paulo n. lopes
myths, mysteries, and realities
james w. pellegrino
triarchic theory of intelligence
robert j. sternberg
The term emotional intelligence was introduced in a 1990 article by Peter Salovey and John D. Mayer. They described emotional intelligence as a set of skills that involve the ability to monitor one's own and others' feelings and emotions, to discriminate among them, and to use this information to guide one's thinking and action. Salovey and Mayer introduced the term as a challenge to intelligence theorists to contemplate an expanded role for the emotional system in conceptual schemes of human abilities, and to investigators of emotion who had historically considered the arousal of affect as disorganizing of cognitive activity. In the spirit of Charles Darwin, who, in his 1872 book The Expression of the Emotions in Man and Animals, viewed the emotional system as necessary for survival and as providing an important signaling system within and across species, Salovey and Mayer emphasized the functionality of feelings and described a set of competencies that might underlie the adaptive use of affectively charged information.
Associated Concepts and Formal Definition
The idea of an emotional intelligence was anticipated, at least implicitly, by various theorists who argued that traditional notions of analytic intelligence are too narrow. Emotional intelligence adds an affective dimension to Robert Sternberg's 1985 work on practical intelligence, is consistent with theorizing by Nancy Cantor and John Kihlstrom (1987) about social intelligence, and is directly related to research on children's emotional competencies by Carolyn Saarni (1999) and others. Emotional intelligence is most similar to one of the multiple intelligences characterized by Howard Gardner in Frames of Mind (1983). Gardner delineated intrapersonal intelligence as awareness of one's feelings and the capacity to effect discriminations among these feelings, label them, enmesh them in symbolic codes, and draw upon them as a means of understanding and guiding one's behavior.
Mayer and Salovey described emotional intelligence more specifically in 1997 by outlining the competencies it encompasses. They organized these competencies along four branches: (1) the ability to perceive, appraise, and express emotion accurately;(2) the ability to access and generate feelings when they facilitate cognition; (3) the ability to understand affect-laden information and make use of emotional knowledge; and (4) the ability to regulate emotions to promote growth and well-being.
Individuals can be more or less skilled at attending to, appraising, and expressing their own emotional states. These emotional states can be harnessed adaptively and directed toward a range of cognitive tasks, including problem solving, creativity, and decision-making. Emotional intelligence also includes essential knowledge about the emotional system. The most fundamental competencies at this level concern the ability to label emotions with words and to recognize the relationships among exemplars of the affective lexicon. Finally, emotional intelligence includes the ability to regulate feelings in oneself and in other people. Individuals who are unable to manage their emotions are more likely to experience negative affect and remain in poor spirits.
Measures and Findings
There are two types of measures of emotional intelligence: self-report questionnaires and ability tests. Self-report measures essentially ask individuals whether or not they have various competencies and experiences consistent with being emotionally intelligent. Ability tests require individuals to demonstrate these competencies, and they rely on tasks and exercises rather than on self-assessment. Self-report and ability measures may yield different findings, because asking people about their intelligence is not the same as having them take an intelligence test.
Self-report measures include relatively short scales, such as Niccola Schutte and colleagues'(1998) scale, intended to assess Salovey and Mayer's original model of emotional intelligence, and the Trait Meta-Mood Scale (TMMS), designed to assess people's beliefs about their propensity to attend with clarity to their own mood states and to engage in mood repair. More comprehensive self-report inventories, such as the Bar-On Emotional Quotient Inventory (EQ-i) encompass a larger number of subscales that tap into personality and other traits related to emotional experience and self-reported, noncognitive competencies.
The advantage of self-report measures is that they provide a global self-evaluation of emotional competence. They draw upon a rich base of self-knowledge and reflect people's experiences across different settings and situations. However, these measures have important limitations: they measure perceived, rather than actual, abilities; and they are susceptible to mood and social desirability biases, as well as deliberate or involuntary self-enhancement. Moreover, self-report measures overlap substantially with personality, and it is unclear whether they contribute to the understanding of social and emotional functioning over and above what personality traits might explain.
To overcome such problems, Mayer, David Caruso, and Salovey (1999) developed an ability test of emotional intelligence. Their first test, called the Multidimensional Emotional Intelligence Scale (MEIS), paved the way for a more reliable, better normed, and more professionally produced test, the Mayer, Salovey, and Caruso Emotional Intelligence Test (MSCEIT). This test asks people to process emotional information and use it to solve various problems, and to rate the effectiveness of different strategies for dealing with emotionally arousing situations. It consists of eight tasks, including decoding facial expressions and visual displays of emotion, understanding blends of emotions and emotional dynamics, integrating emotional information with other thinking processes, and managing emotions for purposes of self-regulation and social interaction. The test can be scored using either expert or consensus norms, and Mayer and his colleagues demonstrated in 2001 that these scoring methods yield similar results.
Ability tests of emotional intelligence avoid the self-enhancement and other biases that plague self-report measures, and they are very different from personality inventories. These are substantial advantages. However, these tests also have limitations. To assess emotional regulation, the MSCEIT evaluates people's knowledge of appropriate strategies for handling various situations, rather than their actual skill in implementing these strategies. It is not known to what extent the abilities assessed by ability tests generalize across situations and social or cultural contexts. While they are intended to assess skills, relying on consensus scoring can make it difficult to distinguish enacted skills from adjustment or conformity, especially because emotionally intelligent behavior necessarily reflects attunement to social norms and expectations.
Evidence suggests that emotional intelligence, assessed through ability tests, represents a coherent and interrelated set of abilities, distinct from (but meaningfully related to) traditional measures of intelligence, and developing with age. Initial studies also suggest that ability measures of emotional intelligence are associated with a range of positive outcomes, including lower peer ratings of aggressiveness and higher teacher ratings of prosocial behavior among school children; less tobacco and alcohol consumption among teenagers; higher self-reported empathy, life satisfaction, and relationship quality among college students; and higher manager ratings of effectiveness among leaders of an insurance company's customer claims teams. Emotional intelligence also seems to explain the perceived quality of social relationships over and above what personality traits and traditional measures of intelligence might explain.
Stronger evidence that emotional skills are associated with social adaptation comes from studies with children, using very different measures. In a large number of studies, children's abilities to read emotions in faces, understand emotional vocabulary, and regulate their emotions have been associated with their social competence and adaptation, as rated by peers, parents, and teachers.
Emotional Intelligence in the Schools
During the 1980s and 1990s, the idea that the social problems of young people (e.g., dropping out of school, illicit drug use, teenage pregnancy) can be addressed through school-based prevention programs became popular among educational reformers. Earlier programs focused primarily on social problem-solving skills or conflict resolution strategies. After the 1995 publication of a best-selling trade book on the topic of emotional intelligence by science writer Daniel Goleman, the concept of emotional intelligence gained enormous popular appeal, and school-based programs of social and emotional learning multiplied. These programs usually deal with emotions explicitly, and they can help children to build a feelings vocabulary, recognize facial expressions of emotion, control impulsive behavior, and regulate feelings such as sorrow and anger.
There is evidence that programs of social and emotional learning that are well designed and well implemented can promote children's social and emotional adjustment. Programs such as Promoting Alternative Thinking Strategies (PATHS), the Seattle Social Development Project, and Resolving Conflict Creatively have been evaluated through studies that track children's development over time. Benefits from these programs may include gains in children's social and emotional bonding to school, lowered dropout rates, a reduced incidence of aggressive or risky behaviors, and improvements in cognitive and emotional functioning. However, social and emotional learning programs usually address a very broad range of competencies, and it is not known to what extent the benefits observed in these studies can be attributed specifically to the training of emotional skills. Moreover, the success of these interventions depends on many factors, including the quality and motivation of the teachers, as well as their capacity to promote informal learning and generalization of skills.
Researchers associated with the Collaborative to Advance Social and Emotional Learning (CASEL) and others have drafted useful guidelines to help educators choose, adapt, and implement effective social and emotional learning programs. Important questions remain to be addressed, however. In dealing with others, people draw upon a very wide range of social and emotional skills, and it may be difficult to address all these competencies through formal or explicit instruction. It is not clear exactly what skills to emphasize, what are the best ways of teaching these skills, and to what extent they generalize across settings and situations.
Emotional skills may contribute to academic achievement in various ways. The ability to perceive and understand emotions may facilitate writing and artistic expression, as well as the interpretation of literature and works of art. Emotional regulation may help children to handle the anxiety of taking tests, or the frustrations associated with any pursuit requiring an investment of time and effort. It may also facilitate control of attention, sustained intellectual engagement, intrinsic motivation, and enjoyment of challenging academic activities.
See also: Intelligence, subentry on Myths, Mysteries, and Realities.
Bar-On, Reuven. 1997. EQ-I: Bar-On Emotional Quotient Inventory. Toronto: Multi-Health Systems.
Cantor, Nancy, and Kihlstrom, John F. 1987. Personality and Social Intelligence. Englewood Cliffs, NJ: Prentice-Hall.
Darwin, Charles. 1872. The Expression of the Emotions in Man and Animals. Chicago: University of Chicago Press.
Gardner, Howard. 1983. Frames of Mind: The Theory of Multiple Intelligences. New York: Basic Books.
Goleman, Daniel. 1995. Emotional Intelligence. New York: Bantam.
Mayer, John d.; Caruso, David R.; and Salovey, Peter. 1999. "Emotional Intelligence Meets Traditional Standards for an Intelligence." Intelligence 27:267–298.
Mayer, John D., and Salovey, Peter. 1997. "What Is Emotional Intelligence?" In Emotional Development and Emotional Intelligence, ed. Peter Salovey and David Sluyter. New York: Basic Books.
Mayer, John d.; Salovey, Peter; Caruso, David r.; and Sitarenios, Gill. 2001. "Emotional Intelligence As a Standard Intelligence." Emotion 1:232–242.
Saarni, Carolyn. 1999. The Development of Emotional Competence. New York: Guilford Press.
Salovey, Peter, and Mayer, John D. 1990. "Emotional Intelligence." Imagination, Cognition, and Personality 9:185–211.
Salovey, Peter; Mayer, John d.; Goldman, Susan l.; Turvey, Carolyn; and Palfai, Tibor P. 1995. "Emotional Attention, Clarity, and Repair: Exploring Emotional Intelligence Using the Trait Meta-Mood Scale." In Emotion, Disclosure, and Health, ed. James Pennebaker. Washington, DC: American Psychological Association.
Salovey, Peter, and Sluyter, David J., eds. 1997. Emotional Development and Emotional Intelligence: Educational Implications. New York: BasicBooks.
Schutte, Nicolla s.; Malouff, John m.; Hall, l. e.; Haggerty, d. j.; Cooper, Joan t.; Golden,C. J.; and Dornheim, L. 1998. "Development and Validation of a Measure of Emotional Intelligence." Personality and Individual Differences 25:167–177.
Sternberg, Robert J. 1985. Beyond IQ: A Triarchic Theory of Human Intelligence. Cambridge, Eng.: Cambridge University Press.
Paulo N. Lopes
Introductory treatments of the measurement of intelligence often begin with a discussion of three pioneers in the field: the French psychologist Alfred Binet (1857–1911), the English psychologist Charles Spearman (1863–1945), and the American psychologist Lewis Terman (1877–1956). Binet initiated the applied mental measurement movement when, in 1905, he introduced the first test of general mental ability. Spearman offered support for a psychologically cohesive dimension of general intellectual ability when, in 1904, he showed that a dominant dimension (called g ) appears to run through heterogeneous collections of intellectual tasks. And Terman championed the application of intelligence testing in schools and in the military. Subsequently, Terman also illustrated how tracking intellectually talented youth longitudinally (i.e., via long-term studies) affords fundamental insights about human development in general.
Binet: The Testing of Mental Ability
Binet was not the first to attempt to measure mental ability. Operating under the maxim of the fourth century b.c.e. Greek philosopher Aristotle, that the mind is informed to the extent that one's sensory systems bring in clear and reliable information, the English scientist Francis Galton (1822–1911) and others had aimed to measure intellect through fundamental psychophysical procedures that indexed the strength of various sensory systems. In contrast, Binet examined complex behaviors, such as comprehension and reasoning, directly. In doing so, his methods could not compare to psychophysical assessments in terms of reliability. But Binet more than made up for this in the validity of his assessment procedure in predicting school performance. Binet's insight was to use an external criterion to validate his measuring tool. Thus, he pioneered the empirically keyed or external validation approach to scale construction. His external criterion was chronological age, and test items were grouped such that the typical member of each age group was able to achieve 50 percent correct answers on questions of varying complexity. With Binet's procedure, individual differences in scale scores, or mental age (MA), manifested wide variation around students of similar chronological age (CA). These components were synthesized by William Stern to create a ratio of mental development: MA/CA. This was later multiplied by 100 to form what became known as the intelligence quotient ("IQ"), namely IQ = MA/CA ×100.
Spearman: The Discovery of g
While Binet was creating the first valid test of general intellectual functioning, Spearman was conducting basic research that offered tangible support for the idea that a psychologically cohesive dimension of general intelligence () underlies performance on any set of items demanding mental effort. In a groundbreaking publication from 1904 called "'General Intelligence': Objectively Determined and Measured," Spearman showed that g appears to run through all heterogeneous collections of intellectual tasks and test items. Ostensibly, items aggregated to form such groupings were seen as a hodgepodge. Yet when such items are all positively correlated and they are summed, the signal received by each is successively amplified and the noise carried by each is successively attenuated. And the total score paints a clear picture of the attribute under analysis.
Spearman and William Brown formalized this property of aggregation in 1910. The Spearman-Brown Prophecy formula estimates the proportion of common or reliable variance running through a composite: rtt= krxx÷ 1 + (k - 1) rxx (where: rtt = common or reliable variance, rxx = average item intercorrelation, and k = number of items). This formula reveals how a collection of items with uniformly light (weak) positive intercorrelations (say, averaging rxx = .15) can create a composite dominated by common variance. If fifty rxx = 15 items were available, for example, their aggregation would generate an individual differences measure having 90 percent common variance (and 10 percent random error). Stated another way, aggregation amplifies signal and lessens noise. As Bert Green stated in his 1978 article "In Defense of Measurement," "given enough sow's ears you can indeed make a silk purse" (p. 666). A large number of weak positive correlations between test items is, in fact, the ideal when measuring broad psychological attributes.
Terman: The Application of IQ
Binet's approach to assessing mental ability was impressive because, unlike psychophysical assessments of sensory systems, his test forecasted teacher ratings and school performance. And Spearman's work identified the dominant dimension responsible for the validity of these forecasts. Subsequently, Terman cultivated the new enterprise of applied psychological testing. For example, he played a key role in America's military effort when he combined forces with the American psychologist Robert Yerkes (1876–1956) to facilitate personnel selection during World War I. The U.S. armed forces needed an efficient means to screen recruits, many of whom were illiterate. One of Terman's students, Arthur Otis, had devised a nonverbal test of general intelligence, and his work was heavily drawn on to build one of the two group intelligence tests used for the initial screening and the appropriate placement of recruits: the Army Alpha (for literates) and Beta (for illiterates). The role that mental measurements played in World War I and, subsequently, in World War II constitutes one of applied psychology's great success stories. Even today, an act of the U.S. Congress mandates a certain minimum score on tests of general mental ability, because training efficiency is compromised prohibitively at IQs less than or equal to 80 (the bottom 10% of those tested).
Following World War I, Terman was one of the first to draw a generalization between the utility of military intellectual assessments and problems in America's schools. In the early 1920s, Terman developed one of the most famous longitudinal studies in all of psychology, exclusively devoted to the intellectually gifted (the top 1%). Terman, a former teacher himself, was aware of the ability range found in homogeneous groupings based on chronological age and became an advocate of homogeneous grouping based on mental age. Drawing on solid empirical findings from his study of 1,528 intellectually precocious youth (a study that continued after his death in 1956 and into the twenty-first century), he proposed that, at the extremes (say, two standard deviations beyond either side of IQ's normative mean), the likelihood of encountering special student needs increases exponentially. Terman noted that structuring educational settings around chronological age often results in classes of students with markedly different rates of learning (because of markedly different mental ages). Optimal rates of curriculum presentation and complexity vary in gradation throughout the range of individual differences in general intelligence. With IQ centered on 100 and a standard deviation of 16, IQs extending from the bottom 1 percent to the top 1 percent in ability cover an IQ range of approximately 63 to 137. But because IQs are known to go beyond 200, this span covers less than half of the possible range. Leta Hollingworth's classic 1942 study, Children above 180 IQ, provided empirical support for the unique educational needs of this special population. These needs have been empirically supported in every decade since.
The Modern Hierarchical Structure of Mental Abilities
Modern versions of intelligence tests index essentially the same construct that was uncovered at the turn of the twentieth century in Spearman's 1904 work, "'General Intelligence': Objectively Determined and Measured"–albeit with much more efficiency and precision. For example, g is a statistical distillate that represents approximately half of what is common among the thirteen subtests comprising the Wechsler Adult Intelligence Scale. As noted by intelligence researcher Ian J. Deary in "Intelligence: A Very Short Introduction," the attribute g represents the research finding that "there is something shared by all the tests in terms of people's tendencies to do well, modestly, or poorly on all of them" (p. 10). In 2001 Deary's team published the longest temporal stability assessment of general intelligence to date (covering a span of sixty-six years, from age eleven to age seventy-seven); they observed a correlation of .62, which rose to over .70 when statistical artifacts were controlled.
John B. Carroll and other modern psychometricians have come to a consensus that mental abilities follow a hierarchical structure, with g at the top of the hierarchy and other broad groups of mental abilities offering psychological import beyond g. Specifically, mathematical, spatial-mechanical, and verbal reasoning abilities all have demonstrated incremental (value-added) validity beyond g in forecasting educational and vocational criteria. Although mathematical, spatial, and verbal reasoning abilities do not have the breadth or depth of external correlates that g does, the incremental validity they offer makes them especially important for educational and vocational planning.
Psychological and Social Correlates of g
Psychologists at poles of the applied educational—industrial spectrum, such as Richard Snow and John Campbell, respectively, have underscored the real-world significance of general intelligence by incorporating it in lawlike empirical generalizations, as in the following two passages:
Given new evidence and reconsideration of old evidence, [g ] can indeed be interpreted as "ability to learn" as long as it is clear that these terms refer to complex processes and skills and that a somewhat different mix of these constituents may be required in different learning tasks and settings. The old view that mental tests and learning tasks measure distinctly different abilities should be discarded. (Snow, p. 22)
General mental ability is a substantively significant determinant of individual differences in job performance for any job that includes information-processing tasks. If the measure of performance reflects the information processing components of the job and any of several well-developed standardized measures used to assess general mental ability, then the relationship will be found unless the sample restricts the variances in performance or mental ability to near zero. The exact size of the relationship will be a function of the range of talent in the sample and the degree to which the job requires information processing and verbal cognitive skills. (Campbell, p. 56)
Modern research on general intelligence has sharpened validity generalizations aimed at forecasting educational outcomes, occupational training, and work performance. But empiricism also has escalated in domains at the periphery of general intelligence's network of external relationships, such as aggression, delinquency and crime, and income and poverty. For some benchmarks, general intellectual ability covaries .70–.80 with academic achievement measures, .40–.70 with military training assignments, .20–.60 with work performance (higher correlations reflect greater job complexity), .30–.40 with income, and around .20 with law-abidingness.
An excellent compilation of positive and negative correlates of g can be found in a 1987 work by Christopher Brand that documents a variety of weak correlations between general intelligence and diverse phenomena. For example, g is positively correlated with altruism, sense of humor, practical knowledge, responsiveness to psychotherapy, social skills, and supermarket shopping ability, and negatively correlated with impulsivity, accident-proneness, delinquency, smoking, racial prejudice, and obesity. This diverse family of correlates is especially thought-provoking because it reveals how individual differences in general intelligence "pull" with them cascades of direct and indirect effects.
Charles Murray's 1998 longitudinal analysis of educational and income differences between siblings is also illuminating. Murray studied biologically related siblings who shared the same home of rearing and socioeconomic class yet differed on average by 12 IQ points. He found that the differences in IQ predicted differences in educational achievement and income over the course of 15 years. His findings corroborate those of other studies that use a similar control for family environment, while not confounding socioeconomic status with biological relatedness.
Experts' definitions of general intelligence appear to fit with g 's nexus of empirical relationships. Most measurement experts agree that measures of general intelligence assess individual differences pertaining to "abstract thinking or reasoning," "the capacity to acquire knowledge," and "problem-solving ability." Naturally, individual differences in these attributes carry over to human behavior in facets of life outside of academic and vocational arenas. Abstract reasoning, problem solving, and rate of learning touch many aspects of life in general, especially in the computer-driven, information-dense society of the United States in the early twenty-first century.
