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Human intelligence is the intellectual prowess of humans, which is marked by complex cognitive feats and high levels of motivation and self-awareness. 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, solve problems, make decisions, retain information, and use language to communicate.
- 1 Correlates
- 2 Theories
- 2.1 Relevance of IQ tests
- 2.2 Theory of multiple intelligences
- 2.3 Triarchic theory of intelligence
- 2.4 PASS theory of intelligence
- 2.5 Piaget's theory and Neo-Piagetian theories
- 2.6 Parieto-frontal integration theory of intelligence
- 2.7 Investment theory
- 2.8 Intelligence compensation theory (ICT)
- 2.9 Bandura's theory of self-efficacy and cognition
- 2.10 Process, personality, intelligence and knowledge theory (PPIK)
- 2.11 Latent inhibition
- 3 Improving
- 4 Measuring
- 5 Intelligence across cultures
- 6 See also
- 7 References
- 8 Further reading
As a construct and measured by intelligence tests, intelligence is one of the most useful concepts used in psychology, because it correlates with lots of relevant variables, like the probability of suffering an accident, earning a higher salary, etc.
A number of studies have shown a correlation between IQ and myopia. 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.
There is evidence that aging causes decline in cognitive functions. In one cross-sectional study, various cognitive functions measured declines by about 0.8 in z-score from age 20 to age 50, the cognitive functions included speed of processing, working memory and long term memory.
Relevance of IQ tests
In psychology, human intelligence is commonly assessed by IQ scores, determined by IQ tests. However, 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.
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.
Theory of multiple intelligences
Howard Gardner's theory of multiple intelligences is based on studies not only of normal children and adults, but also of gifted individuals (including so-called "savants"), of persons who have suffered brain damage, of experts and virtuosos, and of individuals from diverse cultures. Gardner breaks 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 (IQ) tests address only linguistic and logical plus some aspects of spatial intelligence. 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. 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. On the other hand, Jerome Bruner agreed with Gardner that the intelligences were "useful fictions," and went on to state that "his approach is so far beyond the data-crunching of mental testers that it deserves to be cheered."
Howard Gardner describes his first seven intelligences as follows:
- Linguistic intelligence: People high in linguistic intelligence have an affinity for words, both spoken and written.
- Logical-mathematical intelligence: It implies logical and mathematical abilities.
- Spatial intelligence: The ability to form a mental model of a spatial world and to be able to maneuver and operate using that model.
- Musical intelligence: Those with musical intelligence have excellent pitch, and may even be absolute pitch.
- Bodily-kinesthetic intelligence: The ability to solve problems or to fashion products using one's whole body, or parts of the body. Gifted people in this intelligence may be good dancers, athletes, surgeons, craftspeople, and others.
- Interpersonal intelligence: The ability to see things from the perspective of others, or to understand people in the sense of empathy. Strong interpersonal intelligence would be an asset in those who are teachers, politicians, clinicians, religious leaders, etc.
- Intrapersonal intelligence: It is a capacity to form an accurate, veridical model of oneself and to be able to use that model to operate effectively in life.
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. 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 as the Theory of Successful Intelligence by Sternberg. Intelligence is now 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.
PASS theory of intelligence
Based on A. R. Luria's (1966) seminal work on the modularization of brain function, and supported by decades of neuroimaging research, the PASS Theory of Intelligence proposes that cognition is organized in three systems and four processes. The first process 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, 1973), and studies in cognitive psychology involved in promoting a better look at intelligence.
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:
- sensory motor stage (birth-2yrs);
- pre-operational stage (2yrs-7rs);
- concrete operational stage (7rs-11yrs); and
- formal operations stage (11yrs-16yrs)
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". 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. 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.
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.
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.
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. Subsequent neuroimaging and lesion studies report general consensus with the theory. A review of the neuroscience and intelligence literature concludes that the parieto-frontal integration theory is the best available explanation for human intelligence differences.
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. The 'investment theory' by Cattell 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. It is essential to highlight that the investment theory suggests that personality traits affect 'actual' ability, and not scores on an IQ test. 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.
Intelligence compensation theory (ICT)
The intelligence compensation theory (a term first coined by Wood and Englert, 2009) 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. 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; 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.
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.
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. Bandura's 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.
