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Intelligence, term usually referring to a general mental capability to reason, solve problems, think abstractly, learn and understand new material, and profit from past experience. Intelligence can be measured by many different kinds of tasks. Likewise, this ability is expressed in many aspects of a person’s life. Intelligence draws on a variety of mental processes, including memory, learning, perception, decision-making, thinking, and reasoning.

Most people have an intuitive notion of what intelligence is, and many words in the English language distinguish between different levels of intellectual skill: bright, dull, smart, stupid, clever, slow, and so on. Yet no universally accepted definition of intelligence exists, and people continue to debate what, exactly, it is. Fundamental questions remain: Is intelligence one general ability or several independent systems of abilities? Is intelligence a property of the brain, a characteristic of behavior, or a set of knowledge and skills?

The simplest definition proposed is that intelligence is whatever intelligence tests measure. But this definition does not characterize the ability well, and it has several problems. First, it is circular: The tests are assumed to verify the existence of intelligence, which in turn is measurable by the tests. Second, many different intelligence tests exist, and they do not all measure the same thing. In fact, the makers of the first intelligence tests did not begin with a precise idea of what they wanted to measure. Finally, the definition says very little about the specific nature of intelligence.

Whenever scientists are asked to define intelligence in terms of what causes it or what it actually is, almost every scientist comes up with a different definition. For example, in 1921 an academic journal asked 14 prominent psychologists and educators to define intelligence. The journal received 14 different definitions, although many experts emphasized the ability to learn from experience and the ability to adapt to one’s environment. In 1986 researchers repeated the experiment by asking 25 experts for their definition of intelligence. The researchers received many different definitions: general adaptability to new problems in life; ability to engage in abstract thinking; adjustment to the environment; capacity for knowledge and knowledge possessed; general capacity for independence, originality, and productiveness in thinking; capacity to acquire capacity; apprehension of relevant relationships; ability to judge, to understand, and to reason; deduction of relationships; and innate, general cognitive ability.

People in the general population have somewhat different conceptions of intelligence than do most experts. Laypersons and the popular press tend to emphasize cleverness, common sense, practical problem solving ability, verbal ability, and interest in learning. In addition, many people think social competence is an important component of intelligence.

Most intelligence researchers define intelligence as what is measured by intelligence tests, but some scholars argue that this definition is inadequate and that intelligence is whatever abilities are valued by one’s culture. According to this perspective, conceptions of intelligence vary from culture to culture. For example, North Americans often associate verbal and mathematical skills with intelligence, but some seafaring cultures in the islands of the South Pacific view spatial memory and navigational skills as markers of intelligence. Those who believe intelligence is culturally relative dispute the idea that any one test could fairly measure intelligence across different cultures. Others, however, view intelligence as a basic cognitive ability independent of culture.

In recent years, a number of theorists have argued that standard intelligence tests measure only a portion of the human abilities that could be considered aspects of intelligence. Other scholars believe that such tests accurately measure intelligence and that the lack of agreement on a definition of intelligence does not invalidate its measurement. In their view, intelligence is much like many scientific concepts that are accurately measured well before scientists understand what the measurement actually means. Gravity, temperature, and radiation are all examples of concepts that were measured before they were understood.

The first intelligence tests were short-answer exams designed to predict which students might need special attention to succeed in school. Because intelligence tests were used to make important decisions about people’s lives, it was almost inevitable that they would become controversial. Today, intelligence tests are widely used in education, business, government, and the military. However, psychologists continue to debate what the tests actually measure and how test results should be used.

A. Early test
Interest in measuring individual differences in mental ability began in the late 19th century. Sir Frances Galton, a British scientist, was among the first to investigate these differences. In his book Hereditary Genius (1869), he compared the accomplishments of people from different generations of prominent English families. No formal measures of intelligence existed at the time, so Galton evaluated each of his subjects on their fame as judged by encyclopedia entries, honors, awards, and similar indicators. He concluded that eminence of the kind he measured ran in families and so had a hereditary component. Believing that some human abilities derived from hereditary factors, Galton founded the eugenics movement, which sought to improve the human species through selective breeding of gifted individuals.

Between 1884 and 1890 Galton operated a laboratory at the South Kensington Museum in London (now the Victoria and Albert Museum) where, for a small fee, people could have themselves measured on a number of physical and psychological attributes. He tried to relate intellectual ability to skills such as reaction time, sensitivity to physical stimuli, and body proportions. For example, he measured the highest and lowest pitch a person could hear and how well a person could detect minute differences between weights, colors, smells, and other physical stimuli. Despite the crude nature of his measurements, Galton was a pioneer in the study of individual differences. His work helped develop statistical concepts and techniques still in use today. He also was the first to advance the idea that intelligence can be quantitatively measured.

In the 1890s American psychologist James McKeen Cattell, who worked with Galton in England, developed a battery of 50 tests that attempted to measure basic mental ability. Like Galton, Cattell focused on measurements of sensory discrimination and reaction times. Cattell’s work—and by association, Galton’s—was unsupported in 1901, when a study showed that the measurements had no correlation with academic achievement in college. Later researchers, however, pointed out that Cattell’s test subjects were limited to Columbia University students, whose high academic performance was not representative of the general population. Better-designed tests given to broader samples have shown that reaction time and processing speed on perceptual tasks do correlate with academic achievement.

B. The Binet-simon test
Alfred Binet, a prominent French psychologist, was the first to develop an intelligence test that accurately predicted academic success. In the late 19th century, the French government began compulsory education for all children. Prior to this time, most schoolchildren came from upper-class families. With the onset of mass education, French teachers had to educate a much more diverse group of children, some of whom appeared mentally retarded or incapable of benefiting from education. Teachers had no way of knowing which of the “slow” students had true learning problems and which simply had behavioral problems or poor prior education. In 1904 the French Ministry of Public Instruction asked Binet and others to develop a method to objectively identify children who would have difficulty with formal education. Objectivity was important so that conclusions about a child’s potential for learning would not be influenced by any biases of the examiner. The government hoped that identifying children with learning problems would allow them to be placed in special remedial classes in which they could profit from schooling. Binet and colleague Théodore Simon took on the job of developing a test to assess each child’s intelligence.

As Binet and Simon developed their test, they found that tests of practical knowledge, memory, reasoning, vocabulary, and problem solving worked better at predicting school success than the kind of simple sensory tests that Galton and Cattell had used. Children were asked, among other tasks, to perform simple commands and gestures, repeat spoken digits, name objects in pictures, define common words, tell how two objects are different, and define abstract terms. Similar items are used in today’s intelligence tests. Binet and Simon published their first test in 1905. Revisions to this test followed in 1908 and 1911.

