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Theoretical and academic definitions of intelligence may not be as useful in clinical and therapeutic applications. For example, The clinical situation presented by those with borderline intellectual and adaptive functioning requires comprehensive analysis of all diagnostic, testing,educational placement, and psychosocial factors. This has been addressed in both the 8th (2005) and 9th (2009) editions of ''Kaplan & Sadock's Comprehensive Textbook of Psychiatry'' by Yale child psychiatrist Frank John Ninivaggi. MD. |
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==Theories of intelligence== |
==Theories of intelligence== |
Revision as of 11:59, 11 July 2009
- For "active intelligence" and its collection, see Intelligence (information gathering) and Espionage. For other uses, see Intelligence (disambiguation).
- "Intellect" redirects here. For other uses, see Intellect (disambiguation).
- "Human intelligence" redirects here. For human intelligence (HUMINT) in military and espionage contexts, see HUMINT.
Intelligence is an umbrella term used to describe a property of the mind that encompasses many related abilities, such as the capacities to reason, to plan, to solve problems, to think abstractly, to comprehend ideas, to use language, and to learn. There are several ways to define intelligence. In some cases, intelligence may include traits such as creativity, personality, character, knowledge, or wisdom. However there is no agreement on which traits define the phenomenon of intelligence agreed upon by a majority across the various concerned disciplines.
Theories of intelligence can be divided into those based on a unilinear construct of general intelligence and those based on multiple intelligences. Francis Galton, influenced by his cousin Charles Darwin, was the first to advance a theory of general intelligence. For Galton, intelligence was a real faculty with a biological basis that could be studied by measuring reaction times to certain cognitive tasks. Galton's research on measuring the head size of British scientists and ordinary citizens led to the conclusion that head size had no relationship with the person's intelligence.
Alfred Binet and the French school of intelligence believed that intelligence was an average of numerous dissimilar abilities, rather than a unitary entity with specific identifiable properties. The Stanford-Binet intelligence test has been used by both theorists of general intelligence and multiple intelligence.
Definitions
Intelligence comes from the Latin verb intellegere, which means "to understand". By this rationale, intelligence (as understanding) is arguably different from being "smart" (able to adapt to one's environment). At least two major "consensus" definitions of intelligence have been proposed. First, from Intelligence: Knowns and Unknowns, a report of a task force convened by the American Psychological Association in 1995:
Individuals differ from one another in their ability to understand complex ideas, to adapt effectively to the environment, to learn from experience, to engage in various forms of reasoning, to overcome obstacles by taking thought. Although these individual differences can be substantial, they are never entirely consistent: a given person’s intellectual performance will vary on different occasions, in different domains, as judged by different criteria. Concepts of "intelligence" are attempts to clarify and organize this complex set of phenomena. Although considerable clarity has been achieved in some areas, no such conceptualization has yet answered all the important questions and none commands universal assent. Indeed, when two dozen prominent theorists were recently asked to define intelligence, they gave two dozen somewhat different definitions.[1][2]
A second definition of intelligence comes from "Mainstream Science on Intelligence", which was signed by 52 intelligence researchers in 1994:
A very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. It is not merely book learning, a narrow academic skill, or test-taking smarts. Rather, it reflects a broader and deeper capability for comprehending our surroundings—"catching on", "making sense" of things, or "figuring out" what to do.[3]
Another simple and efficient definition is: the ability to apply knowledge in order to perform better in an environment.
