Intelligence: An Overview
This entry covers intelligence and intelligence testing. Intelligence is a difficult and often misused concept that has had an important impact on education. The entry will first review the definition and history of the concept of intelligence. Descriptions of the critical issues of measurement and application of the concept are then addressed. Intelligence tests commonly used in the schools are also described. Ways that tests are used in academic settings are covered with a short description of the qualifications for those who use the tests. Finally research trends and the emerging changes in the development of the concept of intelligence are addressed.
The specific meaning of intelligence in terms of how the concept is applied in education and schooling is difficult to convey. Everyone thinks they know intelligent performance when they see it, but when they try to define it, the elusive-ness of the trait becomes apparent (Sternberg, Grigorenko, & Kidd, 2005). As Wagner (2000) has pointed out, definitions of intelligence have been notoriously inconsistent over the last century. Early definitions have tended to focus on specific or general abilities. For example, the work of Charles Spearman (1863–1945) over a century ago emphasized general ability (sometimes referred to as g) that involved recognition of relationships (e.g., Spearman, 1904), and intelligent activity involved combining this g with specific abilities. Alfred Binet (1857–1911) and Théodore Simon (1872–1961), working at around the same time, defined intelligence as “judgment, otherwise called good sense, practical sense, initiative, the faculty of adapting one's self to circumstances. To judge well, to comprehend well, to reason well, these are the essential activities of intelligence” (Binet & Simon, 1905, p. 43). Lewis Terman (1877–1956), largely credited for bringing intelligence testing into U.S. schools and developing the first versions of the Stanford-Binet Intelligence Test, emphasized knowledge and abstract thinking in defining intelligence (Aiken, 2003, Hegarty, 2007, Terman, 1918). The definition provided by David Wechsler (1896– 1981) was “The aggregate or global capacity of the individual to act purposefully, to think rationally and to deal effectively with his environment” (Wechsler, 1958, p. 7).
Most of these definitions seemed to have an orientation to academic learning and performance. More recent definitions have been moving toward practical definitions with a view toward how the person functions in the real world as well as in traditional academic settings (Wagner, 2000). For example, in their 1998 book, Eleanor Amour-Thomas and Sharon-Ann Gopaul-McNichol have suggested the importance of a relativistic definition that recognized the significance of the interaction between the biological nature of the individual and the cultural and environmental context surrounding the person. Howard Gardner conceived intelligence as “a biopsycho-logical potential to process information in certain ways, in order to solve problems or fashion products that are valued in a culture or community” (cited in Shearer, 2004, p. 3). Gardner saw intelligent behavior as related to specific kinds of functioning in the real world. Another of the more contemporary theorists, Robert Sternberg, defined intelligence from the perspective of research in cognitive information processing. His approach to intelligence implies successful performance in the real world and depends on an understanding of research in the ways in which the brain might work to produce intelligent behavior such as problem solving, adapting and learning. His theory is organized into three subtheories that address analytical, practical, and creative aspects of intelligent performance (Sternberg, 1994: Sternberg, Castejón, Prieto, Hautamäki, & Grigorenko, 2001). While many more definitions and approaches can be cited, they generally suggest that definitions of intelligence involve ability to learn, problem solve, and adapt. Further, later definitions move away from the notion of a unitary concept such as g to one that involves creativity, personal characteristics and traits, attention to the nature of the task or problem being addressed, the research on the brain and function, and environmental adaptation (Sternberg, Griegorenko, & Kidd, 2005; Sattler, 2001; Shearer, 2004).
Although many claim that intelligence is defined by what intelligence tests measure, many other theorists and researchers argue that this definition is too circular and narrow. Scores on intelligence tests are designed to reflect the definitions of intelligence rather than serve as the definition of intelligence (Gardner, Kornhaber, & Wake,1996), or an exact and unqualified representation of intellectual ability.