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 more slowly 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.
Process, personality, intelligence and knowledge theory (PPIK)
This section needs expansion with: more extensive and clear explanations. You can help by adding to it. (March 2018)
Developed by Ackerman, the PPIK (process, personality, intelligence and knowledge) theory further develops the approach on intelligence as proposed by Cattell, the Investment theory and Hebb, suggesting a distinction between intelligence as knowledge and intelligence as process (two concepts that are comparable and related to Gc and Gf respectively, but broader and closer to Hebb's notions of "Intelligence A" and "Intelligence B") and integrating these factors with elements such as personality, motivation and interests.
Ackerman describes the difficulty of distinguishing process from knowledge, as content cannot be entirely eliminated from any ability test. Personality traits have not shown to be significantly correlated with the intelligence as process aspect 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. On the other hand, the intelligence as knowledge factor has been associated with personality traits of Openness and Typical Intellectual Engagement, which also strongly correlate with verbal abilities (associated with crystallized intelligence).
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.
IQ leads to greater success in education, but independently education raises IQ scores. A 2017 meta-analysis suggests education increases IQ by 1-5 points per year of education, or at least increases IQ test taking ability.
Attempts to raise IQ with brain training have led to increases on aspects related with the training tasks – for instance working memory – but it is yet unclear if these increases generalise to increased intelligence per se.
A 2008 research paper claimed that practicing a dual n-back task can increase fluid intelligence (Gf), as measured in several different standard tests. This finding received some attention from popular media, including an article in Wired. 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. 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).
Substances which actually or purportedly improve intelligence or other mental functions are called nootropics. A meta analysis shows omega 3 fatty acids improves cognitive performance among those with cognitive deficits, but not among healthy subjects. A meta-regression shows omega 3 fatty acids improve the moods of patients with major depression (major depression is associated with mental deficits). However, exercise, not just performance-enhancing drugs, enhances cognition for healthy and non healthy subjects as well.
On the philosophical front, conscious efforts to influence intelligence raise ethical issues. 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.
Transhumanist theorists study the possibilities and consequences of developing and using techniques to enhance human abilities and aptitudes.
Eugenics is a social philosophy which advocates the improvement of human hereditary traits through various forms of intervention. 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.
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. 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.
Intelligence tests are widely used in educational, 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. Intelligence is significantly correlated with successful training and performance outcomes, and IQ/g is the single best predictor of successful job performance.
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, 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. (Although, an alternative interpretation was recently advanced by van der Maas and colleagues. 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 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, which are not found when g is measured directly by computing the general factor from a broad collection of tests.
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, 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. 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.
Historical psychometric theories
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 for human intelligence 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:
- Fluid intelligence (Gf): includes the broad ability to reason, form concepts, and solve problems using unfamiliar information or novel procedures.
- Crystallized intelligence (Gc): includes the breadth and depth of a person's acquired knowledge, the ability to communicate one's knowledge, and the ability to reason using previously learned experiences or procedures.
- Quantitative reasoning (Gq): the ability to comprehend quantitative concepts and relationships and to manipulate numerical symbols.
- Reading & writing ability (Grw): includes basic reading and writing skills.
- Short-term memory (Gsm): is the ability to apprehend and hold information in immediate awareness and then use it within a few seconds.
- Long-term storage and retrieval (Glr): is the ability to store information and fluently retrieve it later in the process of thinking.
- Visual processing (Gv): is the ability to perceive, analyze, synthesize, and think with visual patterns, including the ability to store and recall visual representations.
- Auditory processing (Ga): is the ability to analyze, synthesize, and discriminate auditory stimuli, including the ability to process and discriminate speech sounds that may be presented under distorted conditions.
- Processing speed (Gs): is the ability to perform automatic cognitive tasks, particularly when measured under pressure to maintain focused attention.
- Decision/reaction time/speed (Gt): reflect the immediacy with which an individual can react to stimuli or a task (typically measured in seconds or fractions of seconds; not to be confused with Gs, which typically is measured in intervals of 2–3 minutes). See Mental chronometry.
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. 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.
While not necessarily a dispute about the psychometric approach itself, there are several controversies regarding the results from psychometric research.
One criticism has been against the early research such as craniometry. 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.
