define intelligence in education

Student Diversity

Intelligence

For nearly a century, educators and psychologists have debated the nature of intelligence, and more specifically whether intelligence is just one broad ability or can take more than one form. Many classical definitions of the concept have tended to define  intelligence  as a single broad ability that allows a person to solve or complete many sorts of tasks, or at least many academic tasks like reading, knowledge of vocabulary, and the solving of logical problems (Garlick, 2002). Other psychologists believe that instead of a single factor, intelligence is a collection of distinct abilities. Still, other psychologists believe that intelligence should be defined in more practical terms. We’ll review three perspectives on intelligence, Spearman’s g, Sternberg’s Triarchic Theory of Intelligence, and Gardner’s Frame of Mind. Understanding theories of intelligence will help us understand variations in students’ intellectual abilities.

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 deemphasized what made each unique. There is research evidence of such a global ability, and the idea of general intelligence often fits with society’s everyday beliefs about intelligence. Partly for these reasons, an entire mini-industry has grown up around publishing tests of intelligence, academic ability, and academic achievement. Since these tests affect the work of teachers, I return to discussing them later in this book.

Video 7.1.1. Intelligence  explains the different definitions of intelligence and the nature/nurture debate in the context of intelligence.

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 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 considered 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 of 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 on 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.

Figure 7.1.1.  Examples of the types of items you might see on an intelligence test.

Wechsler Scales

The Wechsler Adult Intelligence 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. 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 people with intellectual disabilities.

Video 7.1.2.  Brain vs. Bias  provides an overview of the WAIS & WISC tests, standardization and validity, and IQ performance.

The Wechsler scale has also been adapted for preschool children in the form of the Wechsler primary and preschool scale of intelligence-fourth edition (WPPSI-IV) and for older children and adolescents in the form of the Wechsler intelligence scale for children-fifth edition (WISC-V) .

Bias in Intelligence Testing

Intelligence tests and psychological definitions of intelligence have been heavily criticized since the 1970s for being biased in favor of Anglo-American, middle-class respondents and for being inadequate tools for measuring non-academic types of intelligence or talent. Intelligence changes with experience, and intelligence quotients or scores do not reflect that ability to change. What is considered smart varies culturally as well, and most intelligence tests do not take this variation into account. For example, in the West, being smart is associated with being quick. A person who answers a question the fastest is seen as the smartest, but in some cultures, being smart is associated with considering an idea thoroughly before giving an answer. A well- thought out, the contemplative answer is the best answer.

Video 7.1.3. Watch this video to learn more about the history behind intelligence testing.

Theories 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.

Video 7.1.4.  Theories of Intelligence  reviews a few of the different theoretical views of intelligence.

General Intelligence Factor (“g”)

From 1904-to 1905 the French psychologist Alfred Binet (1857–1914) and his colleague Théodore Simon (1872–1961) began working on behalf of the French government to develop a measure that would identify children who would not be successful with the regular school curriculum. The goal was to help teachers better educate these students (Aiken, 1994). 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 the children all assessed the basic abilities to understand, reason, and make judgments. It turned out that the correlations among these different types of measures were, in fact, all positive; that is, 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, reason abstractly, adapt to novel situations, and 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 at Stanford University (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.

Sternberg’s Triarchic theory

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 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 , academic problem solving, and performing calculations, but that they do not typically assess creative intelligence , the ability to adapt to new situations and create new ideas , and/or practical intelligence , the ability to demonstrate common sense and street- smarts.

As Sternberg proposed, research has found that creativity is not highly correlated with analytical intelligence (Furnham & Bakhtiar, 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 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). Ericsson (1998), Weisberg (2006), Hennessey and Amabile (2010), and Simonton (1992) studied creative people and identified at least five components that are likely to be important for creativity as listed in Table 7.1.1.

Table 7.1.1. Important components for creativity

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, & Okazaki, 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 et al., 1993).

Gardner’s Frame of Mind

Theory of multiple intelligences: another champion of the idea of specific types of intelligences rather than one overall intelligence 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. A potential ninth intelligence, existential intelligence, still needs empirical support. Gardner investigated intelligences by focusing on children who were talented in one or more areas and adults who suffered from strokes that compromised some capacities, but not others. Gardner also 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). In addition to brain damage and the existence of savants, Gardner identified these 8 intelligences based on other criteria, including a set developmental history and psychometric findings. See table 7.1.2 for a list of Gardner’s eight specific intelligences.

Table 7.1.2.  Howard Gardner’s eight specific intelligences

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. There is no clear conclusion about how many intelligences there are. Our 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).

Nonetheless, whatever the status of the research evidence, the model itself can be useful as a way for teachers to think about their work. Multiple intelligences suggest the importance of diversifying instruction in order to honor and to respond to diversity in students’ talents and abilities. Viewed like this, whether Gardner’s classification scheme is actually accurate is probably less important than the fact there is (or may be) more than one way to be “smart.” In the end, as with cognitive and learning styles, it may not be important to label students’ talents or intellectual strengths. It may be more important simply to provide important learning and knowledge in several modes or styles, ways that draw on more than one possible form of intelligence or skill. A good example of this principle is your own development in learning to teach. It is well and good to read books about teaching (like this one, perhaps), but it is even better to read books and talk with classmates and educators about teaching and getting actual experience in classrooms. The combination both invites and requires a wide range of your talents and usually proves more effective than any single type of activity, whatever your profile of cognitive styles or intellectual abilities happens to be.

Extremes of Intelligence: Intellectual Disability and Giftedness

The results of studies assessing the measurement of intelligence show that IQ is distributed in the population in the form of a Normal Distribution (or bell curve), which is the pattern of scores usually observed in a variable that clusters around its average . In a normal distribution, the bulk of the scores fall toward the middle, with many fewer scores falling at the extremes. The normal distribution of intelligence shows that on IQ tests, as well as on most other measures, the majority of people cluster around the average (in this case, where IQ = 100), and fewer are either very smart or very dull. Because the standard deviation of an IQ test is about 15, this means that about 2% of people score above an IQ of 130, often considered the threshold for giftedness, and about the same percentage score below an IQ of 70, often being considered the threshold for intellectual disability.

Figure 7.1.2. Distribution of IQ Scores in the General PopulationThe normal distribution of IQ scores in the general population shows that most people have about average intelligence, while very few have extremely high or extremely low intelligence.

Intellectual Disabilities

People with very low IQ define one end of the distribution of intelligence scores. Intellectual disability (or intellectual developmental disorder ) is assessed based on cognitive capacity (IQ) and adaptive functioning. The severity of the disability is based on adaptive functioning, or how well the person handles everyday life tasks. About 1% of the United States population, most of them males, fulfill the criteria for intellectual developmental disorder, but some children who are given this diagnosis lose the classification as they get older and better learn to function in society.

Students with intellectual disabilities score poorly on standardized tests of intelligence. They may have limited language or impaired speech and may not perform well academically. Everyday tasks that most people take for granted, like getting dressed or eating a meal, may be possible, but they may also take more time and effort than usual. Health and safety can sometimes be a concern (for example, knowing whether it is safe to cross a street). For older individuals, finding and keeping a job may require help from supportive others. The exact combination of challenges varies from one person to another, but it always (by definition) involves limitations in  both  intellectual and daily functioning.

