the stimulating environment will improve her intellectual outcomes over the course of her life. But what happens if this experiment is reversed? If a child with an extremely strong genetic background is placed in an environment that does not stimulate him: What happens? Interestingly, according to a longitudinal study of highly gifted individuals, it was found that “the two extremes of optimal and pathological experience are both represented disproportionately in the backgrounds of creative individuals”; however, those who experienced supportive family environments were more likely to report being happy (Csikszentmihalyi & Csikszentmihalyi, 1993, p. 187).

Another challenge to determining the origins of high intelligence is the confounding nature of our human social structures. It is troubling to note that some ethnic groups perform better on IQ tests than others—and it is likely that the results do not have much to do with the quality of each ethnic group’s intellect. The same is true for socioeconomic status. Children who live in poverty experience more pervasive, daily stress than children who do not worry about the basic needs of safety, shelter, and food. These worries can negatively affect how the brain functions and develops, causing a dip in IQ scores. Mark Kishiyama and his colleagues determined that children living in poverty demonstrated reduced prefrontal brain functioning comparable to children with damage to the lateral prefrontal cortex (Kishyama, Boyce, Jimenez, Perry, & Knight, 2009).

The debate around the foundations and influences on intelligence exploded in 1969 when an educational psychologist named Arthur Jensen published the article “How Much Can We Boost I.Q. and Achievement” in the Harvard Educational Review . Jensen had administered IQ tests to diverse groups of students, and his results led him to the conclusion that IQ is determined by genetics. He also posited that intelligence was made up of two types of abilities: Level I and Level II. In his theory, Level I is responsible for rote memorization, whereas Level II is responsible for conceptual and analytical abilities. According to his findings, Level I remained consistent among the human race. Level II, however, exhibited differences among ethnic groups (Modgil & Routledge, 1987). Jensen’s most controversial conclusion was that Level II intelligence is prevalent among Asians, then Caucasians, then African Americans. Robert Williams was among those who called out racial bias in Jensen’s results (Williams, 1970).

Obviously, Jensen’s interpretation of his own data caused an intense response in a nation that continued to grapple with the effects of racism (Fox, 2012). However, Jensen’s ideas were not solitary or unique; rather, they represented one of many examples of psychologists asserting racial differences in IQ and cognitive ability. In fact, Rushton and Jensen (2005) reviewed three decades worth of research on the relationship between race and cognitive ability. Jensen’s belief in the inherited nature of intelligence and the validity of the IQ test to be the truest measure of intelligence are at the core of his conclusions. If, however, you believe that intelligence is more than Levels I and II, or that IQ tests do not control for socioeconomic and cultural differences among people, then perhaps you can dismiss Jensen’s conclusions as a single window that looks out on the complicated and varied landscape of human intelligence.

In a related story, parents of African American students filed a case against the State of California in 1979, because they believed that the testing method used to identify students with learning disabilities was culturally unfair as the tests were normed and standardized using white children ( Larry P. v. Riles ). The testing method used by the state disproportionately identified African American children as mentally retarded. This resulted in many students being incorrectly classified as “mentally retarded.”

What are Learning Disabilities?

Learning disabilities are cognitive disorders that affect different areas of cognition, particularly language or reading. It should be pointed out that learning disabilities are not the same thing as intellectual disabilities. Learning disabilities are considered specific neurological impairments rather than global intellectual or developmental disabilities. A person with a language disability has difficulty understanding or using spoken language, whereas someone with a reading disability, such as dyslexia, has difficulty processing what he or she is reading.

Often, learning disabilities are not recognized until a child reaches school age. One confounding aspect of learning disabilities is that they most often affect children with average to above-average intelligence. In other words, the disability is specific to a particular area and not a measure of overall intellectual ability. At the same time, learning disabilities tend to exhibit comorbidity with other disorders, like attention-deficit hyperactivity disorder (ADHD). Anywhere between 30–70% of individuals with diagnosed cases of ADHD also have some sort of learning disability (Riccio, Gonzales, & Hynd, 1994). Let’s take a look at three examples of common learning disabilities: dysgraphia, dyslexia, and dyscalculia.

Children with  dysgraphia  have a learning disability that results in a struggle to write legibly. The physical task of writing with a pen and paper is extremely challenging for the person. These children often have extreme difficulty putting their thoughts down on paper (Smits-Engelsman & Van Galen, 1997). This difficulty is inconsistent with a person’s IQ. That is, based on the child’s IQ and/or abilities in other areas, a child with dysgraphia should be able to write, but can’t. Children with dysgraphia may also have problems with spatial abilities.

Students with dysgraphia need academic accommodations to help them succeed in school. These accommodations can provide students with alternative assessment opportunities to demonstrate what they know (Barton, 2003). For example, a student with dysgraphia might be permitted to take an oral exam rather than a traditional paper-and-pencil test. Treatment is usually provided by an occupational therapist, although there is some question as to how effective such treatment is (Zwicker, 2005).

Dyslexia is the most common learning disability in children. An individual with  dyslexia  exhibits an inability to correctly process letters. The neurological mechanism for sound processing does not work properly in someone with dyslexia. As a result, dyslexic children may not understand sound-letter correspondence. A child with dyslexia may mix up letters within words and sentences—letter reversals, such as those shown in  Figure 7.17 , are a hallmark of this learning disability—or skip whole words while reading. A dyslexic child may have difficulty spelling words correctly while writing. Because of the disordered way that the brain processes letters and sounds, learning to read is a frustrating experience. Some dyslexic individuals cope by memorizing the shapes of most words, but they never actually learn to read (Berninger, 2008).