Binet and Simon assumed that all children follow the same course of intellectual development but develop at different rates. In developing their test, they noted which items were successfully completed by half of seven-year-olds, which items by half of eight-year-olds, and so on. Through these observations they created the concept of mental age. If a 10-year-old child succeeded on the items appropriate for 10-year-olds but could not pass the questions appropriate for 11-year-olds, that child was said to have a mental age of 10. Mental age did not necessarily correspond with chronological age. For example, if a 6-year-old child succeeded on the items intended for 9-year-olds, then that child was said to have a mental age of 9.

To judge how effectively the test predicted academic achievem ent, Binet asked teachers to rate their students from best to worst. The results showed that students who had been rated higher by their teachers also scored higher on the test. Thus, Binet’s test successfully predicted how students would perform in school.

C. The IQ test
Binet’s test was never widely used in France. Henry Goddard, director of a New Jersey school for children with mental retardation, brought it to the United States. Goddard translated the test into English and began using it to test people for mental retardation. Another American psychologist, Lewis Terman, revised the test by adapting some of Binet’s questions, adding questions appropriate for adults, and establishing new standards for average performance at each age. Terman’s first adaptation, published in 1916, was called the Stanford-Binet Intelligence Scale. The name of the test derived from Terman’s affiliation with Stanford University.

Instead of giving a person’s performance on the Stanford-Binet as a mental age, Terman converted performance into a single score, which he called the intelligence quotient, or IQ. A quotient is the number that results from dividing one number by another. The idea of an intelligence quotient was first suggested by German psychologist William Stern in 1912. To compute IQ, Stern divided mental age by the actual, chronological age of the person taking the test and then multiplied by 100 to get rid of the decimal point. For example, if a 6-year-old girl scored a mental age of 9, she would be assigned an IQ of 150 (9/6 × 100). If a 12-year-old boy scored a mental age of 6, he would be given an IQ of 50 (6/12 × 100). The IQ score, as originally computed, expressed a person’s mental age relative to his or her chronological age. Although this formula works adequately for comparing children, it does not work well for adults because intelligence levels off during adulthood. For example, a 40-year-old person who scored the same as the average 20-year-old would have an IQ of only 50.

Modern intelligence tests—including the current Stanford-Binet test—no longer compute scores using the IQ formula. Instead, intelligence tests give a score that reflects how far the person’s performance deviates from the average performance of others who are the same age. Most modern tests arbitrarily define the average score as 100. By convention, many people still use the term IQ to refer to a score on an intelligence test.

D. Creation of group test
During World War I (1914-1918) a group of American psychologists led by Robert M. Yerkes offered to help the United States Army screen recruits using intelligence tests. Yerkes and his colleagues developed two intelligence tests: the Army Alpha exam for literate recruits, and the Army Beta exam for non-English speakers and illiterate recruits. Unlike previous intelligence tests, which required an examiner to test and interact with each person individually, the Army Alpha and Beta exams were administered to large groups of recruits at the same time. The items on the tests consisted of practical, short-answer problems. The Alpha exam included arithmetic problems, tests of practical judgment, tests of general knowledge, synonym-antonym comparisons, number series problems, analogies, and other problems. The Beta exam required recruits to complete mazes, complete pictures with missing elements, recognize patterns in a series, and solve other puzzles. The army assigned letter grades of A through D- based on how many problems the recruit answered correctly. The army considered the highest-scoring recruits as candidates for officer training and rejected the lowest-scoring recruits from military service. By the end of World War I, psychologists had given intelligence tests to approximately 1.7 million recruits. Modern critics have pointed out that the army tests were often improperly administered. For example, different test administrators used different standards to determine which recruits were illiterate and should be assigned to take the nonverbal Beta exam. Thus, some recruits mistakenly assigned to the Alpha exam may have scored poorly because of their limited English skills, not because of low intelligence.

The use of intelligence tests by the United States military enhanced the credibility and visibility of group mental tests. Following World War I these tests grew in popularity. Most were short-answer tests modeled on the army tests or the Stanford-Binet. For example, Yerkes and Terman developed the National Intelligence Test, a group test for schoolchildren, around 1920. The Scholastic Aptitude Test, or SAT, was introduced in 1926 as a multiple-choice exam to aid colleges and universities in their selection of prospective students.

E. Modern intelligence test
The most widely used modern tests of intelligence are the Stanford-Binet, the Wechsler Intelligence Scale for Children (WISC), the Wechsler Adult Intelligence Scale (WAIS), and the Kaufman Assessment Battery for Children (Kaufman-ABC). Each of the tests consists of a series of 10 or more subtests. Subtests are sections of the main test in which all of the items are similar. Examples of subtests include vocabulary (“Define happy”), similarities (“In what way are an apple and pear alike?”), digit span (repeating digit strings of increasing length from memory), information (“Who was the first president of the United States?”), object assembly (putting together puzzles), mazes (tracing a path through a maze), and simple arithmetic problems. Each item has scoring criteria so the examiner can determine if the answer given is correct.

Items on each subtest are given in order of difficulty until the person being tested misses a certain number of items. Each subtest provides a score. The subtest scores are then added together to obtain a total raw score, which is then converted into an IQ score. Some tests, such as the Wechsler tests, give separate verbal and performance (nonverbal) scores as well as an overall score.

Other intelligence tests, like the Peabody Picture Vocabulary Test or Raven’s Progressive Matrices, consist of only one item type. In the Peabody Picture Vocabulary Test, the test taker must define a word by deciding which picture out of four pictures best represents the meaning of the word said by the examiner. In Raven’s Progressive Matrices, a person is shown a matrix of patterns with one pattern missing. The person must figure out the rules governing the patterns and then use these rules to pick the item that best fills in the missing pattern. The Raven’s test was designed to minimize the influence of culture by relying on nonverbal problems that require abstract reasoning and do not require knowledge of a particular culture.

All of the tests mentioned so far can be individually administered. An examiner tests one person at a time for a specific amount of time, ranging from 20 to 90 minutes. There are also group-administered tests. The Army Alpha test described above was one of the earliest group-administered tests. This test developed into what is now known as the Armed Services Vocational Achievement Battery (ASVAB), which is used to select and classify military recruits. Group tests usually are not as reliable as individually administered tests. They are often shorter and have less variety in item types because of restrictions inherent in group administration. Furthermore, the administrator of an individual test can more fully supervise the test taker’s performance. For example, the administrator can make sure the test taker is motivated and provide additional information when necessary. But group tests are efficient because they can be given to large numbers of people in a short time and at a relatively low cost.