Video 7.1.5.  Intellectual Disabilities  defines intellectual disabilities (ID), explains the characteristics, and how to support students with ID.

Levels of Support for Individuals with Intellectual Disabilities

Intellectual disabilities happen in different degrees or amounts, though most often are relatively mild. Traditionally the intensity or “amount” of the disability was defined by scores on a standardized test of scholastic aptitude (or “IQ test”), with lower scores indicating a more severe disability. Because of the insensitivity of such tests to individuals’ daily social functioning, however, current trends are toward defining intensities by the amount of support needed by the individual. Table 1 summarizes the most commonly used scheme for this purpose, one created by the American Association on Intellectual and Developmental Disabilities (AAMR, 2002). Levels of support range from intermittent  (just occasional or “as needed” for specific activities) to  pervasive  (continuous in all realms of living).

As a classroom teacher, the intellectual disabilities that you are most likely to see are the ones requiring the least support in your classroom. A student requiring only intermittent support may require special help with some learning activities or classroom routines, but not others; he or she might need help with reading or putting on winter clothes, for example, but primarily on occasions when there is pressure to do these things relatively quickly. Students requiring somewhat more support are likely to spend somewhat less time in your classroom and more time receiving special help from other professionals, such as a special education teacher, a speech and language specialist, or an assistant to these professionals. These circumstances have distinct implications for ways of teaching these students.

Teaching Students with Intellectual Disabilities

There are many specific techniques that can help in teaching students with mild or moderate intellectual disabilities, but most can be summarized into three more general strategies. The first is to give more time and practice than usual; the second is to embed activities into the context of daily life or functioning where possible; and the third is to include the child both in social and in academic activities, rather than just one or the other. Let us look briefly at each of these ideas.

Giving More Time and Practice

If a student has a mild intellectual disability, they may be able to learn important fundamentals of the academic curriculum—basic arithmetic, for example, and basic reading. Because of the disability, though, the student may need more time or practice than most other students. They may be able to read many words by sight ( day ,  night ,  morning ,  afternoon , etc.), but need longer than other students to recognize and say them. Or the student may know that 2 + 3 = 5, but need help applying this math fact to real objects; you (or a helper) might need to show the student that two  pencils  plus three  pencils  make five  pencils .

Giving extra help takes time and perseverance, and can try the patience of the student (and of you, too). To deal with this problem, it may help to reward the student frequently for effort and successes with well-timed praise, especially if it is focused on specific, actual achievements; “You added that one correctly,” may be more helpful than “You’re a hard worker,” even if both comments are true. Giving appropriate praise is in turn easier if you set reasonable, “do-able” goals by breaking skills or tasks into steps that the student is likely to learn without becoming overly discouraged. At the same time, it is important not to insult the student with goals or activities that are  too easy or by using curriculum materials clearly intended for children who are much younger. Setting expectations too low actually deprives a student with an intellectual disability of rightful opportunities to learn—a serious ethical and professional mistake (Bogdan, 2006). In many curriculum areas, fortunately, there are already existing materials that are simplified, yet also appropriate for older students (Snell, et al., 2005). Special education teacher-specialists can often help in finding them and in devising effective ways of using them.

Adaptive and Functional Skills

Students with intellectual disabilities present especially clear examples of a universal dilemma of teaching: since there is not enough time to teach everything, how do we choose what to teach? One basis for selecting activities is to relate learning goals to students’ everyday lives and activities, just as you would with all students. This strategy addresses the other defining feature of intellectual disability, the student’s difficulties with adapting to and functioning in everyday living. In teaching addition and subtraction, for example, you can create examples about the purchasing of common familiar objects (e.g. food) and about the need to make or receive change for the purchases. Similar considerations apply to learning new reading or oral language vocabulary. Instead of simply learning words in a “basic reading” series (or reading a textbook), try encouraging the student to learn words that are especially useful to the student’s own life. Often the student, not you yourself, is the best person to decide what these words actually are.

An adaptive, functional approach can help in non-academic areas as well. In learning to read or “tell time” on a clock, for example, try focusing initially on telling the times important to the student, such as when he or she gets up in the morning or when school starts. As you add additional times that are personally meaningful to the student, he or she works gradually towards full knowledge of how to read the hands on a clock. Even if the full knowledge proves slow to develop, however, the student will at least have learned the most useful clock knowledge first.

Include the Student in Group Activities

The keyword here is  inclusion : the student should participate in and contribute to the life of the class as much as possible. This means that wherever possible, the student attends special events (assemblies, field days) with the class; that if the class plays a group game, then the student with the disability is part of the game; that if classmates do an assignment as a group, then if at all possible the student is assigned to one of the groups. The changes resulting from these inclusions are real but can be positive for everyone. On the one hand, they foster acceptance and helpfulness toward the child with the disability; classmates learn that school is partly about providing opportunities for everyone, and not just about evaluating or comparing individuals’ skills. On the other hand, the changes caused by inclusion stimulate the student with the disability to learn as much as possible from classmates, socially and academically. Among other benefits, group activities can give the student chances to practice “belonging” skills—how to greet classmates appropriately, or when and how to ask the teacher a question. These are skills, I might add, that are beneficial for everyone to learn, disabled or not.

Gifted and Talented Students

Giftedness refers to those who have an IQ of 130 or higher (Lally & Valentine-French, 2015). Having an extremely high IQ is clearly less of a problem than having an extremely low IQ, but there may also be challenges to being particularly smart. It is often assumed that schoolchildren who are labeled as “gifted” may have adjustment problems that make it more difficult for them to create social relationships. To study gifted children, Lewis Terman and his colleagues (Terman & Oden, 1959) selected about 1,500 high school students who scored in the top 1% on the Stanford-Binet and similar IQ tests (i.e., who had IQs of about 135 or higher), and tracked them for more than seven decades (the children became known as the “termites” and are still being studied today). This study found that these students were not unhealthy or poorly adjusted, but rather were above average in physical health and were taller and heavier than individuals in the general population. The students also had above-average social relationships and were less likely to divorce than the average person (Seagoe, 1975).

Terman’s study also found that many of these students went on to achieve high levels of education and entered prestigious professions, including medicine, law, and science. Of the sample, 7% earned doctoral degrees, 4% earned medical degrees, and 6% earned law degrees. These numbers are all considerably higher than what would have been expected from a more general population. Another study of young adolescents who had even higher IQs found that these students ended up attending graduate school at a rate more than 50 times higher than that of the general population (Lubinski & Benbow, 2006).

As you might expect based on our discussion of intelligence, kids who are gifted have higher scores on general intelligence “g,” but there are also different types of giftedness. Some children are particularly good at math or science, some at automobile repair or carpentry, some at music or art, some at sports or leadership, and so on. The idea of multiple intelligences leads to new ways of thinking about students who have special gifts and talents. More recently, however, the meaning of  gifted  has broadened to include unusual talents in a range of activities, such as music, creative writing, or the arts (G. Davis & Rimm, 2004). To indicate the change, educators often use the dual term  gifted and talented .