Interest in intelligence in some form has a long history. The Greek philosopher Aristotle (384–322 BCE) studied memory, logical thought, and what knowing means well before the mid- to late 19th-century investigations of the herit-ability of intelligence by Francis Galton (1822–1911) took place in England. Galton, considered one of the first scientific investigators of human intelligence, devised an array of simple tests covering an assortment of mental processes involving memory, senses, and motor behavior which he administered to a large sample of people. Performance was analyzed using statistical methods. These efforts are widely considered the beginning of the mental testing movement (Brennan, 2003). Binet, who was working in France at about the same time as Galton was doing his research, was more focused on mental processes such as the ability to adapt, comprehend, and reason. The idea of public education for the masses had just taken hold and schools were compelled to deal with much more widely divergent abilities and behavior in children than was the case with the more privileged group that had previously attended school. Binet was asked by the French Ministry of Public Instruction to help identify the children who would be successful in school and those who would not (Gardner, Kornhaber, & Wake, 1996). Binet responded with a test for this purpose (Binet & Simon, 1905).
The concept of individual differences was gaining popularity around the world at the same time as Binet's work, spurred by the movement towards universal compulsory education in many countries. At the time, many psychologists were addressing the problem of how to identify children who would have success in education (Thorndike, 1990). In the United States, a number of psychologists, including Edward L. Thorndike (1874–1949) were addressing the problem. Thorndike, working at Teachers College of Columbia University, was central to the development of American and behavioral psychology and was very influential on American education practice (Brennan, 2003). Thorndike emphasized a neural basis of intelligence and felt that education should take advantage of natural intelligence and promote its development (Thorndike, 1990). Henry Goddard (1866–1957) translated the Binet scales and began experimenting with them. Terman standardized and normed the Binet test on California schoolchildren. He also added a concept developed by another psychologist, William Stern (1871–1938), which became the well-known Intelligence Quotient (IQ score). Originally the Binet tests yielded only a mental age, but Stern proposed dividing the mental age by the child's chronological age and multiplying by 100. Thus a child with a mental age score of 10 years, 6 months who is 9 years, 6 months old would have an IQ of 111 (i.e., MA/CA X 100 = (127 months)/(114 months) X 100 = 111) (Thorndike, 1990). A child with a score of 111 would be said to be performing above other children of the same age. A child whose mental age and chronological ages were the same would have an IQ of 100 and would be considered of average intelligence for the child's age.
Modern IQ tests use a scaling method based on the normal curve to compute the IQ score. This scaling method, known as deviation IQ, permits the test user to interpret a person's IQ score in terms of the proportion of people in the normative sample that had scores above and below the person's obtained score. This innovation was developed by Wechsler (1939) principally because the concept of mental age seemed inappropriate to use with adults. That is, intelligence tests of the time were designed with the assumption that a person's intelligence developed until the around the age of 20, at which time mature adult intelligence had been attained. Therefore the highest mental age that could be attained on a test was 20. However, Wechsler took the view that chronological age should be a predictor of mental age. This would not be the case if chronological age was increasing while mental age was not (Thorndike, 1990).
Early intelligence theory emerged from an emphasis on a unitary concept of general ability, as can be seen in the definitions of Binet and Spearman. Spearman created a statistical technique called factor analysis to explore his approach. From his studies with this technique, he was able to report that about half of the variance in tests of mental ability was due to the general (g) factor (Kaplan & Sacuzzo, 2001). The remainder was due to the special ability (e.g., numerical reasoning, vocabulary, mechanical skill) that was required of a person to enable performance of the specific tasks on the test. Later approaches tended to emphasize expanded abilities. For example, Cattell divided g into fluid (gf) and crystallized (gc) intelligence (Horn & Cattell, 1966; Horn & Noll, 1997). Fluid intelligence encompasses abilities involved in thinking, reasoning, and in learning, while crystallized intelligence represents the knowledge and broader understanding that has developed through learning in the environmental setting.
Other theories further recognized the diversity of intelligent performance. In his 1967 book Joy Paul Guil-ford (1897–1987), using factor analysis, devised a model of intelligence he termed the Structure of Intellect in which he proposed three aspects of intelligence: operations, products, and contents. Each of these is broken down further into specific kinds of intellectual activity which Guilford considered interrelated to produce intelligent functioning of specific tasks.
Gardner (1993) proposed a theory of multiple intelligences based on the differential cognitive processing required for demonstration of intelligent or creative performance in different areas. Gardner's theory references eight intelligences. Linguistic and logico-mathematical intelligences are most often associated with academic performance, although others could be relevant depending on the task (Shearer, 2004). Other intelligences identified by Gardner were musical, kinesthetic, spatial, naturalistic, and personal (intrapersonal and interpersonal).