Achievement tests and aptitude tests are very similar to intelligence tests. An achievement test is designed to assess what a person has already learned, whereas an aptitude test is designed to predict future performance or assess potential for learning. Usually the items on achievement tests and aptitude tests relate to a specific area of knowledge, such as mathematics or vocabulary. Because intelligence tests frequently include these same areas of knowledge, many experts believe that it is impossible to distinguish between intelligence tests, achievement tests, and aptitude tests. Often, test makers call their tests achievement tests or aptitude tests to avoid the word intelligence, which can be frightening to some test takers. Examples of achievement and aptitude tests that are widely used include the SAT, the Graduate Record Exam (GRE), the California Achievement Test, the Law School Admissions Test (LSAT), and the Medical College Admission Test (MCAT).

F. Standardization, reliabillity, and validity of tests
An intelligence test, like any other psychological test, must meet certain criteria in order to be accepted as scientific and accurate. A test must be standardized, reliable, and valid.

Standardization refers to the process of defining norms of performance to which all test takers are compared. Before an intelligence test can be used to make meaningful comparisons, the test makers first give the test to a sample of the population representative of the individuals for whom the test is designed. This sample of people is called a normative sample, because it is used to establish norms (standards) of performance on the test. Normative samples usually consist of thousands of people from all areas of the country and all strata of society. Test scores of people in the sample are statistically analyzed to compile the test norms. When the test is made available for general use, these norms are used to determine a score for each person who takes the test. The IQ score or overall score reflects how well the person did compared to people of the same age in the normative sample.

Reliability refers to the consistency of test scores. A reliable test yields the same or close to the same score for a person each time it is administered. In addition, alternate forms of the test should produce similar results. By these criteria, modern intelligence tests are highly reliable. In fact, intelligence tests are the most reliable of all psychological tests.

Validity is the extent to which a test predicts what it is designed to predict. Intelligence tests were designed to predict school achievement, and they do that better than they do anything else. For example, IQ scores of elementary school students correlate moderately with their class grades and highly with achievement test scores. IQ tests also predict well the number of years of education that a person completes. The SAT is somewhat less predictive of academic performance in college. Educators note that success in school depends on many other factors besides intelligence, including encouragement from parents and peers, interest, and motivation.

Intelligence tests also correlate with measures of accomplishment other than academic success, such as occupational status, income, job performance, and other measures of vocational success. However, IQ scores do not predict occupational success as well as they predict academic success. Twenty-five percent or less of the individual differences in occupational success are due to IQ. Therefore, a substantial portion of the variability in occupational success—75 percent or more—is due to factors other than intelligence.

Validity also refers to the degree to which a test measures what it is supposed to measure. A valid intelligence test should measure intelligence and not some other capability. However, making a valid intelligence test is not a straightforward task because there is little consensus on a precise definition of intelligence. Lacking such a consensus, test makers usually evaluate validity by determining whether test performance correlates with performance on some other measure assumed to require intelligence, such as achievement in school.
G. Distribution of IQ scores
IQ scores, like many other biological and psychological characteristics, are distributed according to a normal distribution, which forms a normal curve, or bell curve, when plotted on a graph. In a normal distribution, most values fall near the average, and few values fall far above or far below the average. Although raw scores are not exactly normally distributed, test makers derive IQ scores using a formula that forces the scores to conform to the normal distribution. The normal distribution is defined by its mean (average score) and its standard deviation (a measure of how scores are dispersed relative to the mean). Usually the mean of an IQ test is arbitrarily set at 100 with a standard deviation of 15. Other tests use different values. For example, the SAT originally used a mean of 500 and a standard deviation of 100, although these are now recomputed annually.

Because IQs are distributed along a normal curve, a fixed percentage of scores fall between the mean and any standard deviation value. For example, 34 percent of IQ scores fall between the mean and one standard deviation. For a standard IQ distribution with a mean of 100 and a standard deviation of 15, 34 percent of the cases would fall between 100 and 115. Since the normal curve is symmetrical about the mean, 34 percent of the scores would also fall between 85 and 100, which represents one standard deviation below the mean. To interpret the score of any test, it is important to know the mean and standard deviation of the test. Along with knowledge of the standard deviation and the normative sample used for the test, one can then interpret the score in terms of the percentage of the population scoring higher or lower. If a person obtains a score of 115 on an IQ test, approximately 16 percent of the population will score higher and 84 percent will score lower.

When an IQ test is revised, it is restandardized with a new normative sample. The distribution of raw scores in the sample population determines the IQ that will be assigned to the raw scores of others who take the test. By analyzing the performance over the years of different normative samples on the same tests, researchers have concluded that performance on intelligence tests has risen significantly over time. This phenomenon, observed in industrialized countries around the world, is known as the Flynn effect, named after the researcher who discovered it, New Zealand philosopher James Flynn. Scores on some tests have increased dramatically. For example, scores on the Raven’s Progressive Matrices, a widely used intelligence test, increased 15 points in 50 years when scored by the same norms. In other words, a representative sample of the population that took the test in 1992 scored an average of 15 points higher on the test than a representative sample that took the test in 1942.

It appears that people are getting smarter. However, only some tests show these changes. Tests of visual-spatial reasoning, like the Raven’s test, show the largest changes, while vocabulary and verbal tests show almost no change. Some psychologists believe that people are not really getting smarter but are only becoming better test takers. Others believe the score gains reflect real increases in intelligence and speculate they may be due to improved nutrition, better schooling, or even the effects of television and video games on visual-spatial reasoning.

H. Uses of intelligence tests
Intelligence tests and similar tests are widely used in schools, business, government, the military, and medicine. In many cases, intelligence tests are used to avoid the biases more arbitrary methods of selection introduce. For example, it was once common for colleges to admit students whose parents had attended the college or who came from socially prominent families. By using tests, colleges could select students based on their ability instead of their social position.

Intelligence tests were originally designed for use in schools. In elementary and secondary schools, educators use tests to assess how well a student can be expected to perform and to determine if special educational programs are necessary. Intelligence tests can help to identify students with mental retardation and to determine an appropriate educational program for these students (see Education of Students with Mental Retardation). Intelligence tests may also be required for admission into programs for the gifted or talented (see Education of Gifted Students). Institutions of higher education use achievement or aptitude tests, which are very similar to intelligence tests, for the selection and placement of students.

In business, employers frequently use intelligence and aptitude tests to select job applicants. Since World War I, the United States military has had one of the most comprehensive testing programs for selection and job assignment. Anyone entering the military takes a comprehensive battery of tests, including an intelligence test. For specialized and highly skilled jobs in the military, such as jet pilot, the testing is even more rigorous. Intelligence tests are helpful in the selection of individuals for complex jobs requiring advanced skills. The major reason intelligence tests work in job selection is that they predict who will learn new information required for the job. To a lesser extent, they predict who will make “smart” decisions on the job.