Qualities of the Gifted and Talented

What are students who are gifted and talented like? Generally, they show some combination of the following qualities:

• They learn more quickly and independently than most students their own age.
• They often have a well-developed vocabulary, as well as advanced reading and writing skills.
• They are very motivated, especially on tasks that are challenging or difficult.
• They hold themselves to higher than usual standards of achievement.

Contrary to a common impression, students who are gifted or talented are  not  necessarily awkward socially, less healthy, or narrow in their interests—in fact, quite the contrary (Steiner & Carr, 2003). They also come from all economic and cultural groups.

Ironically, in spite of their obvious strengths as learners, such students often languish in school unless teachers can provide them with more than the challenges of the usual curriculum. A kindergarten child who is precociously advanced in reading, for example, may make little further progress at reading if her teachers do not recognize and develop her skill; her talent may effectively disappear from view as her peers gradually catch up to her initial level. Without accommodation to their unusual level of skill or knowledge, students who are gifted or talented can become bored with school, and eventually, the boredom can even turn into behavior problems.

Partly for these reasons, students who are gifted or talented have sometimes been regarded as the responsibility of special education, along with students with other sorts of disabilities. Often their needs are discussed, for example, in textbooks about special education, alongside discussions of students with intellectual disabilities, physical impairments, or major behavior disorders (Friend, 2008). There is some logic to this way of thinking about their needs; after all, they  are  quite exceptional, and they do require modifications of the usual school programs in order to reach their full potential. But it is also misleading to ignore obvious differences between exceptional giftedness and exceptional disabilities of other kinds. The key difference is in students’ potential. By definition, students with gifts or talents are capable of creative, committed work at levels that often approach talented adults. Other students—including students with disabilities—may reach these levels, but not as soon and not as frequently. Many educators, therefore, think of the gifted and talented not as examples of students with disabilities, but as examples of diversity. As such they are not so much the responsibility of special education specialists, as the responsibility of all teachers to differentiate their instruction.

Supporting Gifted and Talented Students

Supporting the gifted and talented usually involves a mixture of  acceleration  and  enrichment  of the usual curriculum (Schiever & Maker, 2003).  Acceleration involves either a child’s skipping a grade, or else the teacher’s redesigning the curriculum within a particular grade or classroom so that more material is covered faster. Either strategy works, but only up to a point: children who have skipped a grade usually function well in the higher grade, both academically and socially. Unfortunately skipping grades cannot happen repeatedly unless teachers, parents, and the students themselves are prepared to live with large age and maturity differences within single classrooms. In itself, too, there is no guarantee that instruction in the new, higher-grade classroom will be any more stimulating than it was in the former, lower-grade classroom. Redesigning the curriculum is also beneficial to the student, but impractical to do on a widespread basis; even if teachers had the time to redesign their programs, many non-gifted students would be left behind as a result.

Enrichment involves providing additional or different instruction added to the usual curriculum goals and activities. Instead of books at more advanced reading levels, for example, a student might read a wider variety of types of literature at the student’s current reading level, or try writing additional types of literature himself. Instead of moving ahead to more difficult kinds of math programs, the student might work on unusual logic problems not assigned to the rest of the class. Like acceleration, enrichment works well up to a point. Enrichment curricula exist to help classroom teachers working with gifted students (and save teachers the time and work of creating enrichment materials themselves). Since enrichment is not part of the normal, officially sanctioned curriculum, however, there is a risk that it will be perceived as busywork rather than as intellectual stimulation, particularly if the teacher herself is not familiar with the enrichment material or is otherwise unable to involve herself in the material fully.

Obviously, acceleration and enrichment can sometimes be combined. A student can skip a grade and also be introduced to interesting “extra” material at the new grade level. A teacher can move a student to the next unit of study faster than she moves the rest of the class, while at the same time offering additional activities not related to the unit of study directly. For a teacher with a student who is gifted or talented, however, the real challenge is not simply to choose between acceleration and enrichment, but to observe the student, get to know him or her as a unique individual, and offer activities and supports based on that knowledge. This is essentially the challenge of differentiating instruction, something needed not just by the gifted and talented, but by students of all sorts. As you might suspect, differentiating instruction poses challenges in managing instruction.

There is a lively debate among scholars about whether it is appropriate or beneficial to label some children as “gifted and talented” in school and to provide them with accelerated special classes and other programs that are not available to everyone. Although doing so may help the gifted kids (Colangelo & Assouline, 2009), it also may isolate them from their peers and make such provisions unavailable to those who are not classified as “gifted.”

Video 7.1.6.  Gifted and Talented Students: Teaching Strategies  suggests ways to support gifted students.

Candela Citations

• Intelligence. Authored by : Nicole Arduini-Van Hoose. Provided by : Hudson Valley Community College. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Educational Psychology. Authored by : Kelvin Seifert and Rosemary Sutton. Provided by : The Saylor Foundation. Retrieved from : https://courses.lumenlearning.com/educationalpsychology. License : CC BY: Attribution
• Adolescent Psychology. Authored by : Nicole Arduini-Van Hoose. Provided by : Hudson Valley Community College. Retrieved from : https://courses.lumenlearning.com/adolescent. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Intelligence. Authored by : Carole Yue. Provided by : Khan Academy . Retrieved from : https://youtu.be/F9n3hLnwwc0. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Theories of Intelligence. Authored by : Brooke Miller. Provided by : Khan Academy. Retrieved from : https://youtu.be/oaJ01Ex7DLw. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Intellectual Disabilities. Authored by : Fittie Kolbe, Colleen Mcbrien, and Abby Pearlman. Retrieved from : https://youtu.be/ZPB5l67gpKk?t=17. License : All Rights Reserved
• Gifted and Talented Students: Teaching Strategies. Provided by : Teachings in Education. Retrieved from : https://youtu.be/n3gXI1HFcbY. License : All Rights Reserved

Educational Psychology Copyright © 2020 by Nicole Arduini-Van Hoose is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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What Is Intelligence In Psychology

Charlotte Ruhl

Research Assistant & Psychology Graduate

BA (Hons) Psychology, Harvard University

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

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Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

On This Page:

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

Key Takeaways

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

What Is Intelligence?

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

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

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

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

History of Intelligence

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

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

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

Thus, Galton operationalized intelligence as reaction time.

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

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

Theories of Intelligence

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

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

Spearman’s General Intelligence (g)

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

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

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

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

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

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

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

Thurstone’s Primary Mental Abilities

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

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

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

Gardner’s Multiple Intelligences

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

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

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

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

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

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

Triarchic Theory of Intelligence

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

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

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

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

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

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

Other Types of Intelligence

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

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

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

Emotional Intelligence

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

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

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

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

Fluid vs. Crystallized Intelligence

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

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

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

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

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

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

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

Intelligence Testing

Binet-simon scale.