Researchers in the fields of psychology and learning have also defined human intelligence:
Researcher | Quotation |
---|---|
Alfred Binet | Judgment, otherwise called good sense, practical sense, initiative, the faculty of adapting one's self to circumstances...auto-critique.[4] |
David Wechsler | The aggregate or global capacity of the individual to act purposefully, to think rationally, and to deal effectively with his environment.[5] |
Cyril Burt | Innate general cognitive ability[6] |
Howard Gardner | To my mind, a human intellectual competence must entail a set of skills of problem solving—enabling the individual to resolve genuine problems or difficulties that he or she encounters and, when appropriate, to create an effective product—and must also entail the potential for finding or creating problems—and thereby laying the groundwork for the acquisition of new knowledge.[7] |
Linda Gottfredson | The ability to deal with cognitive complexity[8] |
Sternberg & Salter | Goal-directed adaptive behavior[9] |
A mathematical definition of "intelligence" (using notions from computer science) was put forward by Marcus Hutter in his book Universal Artificial Intelligence (Springer 2005). Essentially the same idea as Hutter's, but coming at it from a different angle and with different terminology, was put forward independently by Warren D. Smith in 2006. One may read about it in paper #93 on his web page http://www.math.temple.edu/~wds/homepage/works.html. Mathematical definitions have, as one advantage, that they could be applied to nonhuman intelligences and in the absence of human testers. The Hutter/Smith picture has a number of interesting consequences such as the theorem that "universal" intelligences exist which can emulate any other (Smith calls this a "UACI" and human minds are speculated to be based on the same principles of operation as UACIs); that there are ways of creating quantitative "intelligence tests" which should enable serving as an objective gauge of progress in [artificial intelligence]. Theoretical and academic definitions of intelligence may not be as useful in clinical and therapeutic applications. For example, The clinical situation presented by those with borderline intellectual and adaptive functioning requires comprehensive analysis of all diagnostic, testing,educational placement, and psychosocial factors. This has been addressed in both the 8th (2005) and 9th (2009) editions of Kaplan & Sadock's Comprehensive Textbook of Psychiatry by Yale child psychiatrist Frank John Ninivaggi. MD.
Theories of intelligence
The most widely accepted theory of intelligence is based on psychometrics testing or intelligence quotient (IQ) tests[citation needed]. However, dissatisfaction with traditional IQ tests has led to the development of a number of alternative theories, all of which suggest that intelligence is the result of a number of independent abilities that uniquely contribute to human performance.
Psychometric approach
Despite the variety of concepts of intelligence, the approach to understanding intelligence with the most supporters and published research over the longest period of time is based on psychometrics testing. Such intelligence quotient (IQ) tests include the Stanford-Binet, Raven's Progressive Matrices, the Wechsler Adult Intelligence Scale and the Kaufman Assessment Battery for Children.
Charles Spearman is generally credited with discovering general intelligence, which he reported in his 1904 American Journal of Psychology article titled "General Intelligence," Objectively Determined and Measured.[10][11][12] Based on the results of a series of studies collected in Hampshire, England, Spearman concluded that there was a common function (or group of functions) across intellectual activities including what he called intelligence (i.e., school rank, which Spearman thought of as “present efficiency” in school courses; the difference between school rank and age, which was conceptualized as “native capacity;” teacher ratings; and peer ratings provided by the two oldest students, which was termed “common sense”) and sensory discriminations (i.e., discrimination of pitch, brightness, and weight). This common function became known as “g” or general intelligence.
To objectively determine and measure general intelligence, Spearman invented the first technique of factor analysis (the method of Tetrad Differences) as a mathematical proof of the Two-Factor Theory.[10][11][13] The factor analytic results indicated that every variable measured a common function to varying degrees, which led Spearman to develop the somewhat misleadingly named Two-Factor Theory of Intelligence.[10][13][14] The Two-Factor Theory of Intelligence holds that every test can be divided into a “g” factor and an “s” factor. The g-factor measures the “general” factor or common function among ability tests. The s-factor measures the “specific” factor unique to a particular ability test. Based on a more modern interpretation of his work, Spearman’s g factor represents the fact that any set of cognitive ability tests, no matter how different, tend to all correlate positively.
L. L. Thurstone extended and generalized Spearman’s method of factor analysis into what is called the Centroid method and which became the basis for modern factor analysis.[14][15] Thustone demonstrated that Spearman’s one common factor method (Spearman’s method yielded only a single factor) was a special case of his multiple factor analysis. Thurstone’s research lead him to propose a model of intelligence that included seven orthogonal (unrelated) factors (i.e., verbal comprehension, word fluency, number facility, spatial visualization, associative memory, perceptual speed and reasoning) referred to as the Primary Mental Abilities.[14][16]
In a critical review of the adult testing literature, Raymond B. Cattell found that a considerable percentage of intelligence tests that purported to measure adult intellectual functioning had all of the trappings of using college students in their development.[17] To account for differences between children/adolescents and adults, which past theory did not address, Cattell proposed two types of cognitive abilities in a revision of Spearman’s concept of general intelligence. Fluid intelligence (Gf) was hypothesized as the ability to discriminate and perceive relations (e.g., analogical and syllogistic reasoning), and crystallized intelligence (Gc) was hypothesized as the ability to discriminate relations that had been established originally through Gf, but no longer required the identification of the relation (commonly assessed using information or vocabulary tests). In addition, fluid intelligence was hypothesized to increase until adolescence and then to slowly decline, and crystallized intelligence increases gradually and stays relatively stable across most of adulthood until it declines in late adulthood.