Biological Correlates of g
General intelligence may be studied at different levels of analysis, and, as documented by Arthur Jensen in "The g Factor," modern measures of g have been linked to a variety of biological phenomena. By pooling studies of a variety of kinship correlates of g (e.g., identical and fraternal twins reared together and apart, and a variety of adoption designs), the heritability of general intelligence in industrialized nations has been estimated to be between 60 and 80 percent. These estimates reflect genetic factors responsible for individual differences between people, not overall level of g. In addition, research teams in molecular genetics, led by Robert Plomin, are working to uncover DNA markers associated with g. Using magnetic resonance imaging technology, total brain volume covaries in the high .30s with g after removing the variance associated with body size. Glucose metabolism is related to problem-solving behavior, and the highly gifted appear to engage in more efficient problem-solving behavior that is less energy expensive. Also, highly intellectually gifted individuals show enhanced right hemispheric functioning, and electroencephdographic (EEG) phenomena have been linked to individual differences in g. Finally, some investigators have suggested that dendritic arborization (the amount of branching of dendrites in neurons) is correlated with g.
A Continuing Field of Debate
The above empiricism is widely accepted among experts in the measurement/individual differences field. Yet, it has been common for empiricism pertaining to general intelligence (and interpretative extrapolations emanating from it) to stimulate contentious debate. Indeed, psychologists can be found on all sides of the complex set of issues engendered by assessing individual differences in general intelligence. But this is not new, and it is likely to continue. Because psychological assessments are frequently used for allocating educational and vocational opportunities, and because different demographic groups differ in test score and criterion performance, social concerns have followed the practice of intellectual assessment since its beginning in the early 1900s. In the context of these social concerns, alternative conceptualizations of intelligence, such as Howard Gardner's theory of multiple intelligences, Daniel Goleman's theory of emotional intelligence, and Robert Sternberg's triarchic theory of intelligence have generally been positively received by the public. Yet, measures of these alternative formulations of intelligence have not demonstrated incremental validity beyond what is already gained by conventional measures of intelligence. That is, they have not yet demonstrated incremental validity beyond conventional psychometric tests in the prediction of important life outcomes such as educational achievement, occupational level, and job performance. This is not to say that there is no room for improvement in the prediction process. Innovative measures of mental abilities, however, need to be evaluated against existing measures before one can claim that they capture something new.
See also: Assessment Tools, subentry on Psychometric and Statistical; Binet, Alfred; Intelligence, subentry on Myths, Mysteries, and Realities; Terman, Lewis.
Brand, Christopher. 1987. "The Importance of General Intelligence." In Arthur Jensen: Consensus and Controversy, ed. Sohan Magil and Celia Magil. New York: Falmer.
Campbell, John P. 1990. "The Role of Theory in Industrial and Organizational Psychology." In Handbook of Industrial and Organizational Psychology, 2nd edition, ed. Marvin D. Dunnette and Leaette M. Hough. Palo Alto, CA: Consulting Psychologists Press.
Carroll, John B. 1993. Human Cognitive Abilities: A Survey of Factor-Analytic Studies. Cambridge, Eng.: Cambridge University Press.
Deary, Ian J. 2001. Intelligence: A Very Short Introduction. New York: Oxford University Press.
Gottfredson, Linda S., ed. 1997. "Intelligence and Social Policy" (special issue). Intelligence 24 (1).
Green, Bert F. 1978. "In Defense of Measurement." American Psychologist 33:664–670.
Hollingworth, Leta S. 1942. Children above 180 IQ. New York: World Book.
Jensen, Arthur R. 1998. The g Factor: The Science of Mental Ability. Westport, CT: Praeger.
Murray, Charles. 1998. Income, Inequality, and IQ. Washington, DC: American Enterprise Institute.
Snow, Richard E. 1989. "Aptitude-Treatment Interaction as a Framework for Research on Individual Differences in Learning." In Learning and Individual Differences: Advances in Theory and Research, ed. Phillip. L. Ackerman, Robert J. Sternberg, and Robert G. Glasser. New York: Freeman.
Snyderman, Mark, and Rothman, Stanley. 1987. "Survey of Expert Opinion on Intelligence and Aptitude Testing." American Psychologist 42:137–144.
Spearman, Charles. 1904. "'General Intelligence': Objectively Determined and Measured." American Journal of Psychology 15:201–292.
Terman, Lewis. 1925–1959. Genetic Studies of Genius, 4 vols. Stanford, CA: Stanford University Press.
Thorndike, Robert M., and Lohman, David F. 1990. A Century of Ability Testing. Chicago: Riverside.
The theory of multiple intelligences (MI) was developed by Howard Gardner, a professor of cognition and education at Harvard University. Introduced in his 1983 book, Frames of Mind, and refined in subsequent writings, the theory contends that human intelligence is not a single complex entity or a unified set of processes (the dominant view in the field of psychology). Instead, Gardner posits that there are several relatively autonomous intelligences, and that an individual's intellectual profile reflects a unique configuration of these intelligences.
Definition of Intelligence
In his 1999 formulation of MI theory, Intelligence Reframed, Gardner defines intelligence as "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." By considering intelligence a potential, Gardner asserts its emergent and responsive nature, thereby differentiating his theory from traditional ones in which human intelligence is fixed and innate. Whether a potential will be activated is dependent in large part on the values of the culture in which an individual grows up and the opportunities available in that culture, although Gardner also acknowledges the role of personal decisions made by individuals, their families, and others. These activating forces result in the development and expression of a range of abilities (or intelligences) from culture to culture and also from individual to individual.
Gardner's definition of intelligence is unique as well in that it considers the creation of products such as sculptures and computers to be as important an expression of intelligence as abstract problem solving. Traditional theories do not recognize created artifacts as a manifestation of intelligence, and therefore are limited in how they conceptualize and measure it.
Criteria for intelligences. Gardner does not believe that the precise number of intelligences is known, nor does he believe that they can be identified through statistical analyses of cognitive test results. He began by considering the range of adult endstates that are valued in diverse cultures around the world. To uncover the abilities that support these end-states, he examined a wide variety of empirical sources from different disciplines that had never been used together for the purpose of defining human intelligence. His examination yielded eight criteria for defining an intelligence:
- Two criteria derived from biology: (1) an intelligence should be isolable in cases of brain damage, and (2) there should be evidence for its plausibility and autonomy in evolutionary history.
- Two criteria derived from developmental psychology: (3) an intelligence has to have a distinct developmental history along with a definable set of expert end-state performances, and (4) it must exist within special populations such as idiot savants and prodigies.
- Two criteria derived from traditional psychology: (5) an intelligence needs to be supported by the results of skill training for its relatively independent operation, and (6) also by the results of psychometric studies for its low correlation to other intelligences.
- Two criteria derived from logical analysis: (7) an intelligence must have its own identifiable core operation or set of operations, and (8) it must be susceptible to encoding in a symbol system–such as language, numbers, graphics, or musical notations.
To be defined as an intelligence, an ability has to meet most, though not all, of the eight criteria.
Identified intelligences. As of 2001, Gardner has identified eight intelligences:
- Linguistic intelligence, exemplified by writers and poets, describes the ability to perceive and generate spoken or written language.
- Logical-mathematical intelligence, exemplified by mathematicians and computer programmers, involves the ability to appreciate and utilize numerical, abstract, and logical reasoning to solve problems.
- Musical intelligence, exemplified by musicians and composers, entails the ability to create, communicate, and understand meanings made out of sound.
- Spatial intelligence, exemplified by graphic designers and architects, refers to the ability to perceive, modify, transform, and create visual or spatial images.
- Bodily-kinesthetic intelligence, exemplified by dancers and athletes, deals with the ability to use all or part of one's body to solve problems or to fashion products.
- Naturalistic intelligence, exemplified by archaeologists and botanists, concerns the ability to distinguish, classify, and use features of the environment.
- Interpersonal intelligence, exemplified by leaders and teachers, describes the ability to recognize, appreciate, and contend with the feelings, beliefs, and intentions of other people.
- Intrapersonal intelligence, apparent when individuals pursue a particular interest, choose a field of study or work, or portray their life through different media, involves the ability to understand oneself–including emotions, desires, strengths, and vulnerabilities–and to use such information effectively in regulating one's own life.
Gardner does not claim this roster of intelligences to be exhaustive; MI theory is based wholly on empirical evidence, and the roster can therefore be revised with new empirical findings. In the MI framework, all intelligences are equally valid and important, and though significantly independent of one another, they do not operate in isolation. Human activity normally reflects the integrated functioning of several intelligences. An effective teacher, for example, relies on linguistic and interpersonal intelligences, and possesses knowledge of particular subject areas as well.
Relationship to Other Theories
MI theory bears similarities to several other contemporary theories of intelligence, yet it remains distinct. Although it shares a pluralistic view of intelligence with Robert Sternberg's triarchic theory, MI theory organizes intelligences in terms of content areas, and no single cognitive function, such as perception or memory, cuts across all domains. The triarchic theory, in contrast, posits three intelligences differentiated by functional processes, and each intelligence operates consistently across domains.
Daniel Goleman's theory of emotional intelligence resonates with MI theory in that both acknowledge the social and affective aspects of intelligence. Whereas Goleman views intelligence from a moral and ethical perspective, however, Gardner regards all intelligences as value-free: He does not judge individuals as inferior or superior based on their configuration of intelligences, nor does he judge cultures as inferior or superior because they value one intelligence over another.
MI theory has been criticized on two grounds. First, some critics contend that psychometric research finds correlations, not autonomy, among abilities. Gardner has argued that these correlations are largely due to the use of psychometric instruments designed to measure only a given set of abilities. Second, critics have suggested that human intelligence is different from other human capabilities, such as musical talent. Gardner believes that such a narrow use of the word intelligence reflects a Western intellectual mind-set that does not recognize the diversity of roles that contribute to society.
Implications for Educational Practice
The primary intent for developing MI theory was to chart the evolution and topography of the human mind, not to prescribe educational practice. Nonetheless, MI theory has been discussed widely in the educational field and has been particularly influential in elementary education, where it has provided a useful framework for improving school-based practice in the areas of curricula, instruction, and assessment.
Curricula and instruction. From an MI perspective, curricula, particularly for young children, should encompass a broad range of subject areas that include (but go beyond) reading, writing, and arithmetic, because all intelligences are equally valuable. The visual arts, for example, are a serious domain in and of themselves, and not just as a means to improve reading scores. According to MI theory, the talented artist is just as intelligent as the excellent reader, and each has an important place in society. In The Disciplined Mind, Gardner cautions that an authentic MI-based approach goes beyond conveying factual knowledge about various domains: He stresses the importance of promoting in-depth exploration and real understanding of key concepts essential to a domain.
Because each child's biopsychological potential is different, providing a broad range of subject areas at a young age also increases the likelihood of discovering interests and abilities that can be nurtured and appreciated. Educators who work with at-risk children have been particularly drawn to this application of MI theory, because it offers an approach to intervention that focuses on strengths instead of deficits. By the same token, it extends the concept of the gifted child beyond those who excel in linguistic and logical pursuits to include children who achieve in a wide range of domains.
MI theory can be applied to the development of instructional techniques as well. A teacher can provide multiple entry points to the study of a particular topic by using different media, for example, and then encouraging students to express their understanding of the topic through diverse representational methods, such as pictures, writings, three-dimensional models, or dramatizations. Such instructional approaches make it possible for students to find at least one way of learning that is attuned to their predispositions, and they therefore increase motivation and engagement in the learning process. They also increase the likelihood that every student will attain at least some understanding of the topic at hand.
Assessment. When applied to student assessment, MI theory results in the exploration of a much wider range of abilities than is typical in the classroom, in a search for genuine problem-solving or product-fashioning skills. An MI-based assessment requires "intelligence-fair" instruments that assess each intellectual capacity through media appropriate to the domain, rather than through traditional linguistic or logical methods. Gardner also argues that for assessment to be meaningful to students and instructive for teachers, students should work on problems and projects that engage them and hold their interest; they should be informed of the purpose of the task–and the assessment criteria as well; and they should be encouraged to work individually, in pairs, or in a group. Thus, the unit of analysis extends beyond the individual to include both the material and social context.
MI-based assessments are not as easy to design and implement as standard pencil-and-paper tests, but they have the potential to elicit a student's full repertoire of skills and yield information that will be useful for subsequent teaching and learning. As part of Project Spectrum, Gardner and colleagues developed a set of assessment activities and observational guidelines covering eight domains, including many often ignored by traditional assessment instruments, such as mechanical construction and social understanding. Project Spectrum's work also included linking children's assessments to curricular development and bridging their identified strengths to other areas of learning.
Evidence of the Value of the Theory
MI theory has been incorporated into the educational process in schools around the world. There is much anecdotal evidence that educators, parents, and students value the theory, but, as of 2001, little systematic research on the topic has been completed. The main study was conducted by Mindy Kornhaber and colleagues at Harvard University's Project Zero in the late 1990s. They studied forty-one elementary schools in the United States that had been applying MI theory to school-based practice for at least three years. Among the schools that reported improvement in standardized-test scores, student discipline, parent participation, or performance of students with learning differences, the majority linked the improvement to MI-based interventions. Kornhaber's study also illuminates the conditions under which MI theory is adopted by schools and integrated into the educational process.
The difficulty of research on MI theory in education is correlating changes specifically to the theory, since schools are complex institutions that make it difficult to isolate cause-and-effect relationships. Indeed, since MI theory is meaningful in the context of education only when combined with pedagogical approaches such as project-based learning or artsintegrated learning, it is not possible to study the precise contribution of the theory itself to educational change, only the effect of interventions that are based on it or incorporate it.
See also: Assessment, subentries on Classroom Assessment, Performance Assessment, Portfolio Assessment.
Chen, Jie-Qi; Krechevsky, Mara; and Viens, Julie. 1998. Building on Children's Strengths: The Experience of Project Spectrum. New York: Teachers College Press.
Gardner, Howard. 1993. Frames of Mind: The Theory of Multiple Intelligences. New York: Basic Books.
Gardner, Howard. 1993. Multiple Intelligences: The Theory in Practice. New York: Basic Books.
Gardner, Howard. 1999. Intelligence Reframed: Multiple Intelligences for the 21st Century. New York: Basic Books.
Gardner, Howard. 2000. The Disciplined Mind: Beyond Facts and Standardized Tests: The K–12 Education That Every Child Deserves. New York: Penguin Books.
Goleman, Daniel. 1995. Emotional Intelligence: Why It Can Matter More Than IQ. New York: Bantam Books.
Kornhaber, Mindy L. 1999. "Multiple Intelligences Theory in Practice." In Comprehensive School Reform: A Program Perspective, ed. James H. Block, Susan T. Everson, and Thomas R. Guskey. Dubuque, IA: Kendall/Hunt.
Sternberg, Robert J. 1988. The Triarchic Mind: A New Theory of Human Intelligence. New York: Viking.
MYTHS, MYSTERIES, AND REALITIES
Intelligence and intelligence tests are often at the heart of controversy. Some arguments concern the ethical and moral implications of, for example, selective breeding of bright children. Other arguments deal with the statistical basis of various conclusions such as whether tests are biased, or how much of intelligence is genetically determined. What one hears less often is discussion of the construct of intelligence itself: What is intelligence? How does it grow? How and why do people differ intellectually? Questions like these, along with many others, which are central to any discussion of intelligence and intelligence testing, are less often raised, much less answered.
Historical Roots of Intelligence Tests
Intelligence testing began as a more or less scientific pursuit into the nature of differences in human intellect. However, it soon acquired practical significance as a tool for predicting school achievement and selecting individuals for various educational programs. Sir Francis Galton's work in the late 1800s formed the background for much of the research and theory pursued during the twentieth century on the assessment of individual differences in intelligence.
Galton believed that all intelligent behavior was related to innate sensory ability but his attempts to empirically validate that assumption were largely unsuccessful. In France, Alfred Binet and Victor Henri (1896) criticized the approach advocated by Galton in England and James McKeen Cattell in the United States and argued that appropriate intelligence testing must include assessment of more complex mental processes, such as memory, attention, imagery, and comprehension. In 1904, Binet and Théodore Simon were commissioned by the French Minister of Public Instruction to develop a procedure to select children unable to benefit from regular public school instruction for placement in special educational programs. In 1905 Binet and Simon published an objective, standardized intelligence test based on the concepts developed earlier by Binet and Henri. The 1905 test consisted of thirty subtests of mental ability, including tests of digit span, object and body part identification, sentence memory, and so forth. Many of these subtests, with minor modifications, are included in the Stanford-Binet intelligence test of the early twenty-first century.
In 1908 and again in 1911, Binet and Simon published revised versions of their intelligence test. The revised tests distinguished intellectual abilities according to age norms, thus introducing the concept of mental age. The subtests were organized according to the age level at which they could be successfully performed by most children of normal intelligence. As a result, children could be characterized and compared in terms of their intellectual or mental age. The Binet and Simon intelligence test was widely adopted in Europe and in the United States. Lewis Terman of Stanford University developed the more extensive Stanford-Binet test in 1916. This test has been used extensively in several updated versions throughout the United States.
A major change in intelligence testing involved the development of intelligence tests that could be simultaneously administered to large groups. Group tests similar to the original Binet and Simon intelligence test were developed in Britain and the United States. During World War I, group-administered intelligence tests (the Army Alpha and Army Beta tests) were used in the United States to assess the abilities of recruits who could then be selected for various duties based on their performance. In England, from the 1940s to the 1960s, intelligence tests were administered to all children near the age of eleven years to select students for different classes of vocational training.
An enormous number of "mental" tests are available in the early twenty-first century and are typically divided into those involving group versus individual administration. Whereas IQ (the intelligence quotient) was originally reported as the ratio of an individual's mental age to chronological age multiplied by 100 (100 × MA/CA), IQ has long been based upon normative score distributions for particular age groups. All individual and group tests currently yield such deviation IQs where 100 typically represents the 50th percentile and 68 percent of all scores fall between 85 and 115.
Factor Theories of Intelligence
What is intelligence and what do these tests actually assess? Very early in the psychological study of intelligence, Charles Spearman (1904) sought to empirically determine the similarities and differences between various mental tests and school performance measures. He found that many seemingly diverse mental tests were strongly correlated with each other. This led him to postulate a general factor of intelligence, g, that all mental tests measure in common while simultaneously varying in how much the general factor contributes to a given test's performance. On the basis of correlational studies, Spearman argued that intelligence is composed of a general factor that is found in all intellectual functioning plus specific factors associated with the performance of specific tasks. Spearman's theoretical orientation and methods of analysis served as the foundation of all subsequent factor analytic theories of intelligence. Spearman (1927) later developed a more complex factor theory introducing more general "group factors" made up of related specific factors. However, he adhered to his main tenet that a common ability underlies all intellectual behavior. For lack of a better definition, he referred to this as a mental energy or force.
The concept that intelligence is characterized by a general underlying ability plus certain task-or domain-specific abilities constitutes the basis of several major theories of intelligence, including those offered by Cyril L. Burt (1949), Philip E. Vernon (1961), and Arthur Jensen (1998). Quite distinct from theories of intelligence that emphasize g are those that emphasize specific abilities that can be combined to form more general abilities. Lloyd L. Thurstone (1924, 1938) developed factor analytic techniques that first separate out specific or primary factors. Thurstone argued that these primary factors represent discrete intellectual abilities, and he developed distinct tests to measure them. Among the most important of Thurstone's primary mental abilities are verbal comprehension, word fluency, numerical ability, spatial relations, memory, reasoning, and perceptual speed.
Raymond Cattell (1963, 1971) attempted a rapprochement of the theories of Spearman and Thur-stone. In an attempt to produce a g factor, he combined Thurstone's primary factors to form secondary or higher-order factors. Cattell found two major types of higher order factors and three minor ones. The major factors were labeled gf and gc, for fluid and crystallized general intelligence. Cattell argued that the fluid intelligence factor represents an individual's basic biological capacity. Crystallized intelligence represents the types of abilities required for most school activities. Cattell labeled the minor general factors gv, gr, and gs for visual abilities, memory retrieval, and performance speed, respectively. Cattell's initial theory has been substantially extended by individuals such as John L. Horn (1979,1985).
The most recent psychometric research supports a hierarchical model of intellect generally in accord with the outlines of the Cattell-Horn theory. At the top of the hierarchy is g and under are broad group factors such as gf and gc. Below these broad group factors are more specific or narrow ability factors. The majority of intelligence tests focus on providing overall estimates of g (or gf and gc ) since this maximizes the prediction of performance differences among people in other intellectual tasks and situations, including performance in school.