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

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

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

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

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

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

Stanford-Binet Intelligence Scale

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

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

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

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

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

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

WISC and WAIS

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

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

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

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

Above Image: WISC-IV Sample Test Question

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

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

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

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

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

The Flynn Effect

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

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

Aptitude vs. Achievement Tests

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

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

Criticism of Intelligence Testing

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

Reliability and Construct Validity

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

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

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

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

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

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

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

Cultural Specificity

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

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

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

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

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

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

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

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

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

Social and Environmental Factors

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

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

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

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

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

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

Stereotype Threat

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

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

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

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

Self-Fulfilling Prophecy

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

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

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

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

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

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

Extremes of Intelligence

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

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

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

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

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

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

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

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

Intelligence Today

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

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

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

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

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Article Contents

Introduction, intelligence and education: clearly correlated, but what is the direction of causation, different views about education and intelligence and their association in epidemiology, intelligence and education: do they share genetic and environmental influences, conclusions and recommendations.

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Intelligence and education: causal perceptions drive analytic processes and therefore conclusions

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Ian J Deary, Wendy Johnson, Intelligence and education: causal perceptions drive analytic processes and therefore conclusions, International Journal of Epidemiology , Volume 39, Issue 5, October 2010, Pages 1362–1369, https://doi.org/10.1093/ije/dyq072

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Background Educational attainment is associated with many life outcomes, including income, occupation and many health and lifestyle variables. Many researchers use it as a control variable in epidemiological and other social scientific studies, often without specifying exactly what environmental effects or set of personal characteristics is being controlled. Other researchers assume that genetically influenced intelligence drives educational attainment, and think that intelligence is the appropriate control variable. Researchers’ different and often unstated causal assumptions can lead to very different analytical approaches and thus to very different results and interpretations.

Methods, results and conclusions We document several examples of this important variation in the treatment of education and intelligence and their association. We recommend greater clarity in stating underlying assumptions and developing analytical approaches and greater objectivity in interpreting results. We discuss implications for study designs.

Brighter people tend to get more schooling, and the longer-schooled tend to be brighter. These simple facts elicit surprisingly different interpretations among the many epidemiologists and social scientists who measure education and intelligence for research use. Their different interpretations contribute to differences in methodological and analytical treatments that can have profound impacts on study design, methodological choice, results and interpretation of results. Implicit interpretation of the association between these two variables is common throughout epidemiological and other social science research. With regard to health and other outcomes, this observationally ambiguous association involves the statistical issues of mediation, moderation, confounding and direct and indirect effects. These issues are always troublesome because their treatment depends not only on timing of available measurements, but also on understanding of causal pathways. The issues involved in the association between these particular two variables, however, are especially important to the newly emerging field of cognitive epidemiology. One or the other—especially education, due to its greater availability in datasets—is very commonly used as a control variable; intelligence and education are closely inter-related, and they may be measured with varying degrees of precision. Moreover, there is probably some form of longitudinal cascade between them, quite possibly with reciprocal causal and selection effects; 1 yet, the optimal longitudinal data sequence to understand the processes involved in these reciprocal and selection effects is often unavailable. At the same time, because they are not perfectly correlated, neither education nor intelligence is a perfect proxy for the other. It is thus often important to understand objectively which (if either) exerts a causative effect on an outcome.

Intelligence and education have been studied together since the earliest empirical research on these topics. Spearman 2 found teachers’ estimates of intelligence to be correlated with school exam results. Binet 3 developed what we now know as intelligence quotient (IQ) tests to identify those children who would not benefit from normal education. When intelligence and educational outcomes—often assessed as years of full-time education or as highest achieved qualification, and also by school grades or educational achievement test scores—are measured at about the same time, a typical correlation is ∼0.5. 4 Like any other correlation, a cross-sectional correlation between intelligence and education demands an open mind with regard to causal interpretation. Perhaps more intelligent people gain access to more and higher-level education. Perhaps exposure to more education causes higher intelligence test scores. The problem is one that is basic to epidemiology: what is person and what is situation, what is genetic and what is environmental and what is cause and what is effect? Influences may flow in both directions, and longitudinal studies can help to quantify their relative magnitudes.

Does higher intelligence beget better educational outcomes?

In longitudinal studies that measure psychometric intelligence first and educational attainments later (thus assessing that causal chain), there is a moderate to strong correlation between the two, as assessed by years spent in full-time education, the highest qualification obtained by a person or the scores obtained on educational assessments. 5 For example, in a study of approximately 70 000 children in the UK, the general factor from the Cognitive Abilities Test (CAT) battery taken at age 11 years correlated about 0.8 with the general factor of grades on the General Certificate of Secondary Education (GCSE) examinations taken at age 16 years. 6 The general factor of the CAT test had very similar loadings from the three domains of verbal, non-verbal (abstract) and quantitative reasoning. Older studies have reported correlations ranging from 0.60 to 0.96. 7–9 The conclusion from such studies might be that intelligence has stronger causal effects on educational results than vice versa.

Does more education beget higher intelligence?

Most studies of the influence of education on intelligence have not been longitudinal, but they have carefully examined the relation between length of schooling and intelligence, thus attempting to assess the reverse causal chain. Findings generally support the observation that more time in school does lead to greater intelligence. For example, Baltes and Reinert 10 compared the intelligence scores of three cross-sections of German 8- to 10-year olds who were separated in age by 4-month intervals. The intelligence tests used were assessments of induction, verbal comprehension, numerical facility and processing speed from the German Begabungs test system, which was based on Thurstone’s theory and classification of Primary Mental Abilities. Since the German school system at the time required the entering children to be 6 years old as of April 1, it was possible to compare the scores of children whose birthdays fell either just before or just after that dividing point, so that the children were effectively the same chronological ages but had a 1-year difference in schooling. Baltes and Reinert found that 8-year olds who had received an extra year of schooling performed more like the least schooled 10-year olds than the least schooled 8-year olds. They noted, also, that the test most affected in this way—the Grundrechnen test of numerical facility—‘is heavily loaded with material that is covered in the grade levels used’. Tests of more fluid skills were less affected; for example, the Buchstabenzaehlen test of letter counting, which assessed processing speed, and which contained material much less based on taught materials. Schmidt 11 reported analogous results from a South African community of East Indian immigrants who had varying exposure to school that was not dependent on ability. There, the correlations between schooling and two measures of non-verbal intelligence and one measure of verbal intelligence ranged from 0.49 to 0.68. The conclusion from such studies might be that education influences the development of intelligence. However, this requires the caveat that the so-called ‘intelligence tests’ should be scrutinized to examine the extent to which they contain materials that appear in the taught curriculum.

So, it is possible that intelligence causes differences in educational outcomes, or that education causes intelligence differences, or a bit of both. Indeed, it is probably more complex than this. Readers can find further detailed consideration of possible non-linear effects of schooling on mental test scores, and the parts played by measurement error in intelligence and education measurement in a rather technical paper by Hansen et al. 12 In this article, too, is the interesting idea of using a latent trait of ‘ability’ that might underlie both schooling and scores on achievement tests that are often used as indicators of intelligence.

A major part of the effect of education on cognition … is also indirect. In these data, the influence of education on cognition is mostly through its influence on adult SEP…. The total impact of socioeconomic circumstances [both childhood and adult] on cognitive abilities … is substantial…. This merits the appropriate modeling of the impact of socioeconomic circumstances.