Robert Sternberg also proposed a theory informed by research from cognitive psychology. Sternberg's model is named the triarchic theory of intelligence because it is composed of three kinds of components: memory-analytic, creative-synthetic, and practical-contextual. The first component is related to the academic view of intelligence and is most similar to what most intelligence tests measure. The second component is necessary for creative endeavors, including traditionally academic areas such as science and mathematics. Finally, the practical-contextual is necessary for success in an everyday environment like school or business (Sternberg, 1994). Daniel Golman (1995) has proposed an emotional intelligence that bears some similarity to the personal intelligences of Gardner and the practical intelligence of Sternberg, but goes further in tying emotion and personality to the capacity for intelligent behavior. For example, fear, excitement, or anger may contribute to how one behaves regardless of one's knowledge or capacity to reason.
In the first half of the 20th century, research in intelligence was heavily influenced by factor analysis (first used by Spearman). Factor analysis is a statistical procedure that enables the systematic study of the relationships within a set of variables in order to find the common aspects. Research and theory emerging in the second half of the 20th into the 21st century has begun to have an impact on the methods of assessment of intelligence (Gardner, et al., 1996). For example, research in cognitive psychology, neuro-psychology, cognitive science (Kolak, Hirstein, Mandik, & Waskan 2006), biopsychology and evolutionary processes (Geary, 2005), and cultural psychology (Armour-Thomas and Gopaul-McNicol, 1998) has begun to affect theory and research in intelligence, its measurement and applications.
Two kinds of intelligence tests will be presented here. The first, group tests, are used to identify the range of IQ scores in a group, usually for research or administrative purposes. Group tests tend to have more specific content and question formats, and are designed for more specific purposes than individually administered tests, which aim for a relatively more comprehensive clinical picture of the individual's cognitive functioning. The individual tests are designed to provide much more information about the individual. They are only used by professionals who are trained and licensed to administer and interpret these assessment instruments as part of a comprehensive clinical assessment that contributes information useful for planning educational or therapeutic interventions. These tests provide a variety of scores and clinical information that licensed professional psychologists may use to plan interventions in schools, family, or other settings. In other words, the usefulness of individual intelligence tests goes well beyond the scores on the test. For this reason, group tests are not suitable substitutes for individual assessments when planning clinical or educational interventions.
Group Tests of Intelligence. Two examples of group intelligence test are discussed here. The Cognitive Abilities Test (Multilevel Edition, Form 6 [CogAT-6]) (Lohman 2001), and the Multidimensional Aptitude Battery, Second Edition (MAB-II) (Jackson, 1998) were chosen because they may be used in school or educational settings.
The Multidimensional Aptitude Battery-II (MAB-II) is a multiple-choice assessment of aptitude and intelligence that can be administered to groups or individuals above the age of 16. The instrument was designed to obtain scores similar to that of the individually administered Wechsler Adult Intelligence Scale-Revised (WAIS-R) in a group, as opposed to individual administration. The MAB-II produces composite scores: Verbal Scale (Information, Comprehension, Arithmetic, Similarities, Vocabulary), Performance Scale (Digit Symbol, Picture Completion, Spatial, Picture Arrangement, and Object Assembly) and Full Scale. The test can be pencil and paper or computer-administered.
The MAB-II is considered to be a useful tool for assessing cognitive abilities when large numbers of students must be screened. It is a well-developed and empirically sound instrument that provides correlations between subtest scores and occupational strengths (Thompson, 2003). The test can be administered by a proctor, rather than by a post-master's-level professional. As a result, the MAB-II should not be used for making clinical diagnoses about intelligence (Widaman, 2003). Additionally, MAB-II should not be administered to students with a learning disability related to reading comprehension or whose reading level is below ninth grade because the test relies on the test-takers' reading ability (Thompson, 2003).