With his student John L. Horn, Cattell indicated that Gf and Gc were only two among several factors manifest in intelligence tests scores under the umbrella of what became known as Gf/Gc Theory.[18] General visualization (Gv; visual acuity, depth perception), general fluency (F, facility in recalling words), general speediness (Gs; performance on speeded, simple tasks) were among several cognitive ability factors added to Gf/Gc Theory.
J. P. Guilford sought to more fully explore the scope of the adult intellect by providing the concept of intelligence with a strong, comprehensive theoretical backing.[19][20] The Structure-of-Intellect model (SI model) was designed as a cross classification system with intersections in the model providing the basis for abilities similar to Mendeleev’s periodic table in chemistry. The three-dimensional cube—shaped model includes five content categories (the way in which information is presented on a test; visual, auditory, symbolic, semantic, and behavioral), six operation categories (what is done on a test; evaluation, convergent production, divergent production, memory retention, memory recording, and cognition), and six product categories (the form in which information is processed on a test; units, classes, relations, systems, transformations, and implications). The intersection of three categories provides a frame of reference for generating one or more new hypothetical factors of intelligence.
John B. Carroll re-analyzed 461 datasets in the single most comprehensive study of cognitive abilities.[12][21] This analysis led him to propose the Three-Stratum Theory, which is a hierarchical model of intellectual functioning. The stratums represent three different levels of generality over the domain of cognitive abilities. At the bottom is the first stratum, which is represented by narrow abilities that are highly specialized (e.g., induction, spelling ability). The second stratum is represented by broad abilities that include moderate specializations in various domains. Carroll identified eight second-stratum factors: fluid intelligence, crystallized intelligence, general memory and learning, broad visual perception, broad auditory perception, broad retrieval ability, broad cognitive speediness, and processing speed (reaction time decision speed). Carroll has noted the similarity of his second stratum abilities and the Gf/Gc factors, although the Three-Stratum Theory does not incorporate the developmental trajectories associated with Gf/Gc Theory. Carroll accepted Spearman’s concept of general intelligence, for the most part, as a representation of the uppermost third stratum.
More recently, an amalgamation the Gf-Gc theory of Cattell and Horn with Carroll's Three-Stratum theory has led to the Cattell-Horn-Carroll (CHC) theory of cognitive abilities.[22] CHC researchers have produced numerous studies that have influenced diagnostic issues and test development.[23]
Intelligence, as measured by IQ and other aptitude tests, is widely used in educational, business, and military settings due to its efficacy in predicting behavior. g is highly correlated with many important social outcomes - individuals with low IQs are more likely to be divorced, have a child out of marriage, be incarcerated, and need long term welfare support, while individuals with high IQs are associated with more years of education, higher status jobs and higher income.[24] Intelligence is significantly correlated with successful training and performance outcomes, and g is the single best predictor of successful job performance.[25]
Controversies
IQ tests were originally designed to identify mentally "defective" children.[26] The inventors of the IQ did not necessarily believe they were measuring fixed intelligence.[citation needed] Despite this, critics argue that intelligence tests have been used to support nativistic theories which view intelligence as a qualitative object with a relatively fixed quantity.[27]
Critics of the psychometrics point out that intelligence is often more complex and broader in conception than what is measured by IQ tests. Furthermore, skeptics argue that even though tests of mental abilities are correlated, people still have unique strengths and weaknesses in specific areas. Consequently they argue that psychometric theorists over-emphasize g.
Researchers in the field of human intelligence have encountered a considerable amount of public concern and criticism — much more than scientists in other areas normally receive. A number of critics have challenged the relevance of psychometric intelligence in the context of everyday life. There have also been controversies over genetic factors in intelligence, particularly questions regarding the relationship between race and intelligence and sex and intelligence.[28] Another controversy in the field is how to interpret the increases in test scores that have occurred over time, the so-called Flynn effect.