Alternative Theoretical Perspectives
The hierarchical model of human intelligence that has evolved from the psychometric or measurement approach is not the only influential perspective on human intellect. A second view of intelligence, that provided by developmental psychology, stems from the theory of intellectual development proposed by the Swiss psychologist Jean Piaget. This tradition is a rich source of information on the growth and development of intellect. A third view on intelligence, the information-processing or cognitive perspective, is an outgrowth of work in cognitive psychology since the 1970s. It provides elaborate descriptions and theories of the specific mental activities and representations that comprise intellectual functioning. The three perspectives are similar with regard to the general skills and activities that each associates with "being or becoming intelligent." For all three, reasoning and problem-solving skills are the principal components of intelligence. A second area of overlap among the three involves adaptability as an aspect of intelligence.
The differences and separate contributions of the three perspectives to an understanding of human intellect also stand out. The emphasis on individual differences within the psychometric tradition is certainly relevant to any complete understanding of intelligence. A theory of intelligence should take into account similarities and differences among individuals in their cognitive skills and performance capabilities. However, a theory of human intellect based solely on patterns of differences among individuals cannot capture all of intellectual functioning unless there is little that is general and similar in intellectual performance.
In contrast, the developmental tradition emphasizes similarities in intellectual growth and the importance of organism—environment interactions. By considering the nature of changes that occur in cognition and the mechanisms and conditions responsible, one can better understand human intellectual growth and its relationship to the environment. This requires, however, that one focus not just on commonalities in the general course of cognitive growth, but consider how individuals differ in the specifics of their intellectual growth. Such a developmental-differential emphasis seems necessary for a theory to have adequate breadth and to move the study of intelligence away from a static, normative view, where intelligence changes little over development, to a more dynamic view that encompasses developmental change in absolute levels of cognitive power.
Finally, the cognitive perspective helps to define the scope of a theory of intelligence by further emphasizing the dynamics of cognition, through its concentration on precise theories of the knowledge and processes that allow individuals to perform intellectual tasks. Psychometric and developmental theories typically give little heed to these processes, yet they are necessary for a theory of intelligence to make precise, testable predictions about intellectual performance.
No theory developed within any of the three perspectives addresses all of the important elements and issues mentioned above. This includes the more recent and rather broad theories such as Howard Gardner's multiple intelligences theory (1983, 1999) and Robert J. Sternberg's triarchic theory (1985). Both theories represent an interesting blending of psychometric, developmental, and cognitive perspectives.
Uses and Abuses of Tests
Above it was noted that testing was developed in response to pragmatic concerns regarding educational selection and placement. The use of intelligence tests for educational selection and placement proliferated during the decades from the 1930s through 1960s as group tests for children became readily available. Since the early 1980s, however, general intelligence testing has declined in public educational institutions. One reason for diminished used of such tests is a trend away from homogeneous grouping of students and attendant educational tracking. A second reason is that achievement rather than aptitude testing has become increasingly popular. Not surprisingly, such tests tend to be better predictors of subsequent achievement than aptitude or intelligence tests. Even so, it is an established fact that measures of general intelligence obtained in childhood yield a moderate 0.50 correlation with school grades. They also correlate about 0.55 with the number of years of education that individuals complete.
Intelligence and aptitude tests continue to be used with great frequency in military, personnel-selection, and clinical settings. There are also two major uses of intelligence tests within educational settings. One of these is for the assessment of mental retardation and learning disabilities, a use of tests reminiscent of the original reason for development of the Binet and Simon scales in the early 1900s. The second major use is at the postsecondary level. College entrance is frequently based upon performance on measures such as the SAT, first adopted in the United States by the College Entrance Examination Board in 1937. Performance on the SAT, together with high school grades, is the basis for admission to many American colleges and universities. The ostensible basis for using SAT scores is that they moderately predict freshman grade point average–precisely what they were originally designed to do. However, considerable debate has arisen about the legitimacy and value of continued use of SAT scores for college admission decisions.
Throughout the history of the testing movement, dating back to the early 1900s and extending to the early twenty-first century, there has been controversy concerning the (mis) use of test results. One of the earliest such debates was between Lewis Terman, who helped develop the revised Stanford-Binet and other tests, and the journalist Walter Lippman. A frequent issue in debates about the uses and abuses of intelligence tests in society is that of bias. It is often argued that most standardized intelligence tests have differential validity for various racial, ethnic, and socioeconomic groups. Since the tests emphasize verbal skills and knowledge that are part of Western schooling, they are presumed to be unfair tests of the cognitive abilities of other groups. As a response to such arguments, attempts have been made to develop culture-fair or culture-free tests. The issue of bias in mental testing is beyond this brief review and Arthur R. Jensen (1980; 1981) can be consulted for highly detailed treatments of this topic. Evidence in the 1990s suggests that no simple form of bias in either the content or form of intelligence tests accounts for the mean score differences typically observed between racial and ethnic groups.
Factors Affecting Test Scores
Much of the research on intelligence has focused on specific factors affecting test scores. This includes research focused on environmental versus genetic contributions to IQ scores, related issues such as race differences in IQ, and overall population trends in IQ.
One of the most extensively studied and hotly debated topics in the study of intelligence is the contribution of heredity and environment to individual differences in test scores. Given a trait such as measured intelligence on which individuals vary, it is inevitable for people to ask what fraction is associated with differences in their genotypes (the so-called heritability of the trait) as well as what fraction is associated with differences in environmental experience. There is a long history of sentiment and speculation with regard to this issue. It has also proven difficult to answer this question in a scientifically credible way, in large measure due to the conceptual and statistical complexity of separating out the respective contributions of heredity and environment. Adding to the complexity is the need to obtain test score data from people who have varying kinship and genetic relationships, including identical and fraternal twins, siblings, and adoptive children with their biological and adoptive parents. Nonetheless, evidence has slowly been gathered that heritability is sizeable and that it varies across populations. For IQ, heritability is markedly lower for children, about 0.45, than for adults where it is about0.75. This means that with age, differences in test scores increasingly reflect differences in the genotype and in individual life experience rather than differences in the families within which they were raised. The factors underlying this shift as well as the mechanism by which genes contribute to individual differences in IQ scores are largely unknown. The same can be said for understanding environmental contributions to those differences. A common misconception is that traits like IQ with high heritability mean that the results are immutable, that the environment has little or no impact, or that learning is not involved. This is wrong since heritable traits like vocabulary size are known to depend on learning and environmental factors.
Perhaps no topic is more controversial than that of race differences in IQ, especially since it is so often tied up with debates about genetics and environmental influences. It is an established fact that there are significant differences between racial and ethnic groups in their average scores on standardized tests of intelligence. In the United States, the typical difference between Caucasians and African Americans is 15 points or one standard deviation. A difference of this magnitude has been observed for quite a long period of time with little evidence that the difference has declined despite significant evidence that across the world IQ scores have risen substantially over the last fifty years. The latter phenomenon is known as the "Flynn Effect," and it, like so many other phenomena associated with test scores, begs for an adequate explanation.
There is a tendency to interpret racial and ethnic differences in mean IQ scores as being determined by genetic factors since, as noted above, IQ scores in general have a fairly high level of heritability and the level of heritability seems to be about the same in different racial and ethnic groups. There is, however, no logical basis on which to attribute the mean difference between racial groups to either genetic or environmental factors. As one group of researchers stated, "In short, no adequate explanation of the differential between the IQ means of Blacks and Whites is presently available" (Neisser et al., p. 97).
Age and Intelligence
Although most intelligence tests are targeted for school-age populations, there are instruments developed for younger age groups. Such tests emphasize the assessment of perceptual and motor abilities. Unfortunately, measures of infant and pre-school intelligence tend to correlate poorly with intelligence tests administered during the school years. However, there appears to be a high degree of stability in the IQ scores obtained in the early primary grades and IQ scores obtained at the high school level and beyond. Often this is misinterpreted as indicating that an individual's intelligence does not change as a function of schooling or other environmental factors. What such results actually indicate is that an individual's score relative to his or her age group remains fairly constant. In an absolute sense, an individual of age 16 can solve considerably more difficult items and problems than an individual of age 8. Comparing IQ scores obtained at different ages is akin to comparing apples and oranges since the composition of tests changes markedly over age levels.
Research has also studied changes in IQ following early adulthood. A frequent conclusion from research examining age groups ranging from 21 to 60 and beyond is that there is an age-related general decline in intellectual functioning. However, there are serious problems with many such studies since they involve cross-sectional rather than longitudinal contrasts. In those cases where longitudinal data are available, it is less obvious that intelligence declines with age. John L. Horn and Cattell (1967) presented data indicating a possible differential decline in crystallized and fluid intelligence measures. Crystallized intelligence measures focus on verbal skills and knowledge whereas fluid intelligence measures focus on reasoning and problem solving with visual and geometric stimuli. The latter also often place an emphasis on performance speed. Fluid intelligence measures tend to show substantial declines as a function of age, whereas crystallized intelligence measures often show little or no decline until after age 65. Research in the 1990s based on combinations of longitudinal and cross-sectional samples supports the conclusion that there are age-related declines in intelligence, which seem to vary with the type of skill measured, and that the declines are often substantial in the period from age 65 to 80.
After more than 100 years of theory and research on the nature and measurement of intelligence there is much that researchers know but even more that they don't understand. Still lacking is any agreed upon definition of intelligence and many of the empirical findings regarding intelligence test scores remain a puzzle. In their summary paper "Intelligence: Knowns and Unknowns," Ulric Neisser and colleagues (1996) stated:
In a field where so many issues are unresolved and so many questions unanswered, the confident tone that has characterized most of the debate on these topics is clearly out of place. The study of intelligence does not need politicized assertions and recriminations; it needs self restraint, reflection, and a great deal more research. The questions that remain are socially as well as scientifically important. There is no reason to think them unanswerable, but finding the answers will require a shared and sustained effort as well as the commitment of substantial scientific resources. (p. 97)
See also: Gifted and Talented, Education of; Individual Differences, subentry on Abilities and Aptitudes.
Binet, Alfred, and Henri, Victor. 1896. "La Psychologie Individuelle." Année Psychologie 2:411–465.
Block, Ned J., and Dworkin, Gerald. 1976. The IQ Controversy. New York: Pantheon Books
Brody, Nathan. 1992. Intelligence. San Diego, CA: Academic Press.
Burt, Cyril L. 1949. "The Structure of the Mind: A Review of the Results of Factor Analysis." British Journal of Educational Psychology 19:100–111, 176–199.
Carroll, John B. 1978. "On the Theory-Practice Interface in the Measurement of Intellectual Abilities." In Impact of Research on Education, ed. Patrick Suppes. Washington, DC: National Academy of Education.
Carroll, John B. 1993. Human Cognitive Abilities: A Survey of Factor Analytic Studies. Cambridge, Eng.: Cambridge University Press.
Cattell, Raymond B. 1963. "Theory of Fluid and Crystallized Intelligence: A Critical Experiment." Journal of Educational Psychology 54:1–22.
Cattell, Raymond B. 1971. Abilities: Their Structure, Growth and Action. Boston: Houghton Mifflin.
Flynn, John R. 1987. "Massive IQ Gains in 14 Nations: What IQ Tests Really Measure." Psychological Bulletin 101:171–191.
Gardner, Howard. 1983. Frames of Mind: The Theory of Multiple Intelligences. New York: Basic Books.
Gardner, Howard. 1999. Intelligence Reframed: Multiple Intelligences for the 21st Century. New York: Basic Books.
Gould, Stephen, J. 1996. The Mismeasure of Man. New York: Norton.
Gustafsson, Jan-Eric. 1988. "Hierarchical Models of Individual Differences in Cognitive Abilities." In Advances in the Psychology of Human Intelligence, Vol. 4, ed. Robert J. Sternberg. Hillsdale, NJ: Erlbaum.
Herrnstein, Richard, and Murray, Charles. 1994. The Bell Curve: Intelligence and Class Structure in American Life. New York: Free Press.
Horn, John L. 1979. "The Rise and Fall of Human Abilities." Journal of Research on Developmental Education 12:59–78.
Horn, John L. 1985. "Remodeling Old Models of Intelligence." In Handbook of Intelligence: Theories, Measurements, and Applications, ed. Benjamin B. Wolman. New York: Wiley.
Horn, John L., and Cattell, Raymond B. 1967. "Age Differences in Fluid and Crystallized Intelligence." Acta Psychologica 26:107–129.
Jensen, Arthur R. 1980. Bias in Mental Testing. New York: Free Press.
Jensen, Arthur R. 1981. Straight Talk on Mental Tests. New York: Free Press.
Jensen, Arthur R. 1998. The g Factor: The Science of Mental Ability. Westport, CT: Praeger.
Lemann, Nicholas. 1999. The Big Test: The Secret History of the American Meritocracy. New York: Farrar, Strauss, and Giroux.
Neisser, Ulric, et al. 1996. "Intelligence: Knowns and Unknowns." American Psychologist 51:77–101.
Spearman, Charles. 1904. "General Intelligence, Objectively Determined and Measured." American Journal of Psychology 15:201–293.
Spearman, Charles. 1927. The Abilities of Man: Their Nature and Measurement. New York: Macmillan.
Sternberg, Robert J. 1985. Beyond IQ: A Triarchic Theory of Human Intelligence. New York: Cambridge University Press.
Thurstone, Lloyd L. 1924. The Nature of Intelligence. London and New York: Harcourt Brace.
Thurstone, Lloyd L. 1938. Primary Mental Abilities. Psychometric Monographs No. 1. Chicago: University of Chicago Press.
Vernon, Philip E. 1961. The Structure of Human Abilities. London: Methuen.
James W. Pellegrino
TRIARCHIC THEORY OF INTELLIGENCE
The triarchic theory of intelligence is based on a broader definition of intelligence than is typically used. In this theory, intelligence is defined in terms of the ability to achieve success in life based on one's personal standards–and within one's sociocultural context. The ability to achieve success depends on the ability to capitalize on one's strengths and to correct or compensate for one's weaknesses. Success is attained through a balance of analytical, creative, and practical abilities–a balance that is achieved in order to adapt to, shape, and select environments.
Information-Processing Components Underlying Intelligence
According to Robert Sternberg's proposed theory of human intelligence, a common set of universal mental processes underlies all aspects of intelligence. Although the particular solutions to problems that are considered "intelligent" in one culture may be different from those considered intelligent in another, the mental processes needed to reach these solutions are the same.
Metacomponents, or executive processes, enable a person to plan what to do, monitor things as they are being done, and evaluate things after they are done. Performance components execute the instructions of the metacomponents. Knowledge-acquisition components are used to learn how to solve problems or simply to acquire knowledge in the first place. For example, a student may plan to write a paper (metacomponents), write the paper (performance components), and learn new things while writing (knowledge-acquisition components).
Three Aspects of Intelligence
According to the triarchic theory, intelligence has three aspects: analytical, creative, and practical.
Analytical intelligence. Analytical intelligence is involved when the components of intelligence are applied to analyze, evaluate, judge, or compare and contrast. It typically is involved in dealing with relatively familiar kinds of problems where the judgments to be made are of a fairly abstract nature.
In one study, an attempt was made to identify the information-processing components used to solve analogies such as: A is to B as C is to: D1, D2, D3, D4 (e.g., lawyer is to client as doctor is to [a] nurse, [b] medicine, [c] patient, [d] MD). There is an encoding component, which is used to figure out what each word (e.g., lawyer ) means, while the inference component is used to figure out the relation between lawyer and client.
Research on the components of human intelligence has shown that although children generally become faster in information processing with age, not all components are executed more rapidly with age. The encoding component first shows a decrease in processing time with age, and then an increase. Apparently, older children realize that their best strategy is to spend more time in encoding the terms of a problem so that they later will be able to spend less time in making sense of these encodings. Similarly, better reasoners tend to spend relatively more time than do poorer reasoners in global, up-front metacomponential planning when they solve difficult reasoning problems. Poorer reasoners, on the other hand, tend to spend relatively more time in detailed planning as they proceed through a problem. Presumably, the better reasoners recognize that it is better to invest more time up front so as to be able to process a problem more efficiently later on.
Creative intelligence. In work with creativeintelligence problems, Robert Sternberg and Todd Lubart asked sixty-three people to create various kinds of products in the realms of writing, art, advertising, and science. For example, in writing, they would be asked to write very short stories, for which the investigators would give them a choice of titles, such as "Beyond the Edge" or "The Octopus's Sneakers." In art, the participants were asked to produce art compositions with titles such as "The Beginning of Time" or "Earth from an Insect's Point of View." Participants created two products in each domain.
Sternberg and Lubart found that creativity is relatively, although not wholly, domain-specific. In other words, people are frequently creative in some domains, but not in others. They also found that correlations with conventional ability tests were modest to moderate, demonstrating that tests of creative intelligence measure skills that are largely different from those measured by conventional intelligence tests.
Practical intelligence. Practical intelligence involves individuals applying their abilities to the kinds of problems that confront them in daily life, such as on the job or in the home. Much of the work of Sternberg and his colleagues on practical intelligence has centered on the concept of tacit knowledge. They have defined this construct as what one needs to know, which is often not even verbalized, in order to work effectively in an environment one has not been explicitly taught to work in–and that is often not even verbalized.
Sternberg and colleagues have measured tacit knowledge using work-related problems one might encounter in a variety of jobs. In a typical tacit-knowledge problem, people are asked to read a story about a problem someone faces, and to then rate, for each statement in a set of statements, how adequate a solution the statement represents. For example, in a measure of tacit knowledge of sales, one of the problems deals with sales of photocopy machines. A relatively inexpensive machine is not moving out of the showroom and has become overstocked. The examinee is asked to rate the quality of various solutions for moving the particular model out of the showroom.
Sternberg and his colleagues have found that practical intelligence, as embodied in tacit knowledge, increases with experience, but that it is how one profits, or learns, from experience, rather than experience per se, that results in increases in scores. Some people can work at a job for years and acquire relatively little tacit knowledge. Most importantly, although tests of tacit knowledge typically show no correlation with IQ tests, they predict job performance about as well as, and sometimes better than, IQ tests.
In a study in Usenge, Kenya, Sternberg and colleagues were interested in school-age children's ability to adapt to their indigenous environment. They devised a test of practical intelligence for adaptation to the environment that measured children's informal tacit knowledge of natural herbal medicines that the villagers used to fight various types of infections. The researchers found generally negative correlations between the test of practical intelligence and tests of academic intelligence and school achievement. In other words, people in this context often emphasize practical knowledge at the expense of academic skills in their children's development.
In another study, analytical, creative, and practical tests were used to predict mental and physical health among Russian adults. Mental health was measured by widely used paper-and-pencil tests of depression and anxiety, while physical health was measured by self-report. The best predictor of mental and physical health was the practical-intelligence measure, with analytical intelligence being the second-best measure and creative intelligence being the third.
Factor-analytic studies seek to identify the mental structures underlying intelligence. Four separate factor-analytic studies have supported the internal validity of the triarchic theory of intelligence. These studies analyzed aspects of individual differences in test performance in order to uncover the basic mental structures underlying test performance. In one study of 326 high school students from throughout the United States, Sternberg and his colleagues used the so-called Sternberg Triarchic Abilities Test (STAT) to investigate the validity of the triarchic theory. The test comprises twelve subtests measuring analytical, creative, and practical abilities. For each type of ability, there are three multiple-choice tests and one essay test. The multiple-choice tests involve verbal, quantitative, and figural content. Factor analysis on the data was supportive of the triarchic theory of human intelligence, as it was measured relatively separate and independent analytical, creative, and practical factors. The triarchic theory also was consistent with data obtained from 3,252 students in the United States, Finland, and Spain. The study revealed separate analytical, creative, and practical factors of intelligence.
In another set of studies, researchers explored the question of whether conventional education in school systematically discriminates against children with creative and practical strengths. Motivating this work was the belief that the systems in most schools strongly tend to favor children with strengths in memory and analytical abilities.
The Sternberg Triarchic Abilities Test was administered to 326 high-school students around the United States and in some other countries who were identified by their schools as gifted (by whatever standard the school used). Students were selected for a summer program in college-level psychology if they fell into one of five ability groupings: high analytical, high creative, high practical, high balanced (high in all three abilities), or low balanced (low in all three abilities). These students were then randomly divided into four instructional groups, emphasizing memory, analytical, creative, or practical instruction. For example, in the memory condition, they might be asked to describe the main tenets of a major theory of depression. In the analytical condition, they might be asked to compare and contrast two theories of depression. In the creative condition, they might be asked to formulate their own theory of depression. In the practical condition, they might be asked how they could use what they had learned about depression to help a friend who was depressed.
Students who were placed in instructional conditions that better matched their pattern of abilities outperformed students who were mismatched. In other words, when students are taught in a way that fits how they think, they do better in school. Children with creative and practical abilities, who are almost never taught or assessed in a way that matches their pattern of abilities, may be at a disadvantage in course after course, year after year.