Dyscalculia

Dyscalculia  is difficulty in learning or comprehending arithmetic. This learning disability is often first evident when children exhibit difficulty discerning how many objects are in a small group without counting them. Other symptoms may include struggling to memorize math facts, organize numbers, or fully differentiate between numerals, math symbols, and written numbers (such as “3” and “three”).

Additional Supplemental Resources

• Use Google’s QuickDraw web app on your phone to quickly draw 5 things for Google’s artificially intelligent neural net. When you are done, the app will show you what it thought each of the drawings was. How does this relate to the psychological idea of concepts, prototypes, and schemas? Check out here.  Works best in Chrome if used in a web browser
• This article lists information about a variety of different topics relating to speech development, including how speech develops and what research is currently being done regarding speech development.
• The Human intelligence site includes biographical profiles of people who have influenced the development of intelligence theory and testing, in-depth articles exploring current controversies related to human intelligence, and resources for teachers.

• In 2000, psychologists Sheena Iyengar and Mark Lepper from Columbia and Stanford University published a study about the paradox of choice.  This is the original journal article.
• Mensa , the high IQ society, provides a forum for intellectual exchange among its members. There are members in more than 100 countries around the world.  Anyone with an IQ in the top 2% of the population can join.
• This test developed in the 1950s is used to refer to some kinds of behavioral tests for the presence of mind, or thought, or intelligence in putatively minded entities such as machines.
• Your central “Hub” of information and products created for the network of Parent Centers serving families of children with disabilities.
• How have average IQ levels changed over time? Hear James Flynn discuss the “Flynn Effect” in this Ted Talk. Closed captioning available.
• We all want customized experiences and products — but when faced with 700 options, consumers freeze up. With fascinating new research, Sheena Iyengar demonstrates how businesses (and others) can improve the experience of choosing. This is the same researcher that is featured in your midterm exam.
• What does an IQ Score distribution look like?  Where do most people fall on an IQ Score distribution?  Find out more in this video. Closed captioning available.
• How do we solve problems?  How can data help us to do this?  Follow Amy Webb’s story of how she used algorithms to help her find her way to true love. Closed captioning available.
• In this Ted-Ed video, explore some of the ways in which animals communicate, and determine whether or not this communication qualifies as language.  A variety of discussion and assessment questions are included with the video (free registration is required to access the questions). Closed captioning available.
• Watch this Ted-Ed video to learn more about the benefits of speaking multiple languages, including how bilingualism helps the brain to process information, strengthens the brain, and keeps the speaker more engaged in their world.  A variety of discussion and assessment questions are included with the video (free registration is required to access the questions). Closed captioning available.
• This video is on how your mind can amaze and betray you includes information on topics such as concepts, prototypes, problem-solving and mistakes in thinking. Closed captioning available.
• This video on language includes information on topics such as the development of language, language theories, and brain areas involved in language, as well as language disorders. Closed captioning available.
• This video on the controversy of intelligence includes information on topics such as theories of intelligence, emotional intelligence, and measuring intelligence. Closed captioning available.
• This video on the brains vs. bias includes information on topics such as intelligence testing, testing bias, and stereotype threat. Closed captioning available.

Access for free at  https://openstax.org/books/psychology-2e/pages/1-introduction

Introduction to Psychology Copyright © 2020 by Julie Lazzara is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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Fluid Intelligence vs. Crystallized Intelligence

Ayesh Perera

B.A, MTS, Harvard University

Ayesh Perera, a Harvard graduate, has worked as a researcher in psychology and neuroscience under Dr. Kevin Majeres at Harvard Medical School.

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:

Fluid intelligence refers to the ability to reason and solve novel problems, independent of any knowledge from the past. It involves the capacity to identify patterns, solve puzzles, and use abstract reasoning. On the other hand, crystallized intelligence refers to the ability to use knowledge, facts, and experience that one has accumulated over time. It includes vocabulary, general world knowledge, and the application of learned information.

Key Takeaways

• Our general intelligence , which enables us to learn and recall, comprises our fluid intelligence and crystallized intelligence.
• Fluid intelligence involves comprehension, reasoning, and problem-solving, while crystallized intelligence involves recalling stored knowledge and past experiences.
• Fluid intelligence and crystallized intelligence rely on distinct brain systems despite their interrelationship in the performance of many tasks.
• Various tools are used to measure fluid and crystallized intelligence, and new research suggests that fluid intelligence can be improved, although it was hitherto supposed to be static.

Our capacity to learn the novel and recall the past is called general intelligence (Cattell, 1963). It is a construct of psychometric investigations of human intelligence and our cognitive abilities.

General intelligence encapsulates correlations among various cognitive tasks which can be categorized into two subdivisions (Cattell, 1971). These are fluid intelligence and crystallized intelligence.

The theory of fluid v. crystallized intelligence simultaneously challenges and extends what was once supposedly the single construct of general intelligence.

Cattell’s Theory of Intelligence

The theory of fluid v. crystallized intelligence was first postulated as a psychometrically based theory by psychologist Raymond B. Cattell in 1963.

Cattell argued that fluid intelligence and crystallized intelligence are two categories of general intelligence.

In his book Intelligence, Its Structure, Growth, and Action, Cattell identified one component of general intelligence as embodying a fluid quality and being directable to any problem (Cattell, 1987).

He proceeded to identify the other component as a part invested in the areas of crystalized skills. He pointed out that the latter involves knowledge acquisition and crystallized skills, which can be upset individually without impacting others.

The two concepts of fluid intelligence and crystallized intelligence were further developed by Cattell’s former student and cognitive psychologist John Leonard Horn (Horn & Cattell, 1967).

Fluid Intelligence

Fluid intelligence is the capacity to think speedily and reason flexibly to solve new problems without relying on past experience and accumulated knowledge.

Fluid intelligence allows us to perceive and draw inferences about relationships among variables and to conceptualize abstract information, which aids problem-solving. It is correlated with essential skills such as comprehension and learning.