In medicine, physicians use intelligence tests to assess the cognitive functioning of patients, such as those with brain damage or degenerative diseases of the nervous system. Psychiatrists and psychologists may use intelligence tests to diagnose the mental capacities of their clients.

I. Criticisms of intelligence tests
Properly used, intelligence tests can provide valuable diagnostic information and insights about intellectual ability that might otherwise be overlooked or ignored. In many circumstances, however, intelligence testing has become extremely controversial, largely because of misunderstandings about how to interpret IQ scores.

1. Validity: One criticism of intelligence tests is that they do not really measure intelligence but only a narrow set of mental capabilities. For example, intelligence tests do not measure wisdom, creativity, common sense, social skills, and practical knowledge—abilities that allow people to adapt well to their surroundings and solve daily problems. The merit of this criticism depends on how one defines intelligence. Some theorists consider wisdom, creativity, and social competence aspects of intelligence, but others do not. Psychologists know little about how to objectively measure these other abilities. Another criticism of IQ tests is that some people may not perform well because they become anxious when taking any timed, standardized test. Their poor performance may reflect their anxiety rather than their true abilities. However, test anxiety is probably not a major cause of incorrect scores.

2. Misintrepretation and misuse: Critics of intelligence testing argue that IQ tests tend to be misinterpreted and misused. Because IQ tests reduce intelligence to a single number, many people mistakenly regard IQ as if it were a fixed, real trait such as height or weight, rather than an abstract concept that was originally designed to predict performance in school. Furthermore, some people view IQ as a measurement of a person’s intrinsic worth or potential, even though many factors other than those measured by IQ tests contribute to life success.

Critics also note that intelligence testing on a large scale can have dangerous social consequences when the results are misused. For example, during the 1920s IQ tests were used to identify “feeble-minded” persons. These persons were then subject to forced sterilization. In the 1927 case Buck v. Bell, the United States Supreme Court upheld the right of states to sterilize individuals judged to be feeble-minded.

In judging the uses of intelligence tests, one must compare how decisions would be made without using the tests. When tests are used to make a decision, there should be evidence that the decision made using the test is better with the test than without it. For example, if schools did not use intelligence or aptitude tests to determine which students need remedial education, teachers would be forced to rely on more subjective and unreliable criteria, such as their personal opinions.

In some cases, institutions use tests when they do not need to. Some colleges and universities require students to take admission tests but then admit 80 percent or more of applicants. Tests are of little use in selection decisions when there is little or no selection. Another criticism of intelligence tests is that they sometimes lead to inflexible cutoff rules. In some states, for example, a person with mental retardation must have an IQ of 50 or below before being allowed to work in a special facility known as a sheltered workshop. Although intelligence is important in determining performance, it is not the only determinant. People with an IQ of 50 vary widely in their skills and abilities. Using an arbitrary cutoff of 50 can make it difficult for people whose IQ is 51 to get essential services.

3. Bias: Psychologists have long known that ethnic and racial groups differ in their average scores on intelligence tests. For example, African Americans as a group consistently average 15 points lower than whites on IQ tests. Such differences between groups have led some people to believe that intelligence tests are culturally biased. Many kinds of test items appear to require specialized information that might be more familiar to some groups than to others. Defenders of IQ tests argue, however, that these same ethnic group differences appear on test items in which cultural content has been reduced.

The question of bias in tests has led intelligence researchers to define bias very precisely and find ways of explicitly assessing it. An intelligence test free of bias should predict academic performance equally well for African Americans, Hispanics, whites, men, women, and any other subgroups in the population. Based on this definition of bias, experts agree that intelligence tests in wide use today have little or no bias for any groups that have been assessed. Many psychologists believe that group differences in performance exist not because of inherent flaws in the tests, but because the tests merely reflect social and educational disadvantages experienced by members of certain racial and ethnic groups in school and other settings. For more information on IQ differences between groups, see the Racial and Ethnic Differences section of this article.

Because they are used for educational and employment testing, tests have been challenged in many court cases. In the 1979 case Larry P. v. Wilson Riles, a group of black parents in California argued that intelligence tests were racially biased. As evidence they cited the fact that black children were disproportionately represented in special education classes. Placement in these classes depended in part on the results of IQ tests. A federal judge hearing the case concluded that the tests were biased and should not be used to place black children in special education. The judge also ordered the state of California to monitor and eliminate disproportionate placement of black children in special education classes. In a 1980 case, PASE v. Hanon, brought in Chicago on the same grounds, a federal judge ruled that the IQ tests being used were not biased (except for a few items). In employment cases, a number of rulings have specified how tests can be used. For example, it is not legal to test applicants for an ability that is not required to do the job.

Scholars have tried to understand the nature of intelligence for many years, but they still do not agree on a single theory or definition. Some theorists try to understand intelligence by analyzing the results of intelligence tests and identifying clusters of abilities. Other theorists believe that intelligence encompasses many abilities not captured by tests. In recent years, some psychologists have tried to explain intelligence from a biological standpoint.
Efforts to explain intelligence began even before Binet and Simon developed the first intelligence test. In the early 1900s British psychologist Charles Spearman made an important observation that has influenced many later theories of intelligence: He noted that all tests of mental ability were positively correlated. Correlation is the degree to which two variables are associated and vary together (see Psychology: Correlational Studies). Spearman found that individuals who scored high on any one of the mental tests he gave tended to score high on all others. Conversely, people who scored low on any one mental test tended to score low on all others.

Spearman reasoned that if all mental tests were positively correlated, there must be a common variable or factor producing the positive correlations. In 1904 Spearman published a major article about intelligence in which he used a statistical method to show that the positive correlations among mental tests resulted from a common underlying factor. His method eventually developed into a more sophisticated statistical technique known as factor analysis. Using factor analysis, it is possible to identify clusters of tests that measure a common ability.

Based on his factor analysis, Spearman proposed that two factors could account for individual differences in scores on mental tests. He called the first factor general intelligence or the general factor, represented as g. According to Spearman, g underlies all intellectual tasks and mental abilities. The g factor represented what all of the mental tests had in common. Scores on all of the tests were positively correlated, Spearman believed, because all of the tests drew on g. The second factor Spearman identified was the specific factor, or s. The specific factor related to whatever unique abilities a particular test required, so it differed from test to test. Spearman and his followers placed much more importance on general intelligence than on the specific factor.

