Human intelligence

Not to be confused with Human intelligence (intelligence collection), the espionage discipline.

Human intelligence is the intellectual capacity of humans, which is characterized by perception, consciousness, self-awareness, and volition. Through their intelligence, humans possess the cognitive abilities to learn, form concepts, understand, apply logic, and reason, including the capacities to recognize patterns, comprehend ideas, plan, problem solve, make decisions, retain information, and use language to communicate. Intelligence enables humans to experience and think.

Evolution of intelligence

The ancestors of modern humans evolved large and complex brains exhibiting an ever-increasing intelligence through a long evolutionary process (see Homininae). Different explanations have been proposed.

Correlates

Some studies have shown a direct link between an increased birth weight and an increased intelligence quotient.[1][2][3]

According to Rosemary Hopcroft, a sociologist at the University of North Carolina at Charlotte, intelligence is inversely linked with sexual frequency (people with higher levels of education often report lower numbers of sexual partners).[4] In parallel, self-reported intelligence has been linked to unconventional sexual practices and frequent sexual activity, thoughts and fantasies.[5]

A number of studies have shown a correlation between IQ and myopia.[6] Some suggest that the reason for the correlation is environmental, whereby intelligent people are more likely to damage their eyesight with prolonged reading, while others contend that a genetic link exists.[7]

In May, 2013, a study showed that the ability to ignore distractions correlates with intelligence.[8]

In September, 2014, a study on finding genetic variants associated with cognitive performance found no specific gene directly responsible for intelligence. Rather it's the sum of many indirect genes and of the environment.[9]

Theories of intelligence

There are critics of IQ, who do not dispute the stability of IQ test scores, or the fact that they predict certain forms of achievement rather effectively. They do argue, however, that to base a concept of intelligence on IQ test scores alone is to ignore many important aspects of mental ability.[10]

On the other hand, Linda S. Gottfredson (2006) has argued that the results of thousands of studies support the importance of IQ for school and job performance (see also the work of Schmidt & Hunter, 2004). She says that IQ also predicts or correlates with numerous other life outcomes. In contrast, empirical support for non-g intelligences is lacking or very poor. She argued that despite this the ideas of multiple non-g intelligences are very attractive to many because they suggest that everyone can be intelligent in some way.[11]

Theory of multiple intelligences

Howard Gardner's theory of multiple intelligences is based on studies not only of 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 a number of different components. In the first edition of his book "Frames of Mind" (1983), he described seven distinct types of intelligence—logical-mathematical, linguistic, spatial, musical, kinesthetic, interpersonal, and intrapersonal. In a second edition of this book, he added two more types of intelligence—naturalist and existential intelligences. He argues that psychometric tests address only linguistic and logical plus some aspects of spatial intelligence.[10] A major criticism of Gardner's theory is that it has never been tested, or subjected to peer review, by Gardner or anyone else, and indeed that it is unfalsifiable.[12] Others (e.g. Locke, 2005) have suggested that recognizing many specific forms of intelligence (specific aptitude theory) implies a political—rather than scientific—agenda, intended to appreciate the uniqueness in all individuals, rather than recognizing potentially true and meaningful differences in individual capacities. Schmidt and Hunter (2004) suggest that the predictive validity of specific aptitudes over and above that of general mental ability, or "g", has not received empirical support.

Howard Gardner mentions in his Multiple Intelligences The Theory in Practice[13] book, briefly about his main seven intelligences he introduced. In his book, he starts by describing Linguistic and Logical Intelligence because he believed that society has put these two intelligences on a pedestal. However, Gardner believes all of the intelligences he found are equal. Note: At the time of the publication of Gardner's book Multiple Intelligences The Theory in Practice, naturalist and existential intelligences were not mentioned.

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.[14] 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.[15][16] 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.[17][18][19][20]

PASS theory of intelligence

Based on A. R. Luria's (1966)[21] seminal work on the modularization of brain function, and supported by decades of neuroimaging research, the PASS Theory of Intelligence[22] proposes that cognition is organized in three systems and four processes. The first is the Planning, which involves executive functions responsible for controlling and organizing behavior, selecting and constructing strategies, and monitoring performance. The second is the Attention process, which is responsible for maintaining arousal levels and alertness, and ensuring focus on relevant stimuli. The next two are called Simultaneous and Successive processing and they involve encoding, transforming, and retaining information. Simultaneous processing is engaged when the relationship between items and their integration into whole units of information is required. Examples of this include recognizing figures, such as a triangle within a circle vs. a circle within a triangle, or the difference between 'he had a shower before breakfast' and 'he had breakfast before a shower.' Successive processing is required for organizing separate items in a sequence such as remembering a sequence of words or actions exactly in the order in which they had just been presented. These four processes are functions of four areas of the brain. Planning is broadly located in the front part of our brains, the frontal lobe. Attention and arousal are combined functions of the frontal lobe and the lower parts of the cortex, although the parietal lobes are also involved in attention as well. Simultaneous processing and Successive processing occur in the posterior region or the back of the brain. Simultaneous processing is broadly associated with the occipital and the parietal lobes while Successive processing is broadly associated with the frontal-temporal lobes. The PASS (Planning/Attention/Simultaneous/Successive) theory is heavily indebted to both Luria (1966,[21] 1973[23]), and studies in cognitive psychology involved in promoting a better look at intelligence.[24]

Piaget's theory and Neo-Piagetian theories

In Piaget's theory of cognitive development the focus is not on mental abilities but rather on a child's mental models of the world. As a child develops, increasingly more accurate models of the world are developed which enable the child to interact with the world better. One example being object permanence where the child develops a model where objects continue to exist even when they cannot be seen, heard, or touched.