As Raymond Cattell (1967) pointed out, it is a capacity to “perceive relationships independent of previous specific practice or instruction related to those relationships”.

Examples of the use of fluid intelligence include solving puzzles, constructing strategies to deal with new problems, seeing patterns in statistical data, and engaging in speculative philosophical reasoning (Unsworth, Fukuda, Awh & Vogel, 2014).

Horn (1969) pointed out that fluid intelligence is formless and relies only minimally upon acculturation and prior learning, which includes both formal and informal education.

He further contended that fluid intelligence is capable of flowing into a myriad of diverse cognitive activities. Consequently, the ability to solve abstract problems and engage in figural analyses and classifications, Horn argued, is dependent upon one’s level of fluid intelligence (Horn, 1968).

Fluid intelligence has long been thought to peak during the late 20s before beginning to decline (Cacioppo & Freberg 2012) gradually.

The decline of fluid intelligence is likely to be related to the deterioration of neurological functioning but may also decline as it is used less frequently during older age.

This decline of fluid intelligence has been attributed to the brain’s local atrophy in the right cerebellum , age-related changes in the brain, and a want of training (Cavanaugh & Blanchard-Fields, 2006).

Recent research, however, challenges previous assumptions and suggests that certain parts of fluid intelligence may not peak until even age 40.

Measurements of Fluid Intelligence

Woodcock-johnson tests of cognitive abilities.

The Third Edition of Woodcock-Johnson Tests of Cognitive Abilities comprises concept formation, which involves categorical thinking, and analysis synthesis, which involves sequential reasoning (Woodcock, McGrew & Mather, 2001).

Concept formation herein requires the inference of underlying rules to solve puzzles presented in ascending order of difficulty (Schrank & Flanagan 2003).

Analysis synthesis, on the other hand, requires the learning and the oral presentation of solutions to logic puzzles that emulate a mathematics system. The association of procedural learning with muscle memory can make certain actions second nature (Bullemer, Nissen, & Willingham, 1989).

Raven’s Progressive Matrices

Raven’s Progressive Matrices evaluate the capacity to discern relationships among various mental representations (Raven, Raven & Court 2003).

It is a non-verbal multiple-choice test that requires the completion of several drawings based on the test takers’ ability to notice pertinent features based on the spatial positioning of several objects (Ferrer, O”Hare & Bunge 2009).

Wechsler Intelligence Scales for Children

The Wechsler Intelligence Scales for Children, Fourth Edition, relies exclusively on visual stimuli and is a non-verbal test that consists of a matrix reasoning test and a picture concept assessment (Wechsler, 2003).

The picture concept task evaluates a child’s capacity to discern the underlying traits governing a set of materials while the matrix reasoning test assesses the child’s ability to begin with stated governing traits/rules to identify the solution to a novel problem (Flanagan & Kaufman, 2004).

The solution herein is the picture for a puzzle that fits the stated rule.

What Is Crystallized Intelligence?

Crystallized Intelligence refers to the ability to utilize skills and knowledge acquired via prior learning (Horn, 1969). The use of crystallized intelligence involves the recalling of pre-existing information as well as skills.

Examples of the use of Crystallized Intelligence, on the other hand, include recalling historical events and dates, remembering geographical locations, building one’s vocabulary, and reciting poetic texts (Horn, 1968).

Crystallized Intelligence results from accumulated knowledge, including knowledge of how to reason, language skills and an understanding of technology. This type of intelligence is linked to eduction, experience and cultural background and is measured by tests of general information.

The use of crystallized intelligence involves the recalling of pre-existing information as well as skills. For example, knowing how to ride a bike or read a book.

Horn (1969) explained that Crystallized Intelligence is a “precipitate out of experience” which stems from a prior application of fluid intelligence.

Effectively completing tasks involving language mechanics (such as vocabulary building) and general information relies on one’s Crystallized Intelligence.

Crystallized Intelligence rises gradually and remains stable throughout adulthood until it begins to decline after age 60 (Cavanaugh & Blanchard-Fields, 2006).

Despite the observance of this general trend, the age at which Crystallized Intelligence reaches its peak is yet to be ascertained (Desjardins, Warnke & Jonas, 2012).

Measurements of Crystallized Intelligence

The c-test .

The C-Test is a text completion test initially proposed as a foreign language proficiency test that provides an integrative measure of crystallized intelligence (Baghaei & Tabatabaee-Yazdi, 2015).

The underlying construct of the C-Test corresponds to the abilities undergirding the language component of crystallized intelligence.

However, research implies that the careful selection of texts from relevant domains of knowledge can enable the C-Test to measure the factual knowledge component of crystallized intelligence as well.

The Wechsler Adult Intelligence Scale (WAIS)

The revised form of the Wechsler Adult Intelligence Scale, which has been used since 1981, comprises five performance and six verbal subtests (Kaufman & Lichtenberger 2006).

These verbal tests include comprehension, information, digit span, vocabulary, similarities, and arithmetic (Wechsler Adult Intelligence Scale-Revised). Most of these verbal tests are widely construed as capable of measuring crystallized intelligence.

How the Intelligence Types Work Together

While fluid intelligence and Crystallized Intelligence are distinct, it is important to note the multiplicity of the tasks that involve both these components. For instance, in taking a math exam, one may rely on one’s fluid intelligence to construct a strategy to respond to the given questions within the allocated time.

However, at the same time, one might have to utilize one’s Crystallized Intelligence to recall various mathematical concepts and theories in providing the correct answers.

Likewise, an entrepreneur might have to use her fluid intelligence to identify a new opportunity in the market. However, creating a product to meet consumer demand might require past knowledge and, therefore, the use of her Crystallized Intelligence.