Throughout his life, Spearman argued that g, as he had mathematically defined it using factor analysis, was really what scientists should mean by intelligence. He was also aware that his mathematical definition of general intelligence did not explain what produced g. In the 1920s he suggested that g measured a mental “power” or “energy.” Others who have continued to investigate g speculate that it may relate to neural efficiency, neural speed, or some other basic properties of the brain.
Much of the research on mental abilities that followed Spearman consisted of challenges to his basic position. In the early 20th century, a number of psychologists produced alternatives to Spearman’s two-factor theory by using different methods of factor analysis. These researchers identified group factors, specific abilities thought to underlie particular groups of test items. For example, results from tests of vocabulary and similarities (“How are an apple and orange alike?”) tend to correlate with each other but not with tests of spatial ability. Both the vocabulary and similarities tests contain verbal content, so psychologists might identify a verbal factor based on the correlation between the tests. Although most psychologists agreed that specialized abilities or group factors existed, they debated the number of factors and whether g remained as an overall factor.

In 1938 American psychologist Louis L. Thurstone proposed that intelligence was not one general factor, but a small set of independent factors of equal importance. He called these factors primary mental abilities. To identify these abilities, Thurstone and his wife, Thelma, devised a set of 56 tests. They administered the battery of tests to 240 college students and analyzed the resulting test scores with new methods of factor analysis that Thurstone had devised. Thurstone identified seven primary mental abilities: (1) verbal comprehension, the ability to understand word meanings; (2) verbal fluency, or speed with verbal material, as in making rhymes; (3) number, or arithmetic, ability; (4) memory, the ability to remember words, letters, numbers, and images; (5) perceptual speed, the ability to quickly distinguish visual details and perceive similarities and differences between pictured objects; (6) inductive reasoning, or deriving general ideas and rules from specific information; and (7) spatial visualization, the ability to mentally visualize and manipulate objects in three dimensions.

Others who reanalyzed Thurstone’s results found two problems with his conclusions. First, Thurstone used only college students as subjects in his research. College students perform better on intelligence tests than do individuals in the general population, so Thurstone’s subjects did not represent the full range of intellectual ability. By restricting the range of ability in his sample, he drastically reduced the size of the correlations between tests. These low correlations contributed to his conclusion that no general intelligence factor existed. To understand why restricting the range of ability reduces the size of correlations, consider an analogy. Most people would agree that in basketball, height is important in scoring. But in the National Basketball Association (NBA), the correlation between players’ scoring and heights is zero. The reason is that NBA players are heavily selected for their height and average 15 cm (6 in) taller than the average height in the general population. When Thurstone gave his tests to a more representative sample of the population, he found larger correlations among his tests than he had found using only college students.

A second problem with Thurstone’s results was that, even in college students, the tests that Thurstone used were still correlated. The method of factor analysis that Thurstone had devised made the correlations harder to identify. When other researchers reanalyzed his data using other methods of factor analysis, the correlations became apparent. The researchers concluded that Thurstone’s battery of tests identified the same g factor that Spearman had identified.

In the 1960s American psychologists Raymond Cattell and John Horn applied new methods of factor analysis and concluded there are two kinds of general intelligence: fluid intelligence (gf) and crystallized intelligence (gc). Fluid intelligence represents the biological basis of intelligence. Measures of fluid intelligence, such as speed of reasoning and memory, increase into adulthood and then decline due to the aging process. Crystallized intelligence, on the other hand, is the knowledge and skills obtained through learning and experience. As long as opportunities for learning are available, crystallized intelligence can increase indefinitely during a person’s life. For example, vocabulary knowledge is known to increase in college professors throughout their life span.

In addition to identifying the two subtypes of general intelligence, Cattell also developed what he called investment theory. This theory sought to explain how an investment of biological endowments (fluid intelligence) could contribute to learned skills and knowledge (crystallized intelligence). As one might expect, it is very difficult to separate the biological basis of intelligence from what is learned. As Cattell was aware, nearly all mental tests draw on both crystallized and fluid intelligence. Consequently, crystallized and fluid abilities are correlated with each other. Some researchers interpret this correlation between the two factors as evidence of Spearman’s factor of general intelligence, g. They see Cattell’s theory as a refinement of Spearman’s original theory, not a departure from it.

In 1983 American psychologist Howard Gardner proposed a theory that sought to broaden the traditional definition of intelligence. He felt that the concept of intelligence, as it had been defined by mental tests, did not capture all of the ways humans can excel. Gardner argued that we do not have one underlying general intelligence, but instead have multiple intelligences, each part of an independent system in the brain.

In formulating his theory, Gardner placed less emphasis on explaining the results of mental tests than on accounting for the range of human abilities that exist across cultures. He drew on diverse sources of evidence to determine the number of intelligences in his theory. For example, he examined studies of brain-damaged people who had lost one ability, such as spatial thinking, but retained another, such as language. The fact that two abilities could operate independently of one another suggested the existence of separate intelligences. Gardner also proposed that evidence for multiple intelligences came from prodigies and savants. Prodigies are individuals who show an exceptional talent in a specific area at a young age, but who are normal in other respects. Savants are people who score low on IQ tests—and who may have only limited language or social skills—but demonstrate some remarkable ability, such as extraordinary memory or drawing ability. To Gardner, the presence of certain high-level abilities in the absence of other abilities also suggested the existence of multiple intelligences.

Gardner initially identified seven intelligences and proposed a person who exemplified each one. Linguistic intelligence involves aptitude with speech and language and is exemplified by poet T. S. Eliot. Logical-mathematical intelligence involves the ability to reason abstractly and solve mathematical and logical problems. Physicist Albert Einstein is a good example of this intelligence. Spatial intelligence is used to perceive visual and spatial information and to conceptualize the world in tasks like navigation and in art. Painter Pablo Picasso represents a person of high spatial intelligence. Musical intelligence, the ability to perform and appreciate music, is represented by composer Igor Stravinsky. Bodily-kinesthetic intelligence is the ability to use one’s body or portions of it in various activities, such as dancing, athletics, acting, surgery, and magic. Martha Graham, the famous dancer and choreographer, is a good example of bodily-kinesthetic intelligence. Interpersonal intelligence involves understanding others and acting on that understanding and is exemplified by psychiatrist Sigmund Freud. Intrapersonal intelligence is the ability to understand one’s self and is typified by the leader Mohandas Gandhi. In the late 1990s Gardner added an eighth intelligence to his theory: naturalist intelligence, the ability to recognize and classify plants, animals, and minerals. Naturalist Charles Darwin is an example of this intelligence. According to Gardner, each person has a unique profile of these intelligences, with strengths in some areas and weaknesses in others.

Gardner’s theory found rapid acceptance among educators because it suggests a wider goal than traditional education has adopted. The theory implies that traditional school training may neglect a large portion of human abilities, and that students considered slow by conventional academic measures might excel in other respects. A number of schools have formed with curriculums designed to assess and develop students’ abilities in all of the intelligences Gardner identified.

