Intelligence has been defined in many different ways including as one's capacity for logic, understanding, self-awareness, learning, emotional knowledge, planning, creativity and problem solving. It can be more generally described as the ability to perceive information, and to retain it as knowledge to be applied towards adaptive behaviors within an environment or context.
Intelligence is most widely studied in humans, but has also been observed in non-human animals and in plants. Artificial intelligence is intelligence in machines. It is commonly implemented in computer systems using program software.
Within the discipline of psychology, various approaches to human intelligence have been adopted. The psychometric approach is especially familiar to the general public, as well as being the most researched and by far the most widely used in practical settings.
History of the term
Intelligence derives from the Latin verb ability to think intelligere, to comprehend or perceive. A form of this verb, intellectus, became the medieval technical term for understanding, and a translation for the Greek philosophical term nous. This term was however strongly linked to the metaphysical and cosmological theories of teleological scholasticism, including theories of the immortality of the soul, and the concept of the Active Intellect (also known as the Active Intelligence). This entire approach to the study of nature was strongly rejected by the early modern philosophers such as Francis Bacon, Thomas Hobbes, John Locke, and David Hume, all of whom preferred the word "understanding" in their English philosophical works. Hobbes for example, in his Latin De Corpore, used "intellectus intelligit" (translated in the English version as "the understanding understandeth") as a typical example of a logical absurdity. The term "intelligence" has therefore become less common in English language philosophy, but it has later been taken up (with the scholastic theories which it now implies) in more contemporary psychology.
A very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. It is not merely book learning, a narrow academic skill, or test-taking smarts. Rather, it reflects a broader and deeper capability for comprehending our surroundings—"catching on," "making sense" of things, or "figuring out" what to do.
Individuals differ from one another in their ability to understand complex ideas, to adapt effectively to the environment, to learn from experience, to engage in various forms of reasoning, to overcome obstacles by taking thought. Although these individual differences can be substantial, they are never entirely consistent: a given person's intellectual performance will vary on different occasions, in different domains, as judged by different criteria. Concepts of "intelligence" are attempts to clarify and organize this complex set of phenomena. Although considerable clarity has been achieved in some areas, no such conceptualization has yet answered all the important questions, and none commands universal assent. Indeed, when two dozen prominent theorists were recently asked to define intelligence, they gave two dozen, somewhat different, definitions.
|Alfred Binet||Judgment, otherwise called "good sense," "practical sense," "initiative," the faculty of adapting one's self to circumstances ... auto-critique.|
|David Wechsler||The aggregate or global capacity of the individual to act purposefully, to think rationally, and to deal effectively with his environment.|
|Lloyd Humphreys||"...the resultant of the process of acquiring, storing in memory, retrieving, combining, comparing, and using in new contexts information and conceptual skills."|
|Cyril Burt||Innate general cognitive ability|
|Howard Gardner||To my mind, a human intellectual competence must entail a set of skills of problem solving — enabling the individual to resolve genuine problems or difficulties that he or she encounters and, when appropriate, to create an effective product — and must also entail the potential for finding or creating problems — and thereby laying the groundwork for the acquisition of new knowledge.|
|Linda Gottfredson||The ability to deal with cognitive complexity.|
|Sternberg & Salter||Goal-directed adaptive behavior.|
|Reuven Feuerstein||The theory of Structural Cognitive Modifiability describes intelligence as "the unique propensity of human beings to change or modify the structure of their cognitive functioning to adapt to the changing demands of a life situation."|
|Charles Spearman||"...all branches of intellectual activity have in common one fundamental function, whereas the remaining or specific elements of the activity seem in every case to be wholly different from that in all the others."|
|Legg & Hutter||A synthesis of 70+ definitions from psychology, philosophy, and AI researchers: "Intelligence measures an agent’s ability to achieve goals in a wide range of environments," which has been mathematically formalized.|
|Alexander Wissner-Gross||F = T ∇ Sτ |
What is considered intelligent varies with culture. For example, when asked to sort, the Kpelle people take a functional approach (metaphorical). A Kpelle participant stated "the knife goes with the orange because it cuts it." (metonymical). When asked how a fool would sort, they sorted linguistically, putting the knife with other implements and the orange with other foods (also metaphorical), which is the style considered intelligent in other cultures.
Human intelligence is the intellectual capacity of humans, which is characterized by perception, consciousness, self-awareness, and volition. Intelligence enables humans to remember descriptions of things and use those descriptions in future behaviors. It is a cognitive process. It gives humans the cognitive abilities to learn, form concepts, understand, and reason, including the capacities to recognize patterns, comprehend ideas, plan, problem solve, and use language to communicate. Intelligence enables humans to experience and think.