Piaget's theory described four main stages and many sub-stages in the development. These four main stages are:

Degree of progress through these stages are correlated, but not identical with psychometric IQ.[26][27] Piaget conceptualizes intelligence as an activity more than a capacity.

One of Piaget's most famous studies focused purely on the discriminative abilities of children between the ages of two and a half years old, and four and a half years old. He began the study by taking children of different ages and placing two lines of sweets, one with the sweets in a line spread further apart, and one with the same number of sweets in a line placed more closely together. He found that, "Children between 2 years, 6 months old and 3 years, 2 months old correctly discriminate the relative number of objects in two rows; between 3 years, 2 months and 4 years, 6 months they indicate a longer row with fewer objects to have "more"; after 4 years, 6 months they again discriminate correctly".[28] Initially younger children were not studied, because if at the age of four years a child could not conserve quantity, then a younger child presumably could not either. The results show however that children that are younger than three years and two months have quantity conservation, but as they get older they lose this quality, and do not recover it until four and a half years old. This attribute may be lost temporarily because of an overdependence on perceptual strategies, which correlates more candy with a longer line of candy, or because of the inability for a four-year-old to reverse situations.[25] By the end of this experiment several results were found. First, younger children have a discriminative ability that shows the logical capacity for cognitive operations exists earlier than acknowledged. This study also reveals that young children can be equipped with certain qualities for cognitive operations, depending on how logical the structure of the task is. Research also shows that children develop explicit understanding at age 5 and as a result, the child will count the sweets to decide which has more. Finally the study found that overall quantity conservation is not a basic characteristic of humans' native inheritance.[25]

Piaget's theory has been criticized for the age of appearance of a new model of the world, such as object permanence, being dependent on how the testing is done (see the article on object permanence). More generally, the theory may be very difficult to test empirically because of the difficulty of proving or disproving that a mental model is the explanation for the results of the testing.[29]

Neo-Piagetian theories of cognitive development expand Piaget's theory in various ways such as also considering psychometric-like factors such as processing speed and working memory, "hypercognitive" factors like self-monitoring, more stages, and more consideration on how progress may vary in different domains such as spatial or social.[30][31]

Parieto-frontal integration theory of intelligence

Based on a review of 37 neuroimaging studies, Jung and Haier (2007) proposed that the biological basis of intelligence stems from how well the frontal and parietal regions of the brain communicate and exchange information with each other.[32] Subsequent neuroimaging and lesion studies report general consensus with the theory.[33][34][35] A review of the neuroscience and intelligence literature concludes that the parieto-frontal integration theory is the best available explanation for human intelligence differences.[36]

Investment theory

Based on the Cattell–Horn–Carroll theory , the tests of intelligence most often used in the relevant studies include measures of fluid ability (Gf) and crystallized ability (Gc); that differ in their trajectory of development in individuals.[37] The 'investment theory' by Cattell [38] states that the individual differences observed in the procurement of skills and knowledge (Gc) are partially attributed to the 'investment' of Gf, thus suggesting the involvement of fluid intelligence in every aspect of the learning process.[39] It is essential to highlight that the investment theory suggests that personality traits affect 'actual' ability, and not scores on an IQ test.[40] In association, Hebb's theory of intelligence suggested a bifurcation as well, Intelligence A (physiological), that could be seen as a semblance of fluid intelligence and Intelligence B (experiential), similar to crystallized intelligence.[41]

Intelligence Compensation Theory (ICT)

The Intelligence Compensation Theory (a term first coined by Wood and Englert, 2009)[42] states that individuals who are comparatively less intelligent work harder, more methodically, become more resolute and thorough (more conscientious) in order to achieve goals, to compensate for their 'lack of intelligence' whereas more intelligent individuals do not require traits/behaviours associated with the personality factor conscientiousness to progress as they can rely on the strength of their cognitive abilities as opposed to structure or effort.[43][44] The theory suggests the existence of a causal relationship between intelligence and conscientiousness, such that the development of the personality trait conscientiousness is influenced by intelligence. This assumption is deemed plausible as it is unlikely that the reverse causal relationship could occur;[45] implying that the negative correlation would be higher between fluid intelligence (Gf) and conscientiousness. The justification being the timeline of development of Gf, Gc and personality, as crystallized intelligence would not have developed completely when personality traits develop. Subsequently, during school-going ages, more conscientious children would be expected to gain more crystallized intelligence (knowledge) through education, as they would be more efficient, thorough, hard-working and dutiful.[46]

This theory has recently been contradicted by evidence, that identifies compensatory sample selection. Thus, attributing the previous findings to the bias in selecting samples with individuals above a certain threshold of achievement.[47]

Bandura's theory of self-efficacy and cognition

The view of cognitive ability has evolved over the years, and it is no longer viewed as a fixed property held by an individual. Instead, the current perspective describes it as a general capacity, comprising not only cognitive, but motivational, social and behavioural aspects as well. These facets work together to perform numerous tasks. An essential skill often overlooked is that of managing emotions, and aversive experiences that can compromise one's quality of thought and activity. The link between intelligence and success has been bridged by crediting individual differences in self-efficacy. The theory identifies the difference between possessing skills and being able to apply them in challenging situations. Thus, the theory suggests that individuals with the same level of knowledge and skill may perform badly, averagely or excellently based on differences in self-efficacy.