A follow-up study examined learning of social studies and science by 225 third-graders in Raleigh, North Carolina, and 142 eighth-graders in Baltimore, Maryland, and Fresno, California. In this study, students were assigned to one of three instructional conditions. In the first condition, they were taught the course they would have learned had there been no intervention, which placed an emphasis on memory. In the second condition, students were taught in a way that emphasized critical (analytical) thinking, and in the third condition they were taught in a way that emphasized analytical, creative, and practical thinking. All students' performance was assessed for memory learning (through multiple-choice assessments) as well as for analytical, creative, and practical learning (through performance assessments).
Students in the triarchic-intelligence (analytical, creative, practical) condition outperformed the other students in terms of the performance assessments. Interestingly, children in the triarchic instructional condition outperformed the other children on the multiple-choice memory tests. In other words, to the extent that one's goal is just to maximize children's memory for information, teaching triarchically is still superior. This is because it enables children to capitalize on their strengths and to correct or to compensate for their weaknesses, allowing them to encode material in a variety of interesting ways.
In another study, involving 871 middle-school students and 432 high school students, researchers taught reading either triarchically or through the regular curriculum. At the middle-school level, reading was taught explicitly. At the high school level, reading was infused into instruction in mathematics, physical sciences, social sciences, English, history, foreign languages, and the arts. In all settings, students who were taught triarchically substantially outperformed students who were taught in standard ways.
The triarchic theory of intelligence provides a useful way of understanding human intelligence. It seems to capture important aspects of intelligence not captured by more conventional theories. It also differs from the theories of Howard Gardner, which emphasize eight independent multiple intelligences (such as linguistic and musical intelligence), and from the theory of emotional intelligence. The triarchic theory emphasizes processes of intelligence, rather than domains of intelligence, as in Gardner's theory. It also views emotions as distinct from intelligence. Eventually, a theory may be proposed that integrates the best elements of all existing theories.
See also: Creativity; Intelligence, subentry on> Myths, Mysteries, AND Realities.
Gardner, Howard. 1983. Frames of Mind: The Theory of Multiple Intelligences. New York: Basic Books.
Gardner, Howard. 1999. Intelligence Reframed: Multiple Intelligences for the 21st Century. New York: Basic Books.
Sternberg, Robert J. 1977. Intelligence, Information Processing, and Analogical Reasoning: The Componential Analysis of Human Abilities. Hills-dale, NJ: Erlbaum.
Sternberg, Robert J. 1981. "Intelligence and Nonentrenchment." Journal of Educational Psychology 73:1–16.
Sternberg, Robert J. 1993. Sternberg Triarchic Abilities Test. Unpublished test.
Sternberg, Robert J. 1997. Successful Intelligence. New York: Plume.
Sternberg, Robert J. 1999. "The Theory of Successful Intelligence." Review of General Psychology 3:292–316.
Sternberg, Robert j.; Ferrari, Michel; Clinkenbeard, Pamela R.; and Grigorenko, Elena L. 1996. "Identification, Instruction, and Assessment of Gifted Children: A Construct Validation of a Triarchic Model." Gifted Child Quarterly 40 (3):129–137.
Sternberg, Robert j.; Forsythe, George B.; Hedlund, Jennifer; Horvath, Joe; Snook, Scott; Williams, Wendy m.; Wagner, Richard K.; and Grigorenko, Elena L. 2000. Practical Intelligence in Everyday Life. New York: Cambridge University Press.
Sternberg, Robert j.; Grigorenko, Elena L.; Ferrari, Michel; and Clinkenbeard, Pamela r. 1999. "A Triarchic Analysis of an Aptitude-Treatment Interaction." European Journal of Psychological Assessment 15 (1):1–11.
Sternberg, Robert J., and Lubart, Todd I. 1995. Defying the Crowd: Cultivating Creativity in a Culture of Conformity. New York: Free Press.
Sternberg, Robert J., and Rifkin, Bathseva. 1979. "The Development of Analogical Reasoning Processes." Journal of Experimental Child Psychology 27:195–232.
Sternberg, Robert j.; Torff, Bruce; and Grigorenko, Elena L. 1998. "Teaching Triarchically Improves School Achievement." Journal of Educational Psychology 90: 374–384.
Robert J. Sternberg
SALOVEY, PETER; LOPES, PAULO N.; LUBINSKI, DAVID; BLESKE-RECHEK, APRIL; CHEN, JIE-QI; PELLEGRINO, JAMES W.; STERNBERG, ROBERT J.. "Intelligence." Encyclopedia of Education. 2002. Encyclopedia.com. 27 Aug. 2016 <http://www.encyclopedia.com>.
SALOVEY, PETER; LOPES, PAULO N.; LUBINSKI, DAVID; BLESKE-RECHEK, APRIL; CHEN, JIE-QI; PELLEGRINO, JAMES W.; STERNBERG, ROBERT J.. "Intelligence." Encyclopedia of Education. 2002. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1G2-3403200322.html
SALOVEY, PETER; LOPES, PAULO N.; LUBINSKI, DAVID; BLESKE-RECHEK, APRIL; CHEN, JIE-QI; PELLEGRINO, JAMES W.; STERNBERG, ROBERT J.. "Intelligence." Encyclopedia of Education. 2002. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1G2-3403200322.html
Empirical work in geropsychology began in the early part of the twentieth century with the observation that there were apparent declines in intellectual performance when groups of young and old persons were compared on the same tasks. This early work was done primarily with measures designed for assessing children or young adults. The intellectual processes used in the development of cognitive structures and functions in childhood, however, are not always the most relevant processes for the maintenance of intelligence into old age, and a reorganization of cognitive structures (for example, mental abilities) may indeed be needed to meet the demands of later life. Nevertheless, certain basic concepts relevant to an understanding of intelligence in childhood remain relevant at adult levels. Changes in basic abilities and measures of intelligence must therefore be studied over much of the life course, even though the manner in which intellectual competence is organized and measured may change with advancing age.
This section will first review the historical background for the study of adult intelligence. Alternative formulations of the conceptual nature of intelligence will then be described. Next, changes in intellectual competence that represent actual decrement that individuals experience will be differentiated from the apparently lower performance of older persons that is not due to intellectual decline, but instead reflects a maintained, but obsolescent, functioning of older cohorts when compared to younger peers. This is the distinction between data on age differences gained from cross-sectional comparison of groups differing in age and data acquired by means of longitudinal studies of the same individuals over time. This discussion will also include information on the ages at which highest levels of intellectual competence are reached, magnitudes of within-generation age changes, and an assessment of generational differences. Some attention will be given to the distinction between academic and practical intelligence. Finally, the influences of health, lifestyles, and education will be considered. This will provide an understanding of why some individuals show intellectual decrement in early adulthood while others maintain or increase their level of functioning well into old age.
Intellectual development from young adulthood through old age has become an important topic because of the increase in average life span and the ever-larger number of persons who reach advanced ages. Assessment of intellectual competence in old age is often needed to provide information relevant to questions of retirement for cause (in the absence of mandatory retirement for reasons of age), or to determine whether sufficient competence remains for independent living, for medical decision making, as well as for the control and disposition of property. Level of intellectual competence may also need to be assessed in preparation for entering retraining activities required for late-life career changes.
Four influential theoretical positions have had a major impact on empirical research on intelligence and age. The earliest conceptualization came from Sir Charles Spearman's work in 1904. Spearman suggested that a general dimension of intelligence (g) underlied all purposeful intellectual pursuits. All other components of such pursuits were viewed as task or item specific (s). This view underlies the family of assessment devices that were developed at the beginning of the twentieth century; particularly the work of Alfred Binet and Henri Simon in France. Thinking of a single, general form of intelligence may be appropriate for childhood, when measurement of intellectual competence is used primarily to predict scholastic performance. However, a singular concept is not useful beyond adolescence, because there is no single criterion outcome to be predicted in adults. Also, there is convincing empirical evidence to support the existence of multiple dimensions of intelligence that display a different life-course pattern.
The notion of a single dimension of intelligence became popular during World War I, when Robert Yerkes constructed the Army Alpha intelligence test for purposes of classifying the large number of inductees according to their ability level. Because of the predominantly verbal aspects of this test, it was soon supplemented by performance measures suitable for illiterate or low-literate inductees. Assessing a single dimension of intelligence also widely influenced educational testing. It was around this time that Lewis Terman, a psychologist working at Stanford University, adapted the work of Binet and Simon for use in American schools and introduced the Stanford-Binet test, which dominated educational testing for many decades. Terman was also responsible for the introduction of the IQ concept. He argued that one could compute an index (the intelligence quotient, or IQ) that represents the ratio of a person's mental age (as measured by the Stanford-Binet test) divided by the person's chronological age. An IQ value of 100 was assigned to be equivalent to the average performance of a person at a given age. The IQ range from 90 to 110 represented the middle 50 percent of the normal population. Because there is no linear relation between mental and chronological age past adolescence, however, the Stanford-Binet approach did not work well with adults (see below).
An early influential multidimensional theory of intelligence was Edward. L. Thorndike's view that different dimensions of intelligence would display similar levels of performance within individuals. Thorndike also suggested that all categories of intelligence possessed three attributes: power, speed, and magnitude (see Thorndike & Woodworth, 1901). This approach is exemplified by the work of David Wechsler. The Wechsler Adult Intelligence Scale (WAIS) consists of eleven distinct subscales of intelligence, derived from clinical observation and earlier mental tests, combined into two broad dimensions: verbal intelligence and performance (nonverbalmanipulative) intelligence. These dimensions can then be combined to form a total global IQ. The global IQ (comparable to the Stanford-Binet IQ) is statistically adjusted to have a mean of 100 for any normative age group. The range of the middle 50 percent of the population is also set to range from 90 to 110. The Wechsler scales were used in the clinical assessment of adults with psychopathologies, and some of the subtests are still used by neuropsychologists to help diagnose the presence of a dementia.
The Wechsler verbal and performance scales are highly reliable in older persons, but measurable differences between the two are often used as a rough estimate of age decline, a use that has not proven to be very reliable. A more significant limitation of the test for research on intellectual aging, however, has been the fact that the factor structure of the scales does not remain invariant across age. As a consequence, most recent studies of intellectual aging in community-dwelling populations have utilized some combination of the primary mental abilities.
Factorially simpler multiple dimensions of intelligence were identified in the work of Louis Leon Thurstone during the 1930s, which was expanded upon by J. P. Guilford in 1967. (The primary mental abilities described by Thurstone and Guilford have also formed the basis for this author's own work; see Schaie, 1996b.) Major intellectual abilities that account for much of the observed individual differences in intelligence include verbal meaning (recognition vocabulary), inductive reasoning (the ability to identify rules and principles), spatial orientation (rotation of objects in two- or three-dimensional space), number skills (facility with arithmetic skills), word fluency (recall vocabulary), and perceptual speed. Further analyses of the primary intellectual abilities have identified several higher-order dimensions, including those of fluid intelligence (applied to novel tasks) and crystallized intelligence (applied to acculturated information).
The introduction of Piagetian thought into American psychology led some investigators to consider the application of Piagetian methods to adult development. However, Jean Piaget's (1896–1980) original work assumed that intellectual development was complete once the stage of formal operations had been reached during young adulthood. Hence, this approach has contributed only sparsely to empirical work on adult intelligence.
There are also discernable secular trends that cut across theoretical positions on different aspects of adult intelligence. Diana Woodruff-Pak has identified four stages: (1) until the mid-1950s, concerns were predominantly with identifying steep and apparently inevitable age-related decline; (2) the late 1950s through the mid-1960s saw the discovery that there was stability as well as decline; (3) beginning with the mid-1970s, external social and experiential effects that influenced cohort differences in ability levels were identified; and (4) in the 1980s and 1990s the field has been dominated by attempts to alter experience and manipulate age differences. Successful demonstrations of the modifiability of intellectual performance has led researchers to expand definitions of intelligence and to explore new methods of measurement.
Conceptualizations of intelligence
Past approaches to the study of intelligence (from its origin in work with children) were primarily concerned with academic or intellectual performance outcomes. Current conceptualizations of intelligence, by contrast, often distinguish between academic, practical, and social intelligence. All of these, however, are basically manifestations of intellectual competence. The contemporary study of intellectual competence has been largely driven by three perspectives: The first sees competence as a set of latent variables (latent variables are not directly observable but are inferred by statistical means, e.g., factor analysis, from sets of observed variables that are related to the "latent variables") that represent permutations of variables identified by studies of basic cognition. This perspective has been characterized as a componential or hierarchical approach. The second perspective views competence as involving specific knowledge bases. The third focuses on the "fit" or congruence between an individual's intellectual competence and the environmental demands faced by the individual.
Componential/hierarchical approaches to intelligence. The three major examples of such approaches are: Robert Sternberg's triarchic theory of intelligence; Paul Baltes' two-dimensional model; and the hierarchical model linking intellectual competence with basic cognition proposed by Sherry Willis and K. Warner Schaie.
Sternberg proposed a triarchic theory of adult intellectual development that involves metacomponents, and experiential and contextual aspects (a metacomponent is a necessary component required for the others). The metacomponential part of the theory involves an information-processing approach to basic cognition, including processes such as encoding, allocation of mental resources, and monitoring of thought processes. The second component of the theory posits that these processes operate at different levels of experience, depending upon the task—the basic components can operate in a relatively novel fashion or, with experience, they may become automatized. For example, identifying a driver's response pattern under a specific traffic condition; this response then becomes automatic whenever a similar condition is encountered. According to Sternberg, the most intelligent person is the one who can adjust to a change in a problem situation and who can eventually automate the component processes of task solution. The third aspect of the theory is concerned with how the individual applies the metacomponents in adjusting to a change in the environment.
Baltes proposed a two-dimensional componential model of cognition. The first component is identified as the mechanics of intelligence, which represent the basic cognitive processes that serve as underpinnings for all intelligent behavior. The second component of the theory is labeled the pragmatics of intelligence. This is the component that is influenced by experience. Baltes argues that the environmental context is critical to the particular form or manifestation in which pragmatic intelligence is shown. The concept of wisdom has been linked with, and studied within, the pragmatics of intelligence.
Willis and Schaie conceptualized a hierarchical relationship between basic cognition and intellectual competence. Basic cognition is thought to be represented by domains of psychometric intelligence, such as the second-order constructs of fluid and crystallized intelligence and the primary mental abilities associated with each higher-order construct. The cognitive abilities represented in traditional approaches to intelligence are proposed to be universal across the life span and across cultures. When nurtured and directed by a favorable environment at a particular life stage, these processes and abilities develop into cognitive competencies that are manifested in daily life as cognitive performance.
Intellectual competence, as represented in activities of daily living, is seen in the phenotypic expressions of intelligence that are context- or age-specific. The particular activities and behaviors that serve as phenotypic expressions of intelligence vary with the age of the individual, with a person's social roles, and with the environmental context. Problem solving in everyday activities is complex and involves multiple basic cognitive abilities. Everyday competence also involves substantive knowledge, as well as the individual's attitudes and values associated with a particular problem domain.
Age changes in intelligence
A number of longitudinal studies have been conducted in the United States and in Europe covering substantial age ranges. An important new addition is the initiation of longitudinal studies in the very old, providing hope for better information on age changes in the nineties and beyond.
Longitudinal studies of intelligence usually show a peak of intellectual performance in young adulthood or early middle age, with a virtual plateau until early old age and accelerating average decline thereafter. However, it should be noted that different intellectual skills reach peak performance at different ages and decline at different rates. Figure 1 provides an example from the Seattle Longitudinal Study, a large scale study of community-dwelling adults. This figure shows age changes from twenty-five to eighty-eight years of age for six primary mental abilities. Note that only perceptual speed follows a linear pattern of decline from young adulthood to old age, and that verbal ability does not reach a peak until midlife and still remains above early adult performance in advanced old age. Similar patterns have been obtained in meta-analyses of the WAIS (cf. McArdle, 1994).
It should also be noted that there are wide individual differences in change in intellectual competence over time. For example, when change in large groups of individuals was monitored over a seven-year interval, it was found that the ages 60 to 67 and 67 to 74 were marked by stability of performance, while even from ages 74 to 84 as many as 40 percent of study participants remained stable. However, it was also found that by their mid-sixties almost all persons had significantly declined on at least one ability, while remaining stable on others.
Age differences in intelligence
Findings from age-comparative (cross-sectional) studies of intellectual performance are used to compare adults of different ages at a single point in time. Because of substantial generational differences, these studies show far greater age differences than the within-individual changes observed in longitudinal data. Ages of peak performance are found to be earlier (for later-born cohorts) in cross-sectional studies. Modest age differences are found by the early fifties for some, and by the sixties for most, dimensions of intelligence. On the WAIS, age differences are moderate for the verbal part of the test, but substantial for the performance scales. Because of the slowing in the rate of positive cohort differences (a later-born cohort performs at a higher level than an earlier-born cohort at the same ages), age difference profiles have begun to converge somewhat more with the age-change data from longitudinal studies. Both peak performance and onset of decline seem to be shifting to later ages for most variables.
Figure 2 presents age differences over the age range from twenty-five to eighty-one for samples tested in 1991, found in the Seattle Longitudinal Study, which can be directly compared to the longitudinal data presented in Figure 1. Particularly noteworthy is the fact that cross-sectional age differences are greater than those observed in longitudinal studies—except for numerical skills, which show greater decline when measured longitudinally.
More recent studies of the WAIS with normal individuals (the WAIS has been widely applied to samples with neuropathology or mental illness, so it is important to state that the work referred to is on normal individuals) use approaches that involve latent variable models (see McArdle & Prescott, 1992; Rott, 1993), while other analyses have been conducted at the item level. A study by Sands, Terry, and Meredith (1989) investigated two cohorts spanning the age range from 18 to 61. Improvement in performance was found between the ages of 18 and 40 and between 18 and 54. Between ages 40 and 61, improvement was found for the information, comprehension and vocabulary subtests, while there was a mixed change (gain on the easy items and decline on the difficult items) on picture completion and a decline on digit symbol and block design (with decline only for the most difficult items of the latter test). The discrepancies between the longitudinal and cross-sectional findings on the WAIS, as well as on the primary mental abilities, can be attributed largely to cohort differences in attained peak level and rate of change arising as a consequence of the different life experiences of successive generations.
Since women, on average, live longer than men, one might ask whether there are differential patterns by sex. Most studies find that there are average-level differences between men and women at all ages, with women doing better on verbal skills and memory, while men excel on numerical and spatial skills. The developmental course of intellectual abilities, however, tends to have parallel slopes for men and women.
Cohort differences in intellectual abilities
Cohort differences in psychometric abilities have been most intensively examined in the Seattle Longitudinal Study. Cumulative cohort differences for cohorts born from 1897 to 1966 are shown in Figure 3 for the abilities discussed above. There is a linear positive pattern for inductive reasoning and verbal memory, a positive pattern for spatial orientation, but curvilinear or negative patterns for numeric ability and perceptual speed. Factors thought to influence these cohort differences include changes in average educational exposure and changes in educational practices, as well as the control of early childhood infectious diseases and the adoption of healthier lifestyles by more recent cohorts. Similar differences have also been found using biologically related parent-offspring dyads compared at approximately similar ages.
The effect of these cohort differences is to increase age differences in intelligence between young and old for those skills where there have been substantial gains across successive generations (e.g., inductive reasoning), but to decrease age differences in instances were younger generations perform more poorly (e.g., number skills). Hence, it should be kept in mind that some older persons seem to perform poorly when compared with their younger peers not because they have suffered mental decline, but because they are experiencing the consequences of obsolescence.
Much of the work done by psychologists on intelligence has concerned those aspects that are sometimes called academic intelligence. However, an equally important aspect of intelligence is concerned with the question of how individuals can function effectively on tasks and in situations encountered on a daily basis. It has been shown that individual differences in performance on everyday tasks can be accounted for by a combination of performance levels on several basic abilities. Competence in various everyday activities (e.g., managing finances, shopping, using medications, using the telephone) involve several cognitive abilities or processes that cut across or apply to various substantive domains. But the particular combination or constellation of basic abilities varies, of course, across different tasks of daily living. It is important to note that the basic abilities are seen as necessary (but not sufficient) antecedents for everyday competence.
Other variables, such as motivation and meaning, and in particular the role of the environment or context, determine the particular types of applied activities and problems in which practical intelligence is manifested. Everyday competence also involves substantive knowledge associated with the particular everyday-problem domain, as well as attitudes and values with regard to the problem domain. Both the sociocultural context and the microenvironment determine the expression of practical intelligence for a given individual. For example, while the ability to travel beyond one's dwelling has been of concern through the ages, comprehending airline schedules and operating computer-driven vehicles are only recent expressions of practical intelligence. The environment also plays an important role in the maintenance and facilitation of everyday competence as people age. Environmental stimulation and challenges, whether they occur naturally or through planned interventions, have been shown to be associated with the maintenance and enhancement of everyday competence in the elderly. Practical intelligence appears to peak in midlife and then decline, following closely the changes observed in the underlying cognitive abilities associated with specific everyday problems.