Stephen Jay Gould was one of the most vocal critics of intelligence testing. In his book The Mismeasure of Man Gould argued that intelligence could not be quantified to a single numerical entity. He also challenged the hereditarian viewpoint on intelligence. Many of Gould's criticisms were aimed at Arthur Jensen, who responded that his work had been misrepresented.[29] Gould also investigated the methods of nineteenth century craniometry. Jenson stated that drawing conclusions from early intelligence research is like condemning the auto industry by criticizing the performance of the Model T.
Multiple intelligences
Howard Gardner's theory of multiple intelligences is based on studies not only on normal children and adults but also by studies of gifted individuals (including so-called "savants"), of persons who have suffered brain damage, of experts and virtuosos, and of individuals from diverse cultures. This led Gardner to break intelligence down into at least eight different components: logical, linguistic, spatial, musical, kinesthetic, naturalist, intrapersonal and interpersonal intelligences. He argues that psychometric tests address only linguistic and logical plus some aspects of spatial intelligence; other forms have been entirely ignored. Moreover, the paper-and-pencil format of most tests rules out many kinds of intelligent performance that matter in everyday life, such as social intelligence.[30]
Most of theories of multiple intelligences are relatively recent in origin, though Louis Thurstone proposed a theory of multiple "primary abilities" in the early 20th Century.
Triarchic Theory of Intelligence
Robert Sternberg proposed the Triarchic Theory of Intelligence to provide a more comprehensive description of intellectual competence than traditional differential or cognitive theories of human ability.[31] The Triarchic Theory describes three fundamental aspects of intelligence. Analytic intelligence comprises the mental processes through which intelligence is expressed. Creative intelligence is necessary when an individual is confronted with a challenge that is nearly, but not entirely, novel or when an individual is engaged in automatizing the performance of a task. Practical intelligence is bound in a sociocultural milieu and involves adaptation to, selection of, and shaping of the environment to maximize fit in the context. The Triarchic Theory does not argue against the validity of a general intelligence factor; instead, the theory posits that general intelligence is part of analytic intelligence, and only by considering all three aspects of intelligence can the full range of intellectual functioning be fully understood.
More recently, the Triarchic Theory has been updated and renamed the Theory of Successful Intelligence by Sternberg.[32][33] Intelligence is defined as an individual’s assessment of success in life by the individual’s own (idiographic) standards and within the individual’s sociocultural context. Success is achieved by using combinations of analytical, creative, and practical intelligence. The three aspects of intelligence are referred to as processing skills. The processing skills are applied to the pursuit of success through what were the three elements of practical intelligence: adapting to, shaping of, and selecting of one’s environments. The mechanisms that employ the processing skills to achieve success include utilizing one’s strengths and compensating or correcting for one’s weaknesses.
Sternberg’s theories and research on intelligence remain contentious within the scientific community.[34][35][36][37]
Emotional intelligence
Daniel Goleman and several other researchers have developed the concept of emotional intelligence and claim it is at least as "important" as more traditional sorts of intelligence. These theories grew from observations of human development and of brain injury victims who demonstrate an acute loss of a particular cognitive function — e.g. the ability to think numerically, or the ability to understand written language — without showing any loss in other cognitive areas.
PASS Theory
PASS theory has been offered as an alternative to general intelligence, and is based on a description of neuropsychological processes.[38][39][40] These authors suggested that a unidimensional model with just intelligence fails to assist researchers and clinicians who study learning disabilities, disorders of attention, mental retardation, and interventions designed for special populations who face those challenges. The PASS model covers four kinds of competencies that are associated with areas of the brain. (1) The planning processes involve decision making, problem solving, and performing activities and requires goal setting and self-monitoring. (2) The attention/arousal component involves selectively attending to a particular stimulus, ignoring distractions, and maintaining vigilance. (3) Simultaneous processing involves the integration of stimuli into a group and requires the observation of relationships. (4) Successive processing involves the integration of stimuli into serial order. The planning and attention/arousal components comes from structures located in the frontal lobe, and the simultaneous and successive processes come from structures located in the posterior region of the cortex.