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. 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.
Intelligence across cultures
Psychologists have shown that the definition of human intelligence is unique to the culture that one is studying. Robert Sternberg is among the researchers who have discussed how one's culture affects the person's interpretation of intelligence, and he further believes that to define intelligence in only one way without considering different meanings in cultural contexts may cast an investigative and unintentionally egocentric view on the world. To negate this, psychologists offer the following definitions of intelligence:
- Successful intelligence is the skills and knowledge needed for success in life, according to one's own definition of success, within one's sociocultural context.
- Analytical intelligence is the result of intelligence's components applied to fairly abstract but familiar kinds of problems.
- Creative intelligence is the result of intelligence's components applied to relatively novel tasks and situations.
- Practical intelligence is the result of intelligence's components applied to experience for purposes of adaption, shaping and selection.
Although typically identified by its western definition, multiple studies support the idea that human intelligence carries different meanings across cultures around the world. In many Eastern cultures, intelligence is mainly related with one's social roles and responsibilities. A Chinese conception of intelligence would define it as the ability to empathize with and understand others — although this is by no means the only way that intelligence is defined in China. In several African communities, intelligence is shown similarly through a social lens. However, rather than through social roles, as in many Eastern cultures, it is exemplified through social responsibilities. For example, in the language of Chi-Chewa, which is spoken by some ten million people across central Africa, the equivalent term for intelligence implies not only cleverness but also the ability to take on responsibility. Furthermore, within American culture there are a variety of interpretations of intelligence present as well. One of the most common views on intelligence within American societies defines it as a combination of problem-solving skills, deductive reasoning skills, and Intelligence quotient (IQ), while other American societies point out that intelligent people should have a social conscience, accept others for who they are, and be able to give advice or wisdom.
- Neuroscience and intelligence § Humans
- Outline of human intelligence
- Race and intelligence
- Self-test of Intelligence
- Sex and intelligence
- Theory of multiple intelligences
- Volition (psychology)
- Tirri, Nokelainen (2011). Measuring Multiple Intelligences and Moral Sensitivities in Education. Moral Development and Citizenship Education. Springer. ISBN 978-94-6091-758-5.
- Triglia, A.; Regader, B.; & García-Allen, J.; (2018). "¿Qué es la inteligencia? Del CI a las inteligencias múltiples". Barcelona: EMSE.
- Ritchie, Stuart J.; Tucker-Drob, Elliot M. (2018-06-18). "How Much Does Education Improve Intelligence? A Meta-Analysis". Psychological Science. 28 (8): 1358–1369. doi:10.1177/0956797618774253. PMC 6088505. PMID 29911926.
- Rosenfield, Mark; Gilmartin, Bernard (1998). Myopia and nearwork. Elsevier Health Sciences. p. 23. ISBN 978-0-7506-3784-8.
- 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.
- Denise C. Park, Gérard N. Bischof. "The aging mind: neuroplasticity in response to cognitive training". Retrieved 24 November 2017.CS1 maint: Uses authors parameter (link)
- 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
- 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.
-  Archived January 13, 2010, at the Wayback Machine
- Bruner, Jerome S. "State of the Child". The New York Review of Books. Retrieved 2018-10-16.
- Multiple Intelligences: The Theory in Practice, A Reader. New York: Basic Books. 1993. ISBN 978-0-465-01822-2.
- Sternberg, R.J. (1985). Beyond IQ: A triarchic theory of human intelligence. New York: Cambridge University Press. ISBN 978-0-521-26254-5.
- Sternberg, R.J. (1978). "The theory of successful intelligence". Review of General Psychology. 3 (4): 292–316. doi:10.1037/1089-26126.96.36.1992.
- Sternberg, R.J. (2003). "A broad view of intelligence: The theory of successful intelligence". Consulting Psychology Journal: Practice and Research. 55 (3): 139–154. doi:10.1037/1061-4087.55.3.139.
- 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.
- Brody, N. (2003). "What Sternberg should have concluded". Intelligence. 31 (4): 339–342. doi:10.1016/S0160-2896(02)00190-3.
- 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.
- Gottfredson, L.S. (2003). "On Sternberg's 'Reply to Gottfredson'". Intelligence. 31 (4): 415–424. doi:10.1016/S0160-2896(03)00024-2.