Influences upon intellectual development
Intellectual competence does not operate within a vacuum. It is affected both by an individual's physiological state (i.e., the individual's state of health and, in old age particularly, the presence or absence of chronic disease), as well as the presence or absence of a favorable environmental context and adequate support systems. Figure 4 provides a conceptual schema of the influences that impact the adult development of cognitive/intellectual competence.
Adult cognitive functioning must, of course, be initially based upon both heritable (genetic) influences and the early environmental influences typically experienced within the home of the biological parents. It has been suggested by some behavior geneticists that much of the early environmental influences are nonshared (i.e., not shared by all members of a family). However, there is retrospective evidence that some early shared environmental influences may affect adult intellectual performance (see Schaie & Zuo, 2000). Both genetic and early environmental factors are thought to influence midlife cognitive functioning. Early environmental influences will, of course, also exert influences on midlife social status. Genetic factors are also likely to be implicated in the rate of cognitive decline in adulthood. Thus far, the best-studied gene in this context is the apolipoprotein E (ApoE) gene, one of whose alleles is thought to be a risk factor for Alzheimer's disease. ApoE status is therefore also considered a factor in cognitive development (the expression of this gene is probably not important prior to midlife).
Influence of health. Considerable information is available on the reciprocal effects of chronic disease and intellectual abilities. It has been observed that decline in intellectual performance in old age is substantially accelerated by the presence of chronic diseases. Conditions such as cardiovascular disease, renal disease, osteoarthritis, and diabetes tend to interfere with lifestyles that are conducive to the maintenance of intellectual abilities, while they also have direct effects on brain functioning. One study found that individuals free of chronic disease perform intellectually at levels that are characteristic of those seven years younger who are suffering from such diseases. However, it has also been shown that the age of onset of chronic disease is later, and the disease severity is less, when it occurs in individuals functioning at high intellectual levels.
Influence of lifestyles. Many studies have related individual differences in socioeconomic circumstances (and resultant lifestyles) to the maintenance of high levels of intellectual functioning into old age. In particular, it has been shown that individuals who actively pursue intellectually stimulating activities seem to decline at lower rates than those who do not. Such pursuits may include travel, intensive reading programs, participation in clubs and organizations, and cultural and continuing-education activities. Conversely, those individuals whose opportunities for stimulating activities have been reduced due to the loss of a spouse or other factors restricting their social networks may be at greatest risk for decline.
Influence of education. Both the maintenance of intellectually stimulating activities and the pursuit of healthful lifestyles appear to be dependent to a considerable extent on an individual's level of attained education. Over the course of the twentieth century, in the United States, there was an average increase in educational exposure amounting to approximately six years for men and five years for women. This societal shift may be largely responsible for many of the favorable cohort differences in intellectual abilities described in this article. Those advantaged educationally are also more likely to be engaged in intellectually stimulating work experiences. These, in turn, have been shown to have favorable effects on the maintenance of intellectual functions into old age. Finally, it should be noted that while there is eventual age-related decline in intelligence for both the educationally advantaged and disadvantaged, those who start at a high level are likely to retain sufficient intellectual competence to last throughout life.
K. Warner Schaie
See also Age-Period-Cohort Model; Creativity; Functional Ability; Learning; Problem Solving, Everyday; Wisdom.
Arbuckle, T. Y.; Maag, U.; Pushkar, D.; and Chaikelson, J. S. "Individual Differences in Trajectory of Intellectual Development over 45 Years of Adulthood." Psychology and Aging 13 (1998): 663–675.
Baltes, P. B. "The Aging Mind: Potentials and Limits." Gerontologist 33 (1993): 580–594.
Baltes, P. B.; Mayer, K. U.; Helmchen, H.; and Steinhagen-Thiessen, E. "The Berlin Aging Study (BASE): Overview and Design." Ageing and Society 13 (1993): 483–533.
Binet, A., and Simon, T. "Methodes Nouvelles pour le Diagnostic du Niveau Intellectuel des Anormaux." L'Annee Psychologique 11 (1905): 102–191.
Bosworth, H. B., and Schaie, K. W. "Survival Effects in Cognitive Function, Cognitive Style, and Sociodemographic Variables in the Seattle Longitudinal Study." Experimental Aging Research 25 (1999): 121–139.
Busse, E. W. "Duke Longitudinal Studies of Aging." Zeitschrift für Gerontologie 26 (1993): 123–128.
Carroll, J. B. Human Cognitive Abilities: A Survey of Factor-Analytic Studies. New York: Cambridge University Press, 1993.
Cunningham, W. R., and Owens, W. A., Jr. "The Iowa State Study of the Adult Development of Intellectual Abilities." In Longitudinal Studies of Adult Psychological Development. Edited by K. W. Schaie. New York: Guilford, 1983. Pages 20–39.
Eichorn, D. H.; Clausen, J. A.; Haan, N.; Honzik, M. P.; and Mussen, P. H. Present and Past in Middle Life. New York: Academic Press, 1981.
Gribbin, K.; Schaie, K. W.; and Parham, I. A. "Complexity of Life Style and Maintenance of Intellectual Abilities." Journal of Social Issues 36 (1980): 47–61.
Guilford, J. P. The Nature of Human Intelligence. New York: McGraw-Hill, 1967.
Horn, J. L., and Hofer, S. M. "Major Abilities and Development in the Adult Period." In Intellectual Development. Edited by R. J. Sternberg and C. A. Berg. Cambridge, U.K.: Cambridge University Press, 1992.
Hultsch, D. F.; Hertzog, C.; Small, B. J.; McDonald-Miszlak, L.; and Dixon, R. A. "Short-Term Longitudinal Change in Cognitive Performance in Later Life." Psychology and Aging 7 (1992): 571–584.
Matarazzo, J. D. Wechsler's Measurement and Appraisal of Adult Intelligence, 5th ed. Baltimore: Williams & Wilkins, 1972.
McArdle, J. J. "Structural Factor Analysis Experiments with Incomplete Data." Mutivariate Experimental Research 29 (1994): 404–454.
McArdle, J. J., and Prescott, C. A. "Age-Based Construct Validation Using Structural Equation Modeling." Experimental Aging Research 18 (1992): 87–115.
Plomin, R., and Daniels, D. "Why Are Two Children in the Same Family So Different from Each Other?" The Behavioral and Brain Sciences 10 (1987): 1–16.
Poon, L. W.; Sweaney, A. L.; Clayton, G. M.; and Merriam, S. B. "The Georgia Centenarian Study." International Journal of Aging and Human Development 34 (1992): 1–17.
Rott, C. "Intelligenzentwicklung im Alter [Development of Intelligence in Old Age]." Zeitschrift für Gerontologie 23 (1990): 252–261.
Sands, L. P.; Terry, H.; and Meredith, W. "Change and Stability in Adult Intellectual Functioning Assessed by Wechsler Item Responses." Psychology and Aging 4 (1989): 79–87.
Schaie, K. W. "Midlife Influences upon Intellectual Functioning in Old Age." International Journal of Behavioral Development 7 (1984): 463–478.
Schaie, K. W. "The Hazards of Cognitive Aging." Gerontologist 29 (1989): 484–493.
Schaie, K. W. "The Course of Adult Intellectual Development." American Psychologist 49 (1994): 304–313.
Schaie, K. W. "Generational Differences." In Encyclopedia of Gerontology. Edited by J. E. Birren. San Diego, Calif.: Academic Press, 1996a. Pages 567–576.
Schaie, K. W. Intellectual Development in Adulthood: The Seattle Longitudinal Study. Cambridge, U.K.: Cambridge University Press, 1996b.
Schaie, K. W. "The Impact of Longitudinal Studies on Understanding Development from Young Adulthood to Old Age." International Journal of Behavioral Development (2000).
Schaie, K. W.; Plomin, R.; Willis, S. L.; Gruber-Baldini, A.; and Dutta, R. "Natural Cohorts: Family Similarity in Adult Cognition." In Psychology and Aging: Nebraska Symposium on Motivation, 1991. Edited by T. Sonderegger. Lincoln: University of Nebraska Press, 1992.
Schaie, K. W., and Willis, S. L. "Theories of Everyday Competence." In Handbook of Theories of Aging. Edited by V. L. Bengtson and K. W. Schaie. New York: Springer, 1999. Pages 174–195.
Schaie, K. W., and Willis, S. L. "A Stage Theory Model of Adult Cognitive Development Revisited." In The Many Dimensions of Aging: Essays in Honor of M. Powell Lawton. Edited by B. Rubinstein, M. Moss, & M. Kleban. New York: Springer, 2000. Pages 175–193.
Schaie, K. W., and Zuo, Y. L. "Family Environments and Adult Cognitive Functioning." In Context of Intellectual Development. Edited by R. L. Sternberg and E. Grigorenko. Hillsdale, N.J.: Erlbaum, 2001.
Schooler, C.; Mulatu, M. S.; and Oates, G. "The Continuing Effects of Substantively Complex Work on the Intellectual Functioning of Older Workers." Psychology and Aging 14 (1999): 483–506.
Spearman, C. "General Intelligence: Objectively Determined and Measured." American Journal of Psychology 15 (1904): 201–292.
Steen, B., and Djurfeldt, H. "The Gerontological and Geriatric Population Studies in Gothenburg, Sweden." Zeitschrift für Gerontologie 26 (1993):163–169.
Sternberg, R. J. Beyond IQ: A Triarchic Theory of Human Intelligence. Cambridge, U.K.: Cambridge University Press, 1985.
Terman, L. M. The Measurement of Intelligence. Boston: Houghton, 1916.
Thorndike, E. L., and Woodworth, R. S. "Influence of Improvement in One Mental Function upon the Efficiency of Other Mental Functions." Psychological Review 8 (1901): 247–261, 384–395, 553–564.
Thurstone, L. L. Primary Mental Abilities. Chicago: University of Chicago Press, 1938.
Willis, S. L., and Schaie, K. W. "Everyday Cognition: Taxonomic and Methodological Considerations." In Mechanisms of Everyday Cognition. Edited by J. M. Puckett and H. W. Reese. Hillsdale, N.J.: Erlbaum, 1993.
Woodruff-Pak, D. S. "Aging and Intelligence: Changing Perspectives in the Twentieth Century." Journal of Aging Studies 3 (1989): 91–118.
Yerkes, R. M. "Psychological Examining in the United States Army." Memoirs of the National Academy of Sciences 15 (1921): 1–890.
Schaie, K. Warner. "Intelligence." Encyclopedia of Aging. 2002. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1G2-3402200206.html
Schaie, K. Warner. "Intelligence." Encyclopedia of Aging. 2002. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1G2-3402200206.html
Intelligence is an abstract concept whose definition continually evolves and often depends upon current social values as much as scientific ideas. Modern definitions refer to a variety of mental capabilities, including the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience, as well as the potential to do these things.
Several theories about intelligence emerged in the twentieth century and with them debate about the nature of intelligence and whether it determined by hereditary factors, the environment, or both. As methods developed to assess intelligence, experts theorized about the measurability of intelligence, its accuracy, and the field known as psychometrics, a branch of psychology dealing with the measurement of mental traits, capacities, and processes. Publication in 1994 of The Bell Curve: Intelligence and Class Structure in American Life by Richard J. Herrnstein and Charles Murray stirred the controversy. Their findings pointed to links between social class, race, and intelligence quotient (IQ) scores, despite questions by many about the validity of IQ tests as a measurement of intelligence or a predictor of achievement and success.
Part of the problem regarding intelligence stems from the fact that nobody has adequately defined what intelligence really means. In everyday life, people have a general understanding that some people are "smart," but when they try to define "smart" precisely, they often have difficulty because a person can be gifted in one area and average or below in another. To explain this phenomenon, some psychologists have developed theories to include multiple components of intelligence.
Since about 1970, psychologists have expanded the notion of what constitutes intelligence. Newer definitions of intelligence encompass more diverse aspects of thought and reasoning. For example, American psychologist Robert Sternberg developed a three-part theory of intelligence which states that behaviors must be viewed within the context of a particular culture; that a person's experiences impact the expression of intelligence; and that certain cognitive processes control all intelligent behavior. When all these aspects of intelligence are viewed together, the importance of how people use their intelligence becomes more important than the question of "how much" intelligence a person has. Sternberg has suggested that some intelligence tests focus too much on what a person has already learned rather than on how well a person acquires new skills or knowledge.
Another multifaceted approach to intelligence is Howard Gardner's proposal that people have eight intelligences:
- Musical: Children with musical intelligence are always singing or tapping out a beat. They are aware of sounds others miss. Musical children are discriminating listeners.
- Linguistic: Children with linguistic intelligence excel at reading, writing, telling stories, and doing crossword or other word puzzles.
- Logical-Mathematical: Children with this type of intelligence are interested in patterns, categories, and relationships. They are good at mathematic problems, science, strategy games, and experiments.
- Bodily-Kinesthetic: These children process knowledge through their senses. They usually excel at athletics and sports , dance, and crafts.
- Spatial: These children think in images and pictures. They are generally good at mazes and jigsaw puzzles. They often spend lots of time drawing, building (with blocks, Legos, or erector sets), and daydreaming.
- Interpersonal: This type of intelligence fosters children who are leaders among their peers, are good communicators, and understand the feelings and motives of others.
- Intrapersonal: These children are shy, very aware of their own feelings, and are self-motivated.
- Naturalist: This type of intelligence allows children to distinguish among, classify, and use features of the environment. These children are likely to make good farmers, gardeners, botanists, geologists, florists, and archaeologists. Naturalist adolescents can often name and describe the features of every make of car around them.
There are many different types of intelligence tests, and they all do not measure the same abilities. Although the tests often have aspects that are related with each other, one should not expect that scores from one intelligence test that measures a single factor will be similar to scores on another intelligence test that measures a variety of factors. Many people are under the false assumption that intelligence tests measure a person's inborn or biological intelligence. Intelligence tests are based on an individual's interaction with the environment and never exclusively measure inborn intelligence. Intelligence tests have been associated with categorizing and stereotyping people. Additionally, knowledge of one's performance on an intelligence test may affect a person's aspirations and motivation to obtain goals. Intelligence tests can be culturally biased against certain groups.
STANFORD-BINET INTELLIGENCE SCALES Consisting of questions and short tasks arranged from easy to difficult, the Stanford-Binet measures a wide variety of verbal and nonverbal skills. Its fifteen tests are divided into the following four cognitive areas: verbal reasoning (vocabulary, comprehension, absurdities, verbal relations); quantitative reasoning (math, number series, equation building); abstract/visual reasoning (pattern analysis, matrices, paper folding and cutting, copying); and short-term memory (memory for sentences, digits, and objects, and bead memory). A formula is used to arrive at the intelligence quotient, or IQ. An IQ of 100 means that the child's chronological and mental ages match. Traditionally, IQ scores of 90–109 are considered average; scores below 70 indicate mental retardation . Gifted children achieve scores of 140 or above. Revised in 1986, the Stanford-Binet intelligence test can be used with children starting at age two. The test is widely used to assess cognitive development and often to determine placement in special education classes.
WECHSLER INTELLIGENCE SCALES The Wechsler intelligence scales are divided into two sections: verbal and nonverbal, with separate scores for each. Verbal intelligence, the component most often associated with academic success, implies the ability to think in abstract terms using either words or mathematical symbols. Performance intelligence suggests the ability to perceive relationships and fit separate parts together logically into a whole. The inclusion of the performance section in the Wechsler scales is especially helpful in assessing the cognitive ability of children with speech and language disorders or whose first language is not English. The test can be of particular value to school psychologists screening for specific learning disabilities because of the number of specific subtests that make up each section.
KAUFMAN ASSESSMENT BATTERY FOR CHILDREN The Kaufman Assessment Battery for Children (KABC) is an intelligence and achievement test for children ages 2.5–12.5 years. It consists of 16 subtests, not all of which are used for every age group. A distinctive feature of the KABC is that it defines intelligence as problem-solving ability rather than knowledge of facts, which it considers achievement. This distinction is evident in the test's division into two parts—intelligence and achievement—which are scored separately and together. The test's strong emphasis on memory and lesser attention to verbal expression are intended to offset cultural disparities between black and white children. In addition, the test may be given to non-native speakers in their first language and to hearing impaired children using American Sign Language.
Babies were once thought to enter the world with minds that were blank slates that developed through a lifetime of experiences. It is as of the early 2000s known that newborns have brains as sophisticated as the most powerful supercomputers, pre-wired with a large capacity for learning and knowledge. In the first few months of life, a baby's brain develops at an amazing rate. At birth, infants have the senses of sight, sound, and touch. At about three or four months, infants begin to develop memory, and it expands quickly. Modern brain imaging techniques have confirmed that children's intelligence is not just hereditary but is also affected greatly by environment. Babies' brains develop faster during their first year than at any other time. By three months, babies can follow moving objects with their eyes, are extremely interested in their surroundings, and can recognize familiar sounds, especially their parents' voices. At six months, infants begin to remember familiar objects, react to unfamiliar people or situations, and realize that objects are permanent. At seven months, babies can recognize their own name. Parents can help their infants develop their intelligence by talking and reading to them, playing with them, and encouraging them to play with a variety of age-appropriate toys .
Toddlers' lives generally revolve around experimenting with and exploring the environment around them. The primary source of learning for toddlers is their families. During their third year, toddlers should be able to sort and group similar objects by their appearance, shape, and function. They also start to understand how some things work, and their memory continues to improve rapidly. They are able to remember and seek out objects that are hidden or moved to a different location. Toddlers should be able to follow two-step instructions and understand contrasting ideas, such as large and small, inside and outside, opened and closed, and more and less. Toddlers also develop a basic understanding of time in relation to their regular activities, such as meals and bedtime.
At age three, preschoolers can say short sentences, have a vocabulary of about 900 words, show great growth in communication, tell simple stories, use words as tools of thought, want to understand their environment, and answer questions. At age four, children can use complete sentences, have a 1,500-word vocabulary, frequently ask questions, and learn to generalize. They are highly imaginative, dramatic, and can draw recognizable simple objects. Preschoolers also should be able to understand basics concepts such as size, numbers, days of the week, and time. They should have an attention span of at least 20 minutes. Children this age are still learning the difference between reality and fantasy. Their curiosity about themselves and the world around them continues to increase.
At age five, children should have a vocabulary of more than 2,000 words. They should be able to tell long stories, carry out directions well, read their own name, count to ten, ask the meaning of words, know colors, begin to know the difference between fact and fiction, and become interested in their surrounding environment, neighborhood, and community. Between the ages of seven and 12, children begin to reason logically and organize their thoughts coherently. However, generally, they can only think about actual physical objects; they cannot handle abstract reasoning. They also begin to lose their self-centered way of thinking. During this age range, children can master most types of conservation experiments and begin to understand that some things can be changed or undone. Early school-age children can coordinate two dimensions of an object simultaneously, arrange structures in sequence, change places or reverse the normal order of items in a series, and take something such as a story, incident, or play out of its usual setting or time and relocate it in another.
Starting at about age 12, adolescents can formulate hypotheses and systematically test them to arrive at an answer to a problem. For example, they can formulate hypotheses based on the phrase "what if." They can think abstractly and understand the form or structure of a mathematical problem. Another characteristic of the later school-age years is the ability to reason contrary to fact. That is, if they are given a statement and asked to use it as the basis of an argument, they are capable of accomplishing the task. Until they reach the age of 15 or 16, adolescents are generally not capable of reasoning as an adult. High school-age adolescents continue to gain cognitive and study skills. They can adapt language to different contexts, master abstract thinking, explore and prepare for future careers and roles, set goals based on feelings of personal needs and priorities, and are likely to reject goals set by others.
Autism is a profound mental disorder marked by an inability to communicate and interact with others. The condition's characteristics include language abnormalities, restricted and repetitive interests, and the appearance of these characteristics in early childhood. As many as two-thirds of children with autistic symptoms are mentally deficient. However, individuals with autism can also be highly intelligent. Autistic individuals typically are limited in their ability to communicate nonverbally and verbally. About half of all autistic people never learn to speak. They are likely to fail in developing social relationships with peers, have limited ability to initiate conversation if they do learn how to talk, and show a need for routine and ritual. Various abnormalities in the autistic brain have been documented. These include variations in the frontal lobes of the brain that focus on control and planning and in the limbic system, a group of structures in the brain that are linked to emotion, behavior, smell, and other functions. Autistic individuals may suffer from a limited development of the limbic system. This would explain some of the difficulties faced by autistic individuals in processing information.