Despite this manifest interrelationship, Crystallized Intelligence is not a type of fluid intelligence that has crystalized over time (Cherry, 2018). However, the investment of fluid intelligence via the learning of new information produces Crystallized Intelligence.

In other words, the critical analyses of problems via fluid intelligence creates and transfers information to long-term memory which constitutes a part of crystallized cntelligence.

Can Fluid Intelligence Be Improved?

Because crystallized intelligence is known to improve over time and remain stable with age, it is generally acknowledged that education and experience increase crystallized intelligence (Cavanaugh & Blanchard-Fields, 2006). However, the approach to fluid intelligence has been characterized by complexity.

Until recently, it was widely held that fluid intelligence is static, largely determined by genetic factors, and therefore, could not be altered. However, some research has suggested that fluid intelligence can be improved.

During some experiments conducted in 2008 by psychologist Susanne M. Jaeggi, 70 participants were subjected to daily tasks and regular training to improve their fluid intelligence (Jaeggi, Buschkuehl, Jonides & Perrig, 2008).

At the end of the period, a notable rise in the participants’ fluid intelligence was observed. A similarly done study by Qiu, Wei, Zhao, and Lin also supported Jaeggi’s conclusions (Qiu, Wei, Zhao, & Lin, 2009).

The key themes are challenging oneself by learning new skills, problem-solving, working memory training, and exposure to intense cognitive tasks systematically and with increasing difficulty. This seems to drive neural changes that facilitate enhanced fluid reasoning abilities.

• Physical exercise – Aerobic exercise like running or swimming can help boost fluid intelligence by promoting brain plasticity and growth.
• Learning new skills – Actively challenging oneself by learning new complex skills and solving mentally demanding problems can improve fluid intelligence over time. The activities should be progressively more difficult.
• Working memory training – Targeted training on working memory tasks, like memory games or mental math sequences, can help improve problem-solving capacities related to fluid intelligence.
• Action video game training – Training with fast-paced action video games that require quick reactions and on-the-fly decision-making provided some cognitive stimulation that improved fluid intelligence-related performance.
• Brain stimulation – Non-invasive brain stimulation techniques like tDCS and TMS showed some preliminary evidence for temporarily and modestly improving reasoning skills tied to fluid intelligence, but more research is still needed.
• Getting good sleep – Getting enough good quality sleep supports cognitive function and consolidation of memories important for neural changes underlying learning, which relates to fluid intelligence capacity.

Baghaei, Purya & Tabatabaee-Yazdi, Mona. (2015). The C-Test: An Integrative Measure of Crystallized Intelligence . Journal of Intelligence, 3 (2), 46-58.

Cacioppo, J. T., & Freberg, L. (2012). Discovering psychology: The science of mind . Cengage learning.

Cattell, R. B. (1963). Theory of fluid and crystallized intelligence: A critical experiment. Journal of Educational Psychology, 54 (1), 1–22.

Cattell, R. B. (1971). Abilities: Their structure, growth, and action . New York: Houghton Mifflin.

Cattell, Raymond B. (1987). Intelligence: Its Structure, Growth, and Action . Elsevier Science Publishers.

Cavanaugh, J. C.; Blanchard-Fields, F (2006). Adult development and aging (5th ed.) . Belmont, CA: Wadsworth Publishing/Thomson Learning.

Desjardins, R., & Warnke, A.J. (2012). Ageing and Skills (PDF) . OECD Education Working Papers.

Ferrer, E., O”Hare, E. D., & Bunge, S. A. (2009). Fluid reasoning and the developing brain . Frontiers in neuroscience, 3 (1), 46–51.

Flanagan, D. P., & Kaufman, A. S. (2004). Essentials of WISC-IV assessment . Hoboken, NJ: John Wiley.

Geary, D. C. (2005). The origin of mind: Evolution of brain, cognition, and general intelligence . Washington, DC: American Psychological Association

Horn, J. L. (1968). Organization of abilities and the development of intelligence. Psychological Review, 75 (3), 242-259.

Horn, J. L. (1969). Intelligence: Why it grows. Why it declines. Trans-action , 4, 23-31.

Horn, J. L., & Cattell, R. B. (1967). Age differences in fluid and crystallized intelligence. Acta Psychologica , 26, 107–129.

Jaeggi, S. M., Buschkuehl, M., Jonides, J., & Perrig, W. J. (2008). Improving fluid intelligence with training on working memory . Proceedings of the National Academy of Sciences, 105 (19), 6829-6833.

Kaplan, J. T., Gimbel, S. I., & Harris, S. (2016). Neural correlates of maintaining one’s political beliefs in the face of counterevidence . Scientific reports, 6 , 39589.

Kaufman, Alan S.; Lichtenberger, Elizabeth (2006). Assessing Adolescent and Adult Intelligence (3rd ed.) . Hoboken (NJ): Wiley.

Martin, JH (2003). Lymbic system and cerebral circuits for emotions, learning, and memory. Neuroanatomy: text and atlas (third ed.) . McGraw-Hill Companies.

Pardo, J. V., Pardo, P. J., Janer, K. W., & Raichle, M. E. (1990). The anterior cingulate cortex mediates processing selection in the Stroop attentional conflict paradigm . Proceedings of the National Academy of Sciences, 87 (1), 256-259.

Qiu, F., Wei, Q., Zhao, L., & Lin, L. (2009, December). Study on improving fluid intelligence through cognitive training system based on Gabor stimulus . In 2009 First International Conference on Information Science and Engineering (pp. 3459-3462). IEEE.

Raven, J. C. (1983). Manual for Raven’s progressive matrices and vocabulary scales. Standard Progressive Matrices .

Schrank, F. A.; Flanagan, D. P. (2003). WJ III Clinical use and interpretation. Scientist-practitioner perspectives . San Diego, CA: Academic Press.