Critics of the multiple intelligences theory have several objections. First, they argue that Gardner based his ideas more on reasoning and intuition than on empirical studies. They note that there are no tests available to identify or measure the specific intelligences and that the theory largely ignores decades of research that show a tendency for different abilities to correlate—evidence of a general intelligence factor. In addition, critics argue that some of the intelligences Gardner identified, such as musical intelligence and bodily-kinesthetic intelligence, should be regarded simply as talents because they are not usually required to adapt to life demands.

In the 1980s American psychologist Robert Sternberg proposed a theory of intelligence that, like Gardner’s theory of multiple intelligences, attempted to expand the traditional conception of intelligence. Sternberg noted that mental tests are often imperfect predictors of real-world performance or success. People who do well on tests sometimes do not do as well in real-world situations. According to Sternberg’s triarchic (three-part) theory of intelligence, intelligence consists of three main aspects: analytic intelligence, creative intelligence, and practical intelligence. These are not multiple intelligences as in Gardner’s theory, but interrelated parts of a single system. Thus, many psychologists regard Sternberg’s theory as compatible with theories of general intelligence.

Analytic intelligence is the part of Sternberg’s theory that most closely resembles the traditional conception of general intelligence. Analytic intelligence is skill in reasoning, processing information, and solving problems. It involves the ability to analyze, evaluate, judge, and compare. Analytic intelligence draws on basic cognitive processes or components.

Creative intelligence is skill in using past experiences to achieve insight and deal with new situations. People high in creative intelligence are good at combining seemingly unrelated facts to form new ideas. According to Sternberg, traditional intelligence tests do not measure creative intelligence, because it is possible to score high on an IQ test yet have trouble dealing with new situations.

Practical intelligence relates to people’s ability to adapt to, select, and shape their real-world environment. It involves skill in everyday living (“street smarts”) and in adapting to life demands, and reflects a person’s ability to succeed in real-world settings. An example given by Sternberg of practical intelligence is of an employee who loved his job but hated his boss. An executive recruiter contacted the employee about a possible new job. Instead of applying for the job, the employee gave the recruiter the name of his boss, who was subsequently hired away from the company. By getting rid of the boss he hated instead of leaving the job he loved, the employee showed adaptation to his real-world environment. People with high practical intelligence may or may not perform well on standard IQ tests.

In Sternberg’s view, “successfully intelligent” people are aware of their strengths and weaknesses in the three areas of intelligence. They figure out how to capitalize on their strengths, compensate for their weaknesses, and further develop their abilities in order to achieve success in life.

Sternberg’s theory has drawn praise because it attempts to broaden the domain of intelligence to more exactly correspond to what people frequently think intelligence is. On the other hand, some critics believe that scientific studies do not support Sternberg’s proposed triarchic division. For example, some propose that practical intelligence is not a distinct aspect of intelligence, but a set of abilities predicted by general intelligence.

Many researchers have taken new approaches to understanding intelligence based on advances in the neurological, behavioral, and cognitive sciences. Some studies have found that differences in IQ correspond with various neurological measures. For example, adults with higher IQs tend to show somewhat different patterns of electrical activity in the brain than do people with lower IQs. In addition, PET (positron emission tomography) scans show that adults with higher IQs have lower rates of metabolism for cortical glucose as they work on relatively difficult reasoning problems than people with lower IQs. That is, people with higher IQs seem to expend less energy in solving difficult problems than those with lower IQs. Other researchers have sought to understand human intelligence by using the computer as a metaphor for the mind and studying how artificial intelligence computer programs relate to human information processing. These new approaches are extremely promising, but their ultimate value has yet to be determined.

In recent years a number of theorists have proposed the existence of emotional intelligence that is complementary to the type of intelligence measured by IQ tests. American psychologists Peter Salovey and John Mayer, who together introduced the concept in 1990, define emotional intelligence as the ability to perceive, understand, express, and regulate emotions. Emotionally intelligent people can use their emotions to guide thoughts and behavior and can accurately read others’ emotions. Daniel Goleman, an American author and journalist, popularized the concept in his book Emotional Intelligence (1995). He expanded the concept to include general social competence.

An American psychologist, Douglas Detterman, has compared general intelligence to a complex system, like a university, city, or country. In this view, IQ tests provide a global rating reflective of the many cognitive processes and learning experiences that compose intelligence, just as a rating of a university is based on an evaluation of its components, such as library size, faculty quality, and size of endowment. Mental tests tend to correlate with each other because they are part of a unified system that works together. The implication of this theory is that understanding general intelligence will require understanding how the cognitive processes of the brain actually work.

Few topics in the social sciences have produced more controversy than the relative influences of nature and nurture on intelligence. Is intelligence determined primarily by heredity or by one’s environment?

The issue has aroused intense debate because different views on the heritability of intelligence lead to different social and political implications. The strictest adherents of a genetic view of intelligence believe that every person is born with a fixed amount of intelligence. They argue that there is little one can do to improve intelligence, so special education programs should not be expected to produce increases in IQ. On the other hand, those who see intelligence as determined mostly by environmental factors see early intervention programs as critical to compensate for the effects of poverty and other disadvantages. In their view, these programs help to create equal opportunities for all people. Perhaps the most controversial issue surrounding intelligence has been the assertion by some people that genetic factors are responsible not only for differences in IQ between individuals, but also for differences between groups. In this view, genetic factors account for the poorer average performance of certain racial and ethnic groups on IQ tests. Others regard genetic explanations for group differences as scientifically indefensible and view as racist the implication that some racial groups are innately less intelligent than others.

Today, almost all scientists agree that intelligence arises from the influence of both genetic and environmental factors. Careful study is required in order to attribute any influence to either environment or heredity. For example, one measure commonly used to assess a child’s home environment is the number of books in the home. But having many books in the home may be related to the parents’ IQ, because highly intelligent people tend to read more. The child’s intelligence may be due to the parents’ genes or to the number of books in the home. Further, parents may buy more books in response to their child’s genetically influenced intelligence. Which of these possibilities is correct cannot be determined without thorough studies of all the factors involved.
In behavioral genetics, the heritability of a trait refers to the proportion of the trait’s variation within a population that is attributable to genetics. The heritability of intelligence is usually defined as the proportion of the variation in IQ scores that is linked to genetic factors. To estimate the heritability of intelligence, scientists compare the IQs of individuals who have differing degrees of genetic relationship. Scientists have conducted hundreds of studies, involving tens of thousands of participants, that have sought to measure the heritability of intelligence. The generally accepted conclusion from these studies is that genetic factors account for 40 to 80 percent of the variability in intelligence test scores, with most experts settling on a figure of approximately 50 percent. But heritability estimates apply only to populations and not to individuals. Therefore, one can never say what percentage of a specific individual’s intelligence is inherited based on group heritabilities alone.