Mental retardation usually refers to people with an IQ below 70. According to the American Psychiatric Association, a mentally retarded person is significantly limited in at least two of the following areas: self-care, communication, home living, social-interpersonal skills, self-direction, use of community resources, functional academic skills, work, leisure, health, and safety . Mental retardation affects roughly 1 percent of the U.S. population. According to the U.S. Department of Education, about 11 percent of school-aged children were enrolled in special education programs for students with mental retardation. There are four categories of mental retardation: mild, moderate, severe, and profound. There are many different causes of mental retardation, both biological and environmental. In about 5 percent of cases, retardation is transmitted genetically, usually through abnormalities in chromosomes, such as Down syndrome or fragile X syndrome . Children with Down syndrome have both mental and motor retardation. Most are severely retarded, with IQs between 20 and 49. Fragile X syndrome, in which a segment of the chromosome that determines gender is abnormal, primarily affects males.
Autism —A developmental disability that appears early in life, in which normal brain development is disrupted and social and communication skills are retarded, sometimes severely.
Down syndrome —A chromosomal disorder caused by an extra copy or a rearrangement of chromosome 21. Children with Down syndrome have varying degrees of mental retardation and may have heart defects.
Fragile X syndrome —A genetic condition related to the X chromosome that affects mental, physical, and sensory development. It is the most common form of inherited mental retardation.
Intelligence quotient (IQ) —A measure of somebody's intelligence, obtained through a series of aptitude tests concentrating on different aspects of intellectual functioning.
Kaufman Assessment Battery for Children —An intelligence and achievement test for children ages 2.5 to 12.5 years.
Psychometrics —The development, administration, and interpretation of tests to measure mental or psychological abilities. Psychometric tests convert an individual's psychological traits and attributes into a numerical estimation or evaluation.
Stanford-Binet intelligence scales —A device designed to measure somebody's intelligence, obtained through a series of aptitude tests concentrating on different aspects of intellectual functioning. An IQ score of 100 represents "average" intelligence.
Wechsler intelligence scales —A test that measures verbal and non-verbal intelligence.
Autism symptoms begins in infancy, but typically the condition is diagnosed between the ages of two to five. The symptoms of mental retardation are usually evident by a child's first or second year. In the case of Down syndrome, which involves distinctive physical characteristics, a diagnosis can usually be made shortly after birth. Mentally retarded children lag behind their peers in developmental milestones such as sitting up, smiling, walking, and talking. They often demonstrate lower than normal levels of interest in their environment and less responsiveness to others, and they are slower than other children in reacting to visual or auditory stimulation. By the time a child reaches the age of two or three, retardation can be determined using physical and psychological tests . Testing is important at this age if a child shows signs of possible retardation because alternate causes, such as impaired hearing, may be found and treated. There is no cure for autism or mental retardation.
When to call the doctor
Parents should consult a healthcare professional if their child's intellectual development appears to be significantly slower than their peers. Children suspected of having intelligence development problems should undergo a comprehensive evaluation to identify their difficulties as well as their strengths. Since no specialist has all the necessary skills, many professionals might be involved. General medical tests as well as tests in areas such as neurology (the nervous system), psychology, psychiatry, special education, hearing, speech and vision, and physical therapy may be needed. A pediatrician or a child and adolescent psychiatrist often coordinates these tests.
Parents should pay close attention to possible symptoms in their children. Autism is diagnosed by observing the child's behavior, communication skills , and social interactions. Medical tests should rule out other possible causes of autistic symptoms. Criteria that mental health experts use to diagnose autism include problems developing friendships, problems with make-believe or social play, endless repetition of words or phrases, difficulty in carrying on a conversation, obsessions with rituals or restricted patterns, and preoccupation with parts of objects. A diagnosis of mental retardation is made if an individual has an intellectual functioning level well below average and significant limitations in two or more adaptive skill areas. If mental retardation is suspected, a comprehensive physical examination and medical history should be done immediately to discover any organic cause of symptoms. If a neurological cause such as brain injury is suspected, the child may be referred to a neurologist or neuropsychologist for testing.
Armstrong, Thomas, and Jennifer Brannen. You're Smarter than You Think: A Kid's Guide to Multiple Intelligences. Minneapolis, MN: Free Spirit Publishing, 2002.
Brill, Marlene Targ. Raising Smart Kids for Dummies. New York: Wiley Publishing, 2003.
Deary, Ian J. Intelligence: A Very Short Introduction. Oxford, UK: Oxford University Press, 2001.
Georgas, James, et al. Culture and Children's Intelligence: Cross-Cultural Analysis of the WISC-III. Burlington, MA: Academic Press, 2003.
Bailey, Ronald. "The Battle for Your Brain: Science Is Developing Ways to Boost Intelligence, Expand Memory, and More. But Will You be Allowed to Change Your Own Mind?" Reason (February 2003): 25–31.
Bower, Bruce. "Essence of G: Scientists Search for the Biology of Smarts-General Factor Used to Determine Intelligence Level." Science News (February 8, 2003): 92–3.
Furnham, Adrian, et al. "Parents Think Their Sons Are Brighter than Their Daughters: Sex Differences in Parental Self-Estimations and Estimations of their Children's Multiple Intelligences." Journal of Genetic Psychology (March 2002): 24–39.
Gottfredson, Linda S. "Schools and the G Factor." The Wilson Quarterly (Summer 2004): 35–45.
Stanford, Pokey. "Multiple Intelligences for Every Classroom." Intervention in School & Clinic (November 2003): 80–85.
Child Development Institute. 3528 E Ridgeway Road Orange, CA 92867. Web site: <www.cdipage.com>.
National Academy of Child & Adolescent Psychiatry. 3615 Wisconsin Ave. NW, Washington, DC 20016. Web site: <www.aacap.org>.
Rosenblum, Gail. "Baby Brainpower." Sesame Workshop, 2004. Available online at <www.sesameworkshop.org/babyworkshop/library/article.php?contentId=860> (accessed November 10, 2004).
"The Theory of Multiple Intelligences." Human Intelligence, Fall 2001. Available online at <www.indiana.edu/~intell/mitheory.shtml> (accessed November 10, 2004).
Ken R. Wells
Wells, Ken. "Intelligence." Gale Encyclopedia of Children's Health: Infancy through Adolescence. 2006. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1G2-3447200314.html
Wells, Ken. "Intelligence." Gale Encyclopedia of Children's Health: Infancy through Adolescence. 2006. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1G2-3447200314.html
Intelligence is defined as the capacity for learning, reasoning, understanding, and similar forms of mental activity. This definition implies that the concept of intelligence is both multifaceted (i.e., reflective of many aspects of mental ability) and implicative of differences among people (i.e., reflective of degrees of capacity, ability, or aptitude among individuals). Yet this definition does not necessarily relate directly to the definition of intelligence used by scientists. In fact there is no consensus on the definition of intelligence among professionals who study it (e.g., psychologists, educators, computer scientists).
There have been multiple attempts to define intelligence. These definitions can be broadly classified into five large groups: (1) consensus definitions, (2) operational definitions, (3) task-based or psychometric definitions, (4) process-based definitions, and (5) domain definitions.
“Consensus definitions” of intelligence are typically associated with attempts of researchers in the field to consolidate a variety of points of view and produce, collectively, a comprehensive common definition. In this regard two symposia that brought together researchers in the field are important. The first symposium, which took place in 1921 under the title “Intelligence and Its Measurement: A Symposium,” focused on the abilities to learn and adapt to the environment. However, the definitions of these abilities varied. For example, the American psychologist Lewis Terman emphasized abstract thinking, whereas another American psychologist, Edward Thorndike, stressed the importance of providing good responses to questions. The second symposium, which took place in 1986, brought together a new generation of intelligence researchers (e.g., Douglas Detterman, Ulric Neisser, Robert Sternberg). By then the field of intelligence had developed markedly, having produced hundreds of research articles and books. The resulting consensus definition kept the reference to learning and adaptive abilities but expanded to include many other abilities, including meta-cognitive abilities.
Although there is still no single consensus definition of intelligence, based on the discussions at these symposia, multiple other meetings, and in the press a broad definition of intelligence includes references to lower-level processes, such as perception and attention, and higher-level processes, such as problem solving, reasoning, and decision making, with regard to learning and demonstrating adaptive behaviors in problem situations. These lower-and higher-level processes are typically referred to in two dimensions: quality and speed. Quality refers to efficacy or lack of errors, and speed refers to time while learning or solving a problem. Intelligence implies the presence of no or few errors and high speed in all processes.
“Operational definitions” of intelligence are closely linked to the concept of intelligence testing. Intelligence testing was conceived of and developed by the French psychologists Alfred Binet and Théodore Simon, who first used such a test to identify learning-impaired Parisian children in the early 1900s. The “invention” was welcomed by psychologists around the world, especially in the United States, and resulted in the development of innumerable tests of intelligence. To reflect the wealth of the research and the differential power of intelligence tests in describing individual differences, the American psychologist Edwin Boring noted in 1923 that intelligence was simply what intelligence tests test. Although obviously circular in nature, this definition of intelligence is still powerful. Researchers and practitioners often use the common metric of IQ (intelligence quotient), even though IQ typically reflects many different theoretical positions when generated by different tests of intelligence. For example, the first tests of intelligence by Binet were primarily based on sensory processes; David Wechsler’s tests (which exist in three versions spanning infancy, childhood, and adulthood) measure primary judgment skills. Then there are theory-based tests, such as the tests of Raymond Cattell, which are based on the theory of crystallized (i.e., acquired and learned over the total life span) and fluid (i.e., transformable to novel materials, situations, and tasks) intelligence, and such modern tests of intelligence as the Cognitive Assessment System (by Jack Naglieri and Jagannath Prasad Das) or K-ABC (by Alan and Nadeen Kaufman), which are both based on the theories of the Soviet neuropsychologist Alexander Luria. Yet as long as a test can generate an IQ, it is assumed to measure intelligence.
“Task-based or psychometric” definitions of intelligence are associated with ideas of defining intelligence through tasks that, by agreement among researchers, call for intelligence. One of the first proponents of task-based definitions of intelligence was the American psychologist Charles Spearman (1863–1945). In the early 1900s Spearman proposed that intelligence includes a so-called general (g -, or mental energy) factor and task-specific factors. The g -factor can explain the observation that indicators of performance on all intelligence tasks tend to correlate with each other (e.g., doing well on one task typically suggests strong performance on other tasks as well), whereas task-specific factors can explain why these correlations are not perfect (e.g., the performance indicators will differ on tasks that involve reading versus arithmetic). Spearman’s work had a tremendous impact on the field of intelligence: Students and followers include Cattell, Wechsler, Anne Anastasi, Detterman, Arthur Jensen, and many others. Spearman’s work also had opponents. For example, Thorndike argued for three forms of intelligence: abstract, mechanical, and social. Similarly Louis Thurstone argued that several primary mental abilities form intelligence (verbal comprehension, word fluency, number facility, spatial visualization, associative memory, perceptual speed, and reasoning). In an attempt to reconcile the theories of Spearman and Thurstone, Cattell proposed a hierarchical theory of intelligence in which lower-level abilities form two higher-order factors, fluid (reasoning with novel stimuli) and crystallized (reasoning with acquired knowledge) intelligence, which in turn contribute to the g -factor. Another opponent of Spearman’s was Joy Paul Guilford, who, developing Thurstone’s ideas, stated that intelligence can be represented by 150 abilities that result from different combinations of operations (e.g., cognition and memory), content (e.g., figural and symbolic), and products (e.g., unit and class).
“Process-based” definitions of intelligence are linked to theories that are not test or task based but, rather, capture processes involved in intelligence across tasks, domains, and tests. For example, the so-called triarchic theory of Robert Sternberg postulates three fundamental processes underlying intelligence: (1) analytical processes, which reflect judgment of a quality of an argument; (2) practical processes, which indicate skills of adaptation to situations or environment; and (3) creative processes, which capture skills of generating new knowledge and practices. Each of these types of processes is “constructed” from three different components: (a) knowledge acquisition components, (b) performance components, and (c) metacognitive components. These componential processes can manifest themselves in any area of human functioning.
“Domain-based” definitions of intelligence are typically associated with domains of expertise. For example, Howard Gardner postulates eight dimensions of intelligence. These dimensions, to a various degree, are present in all people and are recruited when particular types of tasks are performed or in particular domains of expertise. Specifically these intelligences are (1) bodily-kinesthetic, in which sportsmen excel; (2) musical, demonstrated to a high degree by musicians; (3) interpersonal, characteristic of philosophers; (4) intrapersonal, common among politicians; (5) logical-mathematical, possessed by mathematicians; (6) naturalistic, demonstrated by scientists; (7) verbal-linguistic, characteristic of writers; and (8) visual-spatial, necessary at high levels for engineers. Another example of domain-based definitions of intelligence is the theory of emotional intelligence (developed by Peter Salovey, John Mayer, and Daniel Goleman). This theory specifies intelligence in the domain of emotional functioning as the ability to perceive, appraise, express, access, generate, and regulate emotions and feelings.
The concept of IQ was developed by psychologists and statisticians in such a way that the distribution of scores remains relatively constant over a life span. IQs are compared across people, not within an individual, and are characterized by a population mean of 100 and a standard deviation of 15. Yet intelligence changes developmentally, and these changes occur in a number of ways. It is obvious that the intelligence of a one-year-old cannot be compared with the intelligence of a fifty-year-old, although their IQs can be compared. There are many developmental theories, for example those of Jean Piaget (1896–1980), that demonstrate that children reason in ways distinctly different from adults. Thus if a person had an IQ score of 110 at age one and has an IQ score of 110 at age fifty, this person’s “texture” of intelligence has changed, but his or her relative position among peers has remained constant. A few relevant observations should be noted. First, early childhood intelligence is not a good predictor of level of intelligence later in life. Second, intelligence tends to vary across a person’s life span, with a gradual increase toward middle age adulthood and a graduate decline in older ages. Third, it has been reported that in the developed world, intelligence tended to increase during the twentieth century (often called the Flynn effect), but it has appeared to stabilize or even decrease in the twenty-first century.
Individuals in the general population differ in their intelligence. Differences are captured by assessments of intelligence, which include both standardized tests (e.g., K-ABC) and experimental tasks (e.g., computerized tasks administered to register reaction time in response to particular stimuli). To identify the sources of these individual differences, researchers investigate the etiology (i.e., origin) of intelligence.
The etiology of intelligence is typically formulated in psychology as a question of nature and nurture: Does intelligence stem from genes (i.e., nature) or environments (i.e., nurture)? This question can be traced back to ancient times, where it was initially formulated as an “either/or” dilemma. In the early twenty-first century, however, there is a consensus that both hereditary and environmental factors play substantial and complementary roles in the development of intelligence. Two statistical coefficients are typically used to express the contributions of both genes and environments: “heritability,” which shows the amount of variation in intelligence among individuals attributable to genes, and “environmentality,” which captures the variation in intelligence attributable to environment. Both coefficients are relevant only at the level of population analyses and cannot be applied to individuals. Exciting tasks in early twenty-first century research pertain to the identification of specific genes and environments that underlie differences in intelligence. For example, it has been shown that variants in such genes as COMT (a gene responsible for the production of catechol-O-methyl transferase, an enzyme involved in the breakdown of major neurotransmitters) and BDNF (a gene responsible for the production of brain-derived neurotrophic factor, a protein involved in the biochemistry of neuronal survival, growth, and differentiation) are associated with individual differences in cognitive functioning and intelligence. It has also been shown that specific environments, such as impoverished or enriched with certain micronutrients (e.g., iodine), lead to individual differences in intellectual functioning. It is important to realize that neither genes nor environment have a deterministic impact on intelligence. The influence of both types of etiological factors, both additive and interactive, is probabilistic and takes place through the brain. Specifically there is a body of research that establishes evidence regarding which structures and pathways of the brain are associated with solving intellectual tasks and how patterns of brain activation vary among people and in different experimental conditions (e.g., sleep depleted versus deprived).
Although the majority of experts agree on the importance of both genes and environment in the etiology of intelligence, there are still leftovers of the raucous debate of the early 1990s related to the arguments put forth in The Bell Curve. Written by the psychologist Richard Herrnstein and the geneticist Charles Murray, The Bell Curve claimed IQ is hereditary and, as such, the single determinant of a person’s life outcomes. That and similar debates indicate that the concept of intelligence remains a point of disagreement with the capacity to raise charged social issues.
The concept of intelligence is viewed by some as a social construct developed to capture individual differences in cognitive functioning and as such has no “permanent” definition or understanding; both vary with the change of societal context. Thus yet another disagreement in the literature on intelligence pertains to the debate of a “social” versus “real” phenomenon. Those who argue that the concept of intelligence is a social construct suggest it was invented by the privileged classes to maintain their privilege. Those who argue that the concept of intelligence is based on the latent ability truly differentiating people maintain it is a helpful differentiating and predictive concept that has value in decisions pertaining to education and job placement.
Four types of differences are typically discussed in the study of intelligence: sex differences, ethnic and racial differences, cultural differences, and differences in conditions (i.e., intelligence in deaf and hard of hearing versus in hearing people). Males and females tend to demonstrate equivalent or comparable average scores on tests of intelligence. Yet although there are no differences in performance when performance indices are averaged across tasks, there are differences on specific tasks as well as differences in variability and range. Specifically males tend to score higher on spatial and visual tasks, among others, requiring memory, motor tasks involving aiming, and certain tasks requiring mathematical skills. Females tend to score higher on tasks requiring phonological and semantic processing, verbal production and comprehension, and fine motor skills. Broadly speaking, males demonstrate advantages in spatial reasoning, and females demonstrate advantages in verbal reasoning, but this generalized statement can be challenged by the presence and absence of sex differences on other tasks. As of the early twenty-first century there is no consensus on the profile, stability, and nature of sex differences in intelligence.
Another source of group differences in intelligence is variation in performance among different ethnic and racial groups. Group differences are typically seen on standardized tests of intelligence, especially those that rely heavily on g -theories. The differences among ethnic and racial groups demonstrate the underperformance of Hispanic Americans, Native Americans, and African Americans as compared with Asian and white Americans (of a variety of ethnic backgrounds). The differences are asystematic, meaning that the profiles of differences vary for different tasks. In other words, there is no systematic differentiation of profiles of abilities among the ethnic or racial groups. It is of special interest that the ethnic gap appears to be smaller or closed when testing is conducted using tasks from process- or domain-based theories of intelligences.
Similarly people in different cultural groups around the world demonstrate varied performances on intelligence tasks. Moreover definitions of intelligence vary across cultures as well. Thus what is considered to be “intelligent” behavior among the Luo people of Kenya is different from that of Yup’ik people of Alaska. A number of researchers have studied so-called implicit theories of intelligence—ideas about intelligence conceived by laypeople. It turns out that definitions of intelligence in the East and the West, for example, are quite different, with Eastern cultures emphasizing more social-emotional components of intelligence and Western cultures emphasizing information-processing aspects of intelligence.
Another source of group differences is the difference among people with special needs. For example, deaf people tend to score lower on tests of intelligence that call for verbal skills, but their performance on tests of spatial reasoning is similar to hearing individuals. Blind people score lower on spatial tasks (when administered in Braille), but their scores are average on verbal tasks. Thus characteristics of biological development (i.e., hormonal differences), acculturation, education, and various other peculiarities of development can all be related to group differences in intelligence. At this point there is no definitive answer to why these group differences exist.
SEE ALSO Cognition; Intelligence, Social; IQ Controversy; Memory; Multiple Intelligences Theory; Nature vs. Nurture; Psychology; Psychometrics
Cianciolo, Anna T., and Robert J. Sternberg. 2004. Intelligence: A Brief History. Malden, MA: Blackwell.
Deary, Ian J. 2000. Looking down on Human Intelligence: From Psychometrics to the Brain. Oxford: Oxford University Press.
Mackintosh, N. J. 1998. IQ and Human Intelligence. Oxford: Oxford University Press.
Sternberg, Robert J., ed. 2000. Handbook of Intelligence. New York: Cambridge University Press.
Sternberg, Robert J., ed. 2004. International Handbook of Intelligence. New York: Cambridge University Press.
Elena L. Grigorenko
"Intelligence." International Encyclopedia of the Social Sciences. 2008. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1G2-3045301151.html
"Intelligence." International Encyclopedia of the Social Sciences. 2008. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1G2-3045301151.html
The roles of genes and environment in the determination of intelligence have been controversial for more than 100 years. Studies of the question have often been marred by untested assumptions, poor design, and even racism, faults that more modern studies have striven to avoid. Nonetheless, examining the biology of intelligence is an enterprise that continues to be fraught with difficulty, and there remains no real consensus even on how to define the term.
Conventional measures of intelligence are obtained using standard tests, called intelligence quotient tests or, more commonly, IQ tests. These tests have been shown to be reliable and valid. Reliability means that they measure the same thing from person to person, whereas validity means that they measure what they claim to measure. IQ tests measure a person's ability to reason and to solve problems. These abilities are frequently called general cognitive ability, or "g."