A key role of cognition is to allow for one to predict events and in turn devise methods to deal with these events effectively. These skills are dependent on processing of stimuli that is unclear and ambiguous. To learn the relevant concepts, individuals must be able to rely on the reserve of knowledge to identify, develop and execute options. They must be able to apply the learning acquired from previous experiences. Thus, a stable sense of self-efficacy is essential to stay focused on tasks in the face of challenging situations.[48]

To summarize, Bandura's theory of self-efficacy and intelligence suggests that individuals with a relatively low sense of self-efficacy in any field will avoid challenges. This effect is heightened when they perceive the situations as personal threats. When failure occurs, they recover from it slower than others, and credit it to an insufficient aptitude. On the other hand, persons with high levels of self-efficacy hold a task-diagnostic aim that leads to effective performance.[49]

Process, Personality, Intelligence & Knowledge theory (PPIK)

Developed by Ackerman,[50][51] the PPIK theory further developed the approach on intelligence as proposed by Cattell, suggesting a distinction between intelligence as knowledge and intelligence as process, that are comparable to Gc and Gf respectively. It is important to verify that though related, they are not equivalent to the factors of intelligence from the Investment theory. This theory reinforces the perspective of intelligence being in part dependent on the 'investment' of cognitive abilities, but the role of personality, and factors such as motivation and interest were far more accentuated in the PPIK theory. The theory is set apart from Cattel's Investment Theory based on the following; it identifies two factors of General Intelligence – Process and Knowledge, that detaches itself from the concept of fluid intelligence (Gf) and crystallized intelligence (Gc), and is closer to Hebb's model of intelligence. Another significant aspect of the theory is the rendering of specific personality and interest factors in association with intelligence. The description of knowledge is credited to individual differences, where in persons may not overlap much in their skills (E.g. The structure of knowledge held by a Medical Professional may differ significantly from the structure of knowledge of an Architect). The model can be described as follows: When 'Intelligence as process' is being considered, Ackerman describes the difficulty of distinguishing process from knowledge, as content cannot be entirely eliminated from any ability test.[52] At the same time, previous literature [53][54][55][56] has demonstrated the stand-alone information-processing aspects of intelligence. These are related to optimal performance in adolescent age groups. The extent to which the components of process influence learning are yet to be defined. Personality traits have not shown to be significantly correlated with 'Intelligence as process' except in the context of psychopathology. One exception to this generalization has been the finding of sex differences in cognitive abilities, specifically abilities in mathematical and spatial form.[57] On the other hand, 'Intelligence as knowledge' has been associated with personality traits of Openness and Typical Intellectual Engagement.[58][59] They correlate strongly with verbal abilities (associated with crystallized intelligence).

Predicted growth curves for 'Intelligence as process', crystallized intelligence, occupational knowledge and avocational knowledge based on Ackerman's PPIK Theory.

Interests: Based upon reviews and investigations, the following 3 interests were identified as significantly related to intelligence: Realistic, Investigative and Artistic. Individuals with Realistic (or Motoric) interests are said to be inclined towards activities that exert "physical strength, aggressive action, motor coordination and skill.[60]" As the name suggests, those with Investigative (or Intellectual) interests, are identified as "task-oriented people who generally prefer to 'think through,' rather than 'act out,' problems. They have marked needs to organize and understand the world." Finally, persons who express Artistic (or Esthetic) interests "prefer indirect relations with others. They prefer dealing with environmental problems through self-expression in artistic media." Individuals high in Realistic and/or Investigative interests are expected to perform better on tests of 'intelligence as process' (E.g. Reasoning, math). The degree of these two interests was also associated with tasks that are unclassified as either process or knowledge (E.g. Mechanical abilities). On the other hand, the degree of Artistic interest in individuals was found to be closely related to 'intelligence as knowledge' (closer to crystallized abilities).[61] Intelligence is often understood as knowledge in any sphere, but the role of 'interest' drives an individual towards/away from various fields. Conceptually, when intelligence is viewed as a process, it can behave as a resource, that is limited. Hence, an individual will be expected to have either a breadth or depth of knowledge. Only extraordinary persons would have them both. The researchers suggest that most individuals will have a robust pool of knowledge of their own occupation, and limited information about others. Thus, two "experts" may not overlap vastly in the kind of knowledge they hold, as they may belong to diverse fields.

Latent inhibition

Main article: Latent inhibition

Latent inhibition has been related to elements of intelligence, namely creativity and genius.

Improving intelligence

Eugenics is a social philosophy which advocates the improvement of human hereditary traits through various forms of intervention.[62] Conscious efforts to influence intelligence raise ethical issues. Eugenics has variously been regarded as meritorious or deplorable in different periods of history, falling greatly into disrepute after the defeat of Nazi Germany in World War II.