Intelligence and education are commonly used as possible causes and mediators of other outcomes. Epidemiologists, sociologists, psychologists, economists, social geographers and demographers include intelligence and education as possible influences upon a variety of human factors, including health and illnesses, late-life cognitive function, social mobility and subsequent status attainment. Among such researchers there are striking differences in how the association between intelligence and education is viewed and treated analytically.

Examples assuming education is causal

The second path to midlife cognition, that via educational attainment, is easier to conceptualize, since there is clear evidence that schooling per se can lead to cognitive gains, even in late adolescence … Indeed, data from the 1946 birth cohort show that academic performance of the primary school (i.e., its record in sending pupils to selective secondary schools) was predictive of increased cognitive performance … Furthermore, it has been shown in the British 1958 birth cohort that the academic performance of the school is one of the major contributors to social class differences in childhood cognitive function … (p. 621).

Thus, in two ways, the association between education and NART in the Richards and Sacker 14 study might be caused at least in part by inherent cognitive ability per se . Richards’s and Sacker’s discussion of education ignored these possibilities and considered only the possible environmental effects of the educational setting.

The effect of blood pressure on cognition was stronger among women, and was stronger for some measures of cognitive ability than others … Confounding factors of age, educational level, occupational position, smoking, alcohol consumption, use of antihypertensive medication, diagnoses of diabetes, and cardiovascular disease were controlled in the analyses … (p. 1312).

Some economists, too, have examined education as a variable related to health, without considering the role of intelligence in the creation of educational variance. For example, the large study of the US censuses of 1960, 1970 and 1980 found that education was related to mortality. People with less education had higher mortality rates. 21 The conclusion was that, ‘education has a causal impact on mortality’ (p. 189), and that ‘we need to consider education policies more seriously as a means to increase health’ (p. 215). Some possible mediating variables were mentioned, including stress, depression and hostility, but the place of intelligence as a possible influence on educational outcomes was not mentioned. On the other hand, other economists have been nuanced in looking at the contributions of intelligence and education to health. In an analysis of the National Longitudinal Survey of Youth 1979, there was an interaction between them: ‘the causal effect of schooling on health is greatest for individuals with low cognitive ability’. 22

Examples assuming education is an outcome of intelligence

A contrast to the treatment of education as causal is that by Herrnstein and Murray 23 in The Bell Curve . They argued that education should not be statistically controlled at all in examining the association between adolescent cognitive ability and later life outcomes, because intelligence is a determinant of education. Their argument was that there is movement of people into higher levels of education based upon prior intelligence differences that are in part caused by genetic variation. This is actually consistent with current teachings of statistical practice in epidemiology, 24 but both interpretations and statistical approaches rely on causal models of the processes involved that should be tested rather than assumed.

Higher IQ test scores may lead to educational success, and entry into well remunerated, high-status employment with a concomitantly high salary. An alternative, but often ignored, explanation is that educational attainment may represent a proxy for IQ, rather than the converse. That is, people with higher IQs stay longer within education, gaining more and higher qualifications. In this study, IQ at age 11 was moderately strongly correlated with subsequent educational attainment (r = 0.61; p = 0.001) … including education in our statistical models may be regarded as overadjustment (pp. 243–44).

We have now shown that intelligence and education are correlated, and given illustrations of how education is sometimes assumed to be causal in epidemiology without considering that it might be in part an outcome of intelligence, and might even share genetic as well as environmental influences with it. Next, we examine the extent to which this is found.

One way to resolve some of the confusion over the causes of the association between intelligence and education is to examine the transactions among the genetic and environmental influences contributing to them. As we have already noted, the presence of genetic influences on intelligence is well established. These influences increase from <50% of variance in childhood to ∼70% in adulthood. 26–28 The variance accounted for by shared environmental influences on intelligence declines from early childhood to a near-to-zero contribution in adulthood. Non-shared environment contributes a sizeable minority of the influence through most of life, though this term also contains error of measurement.

Multivariate variance decompositions can take this exploration further. They can estimate the environmental and genetic contributions to the correlation between two measured variables such as intelligence and education, and the extent to which the two variables share common genetic and environmental influences. For example, the national test of educational achievement used in The Netherlands at age 12 years (the Cito test) 29 correlated between 0.41 and 0.63 with intelligence test scores gathered at ages 5, 7, 10 (using the Revised Amsterdamse Kinder Intelligentie Test) and 12 years (using the Wechsler Intelligence Test for Children). The additive genetic contributions to variance in the Cito were ∼60%, and genetic influences were the principal reason for the correlations between the intelligence test measures and the Cito. Similar results were obtained by Johnson, McGue and Iacono 4 , 30 in an adolescent sample, where a latent variable representation of school grades formed the measure of achievement and intelligence was measured using abbreviated Wechsler Scales (the children’s scales for the under-16 years of age, and the adult scales for those aged ≥16 years). Almost 70% of the educational variable’s variance could be attributed to genetic influence, and >56% was common to genetic influences on intelligence. Even after other predictors of school grades, including engagement, family risk and disruptive behaviours were included in addition to intelligence, 34% of the genetic influences on school grades were shared with intelligence. In a Swedish twin-based study, intelligence was assessed at military conscription—using tests of reasoning, synonym detection, viusospatial perception and mathematics/physics—and education was based on seven categories from <9 years of education to doctoral studies. The genetic correlation between intelligence and education was >0.5, and varied little (from 0.53 to 0.56) across the range of intelligence, and the shared environmental correlation between the two variables was 1.0. 31 This evidence of shared sources of influence is useful for epidemiologists to know and recognize in discussing results.

In fact, the causes of the association between intelligence and education might be more complex. 32 Analyses of educational attainment at age 24 years in the USA, based on data from the the Minnesota Twin Family Study, showed that the genetic and environmental contributions to educational outcomes can differ at different levels of intelligence. 33 The genetic variation in educational attainment increased 4-fold from low intelligence (people two standard deviations below the mean intelligence level) to high intelligence (two standard deviations above the mean). By contrast, the shared environmental variation increased >10-fold across the same range of intelligence. In simpler terms, this means that, in this particular geographical and temporal setting, one’s rearing environment (including family resources, broadly conceived) was a much more important source of variance in educational outcomes at lower than at higher levels of intelligence, where genetic sources were much more important. A similar set of analyses was conducted in Sweden, with importantly similar and different results. At higher levels of intelligence, as was found in the Minnesota twin sample, 33 genetic variance in educational outcomes were greater than at low levels of intelligence. For shared environment variance, however, the two countries had opposing results: in Sweden, there was more shared environmental variance at higher than lower levels of intelligence. 31 One should not forget, however, the genetic and shared environmental correlations between intelligence and educational attainments, which were strong in both locations.

At present, clinicians are taught to discern cognitive loss when a diagnosis of dementia is considered, and final diagnostic criteria specify that a decline in ability must have occurred before a definite diagnosis of dementia is made. Because in most situations no data on premorbid level of function are available, the general practice is to use education and occupational attainment as substitute measures of premorbid levels of function. In this regard, education adjustment seems useful and necessary, and the present finding of a common genetic factor supports this practice (p. 52).