Almost all genetic studies of the heritability of intelligence (how much is due to genetics and how much is due to the environment) have been obtained from IQ tests. To understand the studies, therefore, it is important to understand what IQ tests measure, and how their use and interpretation have changed over time.
The standard IQ-measurement approach to intelligence is among the oldest of approaches and probably began in 1876, when Francis Galton investigated how much the similarity between twins changed as they developed over time. Galton's study was concerned with measuring psychophysical abilities, such as strength of handgrip or visual acuity. The concept of general cognitive ability was first described by Charles Spearman in 1904. Later, Alfred Binet and Theophile Simon (1916) evaluated intelligence based on judgment, involving adaptation to the environment, direction of one's efforts, and self-criticism.
Most standard test results now include three scores: VIQ, PIQ, and FSIQ. The VIQ score measures verbal ability (verbal IQ), PIQ measures performance ability (performance IQ), and FSIQ provides an overall measurement (full scale IQ). Commonly used IQ tests include the Stanford-Binet Intelligence Scale, the Wechsler Intelligence Scale for Children (WISC), and the Wechsler Adult Intelligence Scales. The results achieved by individual testtakers on one of these IQ tests are likely to be similar to the results they achieve on the others, and they all aim to measure general cognitive ability (among other things). Measures of scholastic achievement, such as the SAT and the ACT correlate highly with "g."
Environmental Effects on Intelligence
The study of intelligence must take environmental effects into account. The Flynn effect describes a phenomenon that indicates that IQ has increased about 3 points per decade over the last fifty years, with children scoring higher than parents in each generation. This increase has been linked to multiple environmental factors, including better nutrition, increased schooling, higher educational attainment of parents, less childhood disease, more complex environmental stimulation, lower birth rates, and a variety of other factors.
Males and females have equivalent "g" scores. The question of racial differences and IQ arose when a 10 point IQ difference between African Americans and Americans of European descent was documented. Two adoption studies indicate that the effect may be in part related to environment factors, including culture. Also, environmental differences similar to those identified with the Flynn effect can be postulated. Studies of black Caribbean children and English children raised in an orphanage in England found that the black Caribbean children had higher IQs than the English children, with mixed racial children in between. A study comparing black children adopted by white families and those who were adopted into black families in the United States showed that black children raised by whites had higher IQ scores, again suggesting that the environment played a role.
Expanded Concepts of Intelligence
Many of the standard measures of IQ, such as the WISC and the Stanford-Binet, have changed their content over the years. Although they both still report verbal, performance, and total scores, the Wechsler model now offers scores for four additional factors (verbal comprehension, perceptual organization, processing speed, and freedom from distractibility). The Stanford-Binet also yields additional scores, including abstract-visual reasoning, quantitative reasoning, and short-term memory.
However, the majority of research into genetic and environmental variance in IQ has centered on the assumption that general cognitive ability is the essence of intelligence. Newer tests that measure specific abilities have not been included in genetic studies. These include, for example, tests that measure creativity in a model for intelligence. The addition of new factors in the Wechsler and Stanford-Binet IQ tests represents a trend toward a broader approach to IQ, and away from the notion that IQ can be understood by the single factor, "g."
Family, Twin, and Adoption Studies
Genetic studies have traditionally used models that evaluate how much of the variability in IQ is due to genes and how much is associated with environment. These studies include family studies, twin studies, and adoption studies.
General cognitive ability runs in families. For first-degree relatives (parents, children, brothers, sisters) living together, correlations of "g" for over 8,000 parent-offspring pairs averaged 0.43 (0.0 is no correlation, 1.0 is complete correlation). For more than 25,000 sibling pairs, "g" correlations averaged 0.47. Heritability estimates range from 40 to 80 percent, meaning that 40 to 80 percent of "g" is due to genes.
In twin studies of over 10,000 pairs of twins, monozygotic (genetically identical) twins averaged an 0.85 correlation of "g," whereas for dizygotic (fraternal, like brothers or sisters) same-sex twins the "g" correlations were 0.60. These twin studies suggest that the heritability (genetic effect) accounts for about half of the variance in "g" scores.
Adoption studies also provide evidence for substantial heritability of "g." The "g" estimate for identical twins raised apart is similar to that of identical twins raised together, proving that for genetically identical individuals, environmental differences did not affect "g." The Colorado Adoption Study (CAP) of first-degree relatives who were adopted also indicated significant heritability of "g." Thus, classical genetic studies indicate that there is a statistically significant and substantial genetic influence on "g."
Newer genetic research on general cognitive ability has focused on developmental changes in IQ, multivariate relations (contributions of multiple factors) among cognitive abilities, and specific genes responsible for the heritability of "g." Developmental changes over time were first studied by Galton in 1876. The CAP study was conducted over twenty-five years and evaluated 245 children who had been separated from their parents at birth and adopted by one month of age. This study, and others, showed that the variance in "g" due to environment for an adopted child in his or her adoptive family is largely unconnected with the shared adoptive family upbringing, that is, a shared parent-sibling environment. For adoptive parents and their adopted children, the parent-offspring correlations for heritability were around zero. For adopted children and their biologic mothers or for children raised with their biologic parents, heritability was the same, increasing with age.
Recent studies indicate that heritability increases over time, with infant measures of about 20 percent, childhood measures at 40 percent, and adult measures reaching 60 percent. Why is there an age effect for the heritability of "g"? Part of this could be due to different genes being expressed over time, as the brain develops. The stability of the heritability measure correlates with changes in brain development, with "maturity" of brain structure achieved after adolescence. Also, it is likely that small gene effects early in life become larger as children and adolescents select or create environments that foster their strengths.
Multivariate relations among cognitive abilities affect more than general cognitive ability as measured by "g." Current models of cognitive abilities include specific components such as spatial and verbal abilities, speed of processing, and memory abilities. Less is known about the heritabilities of these specific cognitive skills. They also show substantial genetic influence, although this influence is less than what has been found for "g." Multivariate genetic analyses indicate that the same genetic factors influence different abilities. In other words, a specific gene found to be associated with verbal ability may also be associated with spatial ability and other specific cognitive abilities. Four studies have shown that genetic effects on measures of school achievement are highly correlated with genetic effects on "g." Also, discrepancies between school achievement and "g," as occurs with under-achievers, are predominantly of environmental origin.
Genes for Intelligence
The search for specific genes associated with IQ is proceeding at a rapid pace with the completion of the Human Genome Project. While defects in single genes, such as the fragile X gene, can cause mental retardation, the heritability of general cognitive ability is most likely due to multiple genes of small effect (called quantitative trait loci, or QTLs) rather than a single gene of large effect. QTLs contribute additively and interchangeably to intelligence.
Genetic studies have identified QTLs associated with "g" on chromosomes 4 and 6. These studies involved both children with high "g" and children with average "g." QTLs on chromosome 6 have been identified and shown to be active in the regions of the brain involved in learning and memory. The gene identified is for insulin-like growth factor 2 receptor, or IGF2R, the exact function of which is still unknown. One allele (alternative form) of IGR2R was found to be present 30 percent of the time in two groups of children with high "g." This was twice the frequency of its occurrence in two groups of children with average "g," and these findings have been successfully replicated in other studies. QTLs associated with "g" have also been identified on chromosome 4. Future identification of QTLs will allow geneticists to begin to answer questions about IQ and development and gene-environment interaction directly, rather than relying on less specific family, adoption, and twin studies.
In summary, intelligence measurements ranging from specific cognitive abilities to "g" have a complex relationship. Genetic contributions are large, and heritability increases with age. Heritability remains high for verbal abilities during adulthood. Finally, the identification of QTLs associated with "g" and with specific cognitive abilities is just beginning.
see also Behavior; Complex Traits; Eugenics; Fragile X syndrome; Genetic Discrimination; Quantitative Traits; Twins.
and Ruth Abramson
Casse, D. "IQ since 'The Bell Curve.'" Commentary Magazine 106, no. 2 (1998): 33-41.
Chiacchia, K. B. "Race and Intelligence." In Encyclopedia of Psychology, 2nd ed., Bonnie Strickland, ed. Farmington Hills, MI: Gale Group, 2001.
Deary, I. J. "Differences in Mental Ability." British Medical Journal 317 (1998): 1701-1703.
Fuller, J. L., and W. R. Thompson. "Cognitive and Intellectual Abilities." In Foundations of Behavior Genetics. St. Louis, MO: C.V. Mosby Co., 1978.
Plomin, R. "Genetics of Childhood Disorders, III: Genetics and Intelligence." Journal of the American Academy of Childhood and Adolescent Psychiatry 38 (1999): 786-788.
Sternberg, R. J., and J. C. Kaufman. "Human Abilities." Annual Review Psychology 49: 479-502.
Sternberg, R. J., and E. L. Grigorenko. "Genetics of Childhood Disorders, I: Genetics and Intelligence." Journal of the American Academy of Childhood and Adolescent Psychiatry 38 (1999): 486-488.
Wright, Harry; Abramson, Ruth. "Intelligence." Genetics. 2003. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1G2-3406500153.html
Wright, Harry; Abramson, Ruth. "Intelligence." Genetics. 2003. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1G2-3406500153.html
An abstract concept whose definition continually evolves and often depends upon current social values as much as scientific ideas. Modern definitions refer to a variety of mental capabilities, including the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience as well as the potential to do so.
Several theories about intelligence emerged in the 20th century and with them debate about the nature of intelligence, whether it is hereditary, environmental or both. As methods developed to assess intelligence, theorizing occurred about the measurability of intelligence, its accuracy and this field known as psychometrics. As the 20th century drew to a close, publication of The Bell Curve by Richard J. Herrnstein and Charles Murray in 1994 stirred the controversy. Their findings pointed to links between social class, race, and IQ scores, despite questions by many about the validity of IQ tests as a measurement of intelligence or a predictor of achievement and success.
Part of the problem regarding intelligence stems from the fact that nobody has adequately defined what intelligence really means. In everyday life, we have a general understanding that some people are "smart," but when we try to define "smart" precisely, we often have difficulty because a person can be gifted in one area and average or below in another. To explain this phenomenon, some psychologists have developed theories to include multiple components of intelligence.
Charles Darwin 's younger cousin, Sir Francis Galton , inspired by the Origin of the Species, developed a forerunner of 20th-century testing in the 1860s when he set out to prove that intelligence was inherited. He used quantitative studies of prominent individuals and their families.
British psychologist and statistician Charles Spearman in 1904 introduced a central concept of intelligence psychometrics, pointing out that people who perform well on one type of intelligence test tend to do well on others also. This general mental ability that carried over from one type of cognitive testing to another, Spearman named g—for general intelligence. Spearman concluded that g consisted mainly of the ability to infer relationships based on one's experiences. Spearman's work led to the idea that intelligence is focused on a single, main component.
French psychologists Alfred Binet and Theodore Simon followed in 1905, introducing the concept of mental age to match chronological age in children with average ability. In bright children, mental age would exceed chronological age; in slower learners, mental age would fall below chronological age. Simon and Binet's test was introduced into the United States in a modified form in 1916 by Stanford psychologist Lewis Terman , and with it the concept of the intelligence quotient (I.Q.), the mental age divided by chronological age and multiplied by 100.
With the adoption of widespread testing using the Stanford-Binet and two versions created for the Army in World War I, the concept of the intelligence test departed from Binet and Simon's initial view. Intelligence became associated with a fixed, innate, hereditary value. That is, one's intelligence, as revealed by IQ tests, was locked at a certain level because of what was seen as its hereditary basis. Although a number of well-known and respected psychologists objected to this characterization of intelligence, it gained popularity, especially among the public.
At this time, people placed great faith in the role of science in improving society; intelligence tests were seen as a specific application of science that could be used beneficially. Unfortunately, because of the nature of the tests and because of many people's willingness to accept test results uncritically, people of racial minorities and certain ethnic groups were deemed to be genetically inferior with regard to intelligence compared to the majority.
Some early psychologists thought that measuring the speed of sensory processes and reaction times might indicate an individual's intelligence. This approach provided no useful results. Subsequently, tests reflecting white American culture and its values provided the benchmark for assessing intelligence. Although such tests indicate the degree of academic success that an individual is likely to experience, many have questioned the link to the abstract notion of intelligence, which extends beyond academic areas.
Immigration laws restricted entry into the United States of "inferior" groups, based on the results of early intelligence testing, according to some scholars. This claim seems to have some merit, although many psychologists objected to the conclusions that resulted from mass intelligence testing. In large part, the immigration laws seemed to reflect the attitudes of Americans in general regarding certain groups of people.
In the 1940s, a different view of intelligence emerged. Rejecting Spearman's emphasis on g, American psychologist L.L. Thurstone suggested that intelligence consists of specific abilities. He identified seven primary intellectual abilities: word fluency, verbal comprehension, spatial ability, perceptual speed, numerical ability, inductive reasoning , and memory .
Taking Thurstone's concept even further, J.P. Guilford developed the theory that intelligence consists of as many as five different operations or processes (evaluation, convergent production, divergent production, memory, and cognition ), five different types of content (visual, auditory, symbolic, semantic, and behavioral) and six different products (units, classes, relations, systems, transformation, and implications). Each of these different components was seen as independent; the result being an intelligence theory that consisted of 150 different elements.
In the past few decades, psychologists have expanded the notion of what constitutes intelligence. Newer definitions of intelligence encompass more diverse aspects of thought and reasoning. For example, psychologist Robert Sternberg developed a three-part theory of intelligence that states that behaviors must be viewed within the context of a particular culture (i.e., in some cultures, a given behavior might be highly regarded whereas in another, the same behavior is given low regard); that a person's experiences impact the expression of intelligence; and that certain cognitive processes control all intelligent behavior. When all these aspects of intelligence are viewed together, the importance of how people use their intelligence becomes more important than the question of "how much" intelligence a person has. Sternberg has suggested that current intelligence tests focus too much on what a person has already learned rather than on how well a person acquires new skills or knowledge. Another multifaceted approach to intelligence is Howard Gardner 's proposal that people have eight intelligences: logical-mathematical, linguistic, musical, spatial, bodily-kinesthetic, interpersonal, intrapersonal and the naturalistic.
Daniel Goleman has written about an emotional intelligence of how people manage their feelings, interact and communicate, combining the interpersonal and intrapersonal of Gardner's eight intelligences.
One feature that characterizes the newly developing concept of intelligence is that it has broader meaning than a single underlying trait (e.g., Spearman's g). Sternberg and Gardner's emergent ideas suggest that any simple attempt at defining intelligence is inadequate given the wide variety of skills, abilities, and potential that people manifest.
Some of the same controversies that surfaced in the early years of intelligence testing have recurred repeatedly throughout this century. They include the question of the relative effects of environment versus heredity , the degree to which intelligence can change, the extent of cultural bias in tests, and even whether intelligence tests provide any useful information at all.
The current approach to intelligence involves how people use the information they possess, not merely the knowledge they have acquired. Intelligence is not a concrete and objective entity, though psychologists have looked for different ways to assess it. The particular definition of intelligence that has currency at any given time reflects the social values of the time as much as the scientific ideas.
The approach to intelligence testing, however, remains closely tied to Charles Spearman's ideas, despite new waves of thinking. Tests of intelligence tend to mirror the values of our culture, linking them to academic skills such as verbal and mathematical ability, although performance-oriented tests exist.
See also Culture-fair test; Stanford-Binet intelligence scales; Wechsler Intelligence Scales
Gardner, Howard. Intelligence Reframed: Multiple intelligences for the 21st Century. New York: Basic Books, 1999.
Gould, S.J. The Mismeasure of Man. New York: W.W. Norton, 1996.
Khalka, Jean Ed. What Is Intelligence? Cambridge: Cambridge University Press, 1994.
"Intelligence." Gale Encyclopedia of Psychology. 2001. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1G2-3406000347.html
"Intelligence." Gale Encyclopedia of Psychology. 2001. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1G2-3406000347.html
Francis Galton in England and Alfred Binet in France were among the most significant within psychology in developing the modern conception of intelligence. Beginning in the 1860s, Galton pursued a programme of investigating individual differences in mental ability by measuring reactions to various physical stimuli and then showing that those measurements were distributed, like height or weight, according to the normal or bell-shaped curve. Although Galton's anthropometric approach was soon abandoned, his insistence that intelligence was a biological entity that was inheritable, and normally distributed in populations, persisted, and became linked to a very different method of assessing intelligence devised by Binet. In response to a governmental education commission, Binet and his colleague Théodore Simon created a set of tests, individually administered, which were designed to track normal intellectual progress. Oriented toward the higher mental processes, the Binet–Simon Intelligence Scale (1905, 1908, 1911) was able to produce a number, the mental age (MA), that characterized the intellectual level of each child administered the examination. Not only did it allow test-takers to be ranked according to the level of their intelligence, but it suggested that intelligence itself was a discrete and measurable entity.
The Binet–Simon Intelligence Scale set the standard for all further developments in the field. Lews M. Terman's 1916 revision of the Binet–Simon scale, the Stanford–Binet, quickly became the benchmark instrument for the assessment of intelligence, and helped to introduce the concept of the intelligence quotient (IQ), a ratio of mental age to chronological age which was adopted from German psychologist Wilhelm Stern and designed to produce a measure of intelligence which was constant over time. Revised in 1937 and again in 1960, the Stanford–Binet has remained one of the pre-eminent individual measures of intelligence. Its main rivals have been the tests of child (WISC) and adult (WAIS) intelligence developed by David Wechsler, starting in the 1940s, which provide, in addition to an overall measure of IQ, individual assessments of verbal and non-verbal ability.
Wechsler's provision of two additional scores highlights one of the persistent theoretical issues pursued in studies of intelligence: whether it is one thing or many. Using factor analysis, British psychologist Charles Spearman (1904) argued that performance on intelligence tests could be explained on the basis of two factors, general intelligence (g) and task-specific abilities (s). Spearman's theory was challenged during the 1920s and 1930s, by L. L. Thurstone in the US and Godfrey Thomson in the UK, both of whom also employed factor analysis, but who used it to argue against g and in favour of the existence of a small number of relatively independent abilities. During the post-war period, Philip E. Vernon, among others, attempted to arbitrate between these competing theories using a hierarchical conception of intelligence, which depicted intelligence as extending from a single overall ability down to a large number of specific skills. This approach was rejected by Joy P. Guilford, however, who proposed instead a three-dimensional model that initially posited 120 independent mental factors and subsequently posited 150. Commencing in the 1970s, various cognitively-based models have been put forward, including most prominently those by Howard Gardner, with his seven discrete types of intelligence, and Robert J. Sternberg, with his triarchic theory of intelligence. These cognitive approaches owe a great deal to the influence of the psychometric tradition and also to developmental studies of intelligence, particularly those associated with Jean Piaget (stages of intellectual development) and Lev Vygotsky (social influences on intellectual development).
The second major theoretical issue in intelligence studies has been over the relative weights of nature and nurture. Galton's work on individual intelligence began with the assumption that intelligence was both biological and inheritable, a belief that ran strong during the heyday of eugenics (1900s–20s), and was used to support such programs as immigration restriction and sterilization of the mentally deficient. Research during the 1930s and 1940s, however, especially at the Iowa Child Welfare Research Station, emphasized the importance of nurture: IQ, for example, was found to change when children were placed in different environments. After the war, studies continued to show the powerful effects of both nature and nurture on IQ. Research on identical twins has led some psychologists to conclude that at least 60% of IQ results from heredity. At the same time, a great deal of data has been collected indicating the influence of nutrition, kind of education received, and degree of sensory stimulation on IQ score.
The enormous professional interest in intelligence has been sustained by its many practical applications. As part of mobilization for World War I, American psychologists created new instruments that could be group administered, and tested approximately 1.75 million army recruits. This programme served to introduce the nation to standardized intelligence testing, and during the 1920s intelligence testing boomed, adopted by schools and industry as a means of efficient placement and assessment of students and personnel. Although some of the infatuation with testing receded by the end of the decade, intelligence and its measurement had by then become permanent features of the social and intellectual landscape. Debates over the provision of educational opportunities, the capabilities of various ethnic or racial groups, and the value of affirmative action have all been conducted at least in part through the language of native intelligence. However ill-defined, intelligence has become a concept of much consequence within the contemporary world.
Ceci, S. J. (1996). On intelligence: a bioecological treatise on intellectual development. Harvard University Press, Cambridge, MA.
Sokal, M. M. (ed.) (1987). Psychological testing and American society, 1890–1930. Rutgers University Press, New Brunswick.