The Cognitive Abilities Test—Multilevel Edition, Form 6 (CogAT-6) is one of the more widely used group ability tests for students in kindergarten through 12th grades. The test is intended to guide instruction to match the cognitive abilities and needs of each student, to provide an “alternative” measure of cognitive development, and to identify achievement-ability discrepancies. The test has a multitheoretical foundation as it is based on Vernon's model of hierarchical abilities, Cattell's model of crystallized and fluid abilities, and Carroll's work specifically on general abstract reasoning. The CogAT-6 is composed of two editions: the Primary and Multilevel Editions, both of which are intended to assess reasoning and problem-solving abilities and can be broken down into Verbal, Nonverbal, and Quantitative Batteries. The Primary Edition is designed for students in K–2nd grade and consists of six subtests. The Multilevel Edition is a nine-subtest instrument that is based on the Lorge-Thorndike Intelligence Tests (Lorge & Thorndike, 1954) and is appropriate for students in 3rd to12th grade. The CogAT-6 has a mean of 100 and standard deviation of 16.
DiPerna's 2005 review of the CogAT-6 suggested that the strengths of the test include a large, representative standardization sample, co-norming with the Iowa Tests, and a theoretical basis. In spite of these positive attributes, significant weaknesses were cited relative to the CogAT's purposes as described earlier. Criticisms included insufficient empirical evidence to support basing instructional recommendations on test results, a lack of reliability and predictive validity to measure cognitive ability and to predict cognitive ability-achievement discrepancies.
Individual Intelligence Tests. The following individual intelligence tests will be reviewed:
- Wechsler Intelligence Scale for Children-IV (WISC-IV)
- Woodcock-Johnson Tests of Cognitive Abilities-III (WJ COG III)
- Stanford-Binet Intelligence Scales, Fifth Edition (SB5)
- Das-Naglieri Cognitive Assessment System (CAS)
- Kaufman Assessment Battery for Children (K-ABC)
The Wechsler scales continue to be the most widely utilized individually administered tests of intelligence (Flanagan & Kaufman, 2004). As previously discussed, the Wechsler tests are based on the g factor or the “overall capacity of the individual to act purposefully, to think rationally, and to deal effectively with the environment” (Sternberg, 2000, p. 481) The Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV) is the current revision of the Wechsler scales for children 6.0 to 16.11 years of age. The WISC-IV comprises 15 sub-tests (5 of which are supplemental). Scores on these tasks contribute to the four composite indices (Verbal Comprehension, Perceptual Reasoning, Working Memory, and Processing Speed) in addition to a Full Scale IQ (FSIQ) score that can range from 40 (very low) to160 (very high), with a mean of 100 representing the average score, and a standard deviation of 15. A profile of the test taker's learning strengths and weaknesses are derived from the test performance. The FSIQ is derived from a combination of all subtest scores and is considered the most representative estimate of global intellectual functioning. However, when large discrepancies between Index scores exist, the FSIQ can be invalid and misleading. In this case, it is most helpful to describe the strengths and weaknesses in the profile and de-emphasize the FSIQ.
The WISC-IV continues to be a reliable and valid instrument. WISC-IV scores can be interpreted in combination with Wechsler Individual Achievement Test, Second Edition (WIAT-II) scores for comparisons between ability and achievement. Flanagan and Kaufman (2004) provide an extensive description of the strengths and limitations of this assessment tool. They cite the WISC-IV's most significant strengths as being “a robust four-factor structure across the age range of the test, increased developmental appropriateness, de-emphasis on time, improved psychometric properties, and an exemplary standardization sample (p. 171).” Flanagan & Kaufman (2004) indicate that none of the WISC-IV's limitations are very serious, although they suggest ways in which its validity could be improved.
Other Weschler scales have been developed to assess IQ for young children and adults. The Wechsler Preschool and Primary Scale of Intelligence, Third Edition (WPPSI-III) (Harcourt Assessment, 2002) can be administered to children 2.6–7.3 years old and the Wechsler and the Wechsler Adult Intelligence Scale, Third Edition (WAIS-III) (Harcourt Assessment, 1997) is given to adults between 16 and 89 years of age.