Unsworth, Nash; Fukuda, Keisuke; Awh, Edward; Vogel, Edward K. (2014). Working memory and fluid intelligence: Capacity, attention control, and secondary memory retrieval . Cognitive Psychology , 71, 1–26.

Wechsler Adult Intelligence Scale–Revised. LIST OF TESTS Available from the CPS Testing Library. Center for Psychological Studies at Nova Southeastern University.

Wechsler, D. (2003). WISC-IV technical and interpretive manual. San Antonio, TX: Psychological Corporation.

Woodcock, R. W.; McGrew, K. S.; Mather, N (2001). Woodcock Johnson III. Itasca, IL: Riverside.

Further Reading

• Kievit, R. A., Davis, S. W., Griffiths, J., Correia, M. M., & Henson, R. N. (2016). A watershed model of individual differences in fluid intelligence. Neuropsychologia, 91 , 186-198.
• General Intelligence
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9.1: Defining and Measuring Intelligence

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Learning Objectives

• Define intelligence and list the different types of intelligences psychologists study.
• Summarize the characteristics of a scientifically valid intelligence test.
• Outline the biological and environmental determinants of intelligence.

Psychologists have long debated how to best conceptualize and measure intelligence (Sternberg, 2003). These questions include how many types of intelligence there are, the role of nature versus nurture in intelligence, how intelligence is represented in the brain, and the meaning of group differences in intelligence.

General (g) Versus Specific (s) Intelligences

In the early 1900s, the French psychologist Alfred Binet (1857–1914) and his colleague Henri Simon (1872–1961) began working in Paris to develop a measure that would differentiate students who were expected to be better learners from students who were expected to be slower learners. The goal was to help teachers better educate these two groups of students. Binet and Simon developed what most psychologists today regard as the first intelligence test, which consisted of a wide variety of questions that included the ability to name objects, define words, draw pictures, complete sentences, compare items, and construct sentences.

Binet and Simon (Binet, Simon, & Town, 1915; Siegler, 1992) believed that the questions they asked their students, even though they were on the surface dissimilar, all assessed the basic abilities to understand, reason, and make judgments. And it turned out that the correlations among these different types of measures were in fact all positive; students who got one item correct were more likely to also get other items correct, even though the questions themselves were very different.

On the basis of these results, the psychologist Charles Spearman (1863–1945) hypothesized that there must be a single underlying construct that all of these items measure. He called the construct that the different abilities and skills measured on intelligence tests have in common the general intelligence factor (g). Virtually all psychologists now believe that there is a generalized intelligence factor, g, that relates to abstract thinking and that includes the abilities to acquire knowledge, to reason abstractly, to adapt to novel situations, and to benefit from instruction and experience (Gottfredson, 1997; Sternberg, 2003). People with higher general intelligence learn faster.

Soon after Binet and Simon introduced their test, the American psychologist Lewis Terman (1877–1956) developed an American version of Binet’s test that became known as the Stanford-Binet Intelligence Test . The Stanford-Binet is a measure of general intelligence made up of a wide variety of tasks including vocabulary, memory for pictures, naming of familiar objects, repeating sentences, and following commands.

Although there is general agreement among psychologists that g exists, there is also evidence for specific intelligence (s), a measure of specific skills in narrow domains . One empirical result in support of the idea of s comes from intelligence tests themselves. Although the different types of questions do correlate with each other, some items correlate more highly with each other than do other items; they form clusters or clumps of intelligences.

One distinction is between fluid intelligence , which refers to the capacity to learn new ways of solving problems and performing activities, and crystallized intelligence , which refers to the accumulated knowledge of the world we have acquired throughout our lives (Salthouse, 2004). These intelligences must be different because crystallized intelligence increases with age—older adults are as good as or better than young people in solving crossword puzzles—whereas fluid intelligence tends to decrease with age (Horn, Donaldson, & Engstrom, 1981; Salthouse, 2004).

Other researchers have proposed even more types of intelligences. L. L. Thurstone (1938) proposed that there were seven clusters of primary mental abilities , made up of word fluency, verbal comprehension, spatial ability, perceptual speed, numerical ability, inductive reasoning, and memory. But even these dimensions tend to be at least somewhat correlated, showing again the importance of g.

One advocate of the idea of multiple intelligences is the psychologist Robert Sternberg. Sternberg has proposed a triarchic (three-part) theory of intelligence that proposes that people may display more or less analytical intelligence, creative intelligence, and practical intelligence . Sternberg (1985, 2003) argued that traditional intelligence tests assess analytical intelligence, the ability to answer problems with a single right answer, but that they do not well assess creativity (the ability to adapt to new situations and create new ideas) or practicality (e.g., the ability to write good memos or to effectively delegate responsibility).

As Sternberg proposed, research has found that creativity is not highly correlated with analytical intelligence (Furnham & Bachtiar, 2008), and exceptionally creative scientists, artists, mathematicians, and engineers do not score higher on intelligence than do their less creative peers (Simonton, 2000). Furthermore, the brain areas that are associated with convergent thinking , thinking that is directed toward finding the correct answer to a given problem, are different from those associated with divergent thinking , the ability to generate many different ideas for or solutions to a single problem (Tarasova, Volf, & Razoumnikova, 2010). On the other hand, being creative often takes some of the basic abilities measured by g, including the abilities to learn from experience, to remember information, and to think abstractly (Bink & Marsh, 2000).