- Luria, A. R. (1966). Higher cortical functions in man. New York: Basic Books.
- Das, J. P., Naglieri, J. A., & Kirby, J. R. (1994). Assessment of cognitive processes. Needham Heights, MA: Allyn & Bacon.
- Luria, A. R. (1973). The working brain: An introduction to neuropsychology. New York.
- Das, J.P. (2002). "A Better look at Intelligence". Current Directions in Psychology. 11 (1): 28–32. doi:10.1111/1467-8721.00162.
- Piaget, J. (2001). Psychology of intelligence. Routledge.
- Elkind, D., & Flavell, J. (1969). Studies in cognitive development: Essays in honor of Jean Piaget. New York: Oxford University Press
- Weinberg, Richard A. (1989). "Intelligence and IQ, Landmark Issues and Great Debates". American Psychologist. 44 (2): 98–104. doi:10.1037/0003-066x.44.2.98.
- Piaget, J. (1953). The origin of intelligence in the child. New Fetter Lane, New York: Routledge & Kegan Paul.
- 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.
- 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.
- 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.
- Jung, R. E.; Haier, R. J. (2007). "The parieto-frontal integration theory (P-FIT) of intelligence: converging neuroimaging evidence". Behavioral and Brain Sciences. 30 (2): 135–187. doi:10.1017/s0140525x07001185. PMID 17655784.
- 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 (2): 124–135. doi:10.1016/j.intell.2008.07.007.
- 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. PMID 25284305.
- 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. PMC 3980800. PMID 23171618.
- Deary, I. J.; Penke, L.; Johnson, W. (2010). "The neuroscience of human intelligence differences" (PDF). Nature Reviews Neuroscience. 11 (3): 201–211. doi:10.1038/nrn2793. PMID 20145623.
- 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.
- Cattell, R. B. (1987). Intelligence: Its structure, growth and action. New York: North-Holland.
- 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. hdl:10419/78682.
- Cattell, R. B. (1971). Abilities: their structure, growth, and action. Boston: Houghton Mifflin.
- 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.
- 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.
- Chamorro-Premuzic, T.; Furnham, A. (2004). "A possible model for explaining the personality–intelligence interface". British Journal of Psychology. 95 (2): 249–264. doi:10.1348/000712604773952458. PMID 15142305.
- 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.
- 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.
- Brody, N. (1992). Intelligence (2nd ed.). New York: Academic Press.
- 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.
- Wood, R., & Bandura, A. (198913). Social cognitive theory of organizational management. Academy of Management Review, 14, 361-384.
- Bandura, A (1993). "Perceived self-efficacy in cognitive development and functioning". Educational Psychologist. 28 (2): 117–148. doi:10.1207/s15326985ep2802_3.
- 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.
- Ackerman, P.L. (1995, August). Personality, intelligence, motivation, and interests: Implications for overlapping traits. Address presented at the annual meeting of the American Psychological Association, New York.
- Detterman, D.K., & Andrist, C.G. (1990). Effect of instructions on elementary cognitive tasks sensitive to individual differences. American Journal of Psychology: 103. 367-390.
- Signorella, M.L.; Jamison, W. (1986). "Masculinity, femininity, androgyny and cognitive performance: A meta-analysis". Psychological Bulletin. 100 (2): 207–238. doi:10.1037/0033-2909.100.2.207.
- 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.
- 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.
- 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.
- 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.
- Brinch, C. N.; Galloway, T. A. (2012). "Schooling in adolescence raises IQ scores". Proceedings of the National Academy of Sciences USA. 109 (2): 425–30. Bibcode:2012PNAS..109..425B. doi:10.1073/pnas.1106077109. PMC 3258640. PMID 22203952.
- "How much does education improve intelligence? A meta-analysis".
- 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.
- Simons, Daniel J.; Boot, Walter R.; Charness, Neil; Gathercole, Susan E.; Chabris, Christopher F.; Hambrick, David Z.; Stine-Morrow, Elizabeth A. L. (2016). "Do "Brain-Training" Programs Work?". Psychological Science in the Public Interest. 17 (3): 103–186. doi:10.1177/1529100616661983. PMID 27697851.