The Woodcock-Johnson Tests of Cognitive Abilities-III (WJ COG III) is also widely used instrument in school settings. The WJ COG III is often administered as the examiner's second choice, if the age-appropriate Wechsler scale has been administered less than three years from the current assessment date. The WJ COG III is based on Catell, Horn, and Carroll's (CHC) concept of intelligence (Reynolds, Keith, Fine, Fisher & Low 2007). The WJ COG III has been normed on individuals age 2 through 90+. The standard battery includes 10 tests, while the extended battery consists of 20. Based on these scores, the examinee earns three Cluster Scores (Verbal Ability, Thinking Ability, and Cognitive Efficiency) and a General Intellectual Ability (GIA) score. Test scores in the standard and extended batteries are not weighted equally when the GIA score is computed.
The WJ COG III has high technical quality and is based on a well-respected theory of cognitive abilities (Schrank, Flanagan, Woodcock, & Mascolo, 2002). It assesses cognitive abilities for a wide age range and uses sophisticated scoring procedures to calculate scores and discrepancies (Sattler, 2001). Additionally, ability and achievement discrepancy norms are provided as the WJ COG III was co-normed with the Woodcock Johnson Tests of Achievement, Third Edition (WJ ACH III). Greater evidence is necessary to understand the utility of the clinical clusters (Schrank, Flanagan, Woodcock, & Mascolo, 2002). The WJ COG III may also overestimate abilities if interpreted incorrectly. For example, the Written Language test score emphasizes one's ability to write brief sentences rather than to develop and organize paragraphs.
The Stanford-Binet Intelligence Scales, Fifth Edition (SB5), a direct descendent of Terman's adaptation of the Binet test developed more than 100 years ago, is used occasionally in the educational setting. The SB5 is based on the CHC theory of intelligence. It is designed for assessing intelligence and cognitive abilities among individuals between the ages of 2 and 85+. The SB5 consists of ten subtests and these scores are used to calculate four composite scores: factor, domain, abbreviated, and full scale (score range 40–160, mean = 100, SD = 15). The five factors measured include Fluid Reasoning, Knowledge, Quantitative Reasoning, Visual-Spatial Reasoning, and Working Memory, each with verbal and nonverbal components. The SB5 contains two domain scales: Nonverbal IQ (NVIQ) and Verbal IQ (VIQ). An Abbreviated Battery IQ (ABIQ) can be determined with two routing subtest scores and the Full Scale IQ (FSIQ) is calculated using all 10 subtests.
The SB5 is advantageous as it is emphasizes both verbal and nonverbal abilities. The instrument is technically sound, according to Johnson and D'Amato (2005), although Kush's 2005 study cites technical limitations (e.g., lower stability for young children and individuals with low cognitive abilities, problematically high correlations with achievement, uncertain factor structure). In spite of these weaknesses, the SB5 is referred to as an outstanding measurement instrument for the assessment of cognitive abilities of children, adolescents, and adults (Johnson & D'Amato, 2005; Kush, 2005).
The Das-Naglieri Cognitive Abilities System (CAS) is a tool based on Luria's cognitive processing model that is intermittently used to evaluate cognitive abilities in schools. The CAS is useful for assessing Planning, Attention, Simultaneous, and Successive (PASS) abilities among students between the ages of 5.0 and 17.11. The instrument's basic battery comprises 8 subtests and the standard battery consists of 12 subtests.
The CAS is an innovative instrument and its development meets high standards of technical adequacy (Meikamp, 2003). When compared to other individually administered general ability tests, it takes less time to administer (Thompson, 2003). Additional empirical research must be completed to support the PASS construct. Factor analyses of subtests support both a 4-factor PASS model as well as a 3-factor model, which suggests that Planning and Attention may or may not be separate factors. (Thompson, 2003).
The Kaufman Assessment Battery for Children, Second Edition (KABC-II) is occasionally utilized in schools as a culture-fair assessment of cognitive abilities for students between the ages of 3 and 18. The KABC-II is based on a dual theoretical framework, Luria's neuropsycholog-ical model (Naglieri, 1998) and the CHC approach. The authors suggest that its multitheoretical base allows the examiner to select which model is most appropriate for interpretation of results depending on the culture and/or verbal skills of the examinee. This assessment instrument contains 20 subtests that contribute to 4 scale scores (Sequential Processing, Simultaneous Processing, Planning, Learning, and Knowledge). The KABC-II has a mean of 100 and standard deviation of 15.