Studies of creative people suggest at least five components that are likely to be important for creativity:

• Expertise . Creative people have carefully studied and know a lot about the topic that they are working in. Creativity comes with a lot of hard work (Ericsson, 1998; Weisberg, 2006).
• Imaginative thinking . Creative people often view a problem in a visual way, allowing them to see it from a new and different point of view.
• Risk taking . Creative people are willing to take on new but potentially risky approaches.
• Intrinsic interest . Creative people tend to work on projects because they love doing them, not because they are paid for them. In fact, research has found that people who are paid to be creative are often less creative than those who are not (Hennessey & Amabile, 2010).
• Working in a creative environment . Creativity is in part a social phenomenon. Simonton (1992) found that the most creative people were supported, aided, and challenged by other people working on similar projects.

The last aspect of the triarchic model, practical intelligence, refers primarily to intelligence that cannot be gained from books or formal learning. Practical intelligence represents a type of “street smarts” or “common sense” that is learned from life experiences. Although a number of tests have been devised to measure practical intelligence (Sternberg, Wagner, & Okagaki, 1993; Wagner & Sternberg, 1985), research has not found much evidence that practical intelligence is distinct from g or that it is predictive of success at any particular tasks (Gottfredson, 2003). Practical intelligence may include, at least in part, certain abilities that help people perform well at specific jobs, and these abilities may not always be highly correlated with general intelligence (Sternberg, Wagner, & Okagaki, 1993). On the other hand, these abilities or skills are very specific to particular occupations and thus do not seem to represent the broader idea of intelligence.

Another champion of the idea of multiple intelligences is the psychologist Howard Gardner (1983, 1999). Gardner argued that it would be evolutionarily functional for different people to have different talents and skills, and proposed that there are eight intelligences that can be differentiated from each other (Table \(\PageIndex{1}\)). Gardner noted that some evidence for multiple intelligences comes from the abilities of autistic savants , people who score low on intelligence tests overall but who nevertheless may have exceptional skills in a given domain, such as math, music, art, or in being able to recite statistics in a given sport (Treffert & Wallace, 2004).

Source: Adapted from Gardner, H. (1999). Intelligence reframed: Multiple intelligences for the 21st century . New York, NY: Basic Books.

The idea of multiple intelligences has been influential in the field of education, and teachers have used these ideas to try to teach differently to different students. For instance, to teach math problems to students who have particularly good kinesthetic intelligence, a teacher might encourage the students to move their bodies or hands according to the numbers. On the other hand, some have argued that these “intelligences” sometimes seem more like “abilities” or “talents” rather than real intelligence. And there is no clear conclusion about how many intelligences there are. Are sense of humor, artistic skills, dramatic skills, and so forth also separate intelligences? Furthermore, and again demonstrating the underlying power of a single intelligence, the many different intelligences are in fact correlated and thus represent, in part, g (Brody, 2003).

Measuring Intelligence: Standardization and the Intelligence Quotient

The goal of most intelligence tests is to measure g, the general intelligence factor. Good intelligence tests are reliable , meaning that they are consistent over time, and also demonstrate construct validity , meaning that they actually measure intelligence rather than something else. Because intelligence is such an important individual difference dimension, psychologists have invested substantial effort in creating and improving measures of intelligence, and these tests are now the most accurate of all psychological tests. In fact, the ability to accurately assess intelligence is one of the most important contributions of psychology to everyday public life.

Intelligence changes with age. A 3-year-old who could accurately multiply 183 by 39 would certainly be intelligent, but a 25-year-old who could not do so would be seen as unintelligent. Thus understanding intelligence requires that we know the norms or standards in a given population of people at a given age. The standardization of a test involves giving it to a large number of people at different ages and computing the average score on the test at each age level .

It is important that intelligence tests be standardized on a regular basis, because the overall level of intelligence in a population may change over time. The Flynn effect refers to the observation that scores on intelligence tests worldwide have increased substantially over the past decades (Flynn, 1999). Although the increase varies somewhat from country to country, the average increase is about 3 IQ points every 10 years. There are many explanations for the Flynn effect, including better nutrition, increased access to information, and more familiarity with multiple-choice tests (Neisser, 1998). But whether people are actually getting smarter is debatable (Neisser, 1997).

Once the standardization has been accomplished, we have a picture of the average abilities of people at different ages and can calculate a person’s mental age, which is the age at which a person is performing intellectually . If we compare the mental age of a person to the person’s chronological age, the result is the intelligence quotient (IQ), a measure of intelligence that is adjusted for age . A simple way to calculate IQ is by using the following formula:

IQ = mental age ÷ chronological age × 100.

Thus a 10-year-old child who does as well as the average 10-year-old child has an IQ of 100 (10 ÷ 10 × 100), whereas an 8-year-old child who does as well as the average 10-year-old child would have an IQ of 125 (10 ÷ 8 × 100). Most modern intelligence tests are based the relative position of a person’s score among people of the same age, rather than on the basis of this formula, but the idea of an intelligence “ratio” or “quotient” provides a good description of the score’s meaning.

A number of scales are based on the IQ. The Wechsler Adult lntelligence Scale (WAIS) is the most widely used intelligence test for adults (Watkins, Campbell, Nieberding, & Hallmark, 1995). The current version of the WAIS, the WAIS-IV, was standardized on 2,200 people ranging from 16 to 90 years of age. It consists of 15 different tasks, each designed to assess intelligence, including working memory, arithmetic ability, spatial ability, and general knowledge about the world (Figure \(\PageIndex{4}\)). The WAIS-IV yields scores on four domains: verbal, perceptual, working memory, and processing speed. The reliability of the test is high (more than 0.95), and it shows substantial construct validity. The WAIS-IV is correlated highly with other IQ tests such as the Stanford-Binet, as well as with criteria of academic and life success, including college grades, measures of work performance, and occupational level. It also shows significant correlations with measures of everyday functioning among the mentally retarded.

The Wechsler scale has also been adapted for preschool children in the form of the Wechsler Primary and Preschool Scale of Intelligence (WPPSI-III) and for older children and adolescents in the form of the Wechsler Intelligence Scale for Children (WISC-IV) .