- 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
- Alexis Madrigal, Forget Brain Age: Researchers Develop Software That Makes You Smarter, Wired, April 2008
- 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.
- Mazereeuw G, Lanctôt KL, Chau SA, Swardfager W, Herrmann N (July 2012). "Effects of ω-3 fatty acids on cognitive performance: a meta-analysis". Neurobiology of Aging. 33 (7): 1482.e17–29. doi:10.1016/j.neurobiolaging.2011.12.014. PMID 22305186.
- Mocking RJ, Harmsen I, Assies J, Koeter MW, Ruhé HG, Schene AH (March 2016). "Meta-analysis and meta-regression of omega-3 polyunsaturated fatty acid supplementation for major depressive disorder". Translational Psychiatry. 6 (3): e756. doi:10.1038/tp.2016.29. PMC 4872453. PMID 26978738.
- Caviola L, Faber NS (2 December 2015). "Pills or Push-Ups? Effectiveness and Public Perception of Pharmacological and Non-Pharmacological Cognitive Enhancement". Frontiers in Psychology. 6: 1852. doi:10.3389/fpsyg.2015.01852. PMC 4667098. PMID 26696922.
- Osborn, F. (1937). "Development of a Eugenic Philosophy". American Sociological Review. 2 (3): 389–397. doi:10.2307/2084871. JSTOR 2084871.
- Jensen, A. R. (1998). The g factor: The science of mental ability. Westport, CT: Praeger.
- 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 (4): 224–241. doi:10.1177/1932202x13507969.
- 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.
- Geary, David M. (2004). The Origin of the Mind: Evolution of Brain, Cognition, and General Intelligence. American Psychological Association (APA). ISBN 978-1-59147-181-3. OCLC 217494183.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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. Bibcode:2010Sci...330..686W. doi:10.1126/science.1193147. ISSN 0036-8075. PMID 20929725.
- Spearman, C.E. (1904). ""General intelligence," objectively determined and measured". American Journal of Psychology. 15 (2): 201–293. doi:10.2307/1412107. JSTOR 1412107.
- 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.
- IQ Testing 101, Alan S. Kaufman, 2009, Springer Publishing Company, ISBN 978-0-8261-0629-2
- The Mismeasure of Man, Stephen Jay Gould, Norton, 1996
- Jensen, A.R. (1982). "The debunking of scientific fossils and straw persons". Contemporary Education Review. 1 (2): 121–135. Retrieved 2008-03-18.
- Schlinger, H.D. (2003). "The Myth of Intelligence". The Psychological Record. 53 (1): 15–33. Retrieved 2008-03-18.
- Intelligence and Culture, Robert Sternberg, American Psychologist, American Psychological Association, 2004, Vol. 59, No. 5, pp. 325-338.
- Intelligence and Culture, Robert Serpell, Handbook of Intelligence, Cambridge University Press, 2000, pp. 549-578.
- Mackintosh, N. J. (2011). IQ and Human Intelligence (second ed.). Oxford: Oxford University Press. ISBN 978-0-19-958559-5. Lay summary (9 February 2012). The second edition of a leading textbook on human intelligence, used in highly selective universities throughout the English-speaking world, with extensive references to research literature.
- Hunt, Earl (2011). Human Intelligence. Cambridge: Cambridge University Press. ISBN 978-0-521-70781-7. Lay summary (28 April 2013). First edition of a comprehensive textbook by a veteran scholar of human intelligence.
- Nisbett, Richard E.; Aronson, Joshua; Blair, Clancy; Dickens, William; Flynn, James; Halpern, Diane F.; Turkheimer, Eric (2012). "Intelligence: new findings and theoretical developments" (PDF). American Psychologist. 67 (2): 130–159. doi:10.1037/a0026699. ISSN 0003-066X. PMID 22233090. Retrieved 22 July 2013. Lay summary (22 July 2013). Major review article in a flagship publication of the American Psychological Association, a thorough review of current research.
- Sternberg, Robert J.; Kaufman, Scott Barry, eds. (2011). The Cambridge Handbook of Intelligence. Cambridge: Cambridge University Press. ISBN 9780521739115. Lay summary (22 July 2013). Authoritative handbook for graduate students and practitioners, with chapters by a variety of authors on most aspects of human intelligence.