These examples illustrate the diversity of assumptions that underlie approaches to study design involving education and intelligence among epidemiologists and other health and social scientists. At the same time, they highlight the impact that such assumptions can have on study design, results and interpretation of results. Because these assumptions are often unstated and unacknowledged, these examples also demonstrate that part of the difficulty in disentangling the possible causal associations linking these two variables can be traced to less-than-objective examination of all of the causal possibilities during study design and interpretation. Some of these difficulties can be remedied by greater attention to, awareness and statement of, underlying assumptions, and the consideration of reasonable alternatives by all researchers making use of education and intelligence and other closely related variables. This is important if we are to understand how cognitive function is involved in the development, maintenance, improvement and deterioration of physical health.

We are far from being the first to state that one must be suspicious about inferences after statistical tests to assess confounding, or mediation. We concentrated narrowly on this matter with respect to how education and intelligence are treated in epidemiology because these closely related variables are critical to understanding the role of cognitive function in epidemiology. We also tried to argue that knowledge about causal background enhances analytical decisions and interpretations. This point is made well, in the context of birth defects epidemiology, and more generally, by Hernán et al. 35

In order to make the points above, we have not always gone into detail on how educational assessments can differ. What are referred to as ‘educational outcomes’ can refer to quite distinct empirical phenomena: e.g. years of schooling completed, highest credential obtained, subjective assessments of academic performance (e.g. class rank) and standardized tests of academic achievement in some content domain. These have different correlations with intelligence test scores, because all result from somewhat different personal traits and circumstances, and they are measured with varying degrees of accuracy. Making such distinctions will be crucial for forming meaningful causal hypotheses about education and intelligence and how they combine to influence people’s lives.

It is clear that not everyone derives the same benefit from any given educational opportunity and that the same educational opportunities are not available to everyone. Distinguishing between the processes involved in education and intelligence is difficult because it requires measurement that can simultaneously establish causal attributions through precise timing and identify both genetic and environmental influences and their relations to the timing of measurement. The data necessary to do this with respect to education and intelligence are not often available. There are clear implications of the above points for study design.

First, the temporal cascade between intelligence and education will be clearer when repeated measures of each are available. This would allow longitudinal models to examine the direction and strengths of the mutual causal influences. Secondly, genetically informative designs—such as twin studies—can help to uncover the environmental and genetic aetiologies of the correlations between intelligence and education, and the other life outcomes with which both are associated. It will be especially interesting when specific genetic variants are found that are associated with intelligence differences, as these can also be examined to discover whether they are associated with educational differences. Thirdly, it should be kept in mind that, even though intelligence and education are correlated, one can still act as a moderator of the other with respect to life outcomes, such as health. 22 Therefore, study designs powerful enough to include interactions between the two are desirable. Fourthly, where it is possible to do so, multiple assessments of intelligence and educational outcomes at a single time point will alleviate the problems of measurement error through the construction of latent variables. 6 , 12 Fifthly, a mind that is kept open to the various plausible interpretations of analyses which involve education and intelligence helps, even when the above design strengths are not available. Finally, we should not be blinkered by considering only intelligence and education. It should be kept in mind that there might be other variables that contribute to the association between intelligence and education. Possible candidates could be personality traits and their influences on coping styles and motivations. Therefore researchers should consider measuring such constructs.

The authors are members of the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative. Funding from the Biotechnology and Biological Sciences Research Council (BBSRC), Engineering and Physical Sciences Research Council (EPSRC), Economic and Social Research Council (ESRC) and Medical Research Council (MRC) (Grant no. G00700704/84698).

Conflict of interest: None declared.

We illustrate that the use of education and intelligence measurements comes with different views about their environmental and genetic origins, and the reasons for their being correlated.

We show how this influences approaches to analyses and the interpretations of results.

We provide some information about the reasons for intelligence and education being correlated.

We provide some suggestions for study designs and argue for researchers to consider all likely interpretations of results involving education and intelligence.

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Multiple Intelligences in Teaching and Education: Lessons Learned from Neuroscience †

This brief paper summarizes a mixed method review of over 500 neuroscientific reports investigating the proposition that general intelligence ( g or IQ) and multiple intelligences (MI) can be integrated based on common and unique neural systems. Extrapolated from this interpretation are five principles that inform teaching and curriculum so that education can be strengths-based and personalized to promote academic achievement. This framework is proposed as a comprehensive model for a system of educational cognitive neuroscience that will serve the fields of neuroscience as well as educators. Five key principles identified are culture matters, every brain is unique—activate strengths, know thyself, embodied cognition/emotional rudder, and make it mean something.

1. Introduction

The pieces of a scientific puzzle are falling into place. For 35 years teachers, students, and parents have been stuck in the middle of the war of words among psychologists regarding the nature of human intelligence. In my view, an interpretation of the neuroscience evidence now builds a coherent bridge between general intelligence ( g or IQ) and multiple intelligences (MI) [ 1 ]. The remainder of this article is based on a similarly personal view, which is most likely not shared by most experts. This battle among theorists has resulted in confusion and unhappy compromises as teachers struggle to serve two masters. On the one side is the IQ tradition that argues that intelligence is unitary and mainly associated with academic skills (reading, math, and such). This tradition advocates for a standardized curriculum emphasizing basic skills development. On the other side are advocates for personalized instruction based on the idea of multiple intelligences [ 2 ]. They argue that human intelligence cannot be summed up with a single number; it is more than scholastic ability; and that student learning will increase with differentiated instruction that emphasizes strength-based activities.

For 35 years a wave of teachers around the world [ 3 ] has agreed with Howard Gardner that their students display very different cognitive profiles, even among those with similar IQ scores. Teachers want to customize their instruction and curriculum accordingly but have been thwarted by public policy and institutional guidelines to quickly raise academic test scores by (for the most part) “teaching to the test”. The result? No progress. Standardized national academic test scores have remained stagnant despite more than two decades of high stakes testing regimes in all 50 states [ 4 , 5 ].

Other barriers to progress are the outdated and inaccurate views (however pervasive among traditional psychologists and educational administrators) that the theory of multiple intelligences is invalid and ineffective [ 6 , 7 ]. This arose from the misguided opinion that MI is somehow against the development of academic skills such as reading and math. Nothing could be further from the truth.

Neuroscience evidence now reveals a neural bridge between IQ-type academic skills and the eight intelligences—linguistic and logical-mathematical (most closely related to academic achievement) and interpersonal and intrapersonal (also associated with school success); and spatial, musical, kinesthetic, and naturalist. The debate of “IQ vs. MI” is based on outdated model of human intelligence. Traditions rooted in a 19th century understanding of the mind are slowly evolving to keep up with the insights provided by advances in neuroscience.

A good scientific theory accurately describes behavior and has predictive power. In 1983 Gardner made several observations about human intelligence that a wealth of neuroscience evidence accumulated over the past 35 years has confirmed. First, academic skills (and IQ) are most closely associated with the linguistic and logical-mathematical intelligences. Second, there are unique neural architectures responsible for each of the intelligences ( Table 1 ) [ 1 ]. Third, each intelligence can be expressed in several qualitatively different ways, including analytical/practical, creative cognition, insight/intuition, and aesthetic judgment [ 8 ].

Multiple intelligences core cognitive units and sample neural correlates [ 1 ].