The KABC-II is an acceptable option for measuring cognitive abilities as it provides a reasonable, well-normed, clinically appealing, and technically sound approach to measuring cognitive abilities and generating diagnoses (Braden, 2005). Other strengths of the KABC-II include smaller score discrepancies between ethnic groups and the ability to compare ability and achievement differences with the Kaufman Test of Educational Achievement, Second Edition, Comprehensive Form. However, it has been criticized for the suggestion that examiners can select the model (Luria or CHC) by which to interpret results. Braden (2005) and Thorndike (2005) suggest that the interchangeability of theoretical models is inappropriate and illogical.
Intelligence testing should not be conducted in a vacuum. In addition to using previously mentioned norm-referenced tests, an assessment should include a variety of other data from a multitude of informants. Sattler (2001) suggests that norm-referenced testing should be accompanied by interviews with a parent, teacher, and student; observations of the student during both the formal testing and natural environment (e.g., classroom, lunchroom, playground); and informal assessment procedures (e.g., district-wide criterion-referenced tests, school records). Such an assessment will provide the most accurate information by which educators can most effectively serve the student.
Group versus Individual Intelligence Tests. Whereas group-administered IQ tests can be very well constructed (Aiken 2003) and can provide valid and reliable information suitable for certain non-clinical applications, they do not provide the same kind of information as individual tests and should not be used for the same purposes. One reason is that group tests primarily emphasize multiple-choice question format, whereas individually administered tests provide a variety of response formats across the test. This allows clinicians to gather considerable clinically useful information about the person being tested, such as the approaches used in problem solving, quality of verbal expression, and other observational data (Domino 2000; Sattler 2001). Group tests were not designed to be used for clinical purposes and therefore should not be utilized in clinical settings or to substitute for individually administered intelligence tests for designing clinical interventions or individual educational programs (IEPs) in school settings.
Individual intelligence tests are designed to be administered by highly trained professionals who interpret data through the lens of learning, cognition, emotion, language, culture, health, and development. The one-on-one setting provides advantages to the test-taker and the examiner. First, it allows the examiner to develop rapport with the test-taker, which can benefit the shy or anxious test-taker. Second, the examiner has the opportunity to observe important test-taking behavior such as impulsiveness, compulsiveness, confidence, anxiety, and wandering attention. which may vary according to the task and contribute to the interpretation of the performance on the test. Third, the examiner can observe specific problem-solving approaches, which may also vary with the task. The integration of these observations with test scores allows the examiner to take a holistic approach in interpreting scores and developing interventions.
Individual intelligence tests are used in schools and other educational settings to provide information about children's and adolescents' ability to express themselves, reason and problem solve, and perform on a variety of tasks. This information can be used to design programs for children with special needs or gifts in academic areas. Despite their shortcomings, intelligence tests are considered useful for identifying children for advanced programs for gifted learners (Pyryt, 1996). These tests also play an especially important role in special education. They can be useful for identifying an expected level of academic performance and also in helping school professionals design individual educational programs (IEP) for students with special needs (Sattler, 2001). However, Kim (2005) found in a meta-analysis of 21 studies that IQ tests are not effective for use in identifying students with special talents.
Research in intelligence is active and robust, and this section surveys the spectrum of investigations of intelligence related to school learning and performance. One active area of research is on the tests of intelligence themselves. Specifically, confirmatory factor analysis, a procedure for statistically examining the fit of data from a test to a hypothesized model, is being increasingly utilized to determine whether the theories and models of intelligence underlying tests is verifiable from performance on the test. For example, confirmatory factor analysis was used to verify the structure of the Kaufman Assessment Battery for Children, Second Edition, and the fit of the performance data to the Cattell-Horn-Carroll model of intelligence (Reynolds, Keith, Fine, Fisher, & Low, 2007). The technique was also used successfully to verify the factor structure of Sternberg's Triarchic Abilities Test Level-H (STAT) (Sternberg, Cas-tejón, Prieto, Hautamäki, & Grigorenk, 2001). A related collection of research is directed at investigating the underlying theories and models of intelligence that have been proposed. Most of this research bases hypotheses and research questions on recent research in fields such as cognitive science, neuroscience, emotion, cultural psychology. An example of this kind of research is provided by Visser and her colleagues. Their research compared performance on tests of the components of Gardner's multiple intelligence theory with people's estimates of their own ability and found only modest significant relationships between estimated and measured abilities, and that people tended to overestimate their abilities (Visser, Ashton, & Vernon, 2008).