Neuroethics considers the ethical, legal and social implications of neuroscience, and deals with issues such as the 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.

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, a process sometimes called biological uplift in science fiction. Experiments on mice have demonstrated superior ability in learning and memory in various behavioral tasks.[63]

IQ leads to greater success in education,[64] but independently education raises IQ scores.[65] Attempts to raise IQ with brain training have led to increases on the training tasks – for instance working memory – but it is as yet unclear if these generalise to increased intelligence per se.[66]

Transhumanist theorists study the possibilities and consequences of developing and using techniques to enhance human abilities and aptitudes, and individuals ameliorating what they regard as undesirable and unnecessary aspects of the human condition.

Substances which actually or purportedly improve intelligence or other mental functions are called nootropics.

A 2008 research paper claimed that practicing a dual n-back task can increase fluid intelligence (Gf), as measured in several different standard tests.[67] This finding received some attention from popular media, including an article in Wired.[68] However, a subsequent criticism of the paper's methodology questioned the experiment's validity and took issue with the lack of uniformity in the tests used to evaluate the control and test groups.[69] For example, the progressive nature of Raven's Advanced Progressive Matrices (APM) test may have been compromised by modifications of time restrictions (i.e., 10 minutes were allowed to complete a normally 45-minute test).

Measuring intelligence

Chart of IQ Distributions on 1916 Stanford-Binet Test
Score distribution chart for sample of 905 children tested on 1916 Stanford-Binet Test

The approach to understanding intelligence with the most supporters and published research over the longest period of time is based on psychometric testing. It is also by far the most widely used in practical settings. Intelligence quotient (IQ) tests include the Stanford-Binet, Raven's Progressive Matrices, the Wechsler Adult Intelligence Scale and the Kaufman Assessment Battery for Children. There are also psychometric tests that are not intended to measure intelligence itself but some closely related construct such as scholastic aptitude. In the United States examples include the SSAT, the SAT, the ACT, the GRE, the MCAT, the LSAT, and the GMAT.[10] Regardless of the method used, almost any test that requires examinees to reason and has a wide range of question difficulty will produce intelligence scores that are approximately normally distributed in the general population.[70][71]

Intelligence tests are widely used in educational,[72] business, and military settings because of their efficacy in predicting behavior. IQ and g (discussed in the next section) are 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.[73] Intelligence is significantly correlated with successful training and performance outcomes, and IQ/g is the single best predictor of successful job performance.[10][74]

General intelligence factor or g

There are many different kinds of IQ tests using a wide variety of test tasks. Some tests consist of a single type of task, others rely on a broad collection of tasks with different contents (visual-spatial,[75] verbal, numerical) and asking for different cognitive processes (e.g., reasoning, memory, rapid decisions, visual comparisons, spatial imagery, reading, and retrieval of general knowledge). The psychologist Charles Spearman early in the 20th century carried out the first formal factor analysis of correlations between various test tasks. He found a trend for all such tests to correlate positively with each other, which is called a positive manifold. Spearman found that a single common factor explained the positive correlations among tests. Spearman named it g for "general intelligence factor". He interpreted it as the core of human intelligence that, to a larger or smaller degree, influences success in all cognitive tasks and thereby creates the positive manifold. This interpretation of g as a common cause of test performance is still dominant in psychometrics. An alternative interpretation was recently advanced by van der Maas and colleagues.[76] Their mutualism model assumes that intelligence depends on several independent mechanisms, none of which influences performance on all cognitive tests. These mechanisms support each other so that efficient operation of one of them makes efficient operation of the others more likely, thereby creating the positive manifold.

IQ tasks and tests can be ranked by how highly they load on the g factor. Tests with high g-loadings are those that correlate highly with most other tests. One comprehensive study investigating the correlations between a large collection of tests and tasks[77] has found that the Raven's Progressive Matrices have a particularly high correlation with most other tests and tasks. The Raven's is a test of inductive reasoning with abstract visual material. It consists of a series of problems, sorted approximately by increasing difficulty. Each problem presents a 3 x 3 matrix of abstract designs with one empty cell; the matrix is constructed according to a rule, and the person must find out the rule to determine which of 8 alternatives fits into the empty cell. Because of its high correlation with other tests, the Raven's Progressive Matrices are generally acknowledged as a good indicator of general intelligence. This is problematic, however, because there are substantial gender differences on the Raven's,[78] which are not found when g is measured directly by computing the general factor from a broad collection of tests.[79]

General collective intelligence factor or c

A recent scientific understanding of collective intelligence, defined as a group’s general ability to perform a wide range of tasks,[80] expands the areas of human intelligence research applying similar methods and concepts to groups. Definition, operationalization and methods are similar to the psychometric approach of general individual intelligence where an individual’s performance on a given set of cognitive tasks is used to measure intelligence indicated by the general intelligence factor g extracted via factor analysis.[81] In the same vein, collective intelligence research aims to discover a ‘c factor’ explaining between-group differences in performance as well as structural and group compositional causes for it.[82]

Historical psychometric theories

Several different theories of intelligence have historically been important. Often they emphasized more factors than a single one like in g factor.