Note: The neural regions noted for each intelligence are those with the highest number of citations and are not the full list of citations in the literature. Intelligence is a complex idea that is represented by the diversity of neural structures cited for each of the multiple intelligences. See the literature [ 1 ] for full description.

2. Neuroscientific Evidence Supporting the Validity of MI Theory

The main criticism of MI is that it lacks empirical, experimental evidence of its validity [ 6 , 7 ]. General intelligence is considered to be valid because there is a wealth of test data amassed for more than 100 years—while there are no tests to measure the eight intelligences. Unrecognized by most researchers is the sizable number of brain studies that are matched to the multiple intelligences. This is a trove of scientific data scattered among many journals that are unread and largely incomprehensible to most non-neuroscientists—until recently.

The validity of any new idea can be difficult to establish especially for a theory of intelligence that challenges prevailing ideas and does not lend itself to psychometric testing. Using a rational-empirical methodology, more than 500 studies of brain function (largely fMRI experiments) were matched to the skills and abilities integral to each of the eight intelligences. Multiple studies of the core abilities for each intelligence were included to maximize reliability.

To summarize, an initial review of more than 318 experiments found a pattern of neural activations well-aligned with the cognitive components for each intelligence [ 1 ]. This was followed by a study of 417 experiments examining specific skill units within each intelligence and their relationships to each other, the other intelligences, and general intelligence [ 9 ]. A third review of 420 reports found that there are observable and meaningful differences in the neural activation patterns among skill level ability groups in four levels of brain analysis: primary regions, subregions, particular structures, and multi-region activations [ 10 ]. A study of 48 resting-state experiments found seven to fifteen intrinsic, functionally connected neural networks that are closely associated with seven of the eight intelligences [ 11 ]. Lastly, the neural architectures cited for general intelligence were compared with a proposed new category of Cognitive Qualities associated with the multiple intelligences. This investigation of 94 neuroscientific studies demonstrated support for the coherence of three Cognitive Qualities (creative cognition, insight/intuition, and aesthetic judgment) that are valued abilities integral to the definition and practical expression of each of the eight intelligences [ 8 ]. 1

Taken together, these investigations indicate that the multiple intelligences have clear, logical, and coherent neural patterns that are comparable to those identified with general intelligence. These data lend support to the proposition that each of the eight intelligences have unique neural architectures and that the idea of general intelligence is not incompatible with MI theory.

An intelligence differs from a skill in its depth, range, and complexity. Each of the multiple intelligences is a composite of related skills and this accounts for their complicated neural architectures. These detailed neural analyses provide a basis for future experimental tests of their ecological validity. However, because of the social-cultural aspects of the intelligences a neural description for MI may only be a framework rather than a complete analysis.

3. Using Neuroscience to Leverage Student Success with the Multiple Intelligences

Perhaps of greater consequence are the practical implications of these scientific observations for teaching and learning. As educators worldwide were exploring diverse ways to implement MI theory, neuroscientists were giving birth to the new field of educational cognitive neuroscience to answer the question: How can insights into brain processes enhance education? Of course, the answer to this question is not simple nor obvious, in fact, John Bruer [ 12 ] famously called the distance between the neuroscience lab and the classroom a “bridge too far”. He later concluded that what is needed was advanced cognitive science theories to properly interpret the neuroscientific evidence [ 13 ]. This is where MI theory serves as a “user interface” between our neural hardware and the cognitive software that activates learning “apps” in the classroom (as well as in everyday life). See conceptual framework in Figure 1 .

Personalized educational cognitive neuroscience: a framework. Note : The bridge between existing psychological models of cognition/behavior and education is spanned by multiple intelligences theory supported by neuroscience validity and efficacy evidence.

Each of the multiple intelligences can serve as “delivery routes” to personalize important cognitive and emotional processes underlying learning such as attention, memory, motivation, creative cognition, problem solving, and understanding [ 14 , 15 , 16 , 17 ]. How best to navigate these cognitive “routes”? We have neuroscience evidence to lend support to several different guiding principles. Each teacher and institution can interpret the principles and their underlying evidence according to the needs and goals of their particular situations.

Perhaps it is best to begin with a list of the most vital and vexing questions posed by teachers over the millennium.

• How to set the stage of the classroom/school to create the context for maximum learning?
• How to enhance cognitive engagement in the instruction and curricular materials?
• How to promote academic excellence?
• How to teach for effective transfer of knowledge from the classroom to real life?
• How to develop the “whole child” and instill the love of lifelong learning?

The following descriptions of five key ideas extracted from the neuroscience literature sketch a framework that speaks to the disparate worlds of the lab and the classroom. These ideas are well supported by the evidence but are offered as an initial sketch as a kind of “communicating bridge” between cognitive scientists and teachers ( Table 2 ).

Five key ideas from neuroscience: Guiding a multiple intelligences-inspired education.

Key Idea 1. Creating a Multiple Intelligences—Inspired Culture [ 16 , 17 , 18 , 19 , 20 , 21 ]

“…the brain and its neuronal activity must be considered a hybrid of both biological and social influences. In other words, our brains are biosocial. The brain is a relational organ that bridges the gap between the biological world of the organism and the social world of the environment and its culture”. [ 18 ] (p. 352)

A distinct advantage of embedding MI in the learning culture is that it can easily span across diverse cultures because of its cross-cultural origins. Every school represents a cultural system of educational beliefs, social ideas, and practices. As learning culture leaders, teachers can positively frame each child’s experience by simply acknowledging that we each have our unique profile of MI history, preferences, and perspectives. The natural language of MI can be used to advantage when communicating with culturally different students and their families. The foundation is to acknowledge and value each of the multiple intelligences as important, valuable, and potentially useful to each child in the classroom.

Key Idea 2. Every Brain is Unique—Activate Strengths! [ 15 , 22 , 23 , 24 , 25 , 26 ]

“…neuroimaging studies clearly show that patterns of brain activation and structure vary in systematic ways between individuals differing in working memory and other higher cognitive abilities. Both experience and genetic factors may contribute to such individual differences… has implications for human performance”. [ 22 ] (p. 70)

Students all have uniquely configured neural wiring that influences how they perform on classroom tasks. Teachers might experience great anxiety at the thought of having to cater to the learning profiles of so many different student brains. An impossible task! But perhaps with advances in computer software and apps and innovative assessments we are making progress towards the goal of personalization of instruction, so that students with specific strengths can exercise some choice about how information is presented to them. My own work in validating a standardized assessment—Multiple Intelligences Developmental Assessment Scales (MIDAS ® )—shows promise as a tool to understand the cognitive and neural differences among students [ 23 , 24 , 25 ]. This is a useful tool providing a practical bridge between neuroscientists and educators seeking to understand the minds and brains of individuals.

Key Idea 3. Know Thyself [ 2 , 27 , 28 , 29 ]

“Intrapersonal intelligence involves the capacity to understand oneself, to have an effective working model of oneself—including one’s own desires, fears, and capacities—and to use such information effectively in regulating one’s own life”. [ 2 ] (p. 43)

Neuroscience investigations into how the brain processes intrapersonal intelligence can be categorized into several distinct functions including: self-awareness, self-regulation, and executive functions. The frontal lobes and cortical midline structures (CMS) are known to be the core processing regions for many self-functions [ 27 ]. There are an unlimited number of ways that teachers can build into every subject activities to promote self-regulation and executive functions associated with excellence and achievement [ 28 ]. It begins with the teacher enhancing the students’ self-understanding and appreciation for the potential of their unique MI strengths.