COLIN BLAKEMORE and SHELIA JENNETT. "intelligence." The Oxford Companion to the Body. 2001. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1O128-intelligence.html
COLIN BLAKEMORE and SHELIA JENNETT. "intelligence." The Oxford Companion to the Body. 2001. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1O128-intelligence.html
Many advocates of IQ testing assume that the usual battery of IQ tests combine to produce a measure of intelligence which is genetically transmitted and consequently immutable. Critics argue that the tests were not originally intended to provide a fixed measure of intelligence, unamenable to improvement, and that the assumption that a unitary measure can be provided at all is an unjustifiable reification of a culture-bound concept. Much effort and energy has been invested in this debate, but no convincing conclusions have been evinced in either direction, and estimates of the heritability of IQ still range between zero and 80 per cent. The majority of such estimates are based upon studies of individuals brought up in different environments, whose genetic characteristics are similar or the same (particularly siblings, most often twins). In these circumstances, it is claimed, the factors of inheritance and environment can be separated out, allowing estimates to be made of their respective effects. In reality, It is often very much harder to achieve this, and much criticism of these studies has been directed at the difficulties of ensuring that environments are sufficiently independent to allow such estimates to be made.
There have also been well-publicized accusations that one of the most influential contributors to the debate in the middle years of the century. Sir Cyril Burt, fabricated his results to make it appear that the heritable component accounted for the vast majority (around 80 per cent) of variability in IQ scores. Protagonists include Hans Eysenck, a psychologist who maintains a belief in a high heritable component for IQ, and Leon Kamin, a human geneticist who argues that the debate is unlikely ever to be conclusive, and in any case is misconceived for the reasons given above (see Eysenck and and Kamin , Intelligence: The Battle for the Mind, 1981
). In one analysis which provoked fierce controversy, Arthur R. Jensen (‘How Much Can We Boost IQ and Educational Achievement?’, Harvard Educational Review, 1969)
argued that intelligence is largely explained by genetic factors, and that the poverty of American Blacks was not sufficient to explain away the differences in their test performances in relation to Whites. Critics argued that Jensen's data were unsound and the implications of his study unwarranted.
More recently, the relationship between IQ and social class has also become a focus for renewed academic discussion, after being many years in abeyance. For example, in his critique of the class analysis tradition of research, Peter Saunders starts by pointing to Michael Young's classic definition of a meritocracy in terms of individual rewards for ‘intelligence and effort’, deduces that one might therefore expect research on social mobility to include evidence on these two characteristics, but observes that the question of ability has tended to be overlooked in many studies. For Saunders, measured intelligence is a good indicator of people's abilities, and many studies of class mobility arrive unwarrantably at conclusions about inequality of opportunity because researchers fail to take IQ into account. His own research findings (which are hotly disputed) lead him to conclude that class differentials in educational and occupational attainment might simply be ‘a function of differences in average levels of measured intelligence between the classes’. IQ tests purportedly measure these variations in genetic endowments between different individuals. (The exchanges between Saunders and his critics will be found mainly in the journal Sociology, 1995–7
Similarly, Richard Herrnstein and Charles Murray's controversial account of the relationship between intelligence and both class and race in America (The Bell Curve, 1994) argues that IQ is a good indicator of natural ability, and appears to be a largely inherited trait. Here too, sceptics have replied by assembling no little evidence which casts doubt on both of these propositions, and have concluded that educational attainment and IQ scores are both products, not only of putatively natural or genetic origins, but also of socially determined influences. Most obviously, the results of intelligence tests are (at least in part) a reflection of attributes such as miscellaneous information picked up at home and on television, and of the inclination (mainly instilled by school teaching) to try harder at this particular task than at any other. In other words, test results are partly a function of socialization, substantial aspects of which are already influenced by existing inequalities in the distribution of resources between different classes and ethnic groups. The argument here is that, as John Miner (Intelligence in the United States, 1957) long ago observed, ‘no test item that has ever been devised taps native potential directly, independent of the past life and learning of the respondent’. The most sustained of the many critiques of Herrnstein and Murray's study will be found in Claude S. Fischer et al. , Inequality by Design (1996)
, which argues that social inequalities depend more on social circumstances and the structure of society than they do on IQ, which is itself a social product. In particular, social policies set the ‘rules of the game’ within which individual abilities and effort matter, and it is these that perpetuate the differences between rich and poor.
What is undeniable is that IQ tests have, over their history, been considerably misused in the attempt to prove the inferiority of particular ‘races’, using culturally specific criteria of assessment. It is still not entirely clear that modern tests escape such bias. For this reason it would be imprudent to regard the overall results of these tests as giving a reliable indication of a fixed or innate level of general intelligence. For a comprehensive survey of the literature and issues surrounding intelligence testing see N. Brody , Intelligence (1992
). See also DARWINISM; EUGENICS; HEREDITY.
GORDON MARSHALL. "intelligence." A Dictionary of Sociology. 1998. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1O88-intelligence.html
GORDON MARSHALL. "intelligence." A Dictionary of Sociology. 1998. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1O88-intelligence.html
intelligence, in psychology, the general mental ability involved in calculating, reasoning, perceiving relationships and analogies, learning quickly, storing and retrieving information, using language fluently, classifying, generalizing, and adjusting to new situations. Alfred Binet, the French psychologist, defined intelligence as the totality of mental processes involved in adapting to the environment. Although there remains a strong tendency to view intelligence as a purely intellectual or cognitive function, considerable evidence suggests that intelligence has many facets.
Early investigations into intelligence assumed that there was one underlying general factor at its base (the g-factor), but later psychologists maintained that intelligence could not be determined by such a simplistic method. Raymond Cattell argued that intelligence can be separated into two fundamental parts: fluid ability and crystallized ability. Fluid ability is considered innate, basic reasoning skill, while crystallized intelligence is the information and skills that are acquired through experience in a cultural environment. Other psychologists have further divided intelligence into subcategories. Howard Gardner maintained (1985) that intelligence is comprised of seven components: musical, bodily-kinesthetic, logical-mathematical, linguistic, spatial, interpersonal, and intrapersonal. J. P. Guilford tried (1982) to show that there are 150 different mental abilities that constitute intelligence.
It is generally accepted that intelligence is related to both heredity and environment. Studies done on families, particularly among identical twins and adopted children, have shown that heredity is an important factor in determining intelligence; but they have also suggested that environment is a critical factor in determining the extent of its expression. For instance, children reared in orphanages or other environments that are comparatively unstimulating tend to show retarded intellectual development. In recent years, controversy regarding intelligence has centered primarily around how much of each factor, heredity and environment, is responsible for an individual's level of intelligence.
Although a strict definition of intelligence has proven elusive, a number of psychologists have argued that it can be quantified, primarily through testing. In 1905, Alfred Binet and Theodore Simon devised a system for testing intelligence, with scoring based on standardized, average mental levels for various age groups. In 1916 the Binet-Simon Intelligence Scale was expanded and reworked by Lewis Terman at Stanford Univ., and later revisions called the Revised Stanford-Binet Intelligence Tests were published in 1937, 1960, and 1985. A highly successful series of tests, designed by psychologist David Wechsler, have been in wide use for years as diagnostic and evaluative instruments. Known in 1939 as the Wechsler-Bellevue Intelligence Scale, the Wechsler Adult Intelligence Scale is a standard tool for intelligence testing today. All of these tests are administered to one individual at a time by a psychometrician. While no consensus of opinion prevails about what such tests actually measure, their use in education has had great practical value in assigning children to suitable class groups and in predicting academic performance.
The Army Alpha Test, which was first administered to nearly 2 million new recruits in World War I, and the Otis Group Intelligence Scale, were forerunners of many other group tests that are administered economically and quickly to large numbers, and were thus effective for use in schools and industry. National, standardized group tests are administered for college and graduate school entrance, and for a number of civil service positions.
The work of Binet, Terman, and Wilhelm Stern paved the way for a method of classifying intelligence in terms of a standardized measure, with standardization ensured by the large number of individuals of various ages taking the test. German psychologist L. Wilhelm Stern was the first to coin the term intelligence quotient (IQ), a figure derived from the ratio of mental age to chronological age. Although Stern's method for determining IQ is no longer in common use, the term IQ is still used today to describe the results in several different tests. Today, an average IQ score is considered to be 100, with deviations based on this figure. Mentally retarded individuals usually score below 70 in IQ tests, and are classified according to functional ability through reference to a scale of low IQ scores.
One criticism of intelligence testing is that it is difficult to insure that test items are equally meaningful or difficult for members of different sociocultural groups. Testing is often considered validated in part, however, by the finding that the quantity measured by the tests can be closely correlated in American society with career and academic achievement. There has been a decline in interest in pure intelligence tests since the 1920s, with a corresponding increase in the number of mental tests that measure special aptitudes and personality factors (see psychological tests).
See R. J. Sternberg and R. K. Wagner, ed., Practical Intelligence (1986); R. Fancher, The Intelligence Men: Makers of the I.Q. Controversy (1987); P. Chapman, Lewis M. Terman, Applied Psychology, and the Intelligence Testing Movement, 1880–1930 (1988); J. R. Flynn, What Is Intelligence? (2007).
"intelligence." The Columbia Encyclopedia, 6th ed.. 2016. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1E1-intellig.html
"intelligence." The Columbia Encyclopedia, 6th ed.. 2016. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1E1-intellig.html
Intelligence is information concerning a foreign entity, usually (although not always) an adversary, as well as agencies concerned with collection of such information. It is intimately tied with the intelligence cycle, a process whereby raw information is acquired, converted into intelligence, and disseminated to the appropriate consumers.
The intelligence cycle, as defined in the United States Senate hearings of the Church Committee during the mid-1970s, consists of four or five steps. In the first of these, called either planning, direction, or planning and direction, intelligence requirements are determined, a plan for the collection is developed, and agencies are assigned to specific collection tasks. Throughout the intelligence cycle, this first step recurs in the form of continued checking on the productivity of collecting agencies.
The second step, collection, is probably the one that most readily comes to mind when the average person thinks of intelligence. Collection involves actions the layperson would call "spying." Collection includes the gathering of information through means such as surveillance of various types, as well as the cultivation of human contacts. Through these and other means, information sources are exploited, and this information is delivered to the appropriate processing unit.
The third and fourth steps, processing and production, are sometimes viewed as a single step. In the processing phase, raw data is converted into a more usable form; then that information is evaluated, analyzed, integrated, and interpreted to produce what is no longer mere information, but true intelligence. Suppose numerical data on a factory's output is collected; in the processing phase, these numbers may be put into the form of a graph, while in the production phase, an analyst determines overall patterns and what they mean.
Finally, there is dissemination, the step in which processed intelligence is distributed to the appropriate consumers, which are usually government or military officials.
█ FURTHER READING:
Martin, David C. Wilderness of Mirrors. New York: Harper & Row, 1980.
Polmar, Norman, and Thomas B. Allen. Spy Book: The Encyclopedia of Espionage. New York: Random House, 1998.
Richelson, Jeffrey T. The U.S. Intelligence Community, fourth edition. Boulder, CO: Westview Press, 1999.
Wright, Peter. Spycatcher: The Candid Autobiography of a Senior Intelligence Officer. New York: Viking, 1987.
HUMINT (Human Intelligence)
Intelligence and Counter-Espionage Careers
Measurement and Signatures Intelligence (MASINT)
SIGINT (Signals Intelligence)
"Intelligence." Encyclopedia of Espionage, Intelligence, and Security. 2004. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1G2-3403300380.html
"Intelligence." Encyclopedia of Espionage, Intelligence, and Security. 2004. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1G2-3403300380.html
in·tel·li·gence / inˈtelijəns/ • n. 1. the ability to acquire and apply knowledge and skills: an eminent man of great intelligence they underestimated her intelligence. ∎ a person or being with this ability: extraterrestrial intelligences. 2. the collection of information of military or political value: the chief of military intelligence | [as adj.] the intelligence department. ∎ people employed in this, regarded collectively: French intelligence has been able to secure numerous local informers. ∎ information collected in this way: the gathering of intelligence. ∎ archaic information in general; news. DERIVATIVES: in·tel·li·gen·tial / inˌteləˈjenchəl/ adj. ( archaic ).
"intelligence." The Oxford Pocket Dictionary of Current English. 2009. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1O999-intelligence.html
"intelligence." The Oxford Pocket Dictionary of Current English. 2009. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1O999-intelligence.html
379. Intelligence (See also Wisdom.)
- Alexander the Great looses the Gordian knot by cutting it with his sword. [Gk. Legend: Brewer Dictionary, 409]
- IQ (intelligence quotient) controversial measurement of intelligence by formula which compares mental age with chronological age. [Western Education.: EB, V : 376]
- Mensa International organization whose members have IQs in the top two percent of the general population. [Am. Pop. Culture: EB, VI: 793]
- Stanford-Binet Intelligence Scale test used to measure IQ; designed to be used primarily with children. [Am. Education: EB, IX: 521]
Intemperance (See DRUNKENNESS .)
Intimidation (See BULLYING .)
Intoxication (See DRUNKENNESS .)
"Intelligence." Allusions--Cultural, Literary, Biblical, and Historical: A Thematic Dictionary. 1986. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1G2-2505500388.html
"Intelligence." Allusions--Cultural, Literary, Biblical, and Historical: A Thematic Dictionary. 1986. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1G2-2505500388.html
Intelligence is the ability to acquire, remember, and use knowledge in order to make judgments, solve problems, and deal with new experiences.
for searching the Internet and other reference sources
Not every student will have the experience of taking an I.Q. (intelligence quotient) test. However, almost all students do know what it is like to take a standardized test. Unlike a test taken for a class, which usually is based on specific material already covered in the classroom, standardized tests typically include a wide range of items that ask the test-taker to use words, solve problems, and understand relationships among concepts. The results often show how the student performed compared to others of the same age or grade level. For example, if a student scores at the 80th percentile, that means this person performed better than 8 out of 10 students of the same age or grade who took the test.
I.Q. tests are used to compare an individual’s performance to that of others on a sampling of school-related tasks. An individual’s performance on all these tasks is averaged and compared to that of other people of the same age. I.Q. varies among people much the way height does. Most people are close to average height, while a small number are much taller or shorter than average. Similarly, the average I.Q. is 100, and most people fall somewhere between 70 and 130. Those who fall below 70 often are diagnosed with mental retardation, while those with an I.Q. higher than 130 often are considered gifted.
How did the practice of measuring intelligence get started? Back in 1905, public school administrators in Paris asked psychologist Alfred Binet to come up with a test that would identify mentally retarded children who could benefit from special help outside the regular classroom. It was hoped that this would help relieve the problem of overcrowded classes. The Simon-Binet test that resulted set the stage for intelligence testing throughout the 1900s.
Stanford-Binet Intelligence Scale
An American psychologist at Stanford University named Lewis Terman revised the Simon-Binet test in 1916. This revision, known as the Stanford-Binet Intelligence Scale, is still in use today, although it has been revised several more times. The latest version includes sections on abstract/visual reasoning, verbal reasoning (word-related problems), quantitative reasoning (number-related problems), and short-term memory.
Wechsler Intelligence Scales
The Wechsler Intelligence Scales are another well-known set of I.Q. tests. Psychologist David Wechsler developed a number of tests in the 1940s, 50s, and 60s that were tailored to children of different ages as well as to adults. Today, many schools use the Wechsler Intelligence Scale for Children–Third Edition (WISC-III) to evaluate children between the ages of 6 and 16. One of
Lewis Terman And The Stanford Study
In the early 1900s, it was widely believed that gifted people were physically inferior, had unusual interests, and found it difficult to relate to others. In the 1920s, psychologist Lewis Terman and his colleagues at Stanford University launched a study of 1*500 children in California who were gifted (LQ.s over 130). After tracking the children for several years, the researchers found that they actually were healthier, taller, better adjusted, and more popular than the average child. As these gifted children grew into young adults, they were more likely to attend college, achieve academically, pursue advanced degrees, and go on to higher-level professional positions in fields such as science, writing, and business They also tended to be more satisfied with their lives as adults.
This dispelled the notion that extremely bright people were “eggheads” who were at a disadvantage socially. It also suggested that I.Q. may be a somewhat reliable predictor of later academic and professional success. At the same time, however, the study showed that a high I.Q. is not a guarantee of success, as there were also many individuals who did not achieve at a high level. While many of the “gifted children” were well educated and had good professional jobs, all levels of employment and income were found.
Wechsler’s contributions is the notion that intelligence can be broken down into two main types of problem-solving: verbal and nonverbal. A Verbal Scale on the WISC-III measures how well children are able to use words to solve problems of different kinds, including some that involve common sense and others that involve more abstract reasoning. The Performance Scale on the test measures how well children use nonverbal abilities to make sense of visual relationships; for instance, by solving a puzzle or deciphering a code.
Intelligence is sometimes classified as left-brained or right-brained, although that is an oversimplification. People can hear words and musical sounds with both ears, but the right ear is believed to have a stronger connection to the left hemisphere of the brain where words and speech are processed. People can hear words spoken into the left ear but they understand them better when assisted by the speech pathway from the right ear. Likewise, the left ear has a stronger connection to the right hemisphere of the brain where musical sounds are processed. People can hear melodies played into the right ear but enjoy them more when assisted by the sound pathway from the left ear.
Defining intelligence is not as simple as giving someone an I.Q. test, however. In fact, scientists still are debating what intelligence really is. Harvard psychologist and education expert Howard Gardner has challenged the notion that there is a single human intelligence, or even just verbal and nonverbal intelligences. Instead, Gardner has proposed a theory of multiple intelligences. He argues that human beings have at least seven separate intelligences, each relatively independent of the others:
- linguistic (reading and writing)
- logical-mathematical (using numbers, solving logic problems)
- spatial (finding one’s way around an environment)
- musical (perceiving and creating patterns of pitch and rhythm)
- bodily-kinesthetic (making precise movements, as in performing surgery or dance)
- interpersonal (understanding others)
- intrapersonal (knowing oneself)
Gardner also believes that any definition of intelligence must take into account what the culture values. For example, while we might consider someone intelligent if that person can use words or numbers well, people of another culture might place more value on skills such as hunting, fishing, or understanding nature. Gardner’s theory favors observation of people over time, rather than short-answer I.Q. tests, for measuring the different intelligence types.
Other psychologists have suggested still other theories for understanding intelligence. Swiss psychologist Jean Piaget, believed that intelligence should be defined as adaptation to the environment. Piaget looked at how children display intelligence at different stages of life, from infancy through adolescence, and tried to make generalizations about how they are able to cope with their surroundings and meet new challenges. More recently, psychologist Robert Sternberg proposed a three-sided theory of intelligence, arguing that intelligence actually is composed of three parts: the ability to analyze information to solve problems, the creative ability to incorporate insights and new ideas, and the practical ability to size up situations and survive in the real world.
Most likely, all of these theories are at least partly correct and can contribute to our overall understanding of intelligence. However, updated versions of the tests developed by Alfred Binet and David Wechsler still are used to measure I.Q. Many psychologists and educators have strong feelings for or against giving I.Q. tests. Some argue that I.Q. tests are very useful for predicting how well a particular child will do in school and judging whether that child needs extra support or more challenges. However, others fear that children who test poorly may be stereotyped as low achievers and not given the level of attention they otherwise would have received. Still others believe that specific test questions put individuals from certain ethnic groups at a disadvantage. For example, think about how some of the verbal expressions used by African American or Latino students differ from those used by their caucasian classmates. A verbal question that asks about a particular word that is commonly used by people of one ethnic group might be unfamiliar to people from other backgrounds. Finally, some experts are concerned that I.Q. tests may underestimate the abilities of people with speech, movement, and other disabilities.
Testing and Evaluation
National Association for Gifted Children, 1707 L Street Northwest, Suite 550, Washington, DC 20036. A national organization for parents and teachers that focuses on the special needs of gifted and talented students. Telephone 202-785-4268 http://www.nagc.org
U.S. Department of Education, 400 Maryland Avenue Southwest, Washington, DC 20202. The department of the federal government that oversees special education programs for mentally retarded and gifted students. Telephone 800-872-5327 http://www.ed.gov
"Intelligence." Complete Human Diseases and Conditions. 2008. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1G2-3497700221.html
"Intelligence." Complete Human Diseases and Conditions. 2008. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1G2-3497700221.html
"intelligence." A Dictionary of Biology. 2004. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1O6-intelligence.html
"intelligence." A Dictionary of Biology. 2004. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1O6-intelligence.html
"intelligence." World Encyclopedia. 2005. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1O142-intelligence.html
"intelligence." World Encyclopedia. 2005. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1O142-intelligence.html
"intelligence." Oxford Dictionary of Rhymes. 2007. Encyclopedia.com. (August 27, 2016). http://www.encyclopedia.com/doc/1O233-intelligence.html
"intelligence." Oxford Dictionary of Rhymes. 2007. Retrieved August 27, 2016 from Encyclopedia.com: http://www.encyclopedia.com/doc/1O233-intelligence.html