Research has shown that IQ scores seem to be trending upward (Flynn, 1984). The research has moved from documentation of the phenomenon across countries and cultures (Flynn, 1987; Daley, Whaley, Sigman, Espinosa, & Neumann, 2003), into investigations of whether people are truly becoming more intelligent or whether other explanations seem more plausible in explaining the phenomenon (Rodgers & Wänström, 2007). Some evidence has been provided that increase in measured IQ seems more related to areas considered more reflective of fluid rather than crystallized intelligence performance, such as mathematics test performance (Dickens & Flynn, 2001; Rodgers & Wänström, 2007).
The importance of cultural context in relation to intelligence cannot be minimized (Benson, 2003; Sternberg, 2004). The early definitions of intelligence were tied directly to school performance but have become more encompassing to include culture, language, social class, and related issues. For example, Sternberg's definition emphasizes success in life (Sternberg, 2004). However, a difficulty emerges in determining the standard criteria to use for this kind of intelligence (Benson, 2003). In primitive society, success might be simply be survival. Traditional IQ tests have long been considered culturally unfair because diverse groups such as those of Hispanic origin, African Americans, and Native Americans have not scored as well on them as White groups (Dickens & Flynn, 2006; Rushton & Jensen, 2006; Sternberg, Grigorenko, & Kidd, 2005). The discrepancy between Black and White Americans' test performance has been used to suggest a genetic determinant of IQ, a view has been attacked as unscientific and simplistic (Cooper, 2005; Cronshaw, Hamilton, Onyura & Wilson, 2006; Sternberg, Grigorenko, & Kidd, 2005). Recent research has shown the gap between Whites and Blacks narrowing (Dickens & Flynn, 2006).
The relationship between intelligence test performance and academic performance is well documented (Brody, 1997; Haywood, 2004; Sattler, 2001). Gagne and St. Pére (2002) found no significant relationship between motivation and IQ scores, and that IQ scores seemed to be even more related to achievement than motivation scores. Other studies have revealed strong relationship between IQ and academic performance. For example, in their 2007 study, Lynn and Mikk found significant relationships between IQ and academic performance in math and science among 10-year-olds in 25 countries and 14-year-olds in 46 countries. Barber (2005) reported significant relationships between literacy and having completed secondary education (among other variables) in 81 countries. Considerable research suggests that one of the factors underlying the relationship between IQ and performance in academic subjects is mental processing speed (Luo, Thompson & Detterman, 2003). Sheppard's 2008 review of 172 studies of intelligence and the speed of information processing concluded that measures of intelligence and speed of mental processing are highly correlated, and males and females are faster on different types of speeded tasks.
This brief summary of the research relevant to theory and practice in intelligence shows that the field is active and dynamic. Also, it should be evident that intelligence researchers of the 21st century are addressing a broader, more complete concept of intelligence than was evident in the previous century. As related research in biology of the mind, emotion, neuropsychology, family dynamics, and cognitive processing progresses to new findings, these results will be incorporated into increasingly useful models and theories of the workings of intelligence and how to assess them.
Intelligence has been a useful concept for planning education for over a century. It is a difficult concept to define. Aspects of the definition that seem to have wide appeal include learning speed, adaptability, and ability to perform successfully. Group intelligence tests can be useful in research, or for assessing groups of students. They are not useful as a replacement for individual intelligence tests administered by qualified examiners in assessing for individual clinical or educational intervention. The Wechsler tests are among the most widely used instruments for assessing intelligence. Further, IQ score is a necessarily incomplete reflection of intelligence. It is far from perfect as an index of a person's total intellectual ability and is not useful in identifying specific talents. Cognitive and brain research has begun to impact theories of intelligence in important ways. Other areas that have impacted the field of intelligence are language, culture, biology, and the neurosciences. Recent theories of intelligence are emphasizing more than one unitary ability.
See also:Intelligence Testing
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