Key Idea 4. Embodied Cognition and the Emotional Rudder [ 19 , 30 , 31 , 32 ]

“Recent findings in the neurosciences indicate reciprocal and parallel neural pathways between the cerebellum—traditionally viewed as controlling gross and fine motor functions but now hypothesized to play a role in thought itself—and the frontal cortex, where working memory and executive functions such as planning, monitoring, task management, and focusing attention occur”. [ 19 ]

The relationship between the body and the mind is now recognized by neuroscientists as being bi-directional and parallel, rather than just the mind directing the body. Immordino-Yang has gone even further in detailing “a framework that situates the emotional brain and its physiological regulatory functions ecologically, spiraling from bodily behavior to embodied neural functioning to social functioning to cultural functioning” [ 19 ] (p. 360). These findings point the way forward for teachers to create opportunities for students to translate subject content into physical movements to maximize memory and understanding.

Awareness of one’s body goes beyond mere physiology associated with the maintenance of life. It is also a platform upon which emotions are played out and translated into feelings. Damasio’s “somatic marker hypothesis” cites physical responses as important elements in decision-making and judgments [ 30 ]. When we direct students’ attention to their physical and emotional responses to a topic, we are providing them with a powerful marker for that information that is accessible in their real life beyond the classroom. Making these connections may provide the keys to enhanced transfer of learning from the classroom to daily life.

Key Idea 5. Make it Mean Something! [ 19 , 27 , 29 , 31 , 33 ]

“…Feelings are influenced by powerful, subjective, cognitive elaborations, and cultural interpretations of bodily and mental states in context. Unlike emotions, feelings are conscious and can sometimes become reportable. Feelings contribute to self-narratives and meaning-making”. [ 19 ] (p. 349) (emphasis added)

Mary Helen Immordino-Yang’s [ 19 ] research into self-narratives and meaning-making belies the view that facts and rational thought can be separated from feelings or practical action. Emotions and feelings are essential rudders that regulate and guide our thinking. They guide how we process new information to answer questions such as: Is this information of only temporary and limited importance? Or is it profoundly important and should I make the effort to rearrange my thinking to accommodate it?

The importance of “meaning making” to maximize engagement, learning, and cognitive transfer has been highlighted by a number of educational neuroscience researchers [ 27 , 31 , 33 ]. Such activities activate multiple neural regions and intelligences in the service of enhanced cognitive and emotional engagement.

4. Conclusions

Self-leadership for life-long learning is the ultimate goal for a person’s education—cultivating the knowledge that one has valuable intellectual abilities that can be developed and used to contribute meaningfully to one’s community. The multiple intelligences perspective contributes to this endeavor. Understanding how education can develop intrapersonal intelligence brings us back to the essential integration of the self within a context and a culture.

The application of neuroscience ideas in schools and classrooms is a complex endeavor and we may only be at the beginning of a long journey towards the goal of an effective interaction between neuroscientists and educators. Multiple intelligences theory provides a broad map of the software of the mind that is aligned with cognitive science and general intelligence. Cultural studies are revealing unspoken assumptions and priorities embedded in schooling that influence instruction and curriculum. The present investigation proposes that the theory of multiple intelligences provides a comprehensive framework for this array of factors influencing the design of instruction and curriculum that will be strengths-based, student centered, and community-relevant. This proposal initiated in 1983 is now supported by evidence from a diverse variety of research fields and perspectives.

*To qualify as an intelligence, each set of abilities has to fair reasonably well in meeting eight criteria as specified in Frames of Mind [ 2 ] (pp. 62–67):

• Identifiable cerebral systems;
• Evolutionary history and plausibility;
• Core set of operations;
• Meaning encoded in a symbol system;
• A distinct developmental history & mastery;
• Savants, prodigies, and exceptional people;
• Evidence from experimental psychology;
• Psychometric findings.

Definition: Intelligence is a biopsychological potential to process information that can be activated in a cultural setting to solve problems or create products that are of value in a culture. Intelligence Reframed [ 20 ] (p. 34).

This research received no external funding

Conflicts of Interest

The author is the creator and publisher of the Multiple Intelligences Developmental Assessment Scales (MIDAS) mentioned in this article. No other potential conflicts of interest are declared.

1 For a more detailed summary see www.MIResearch.org.

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Defining Intelligence

Learning Objectives

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

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

Definitions of 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 (see Table 7.1). 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).

Others psychologists believe that instead of a single factor, intelligence is a collection of distinct abilities. In the late 1930s L.L. Thurstone argued against Spearman’s concept of one general factor, citing evidence that intelligence is made up of seven independent factors: verbal comprehension , word fluency , number facility , spatial visualization , associative memory , perceptual speed , and reasoning .

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 behaviours 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 10.12).

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 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).

This story about the 2007 Virginia Tech shootings illustrates both high and low practical intelligences. During the incident, one student left her class to go get a soda in an adjacent building. She planned to return to class, but when she returned to her building after getting her soda, she saw that the door she used to leave was now chained shut from the inside. Instead of thinking about why there was a chain around the door handles, she went to her class’s window and crawled back into the room. She thus potentially exposed herself to the gunman. Thankfully, she was not shot. On the other hand, a pair of students were walking on campus when they heard gunshots nearby. One friend said, “Let’s go check it out and see what is going on.” The other student said, “No way, we need to run away from the gunshots.” They did just that. As a result, both avoided harm. The student who crawled through the window demonstrated some creative intelligence but did not use common sense. She would have low practical intelligence. The student who encouraged his friend to run away from the sound of gunshots would have much higher practical intelligence.

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 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 10.5 describes each type of intelligence.

Table  10.5

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 difficulty to measure and study emperically (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 Latin 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)

EVERYDAY CONNECTION: Creativity

Dr. Tom Steitz, former Sterling Professor of Biochemistry and Biophysics at Yale University, spent his career looking at the structure and specific aspects of RNA molecules and how their interactions could help produce antibiotics and ward off diseases. As a result of his lifetime of work, he won the Nobel Prize in Chemistry in 2009. He wrote, “Looking back over the development and progress of my career in science, I am reminded how vitally important good mentorship is in the early stages of one’s career development and constant face-to-face conversations, debate and discussions with colleagues at all stages of research. Outstanding discoveries, insights and developments do not happen in a vacuum” (Steitz, 2010, para. 39). Based on Steitz’s comment, it becomes clear that someone’s creativity, although an individual strength, benefits from interactions with others. Think of a time when your creativity was sparked by a conversation with a friend or classmate. How did that person influence you and what problem did you solve using creativity?

characterized as acquired knowledge and the ability to retrieve it. When you learn, remember, and recall information, you are using crystallized 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

find solutions that work in your everyday life by applying knowledge based on your experiences

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.

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.

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

Introduction to Psychology Copyright © 2021 by Southern Alberta Institution of Technology (SAIT) is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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