Although any degree of genetic relationship can and has been studied, studies of twins are particularly informative. Identical twins develop from one egg and are genetically identical to each other. Fraternal twins develop from separate eggs and, like ordinary siblings, have only about half of their genes in common. Comparisons between identical and fraternal twins can be very useful in determining heritability. Scientists have found that the IQ scores of identical twins raised together are remarkably similar to each other, while those of fraternal twins are less similar to each other. This finding suggests a genetic influence in intelligence. Interestingly, fraternal twins’ IQ scores are more similar to each other than those of ordinary siblings, a finding that suggests environmental effects. Some researchers account for the difference by noting that fraternal twins are probably treated more alike than ordinary siblings because they are the same age.

Some of the strongest evidence for genetic influences in intelligence comes from studies of identical twins adopted into different homes early in life and thus raised in different environments. Identical twins are genetically identical, so any differences in their IQ scores must be due entirely to environmental differences and any similarities must be due to genetics. Results from these studies indicate that the IQ scores of identical twins raised apart are highly similar—nearly as similar as those of identical twins raised together. For adoption studies to be valid, placement of twin pairs must be random. If brighter twin pairs are selectively placed in the homes of adoptive parents with higher intelligence, it becomes impossible to separate genetic and environmental influences.

Another way of studying the genetic contribution to intelligence is through adoption studies, in which researchers compare adopted children to their biological and adoptive families. Adopted children have no genetic relationship to their adoptive parents or to their adoptive parents’ biological children. Thus, any similarity in IQ between the adopted children and their adoptive parents or the parents’ biological children must be due to the similarity of the environment they all live in, and not to genetics.

There are two interesting findings from studies of adopted children. First, the IQs of adopted children have only a small relationship to the IQs of their adoptive parents and the parents’ biological children. Second, after the adopted child leaves home, this small relationship becomes smaller. In general, the IQs of adopted children are always more similar to their biological parents’ IQs than to their adoptive parents’ IQs. Further, once they leave the influence of their adoptive home, they become even more similar to their biological parents. Both of these findings suggest the importance of hereditary factors in intelligence.

People sometimes assume that if intelligence is highly heritable, then it cannot be changed or improved through environmental factors. This assumption is incorrect. For example, height has very high heritability, yet average heights have increased in the 20th century among the populations of many industrialized nations, most likely because of improved nutrition and health care. Similarly, performance on IQ tests has increased with each generation (see the Distribution of IQ Scores section of this article), yet few scientists attribute this phenomenon to genetic changes. Thus, many experts believe that improved environments can, to some degree, increase a person’s intelligence.

Some genetic disorders, such as phenylketonuria (PKU) and Down syndrome, may result in mental retardation and low IQ. But evidence for genetic influences should not be interpreted as evidence of a direct connection between genes and intelligence. In PKU, for example, a rare combination of recessive genes sets the stage for a series of biochemical interactions that ultimately results in low IQ. These interactions only occur, however, in the presence of the amino acid phenylalanine. If the disorder is detected early and phenylalanine is withheld from the infant’s diet, then large IQ deficits do not develop.
If genetic influences account for between 40 and 80 percent of the variation in intelligence, then environmental influences account for between 20 and 60 percent of the total variation. Environmental factors comprise all the stimuli a person encounters from conception to death, including food, cultural information, education, and social experiences. Although it is known that environmental factors can be potent forces in shaping intelligence, it is not understood exactly how they contribute to intelligence. In fact, scientists have identified few specific environmental variables that have direct, unambiguous effects on intelligence. Many environmental variables have small effects and differ in their effect on each person, making them difficult to identify.

Schooling is an important factor that affects intelligence. Children who do not attend school or who attend intermittently score more poorly on IQ tests than those who attend regularly, and children who move from low-quality schools to high-quality schools tend to show improvements in IQ. Besides transmitting information to students directly, schools teach problem solving, abstract thinking, and how to sustain attention—all skills required on IQ tests.

Many researchers have investigated whether early intervention programs can prevent the lowered intelligence that may result from poverty or other disadvantaged environments. In the United States, Head Start is a federally funded preschool program for children from families whose income is below the poverty level. Head Start and similar programs in other countries attempt to provide children with activities that might enhance cognitive development, including reading books, learning the alphabet and the numbers, learning the names of colors, drawing, and other activities. These programs often have large initial effects on IQ scores. Children who participate gain as much as 15 IQ points compared to control groups of similar children not in the program. Unfortunately, these gains seem to last only as long as the intervention lasts. When children from these programs enter school, their IQ declines to the level of control groups over a period of several years. This has come to be known as the “fade-out” effect.

Even though early intervention preschool programs do not seem to produce lasting IQ gains, some studies suggest they may have other positive long-term effects. For example, the Consortium for Longitudinal Studies reported that participants are less likely to repeat grades, less likely be placed in remedial classes, and more likely to finish high school than comparable nonparticipants—even though both groups show about the same levels of academic achievement. Preschoolers in early intervention programs may also benefit from improved health and nutrition, and their mothers may sometimes benefit from additional education that the programs provide. Because a substantial portion of the variation in intelligence is due to environmental factors, early intervention programs should be able to produce significant and lasting IQ gains once the specific environmental variables that influence IQ have been identified. Researchers continue to search for the interventions that will increase IQ and, ultimately, academic achievement.

Two environmental variables known to affect intelligence are family size and birth order. Children from smaller families and children who are earlier-born in their families tend to have higher intelligence test scores. These effects, however, are very small and amount to only a few IQ points. They are detectable only when researchers study very large numbers of families.

Although there has been substantial debate about the effects of other environmental variables, certain substances in the prenatal environment may influence later intelligence. For example, some pregnant women who consume large amounts of alcohol give birth to children with fetal alcohol syndrome, a condition marked by physical abnormalities, mental retardation, and behavioral problems. Even exposure to moderate amounts of alcohol may have some negative influence on the development of intelligence, and to date no safe amount of alcohol has been established for pregnant women. Scientists have also discovered that certain substances encountered during infancy or childhood may have negative affects on intelligence. For example, children with high blood levels of lead, as a result of breathing lead-contaminated air or eating scraps of lead-based paint, tend to have lower IQ scores. Prolonged malnutrition during childhood also seems to influence IQ negatively. In each of these cases, a correlation exists between environmental factors and measured intelligence, but one cannot conclude that these factors directly influence intelligence. Other environmental variables in this category include parenting styles and the physical environment of the home.

Although the nature-nurture debate has raged for some time, research points to a conclusion that appeals to common sense: Intelligence is about half due to nature (heredity) and about half due to nurture (environment). The exact mechanisms by which genetic and environmental factors operate remain unknown. Identifying the specific biological and environmental variables that affect intelligence is one of the most important challenges facing researchers in this field.
Are women smarter or are men smarter? Psychologists have studied sex differences in intelligence since the beginning of intelligence testing. The question is a very complicated one, though. One problem is that test makers sometimes eliminate questions that show differences between males and females to eliminate bias from the test. Intelligence tests, therefore, may not show gender differences even if they exist. Even when gender differences have been explicitly studied, they are hard to detect because they tend to be small.