Cattell–Horn–Carroll theory

Many of the broad, recent IQ tests have been greatly influenced by the Cattell–Horn–Carroll theory. It is argued to reflect much of what is known about intelligence from research. A hierarchy of factors is used. g is at the top. Under it there are 10 broad abilities that in turn are subdivided into 70 narrow abilities. The broad abilities are:[83]

Modern tests do not necessarily measure of all of these broad abilities. For example, Gq and Grw may be seen as measures of school achievement and not IQ.[83] Gt may be difficult to measure without special equipment.

g was earlier often subdivided into only Gf and Gc which were thought to correspond to the nonverbal or performance subtests and verbal subtests in earlier versions of the popular Wechsler IQ test. More recent research has shown the situation to be more complex.[83]

Controversies

While not necessarily a dispute about the psychometric approach itself, there are several controversies regarding the results from psychometric research. Examples are the role of genetics vs. environment, the causes of average group differences, or the Flynn effect.

One criticism has been against the early research such as craniometry.[84] A reply has been that drawing conclusions from early intelligence research is like condemning the auto industry by criticizing the performance of the Model T.[85]

Several critics, such as Stephen Jay Gould, have been critical of g, seeing it as a statistical artifact, and that IQ tests instead measure a number of unrelated abilities.[84][86] The American Psychological Association's report "Intelligence: Knowns and Unknowns" stated that IQ tests do correlate and that the view that g is a statistical artifact is a minority one.