Empirical evidence
IQ proponents have pointed out that IQ's predictive validity has been repeatedly demonstrated, for example in predicting important non-academic outcomes such as job performance (see IQ), whereas the various multiple intelligence theories have little or no such support. Meanwhile, the relevance and even the existence of multiple intelligences have not been borne out when actually tested. A set of ability tests that do not correlate together would support the claim that multiple intelligences are independent of each other.[citation needed]
Evolution of intelligence
Our hominid and human ancestors evolved large and complex brains exhibiting an ever-increasing intelligence through a long and mostly unknown evolutionary process. This process was either driven by the direct adaptive benefits of intelligence[41], or − alternatively − driven by its indirect benefits within the context of sexual selection as a reliable signal of genetic resistance against pathogens.[42]
Factors affecting intelligence
Intelligence is an ill-defined, difficult to quantify concept. Accordingly, the IQ tests used to measure intelligence provide only approximations of the posited 'real' intelligence. In addition, a number of theoretically unrelated properties are known to correlate with IQ such as race, gender and height but since correlation does not imply causation the true relationship between these factors is uncertain. Factors affecting IQ may be divided into biological and environmental.
Biological
Evidence suggests that genetic variation has a significant impact on IQ, accounting for three fourths in adults. Despite the high heritability of IQ, few genes have been found to have a substantial effect on IQ, suggesting that IQ is the product of interaction between multiple genes.
Other biological factors correlating with IQ include ratio of brain weight to body weight and the volume and location of gray matter tissue in the brain.
Because intelligence appears to be at least partly dependent on brain structure and the genes shaping brain development, it has been proposed that genetic engineering could be used to enhance the intelligence of animals, a process sometimes called biological uplift in science fiction. Experiments on mice have demonstrated superior ability in learning and memory in various behavioural tasks.[43]
Environmental
Evidence suggests that family environmental factors may have an effect upon childhood IQ, accounting for up to a quarter of the variance. On the other hand, by late adolescence this correlation disappears, such that adoptive siblings are no more similar in IQ than strangers.[44] Moreover, adoption studies indicate that, by adulthood, adoptive siblings are no more similar in IQ than strangers, while twins and full siblings show an IQ correlation.
Consequently, in the context of the nature versus nurture debate, the "nature" component appears to be much more important than the "nurture" component in explaining IQ variance in the general population.
There are indications that, in middle age, intelligence is influenced by life style choices (e.g., long working hours[45]).
Cultural factors also play a role in intelligence. For example, on a sorting task to measure intelligence, Westerners tend to take a taxonomic approach while the Kpelle people take a more functional approach. For example, instead of grouping food and tools into separate categories, a Kpelle participant stated "the knife goes with the orange because it cuts it"[46]
Ethical issues
Since intelligence is susceptible to modification through the manipulation of environment, the ability to influence intelligence raises ethical issues. Transhumanist theorists study the possibilities and consequences of developing and using techniques to enhance human abilities and aptitudes, and ameliorate what it regards as undesirable and unnecessary aspects of the human condition; eugenics is a social philosophy which advocates the improvement of human hereditary traits through various forms of intervention.[47] The perception of eugenics has varied throughout history, from a social responsibility required of society, to an immoral, racist stance.
Neuroethics considers the ethical, legal and social implications of neuroscience, and deals with issues such as difference between treating a human neurological disease and enhancing the human brain, and how wealth impacts access to neurotechnology. Neuroethical issues interact with the ethics of human genetic engineering.
Other species
This section needs expansion. You can help by adding to it. (May 2008) |
Although humans have been the primary focus of intelligence researchers, scientists have also attempted to investigate animal intelligence, or more broadly, animal cognition. These researchers are interested in studying both mental ability in a particular species, and comparing abilities between species. They study various measures of problem solving, as well as mathematical and language abilities. Some challenges in this area are defining intelligence so that it means the same thing across species (eg. comparing intelligence between literate humans and illiterate animals), and then operationalizing a measure that accurately compares mental ability across different species and contexts.