The intelligence tests that you may be most familiar with are aptitude tests , which are designed to measure one’s ability to perform a given task, for instance, to do well in college or in postgraduate training. Most U.S. colleges and universities require students to take the Scholastic Assessment Test (SAT) or the American College Test (ACT), and postgraduate schools require the Graduate Record Examination (GRE), Medical College Admissions Test (MCAT), or the Law School Admission Test (LSAT). These tests are useful for selecting students because they predict success in the programs that they are designed for, particularly in the first year of the program (Kuncel, Hezlett, & Ones, 2010). These aptitude tests also measure, in part, intelligence. Frey and Detterman (2004) found that the SAT correlated highly (between about r = .7 and r = .8) with standard measures of intelligence.

Intelligence tests are also used by industrial and organizational psychologists in the process of personnel selection . Personnel selection is the use of structured tests to select people who are likely to perform well at given jobs (Schmidt & Hunter, 1998). The psychologists begin by conducting a job analysis in which they determine what knowledge, skills, abilities, and personal characteristics ( KSAPs ) are required for a given job. This is normally accomplished by surveying and/or interviewing current workers and their supervisors. Based on the results of the job analysis, the psychologists choose selection methods that are most likely to be predictive of job performance. Measures include tests of cognitive and physical ability and job knowledge tests, as well as measures of IQ and personality.

The Biology of Intelligence

The brain processes underlying intelligence are not completely understood, but current research has focused on four potential factors: brain size, sensory ability, speed and efficience of neural transmission, and working memory capacity.

There is at least some truth to the idea that smarter people have bigger brains. Studies that have measured brain volume using neuroimaging techniques find that larger brain size is correlated with intelligence (McDaniel, 2005), and intelligence has also been found to be correlated with the number of neurons in the brain and with the thickness of the cortex (Haier, 2004; Shaw et al., 2006). It is important to remember that these correlational findings do not mean that having more brain volume causes higher intelligence. It is possible that growing up in a stimulating environment that rewards thinking and learning may lead to greater brain growth (Garlick, 2003), and it is also possible that a third variable, such as better nutrition, causes both brain volume and intelligence.

Another possibility is that the brains of more intelligent people operate faster or more efficiently than the brains of the less intelligent. Some evidence supporting this idea comes from data showing that people who are more intelligent frequently show less brain activity (suggesting that they need to use less capacity) than those with lower intelligence when they work on a task (Haier, Siegel, Tang, & Abel, 1992). And the brains of more intelligent people also seem to run faster than the brains of the less intelligent. Research has found that the speed with which people can perform simple tasks—such as determining which of two lines is longer or pressing, as quickly as possible, one of eight buttons that is lighted—is predictive of intelligence (Deary, Der, & Ford, 2001). Intelligence scores also correlate at about r = .5 with measures of working memory (Ackerman, Beier, & Boyle, 2005), and working memory is now used as a measure of intelligence on many tests.

Although intelligence is not located in a specific part of the brain, it is more prevalent in some brain areas than others. Duncan et al. (2000) administered a variety of intelligence tasks and observed the places in the cortex that were most active. Although different tests created different patterns of activation, as you can see in Figure \(\PageIndex{5}\), these activated areas were primarily in the outer parts of the cortex, the area of the brain most involved in planning, executive control, and short-term memory.

Is Intelligence Nature or Nurture?

Intelligence has both genetic and environmental causes, and these have been systematically studied through a large number of twin and adoption studies (Neisser et al., 1996; Plomin, DeFries, Craig, & McGuffin, 2003). These studies have found that between 40% and 80% of the variability in IQ is due to genetics, meaning that overall genetics plays a bigger role than does environment in creating IQ differences among individuals (Plomin & Spinath, 2004). The IQs of identical twins correlate very highly ( r = .86), much higher than do the scores of fraternal twins who are less genetically similar ( r = .60). And the correlations between the IQs of parents and their biological children ( r = .42) is significantly greater than the correlation between parents and adopted children ( r = .19). The role of genetics gets stronger as children get older. The intelligence of very young children (less than 3 years old) does not predict adult intelligence, but by age 7 it does, and IQ scores remain very stable in adulthood (Deary, Whiteman, Starr, Whalley, & Fox, 2004).

But there is also evidence for the role of nurture, indicating that individuals are not born with fixed, unchangeable levels of intelligence. Twins raised together in the same home have more similar IQs than do twins who are raised in different homes, and fraternal twins have more similar IQs than do nontwin siblings, which is likely due to the fact that they are treated more similarly than are siblings.

The fact that intelligence becomes more stable as we get older provides evidence that early environmental experiences matter more than later ones. Environmental factors also explain a greater proportion of the variance in intelligence for children from lower-class households than they do for children from upper-class households (Turkheimer, Haley, Waldron, D’Onofrio, & Gottesman, 2003). This is because most upper-class households tend to provide a safe, nutritious, and supporting environment for children, whereas these factors are more variable in lower-class households.

Social and economic deprivation can adversely affect IQ. Children from households in poverty have lower IQs than do children from households with more resources even when other factors such as education, race, and parenting are controlled (Brooks-Gunn & Duncan, 1997). Poverty may lead to diets that are undernourishing or lacking in appropriate vitamins, and poor children may also be more likely to be exposed to toxins such as lead in drinking water, dust, or paint chips (Bellinger & Needleman, 2003). Both of these factors can slow brain development and reduce intelligence.

If impoverished environments can harm intelligence, we might wonder whether enriched environments can improve it. Government-funded after-school programs such as Head Start are designed to help children learn. Research has found that attending such programs may increase intelligence for a short time, but these increases rarely last after the programs end (McLoyd, 1998; Perkins & Grotzer, 1997). But other studies suggest that Head Start and similar programs may improve emotional intelligence and reduce the likelihood that children will drop out of school or be held back a grade (Reynolds, Temple, Robertson, & Mann 2001).