See also

References

  1. ↑ Matte TD, Bresnahan M, Begg MD, Susser E (August 2001). "Influence of variation in birth weight within normal range and within sibships on IQ at age 7 years: cohort study". BMJ. 323 (7308): 310–4. doi:10.1136/bmj.323.7308.310. PMC 37317Freely accessible. PMID 11498487.
  2. ↑ "The Future of Children - Sub-Sections". Archived from the original on 2007-10-22. Retrieved 2007-11-28.
  3. ↑ "HEALTH | Intelligence linked to birthweight". BBC News. 2001-08-09. Retrieved 2007-11-28.
  4. ↑ Friedman, L.F. (July 3, 2011). "Intelligent Intercourse". Psychology Today.
  5. ↑ Thompson, Mark (1 October 2010). "3". Who Should You Have Sex With. Sourcebooks Casablanca. p. 78. ISBN 978-1402242045. In my studies, men and women who described themselves as smart, intelligent, logical and imaginative reported thinking about sex more often, fantasizing about sex, and having sex more often than people who did not see themselves as smart or intellectual. They also usually had a wider scope of sexual experiences, including experience with role-playing and other Kinky activities.
  6. ↑ Rosenfield, Mark; Gilmartin, Bernard (1998). Myopia and nearwork. Elsevier Health Sciences. p. 23. ISBN 978-0-7506-3784-8.
  7. ↑ Czepita, D.; Lodygowska, E.; Czepita, M. (2008). "Are children with myopia more intelligent? A literature review". Annales Academiae Medicae Stetinensis. 54 (1): 13–16; discussion 16. PMID 19127804.
  8. ↑ Michael D. Melnick; Bryan R. Harrison; Sohee Park; Loisa Bennetto; Duje Tadinemail (June 3, 2013). "A Strong Interactive Link between Sensory Discriminations and Intelligence". Cell Press Journals. 23 (11): 1013–1017. doi:10.1016/j.cub.2013.04.053.
  9. ↑ Cornelius A. Rietveld; et al. (September 8, 2014). "Common genetic variants associated with cognitive performance identified using the proxy-phenotype method". Proceedings of the National Academy of Sciences of the United States of America. 111: 13790–13794. doi:10.1073/pnas.1404623111.
  10. 1 2 3 4 Neisser, U.; Boodoo, G.; Bouchard, T. J. , J.; Boykin, A. W.; Brody, N.; Ceci, S. J.; Halpern, D. F.; Loehlin, J. C.; Perloff, R.; Sternberg, R. J.; Urbina, S. (1996). "Intelligence: Knowns and unknowns". American Psychologist. 51 (2): 77–101. doi:10.1037/0003-066X.51.2.77. Article in Wikipedia: Intelligence: Knowns and Unknowns
  11. ↑ Gottfredson, L. S. (2006). Social consequences of group differences in cognitive ability (Consequencias sociais das diferencas de grupo em habilidade cognitiva). In C. E. Flores-Mendoza & R. Colom (Eds.), Introducau a psicologia das diferencas individuais (pp. 433-456). Porto Allegre, Brazil: ArtMed Publishers.
  12. ↑ Archived January 13, 2010, at the Wayback Machine.
  13. ↑ Multiple Intelligences: The Theory in Practice, A Reader. New York: Basic Books. 1993. ISBN 0-465-01822-X.
  14. ↑ Sternberg, R.J. (1985). Beyond IQ: A triarchic theory of human intelligence. New York: Cambridge University Press. ISBN 0-521-26254-2.
  15. ↑ Sternberg, R.J. (1978). "The theory of successful intelligence". Review of General Psychology. 3 (4): 292–316. doi:10.1037/1089-2680.3.4.292.
  16. ↑ Sternberg, R.J. (2003). "A broad view of intelligence: The theory of successful intelligence". Consulting Psychology Journal: Practice & Research. 55 (3): 139–154. doi:10.1037/1061-4087.55.3.139.
  17. ↑ Brody, N. (2003). "Construct validation of the Sternberg Triarchic Abilities Test: Comment and reanalysis". Intelligence. 31 (4): 319–329. doi:10.1016/S0160-2896(01)00087-3.
  18. ↑ Brody, N. (2003). "What Sternberg should have concluded". Intelligence. 31 (4): 339–342. doi:10.1016/S0160-2896(02)00190-3.
  19. ↑ Gottfredson, L.S. (2003). "Dissecting practical intelligence theory: Its claims and evidence". Intelligence. 31 (4): 343–397. doi:10.1016/S0160-2896(02)00085-5.
  20. ↑ Gottfredson, L.S. (2003). "On Sternberg's 'Reply to Gottfredson'". Intelligence. 31 (4): 415–424. doi:10.1016/S0160-2896(03)00024-2.
  21. 1 2 Luria, A. R. (1966). Higher cortical functions in man. New York: Basic Books.
  22. ↑ Das, J. P., Naglieri, J. A., & Kirby, J. R. (1994). Assessment of cognitive processes. Needham Heights, MA: Allyn & Bacon.
  23. ↑ Luria, A. R. (1973). The working brain: An introduction to neuropsychology. New York.
  24. ↑ Das, J.P. (2002). "A Better look at Intelligence". Current Directions in Psychology. 11 (1): 28–32. doi:10.1111/1467-8721.00162.
  25. 1 2 3 Piaget, J. (2001). Psychology of intelligence. Routledge.
  26. ↑ Elkind, D., & Flavell, J. (1969). Studies in cognitive development: Essays in honor of Jean Piaget. New York: Oxford University Press
  27. ↑ Weinberg, Richard A. "Intelligence and IQ, Landmark Issues and Great Debates". American Psychologist. 44 (2): 98–104. doi:10.1037/0003-066x.44.2.98.
  28. ↑ Piaget, J. (1953). The origin of intelligence in the child. New Fetter Lane, New York: Routledge & Kegan Paul.
  29. ↑ Kitchener, R. F. (1993). "Piaget's epistemic subject and science education: Epistemological vs. Psychological issues". Science and Education. 2 (2): 137–148. Bibcode:1993Sc&Ed...2..137K. doi:10.1007/BF00592203.
  30. ↑ Demetriou, A. (1998). Cognitive development. In A. Demetriou, W. Doise, K.F.M. van Lieshout (Eds.), Life-span developmental psychology (pp. 179-269). London: Wiley.