Wolfgang Köhler's pioneering research on the intelligence of apes is a classic example of research in this area. Stanley Coren's book, The Intelligence of Dogs[unreliable source?] is a notable popular book on the topic.[48] Nonhuman animals particularly noted and studied for their intelligence include chimpanzees, bonobos (notably the language-using Kanzi) and other great apes, dolphins, elephants and to some extent parrots and ravens. Controversy exists over the extent to which these judgments of intelligence are accurate.[citation needed]
Cephalopod intelligence also provides important comparative study. Cephalopods appear to exhibit characteristics of significant intelligence, yet their nervous systems differ radically from those of most other notably intelligent life-forms (mammals and birds).
Artificial intelligence
Artificial intelligence (or AI) is both the intelligence of machines and the branch of computer science which aims to create it, through "the study and design of intelligent agents"[49] or "rational agents", where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success.[50] General intelligence or strong AI has not yet been achieved and is a long-term goal of AI research.
Among the traits that researchers hope machines will exhibit are reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects.[49][50]
See also
- Active intellect
- Educational psychology
- Individual differences psychology
- Passive intellect
- Intellectual giftedness
- Systems intelligence
- Fertility and intelligence
- Race and intelligence
- Intelligence quotient
- Downing effect
- Flynn effect
- Artificial Intelligence
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and|month=
(help)CS1 maint: multiple names: authors list (link) - ^ Virtanen M., A. Singh-Manoux, J.E. Ferrie, D. Gimeno, M.G. Marmot, M. Elovainio, M. Jokela, J. Vahtera, and M. Kivimäki (2009). "Long Working Hours and Cognitive Function: The Whitehall II Study". American Journal of Epidemiology. 169 (5): 596–605. doi:10.1093/aje/kwn382.
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: CS1 maint: multiple names: authors list (link) - ^ Glick (1975) reported in Resnick, L. (1976). The Nature of Intelligence. Hillsdale, New Jersey: Lawrence Erlbaum Associates.
- ^ Osborn, F. (1937). "Development of a Eugenic Philosophy". American Sociological Review. 2 (3): 389–397. doi:10.2307/2084871. Retrieved 2008-03-20.
- ^ Coren, Stanley (1995). The Intelligence of Dogs. Bantam Books. ISBN 0-553-37452-4. OCLC 30700778.
- ^ a b Goebel, Randy; Poole, David L.; Mackworth, Alan K. (1997). Computational intelligence: A logical approach (pdf). Oxford [Oxfordshire]: Oxford University Press. p. 1. ISBN 0195102703.
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: CS1 maint: multiple names: authors list (link) - ^ a b Canny, John; Russell, Stuart J.; Norvig, Peter (2003). Artificial intelligence: A modern approach. Englewood Cliffs, N.J: Prentice Hall. ISBN 0137903952. OCLC 51325314 60211434 61259102.
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Further reading
- Binet A (1916/2007). The development of intelligence in children. Baltimore: Williams & Wilkins (original); Kessinger Publishing (reprint). ISBN 0548307520.
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suggested) (help)CS1 maint: year (link) - Wake, Warren K.; Gardner, Howard; Kornhaber, Mindy L. (1996). Intelligence: Multiple perspectives. Fort Worth, TX: Harcourt Brace College Publishers. ISBN 0030726298. OCLC 34414874.
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: CS1 maint: multiple names: authors list (link) - Blakeslee, Sandra; Hawkins, Jeff (2004). On intelligence. New York: Times Books. ISBN 0-8050-7456-2. OCLC 55510125.
{{cite book}}
: CS1 maint: multiple names: authors list (link) - Jensen, Arthur (1998). The g factor: The science of mental ability. New York: Praeger. ISBN 0275961036. OCLC 231732886 37024184 60202099.
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value (help) - Terman, L (1916). The measurement of intelligence. Boston: Houghton Mifflin. ISBN 0405064802. OCLC 1111319. ASIN B000H5DEOM
External links
- APA Task Force Examines the Knowns and Unknowns of Intelligence - American Psychological Association, Press release
- IQ Since "The Bell Curve" by Christopher F. Chabris - Commentary magazine
- The cognitive-psychology approach vs. psychometric approach to intelligence - American Scientist magazine
- History of Influences in the Development of Intelligence Theory and Testing - Developed by Jonathan Plucker at Indiana University
Scholarly journals and societies