There appear to be no substantial differences between men and women in average IQ. But the distribution of IQ scores is slightly different for men than for women. Men tend to be more heavily represented at the extremes of the IQ distribution. Men are affected by mental retardation more frequently than are women, and they also outnumber women at very high levels of measured intelligence. Women’s scores are more closely clustered around the mean.

Although there are no differences in overall IQ test performance between men and women, there do seem to be differences in some more specialized abilities. Men, on average, perform better on tests of spatial ability than do women. Spatial ability is the ability to visualize spatial relationships and to mentally manipulate objects. The reason for this difference is unknown. Some psychologists speculate that spatial ability evolved more in men because men were historically hunters and required spatial ability to track prey and find their way back from hunting forays. Others believe that the differences result from parents’ different expectations of boys’ and girls’ abilities.

Many studies have examined whether gender differences exist in mathematical ability, but the results have been inconsistent. In 1990 American researchers statistically combined the results of more than 100 studies on gender differences in mathematics using a technique known as meta-analysis. They found no significant differences in the average scores of males and females on math tests. Research also indicates that the average girl’s grades in mathematics courses equal or exceed those of the average boy. Other studies have found that boys and girls perform equally well on math achievement tests during elementary school, but that girls begin to fall behind boys in later years. For example, male high school seniors average about 45 points higher on the math portion of the SAT than do females.

A 1995 study examined the performance of more than 100,000 American adolescents on various mental tests. The study found that on average, females performed slightly better than males on tests of reading comprehension, writing, perceptual speed, and certain memory tasks. Males tended to perform slightly better than girls on tests of mathematics, science, and social studies. In almost all cases, the average sex differences were small.

Are differences in abilities between men and women biologically based or are they due to cultural influences? There is some evidence on both sides. On the biological side, researchers have studied androgenized females, individuals who are genetically female but were exposed to high levels of testosterone, a male hormone, during their gestation. As these individuals grow up, they are culturally identified as female, but they tend to play with “boys’ toys,” like blocks and trucks, and have higher levels of spatial ability than females who were not exposed to high levels of testosterone. Further evidence for a biological basis for spatial gender differences comes from comparisons of the brains of men and women. Even when corrected for body size, males tend to have slightly larger brains than females. Some scientists speculate that this extra brain volume in males may be devoted to spatial ability.

On the cultural side, many social scientists argue that differences in abilities between men and woman arise from society’s different expectations of them and from their different experiences. Girls do not participate as extensively as boys do in cultural activities thought to increase spatial and mathematical ability. As children, girls are expected to play with dolls and other toys that develop verbal and social skills while boys play with blocks, video games, and other toys that encourage spatial visualization. Later, during adolescence, girls take fewer math and science courses than boys, perhaps because of stereotypes of math and science as masculine subjects and because of less encouragement from teachers, peers, and parents. Many social scientists believe cultural influences account for the relatively low representation of women in the fields of mathematics, engineering, and the physical sciences.

It is important to remember that sex differences, where they exist, represent average differences between men and women as groups, not individuals. Knowing whether an individual is female or male reveals little about that person’s intellectual abilities.

Numerous studies have found differences in measured IQ between different self-identified racial and ethnic groups. For example, many studies have shown that there is about a 15-point IQ difference between African Americans and whites, in favor of whites. The mean scores of IQ scores of the various Hispanic American subgroups fall roughly midway between those for blacks and whites. Although these differences are substantial, there are much larger differences between people within each group than between the means of the groups. This large variability within groups means that a person’s racial or ethnic identification cannot be used to infer his or her intelligence.

The debate about racial and ethnic differences in IQ scores is not about if the differences exist but what causes them. In 1969 Arthur Jensen, a psychology professor at the University of California at Berkeley, ignited the modern debate over racial differences. Jensen published a controversial article in which he argued that black-white differences in IQ scores might be due to genetic factors. Further, he argued that if IQ had a substantial genetic component, remedial education programs to improve IQ should not be expected to raise IQ as they were currently being applied. In 1994 American psychologist Richard Herrnstein and American social analyst Charles Murray renewed the debate with the publication of The Bell Curve (1994). Although only a small portion of the book was devoted to race differences, that portion of the book received the most attention in the popular press. Among other arguments, Herrnstein and Murray suggested it was possible that at least some of the racial differences in average IQ were due to genetic factors. Their arguments provoked heated debates in academic communities and among the general public.

As discussed earlier, research supports the idea that differences in measured intelligence between individuals are partly due to genetic factors. However, psychologists agree that this conclusion does not imply that genetic factors contribute to differences between groups. No one knows exactly what causes racial and ethnic differences in IQ scores. Some scientists maintain that these differences are in part genetically based. Supporters of this view believe that racial and ethnic groups score differently on intelligence tests partly because of genetic differences between the groups. Others think the cause is entirely environmental. In this view, certain racial and ethnic groups do poorer on IQ tests because of cultural and social factors that put them at a disadvantage, such as poverty, less access to good education, and prejudicial attitudes that interfere with learning. Representing another perspective, many anthropologists reject the concept of biological race, arguing that races are socially constructed categories with little scientific basis (see Race). Because of disagreements about the origins of group differences in average IQ, conclusions about these differences must be evaluated cautiously.

Some research indicates that the black-white differential in IQ scores might be narrowing. Several studies have found that the difference in average IQ scores between African Americans and whites has shrunk to 10 points or less, although research has not established this trend clearly. The National Assessment of Educational Progress, a national longitudinal study of academic achievement, also shows that the performance of African Americans on math and science achievement tests improved between 1970 and 1996 when compared to whites.

Educators and researchers have focused much attention on explaining why some ethnic groups perform more poorly than others on measures of intelligence and academic achievement. Another topic of research is why some ethnic groups, particularly Asian Americans, perform so well academically. Compared to other groups, Asian American students get better grades, score higher on math achievement and aptitude tests, and are more likely to graduate from high school and college. The exact reasons for their high academic performance are unknown. One explanation points to Asian cultural values and family practices that place central importance on academic achievement and link success in school with later occupational success. Critics counter that this explanation does not explain why Asian Americans excel in specific kinds of abilities.

The academic and occupational successes of Asian Americans have caused many people to presume Asian Americans have higher-than-average IQs. However, most studies show no difference between the average IQ of Asian Americans and that of the general population. Some studies of Asians in Asia have found a 3 to 7 point IQ difference between Asians and whites, in favor of Asians, but other studies have found no significant differences.


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