  31. ↑ Demetriou, A., Mouyi, A., & Spanoudis, G. (2010). The development of mental processing. Nesselroade, J.R. (2011). Methods in the study of life-span human development: Issues and answers. In W.F. Overton (Ed.), Biology, cognition and methods across the life-span. Volume 1 of the Handbook of life-span development (pp. 36-35), Editor-in-chief: R.M. Lerner. Hoboken, NJ: Wiley.
  32. ↑ Jung, R. E.; Haier, R. J. (2007). "The parieto-frontal integration theory (P-FIT) of intelligence: converging neuroimaging evidence". Behavioral and Brain Sciences. 30: 135–187. doi:10.1017/s0140525x07001185.
  33. ↑ Colom, R.; Haier, R. J.; Head, K.; Alvarez-Linera, J.; Ouiroga, M. A.; Shih, P. C.; Jung, R. E. (2009). "Gray matter correlates of fluid, crystallized, and spatial intelligence: testing the P-FIT model". Intelligence. 37: 124–135. doi:10.1016/j.intell.2008.07.007.
  34. ↑ Vakhtin, A. A.; Ryman, S. G.; Flores, R. A.; Jung, R. E. (2014). "Functional brain networks contributing to the parieto-frontal integration theory of intelligence". NeuroImage. 103: 349–354. doi:10.1016/j.neuroimage.2014.09.055.
  35. ↑ Gläscher, J.; Rudrauf, D.; Colom, R.; Paul, L. K.; Tranel, D.; Damasio, H.; Adolphs, R. (2010). "Distributed neural system for general intelligence revealed by lesion mapping". Social Cognitive and Affective Neuroscience. 9 (3): 265–72. doi:10.1093/scan/nss124. PMID 23171618.
  36. ↑ Deary, I. J.; Penke, L.; Johnson, W. (2010). "The neuroscience of human intelligence differences". Nature Reviews Neuroscience. 11 (3): 201–211. doi:10.1038/nrn2793. PMID 20145623.
  37. ↑ Horn, J. L.; Cattell, R. B. (1966). "Refinement and test of the theory of fluid and crystallized general intelligences". Journal of educational psychology. 57 (5): 253–270. doi:10.1037/h0023816.
  38. ↑ Cattell, R. B. (1987). Intelligence: Its structure, growth and action. New York: North-Holland.
  39. ↑ Kvist, A. V.; Gustafsson, J. E. (2008). "The relation between fluid intelligence and the general factor as a function of cultural background: A test of Cattell's investment theory". Intelligence. 36 (5): 422–436. doi:10.1016/j.intell.2007.08.004.
  40. ↑ Cattell, R. B. (1971). Abilities: their structure, growth, and action. Boston: Houghton Mifflin.
  41. ↑ Hebb. D.O. (1939). Intelligence in man after large removals of cerebral tissue: Report of four frontal lobe cases. Journal qf'Gcneru/ Pswho/o~\: 21. 73-87.
  42. ↑ Wood, P.; Englert, P. (2009). "Intelligence compensation theory: A critical examination of the negative relationship between conscientiousness and fluid and crystallised intelligence". The Australian and New Zealand Journal of Organisational Psychology. 2: 19–29. doi:10.1375/ajop.2.1.19.
  43. ↑ Chamorro-Premuzic, T.; Furnham, A. (2004). "A possible model for explaining the personality–intelligence interface". British Journal of Psychology. 95: 249–264. doi:10.1348/000712604773952458.
  44. ↑ Moutafi, J.; Furnham, A.; Crump, J. (2003). "Demographic and Personality Predictors of Intelligence: A study using the Neo Personality Inventory and the Myers-Briggs Type Indicator". European Journal of Personality. 17: 79–94. doi:10.1002/per.471.
  45. ↑ Moutafi, J.; Furnham, A.; Paltiel, L. (2004). "Why is conscientiousness negatively correlated with intelligence?.". Personality and Individual Differences. 37 (5): 1013–1022. doi:10.1016/j.paid.2003.11.010.
  46. ↑ Brody, N. (1992). Intelligence (2nd ed.). New York: Academic Press.
  47. ↑ Murray, A. L.; Johnson, W.; McGue, M.; Iacono, W. G. (2014). "How are conscientiousness and cognitive ability related to one another? A re-examination of the intelligence compensation hypothesis". Personality and Individual Differences. 70: 17–22. doi:10.1016/j.paid.2014.06.014.
  48. ↑ Wood, R., & Bandura, A. (198913). Social cognitive theory of organizational management. Academy of Management Review, 14, 361-384.
  49. ↑ Bandura, A (1993). "Perceived self-efficacy in cognitive development and functioning". Educational psychologist. 28 (2): 117–148. doi:10.1207/s15326985ep2802_3.
  50. ↑ Ackerman, P. L. (1996). "A theory of adult intellectual development: Process, personality, interests, and knowledge". Intelligence. 22 (2): 227–257. doi:10.1016/S0160-2896(96)90016-1.
  51. ↑ Ackerman, P.L. (1995, August). Personality, intelligence, motivation, and interests: Implicationsfor overlapping traits. Address presented at the annual meeting of the American Psychological Association, New York.
  52. ↑ Detterman, D.K., & Andrist, C.G. (1990). Effect of instructions on elementary cognitive tasks sensitive to individual differences. Americun Journal of Psycho/o,q?: 103. 367-390.
  53. ↑ Carroll, I. B. (1993). Human cognitive abilities: A survey @factor-analytic studies. New York: Cam- bridge University Press.
  54. ↑ Rogers, W.A., Fisk, A.D., & Hertzog, C. (1994). Do ability-performance relationships differentiate age and practice effects in visual search? Journal of Experimental Psychology: Learning. Perception and Cognition. 20. 710-738.
  55. ↑ Sternberg. R.J. (Ed. ). ( I985b). Human uhiliries: At1 irlfbrmutio,l-pro~essi,l~ uppmach. New York: W.H. Freeman.
  56. ↑ Sternberg. R.J., & Berg. C.A. (1987). What are theories of adult intellectual development theories of! In C. Schooler & K. W. Schaie (Eds. ). Coptiti~~ futvtionrng and social .xtrucmrc over the /l/b umr.~. Norwood. NJ: Ablex.
  57. ↑ Signorella, M.L.; Jamison, W. (1986). "Masculinity, femininity, androgyny and cognitive performance: A meta-analysis". Psychological Bulletin. 100: 207–238. doi:10.1037/0033-2909.100.2.207.