Intelligence is improved by education; the number of years a person has spent in school correlates at about r = .6 with IQ (Ceci, 1991). In part this correlation may be due to the fact that people with higher IQ scores enjoy taking classes more than people with low IQ scores, and they thus are more likely to stay in school. But education also has a causal effect on IQ. Comparisons between children who are almost exactly the same age but who just do or just do not make a deadline for entering school in a given school year show that those who enter school a year earlier have higher IQ than those who have to wait until the next year to begin school (Baltes & Reinert, 1969; Ceci & Williams, 1997). Children’s IQs tend to drop significantly during summer vacations (Huttenlocher, Levine, & Vevea, 1998), a finding that suggests that a longer school year, as is used in Europe and East Asia, is beneficial.

It is important to remember that the relative roles of nature and nurture can never be completely separated. A child who has higher than average intelligence will be treated differently than a child who has lower than average intelligence, and these differences in behaviors will likely amplify initial differences. This means that modest genetic differences can be multiplied into big differences over time.

Psychology in Everyday Life: Emotional Intelligence

Although most psychologists have considered intelligence a cognitive ability, people also use their emotions to help them solve problems and relate effectively to others. Emotional intelligence refers to the ability to accurately identify, assess, and understand emotions, as well as to effectively control one’s own emotions (Feldman-Barrett & Salovey, 2002; Mayer, Salovey, & Caruso, 2000).

The idea of emotional intelligence is seen in Howard Gardner’s interpersonal intelligence (the capacity to understand the emotions, intentions, motivations, and desires of other people) and intrapersonal intelligence (the capacity to understand oneself, including one’s emotions). Public interest in, and research on, emotional intellgence became widely prevalent following the publication of Daniel Goleman’s best-selling book, Emotional Intelligence: Why It Can Matter More Than IQ (Goleman, 1998).

There are a variety of measures of emotional intelligence (Mayer, Salovey, & Caruso, 2008; Petrides & Furnham, 2000). One popular measure, the Mayer-Salovey-Caruso Emotional Intelligence Test ( http://www.emotionaliq.org ), includes items about the ability to understand, experience, and manage emotions, such as these:

• What mood(s) might be helpful to feel when meeting in-laws for the very first time?
• Tom felt anxious and became a bit stressed when he thought about all the work he needed to do. When his supervisor brought him an additional project, he felt ____ (fill in the blank).
• anger and fear
• fear and surprise
• disgust and anger
• surprise and disgust
• Action 1: She started to make a list of things at home that she needed to do.
• Action 2: She began thinking about where and when she would go on her next vacation.
• Action 3: She decided it was best to ignore the feeling since it wouldn’t last anyway.

One problem with emotional intelligence tests is that they often do not show a great deal of reliability or construct validity (Føllesdal & Hagtvet, 2009).Although it has been found that people with higher emotional intelligence are also healthier (Martins, Ramalho, & Morin, 2010), findings are mixed about whether emotional intelligence predicts life success—for instance, job performance (Harms & Credé, 2010). Furthermore, other researchers have questioned the construct validity of the measures, arguing that emotional intelligence really measures knowledge about what emotions are, but not necessarily how to use those emotions (Brody, 2004), and that emotional intelligence is actually a personality trait, a part of g, or a skill that can be applied in some specific work situations—for instance, academic and work situations (Landy, 2005).

Although measures of the ability to understand, experience, and manage emotions may not predict effective behaviors, another important aspect of emotional intelligence— emotion regulation —does. Emotion regulation refers to the ability to control and productively use one’s emotions. Research has found that people who are better able to override their impulses to seek immediate gratification and who are less impulsive also have higher cognitive and social intelligence. They have better SAT scores, are rated by their friends as more socially adept, and cope with frustration and stress better than those with less skill at emotion regulation (Ayduk et al., 2000; Eigsti et al., 2006; Mischel & Ayduk, 2004).

Because emotional intelligence seems so important, many school systems have designed programs to teach it to their students. However, the effectiveness of these programs has not been rigorously tested, and we do not yet know whether emotional intelligence can be taught, or if learning it would improve the quality of people’s lives (Mayer & Cobb, 2000).

Key Takeaways

• Intelligence is the ability to think, to learn from experience, to solve problems, and to adapt to new situations. Intelligence is important because it has an impact on many human behaviors.
• Psychologists believe that there is a construct that accounts for the overall differences in intelligence among people, known as general intelligence (g).
• There is also evidence for specific intelligences (s), measures of specific skills in narrow domains, including creativity and practical intelligence.
• The intelligence quotient (IQ) is a measure of intelligence that is adjusted for age. The Wechsler Adult lntelligence Scale (WAIS) is the most widely used IQ test for adults.
• Brain volume, speed of neural transmission, and working memory capacity are related to IQ.
• Between 40% and 80% of the variability in IQ is due to genetics, meaning that overall genetics plays a bigger role than does environment in creating IQ differences among individuals.
• Intelligence is improved by education and may be hindered by environmental factors such as poverty.
• Emotional intelligence refers to the ability to identify, assess, manage, and control one’s emotions. People who are better able to regulate their behaviors and emotions are also more successful in their personal and social encounters.

Exercises and Critical Thinking

• Consider your own IQ. Are you smarter than the average person? What specific intelligences do you think you excel in?
• Did your parents try to improve your intelligence? Do you think their efforts were successful?
• Consider the meaning of the Flynn effect. Do you think people are really getting smarter?
• Give some examples of how emotional intelligence (or the lack of it) influences your everyday life and the lives of other people you know.

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