  58. ↑ Rolfhus, E.L.. & Ackerman, P.L. (1996). Self-report knowledge: At the crossroads of ability. inter- est, and personality. Journal of Educational Psychology, 88. 174- 188.
  59. ↑ Rocklin, T. (1994). The relationship between typical intellectual engagement and openness: A comment on Goff and Ackerman (1992). Journal of Educational Psychology, 86. 145-149.
  60. ↑ Holland, J.L. (1959). "A theory of vocational choice". Journal of Counseling Psychology. 6: 35–45. doi:10.1037/h0040767.
  61. ↑ Holland, J.L. (1973). Making vocational choices: A theory of careers. Englewood Cliffs, NJ: Pren- tice-Hall.
  62. ↑ Osborn, F. (1937). "Development of a Eugenic Philosophy". American Sociological Review. 2 (3): 389–397. doi:10.2307/2084871. JSTOR 2084871.
  63. ↑ Tang YP, Shimizu E, Dube GR, et al. (1999). "Genetic enhancement of learning and memory in mice". Nature. 401 (6748): 63–9. Bibcode:1999Natur.401...63T. doi:10.1038/43432. PMID 10485705.
  64. ↑ Johnson, W.; Brett, C. E.; Deary, I. J. (2010). "The pivotal role of education in the association between ability and social class attainment: A look across three generations". Intelligence. 38: 55–65. doi:10.1016/j.intell.2009.11.008.
  65. ↑ Brinch, C. N.; Galloway, T. A. (2012). "Schooling in adolescence raises IQ scores". Proceedings of the National Academy of Sciences USA. 109: 425–30. doi:10.1073/pnas.1106077109. PMC 3258640Freely accessible. PMID 22203952.
  66. ↑ Shipstead, Zach; Redick, Thomas S.; Engle, Randall W. (2010). "Does Working Memory Training Generalize?". Psychologica Belgica. 50 (3–4): 245–276. doi:10.5334/pb-50-3-4-245.
  67. ↑ Jaeggi, S. M., Buschkuehl, M., Jonides, J., Perrig, W. J. (2008), Improving fluid intelligence with training on working memory, Proceedings of the National Academy of Sciences, vol. 105 no. 19
  68. ↑ Alexis Madrigal, Forget Brain Age: Researchers Develop Software That Makes You Smarter, Wired, April 2008
  69. ↑ Moody, D. E. (2009). "Can intelligence be increased by training on a task of working memory?". Intelligence. 37 (4): 327–328. doi:10.1016/j.intell.2009.04.005.
  70. ↑ Jensen, A. R. (1998). The g factor: The science of mental ability. Westport, CT: Praeger.
  71. ↑ Warne, R. T.; Godwin, L. R.; Smith, K. V. (2013). "Are there more gifted people than would be expected in a normal distribution? An investigation of the overabundance hypothesis". Journal of Advanced Academics. 24: 224–241. doi:10.1177/1932202x13507969.
  72. ↑ Ritter, N.; Kilinc, E.; Navruz, B.; Bae, Y. (2011). "Test Review: Test of Nonverbal Intelligence-4 (TONI-4)". Journal of Psychoeducational Assessment. 29 (5): 384–388. doi:10.1177/0734282911400400.
  73. ↑ Geary, David M. (2004). The Origin of the Mind: Evolution of Brain, Cognition, and General Intelligence. American Psychological Association (APA). ISBN 1-59147-181-8. OCLC 217494183.
  74. ↑ Ree, M.J.; Earles, J.A. (1992). "Intelligence Is the Best Predictor of Job Performance". Current Directions in Psychological Science. 1 (3): 86–89. doi:10.1111/1467-8721.ep10768746.
  75. ↑ Delen, E.; Kaya, F.; Ritter, N. (2012). "Test review: Test of Comprehensive Nonverbal Intelligence-2 (CTONI-2)". Journal of Psychoeducational Assessment. 30 (2): 209–213. doi:10.1177/0734282911415614.
  76. ↑ van der Maas, H. L. J.; Dolan, C. V.; Grasman, R. P. P. P.; Wicherts, J. M.; Huizenga, H. M.; Raijmakers, M. E. J. (2006). "A dynamical model of general intelligence: The positive manifold of intelligence by mutualism". Psychological Review. 113 (4): 842–861. doi:10.1037/0033-295X.113.4.842. PMID 17014305.
  77. ↑ Marshalek, B.; Lohman, D. F.; Snow, R. E. (1983). "The complexity continuum in the radex and hierarchical models of intelligence". Intelligence. 7 (2): 107–127. doi:10.1016/0160-2896(83)90023-5.
  78. ↑ Lynnn, R.; Irving, P. (2004). "Sex differences on the progressive matrices: A meta-analysis". Intelligence. 32 (5): 481–498. doi:10.1016/j.intell.2004.06.008.
  79. ↑ Halpern, D. F.; LaMay, M. L. (2000). "The smarter sex: A critical review of sex differences in intelligence". Educational Psychology Review. 12 (2): 229–246. doi:10.1023/A:1009027516424.
  80. ↑ Woolley, Anita Williams; Chabris, Christopher F.; Pentland, Alex; Hashmi, Nada; Malone, Thomas W. (2010-10-29). "Evidence for a Collective Intelligence Factor in the Performance of Human Groups". Science. 330 (6004): 686–688. doi:10.1126/science.1193147. ISSN 0036-8075. PMID 20929725.
  81. ↑ Spearman, C.E. (1904). ""General intelligence," objectively determined and measured". American Journal of Psychology. 15: 201–293.
  82. ↑ Woolley, Anita Williams; Aggarwal, Ishani; Malone, Thomas W. (2015-12-01). "Collective Intelligence and Group Performance". Current Directions in Psychological Science. 24 (6): 420–424. doi:10.1177/0963721415599543. ISSN 0963-7214.
  83. 1 2 3 IQ Testing 101, Alan S. Kaufman, 2009, Springer Publishing Company, ISBN 978-0-8261-0629-2
  84. 1 2 The Mismeasure of Man, Stephen Jay Gould, Norton, 1996
  85. ↑ Jensen, A.R. (1982). "The debunking of scientific fossils and straw persons". Contemporary Education Review. 1 (2): 121–135. Retrieved 2008-03-18.
  86. ↑ Schlinger, H.D. (2003). "The Myth of Intelligence". The Psychological Record. 53 (1): 15–33. Retrieved 2008-03-18.

Further reading

This article is issued from Wikipedia - version of the 11/20/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.