Note that much of the above definition applies also to the intelligence of non-human animals.
Although humans have been the primary focus of intelligence researchers, scientists have also attempted to investigate animal intelligence, or more broadly, animal cognition. These researchers are interested in studying both mental ability in a particular species, and comparing abilities between species. They study various measures of problem solving, as well as numerical and verbal reasoning abilities. Some challenges in this area are defining intelligence so that it has the same meaning across species (e.g. comparing intelligence between literate humans and illiterate animals), and also operationalizing a measure that accurately compares mental ability across different species and contexts.
Wolfgang Köhler's research on the intelligence of apes is an example of research in this area. Stanley Coren's book, The Intelligence of Dogs is a notable book on the topic of dog intelligence. (See also: Dog intelligence.) Non-human animals particularly noted and studied for their intelligence include chimpanzees, bonobos (notably the language-using Kanzi) and other great apes, dolphins, elephants and to some extent parrots, rats and ravens.
Cephalopod intelligence also provides important comparative study. Cephalopods appear to exhibit characteristics of significant intelligence, yet their nervous systems differ radically from those of backboned animals. Vertebrates such as mammals, birds, reptiles and fish have shown a fairly high degree of intellect that varies according to each species. The same is true with arthropods.
g factor in non-humans
Evidence of a general factor of intelligence has been observed in non-human animals. The general factor of intelligence, or g factor, is a psychometric construct that summarizes the correlations observed between an individual’s scores on a wide range of cognitive abilities. First described in humans, the g factor has since been identified in a number of non-human species.
Cognitive ability and intelligence cannot be measured using the same, largely verbally dependent, scales developed for humans. Instead, intelligence is measured using a variety of interactive and observational tools focusing on innovation, habit reversal, social learning, and responses to novelty. Studies have shown that g is responsible for 47% of the individual variance in cognitive ability measures in primates and between 55% and 60% of the variance in mice (Locurto, Locurto). These values are similar to the accepted variance in IQ explained by g in humans (40-50%).
It has been argued that plants should also be classified as intelligent based on their ability to sense and model external and internal environments and adjust their morphology, physiology and phenotype accordingly to ensure self-preservation and reproduction.
A counter argument is that intelligence is commonly understood to involve the creation and use of persistent memories as opposed to computation that does not involve learning. If this is accepted as definitive of intelligence, then it includes the artificial intelligence of robots capable of "machine learning", but excludes those purely autonomic sense-reaction responses that can be observed in many plants. Plants are not limited to automated sensory-motor responses, however, they are capable of discriminating positive and negative experiences and of 'learning' (registering memories) from their past experiences. They are also capable of communication, accurately computing their circumstances, using sophisticated cost–benefit analysis and taking tightly controlled actions to mitigate and control the diverse environmental stressors.
Artificial intelligence (or AI) is both the intelligence of machines and the branch of computer science which aims to create it, through "the study and design of intelligent agents" or "rational agents", where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. Achievements in artificial intelligence include constrained and well-defined problems such as games, crossword-solving and optical character recognition and a few more general problems such as autonomous cars. General intelligence or strong AI has not yet been achieved and is a long-term goal of AI research.
Among the traits that researchers hope machines will exhibit are reasoning, knowledge, planning, learning, communication, perception, and the ability to move and to manipulate objects. In the field of artificial intelligence there is no consensus on how closely the brain should be simulated.
A theory of hierarchical learning mechanisms, named practopoiesis, may be able to provide a conceptual bridge between biological and artificial intelligence.
Culture's influence on intelligence
Intelligence and culture are very distinct terms. Intelligence can be defined as a person’s cognitive abilities to learn. It is also associated with school performance, IQ, logic, abstract thought, self-awareness, emotional knowledge, memory, planning, creativity, and problem solving. Culture can be defined as a way of life that influences our views, experiences, and engagement with our lives and the world around us. It is shaped by the political, social, and environmental contexts in which we live. Together these form part of the sociocultural theory, coined by Lev Vygotsky. The sociocultural theory investigates “how social factors influence cognition and development, and how social and cultural practices shape and define thought” (Siegler & Abibali, p. 108). More specifically, culture shapes intelligence.
Intelligence and culture is most widely studied in humans. There are not any known studies that exam the culture and intelligence of non-human or plant life in the same way. These are psychological terms that are most easily identified in humans.
The sociocultural theory closely relates to intelligence and culture. Lev Vygotsky was the first researcher to define the sociocultural theory. The theory proposes that children learn a larger part of their cognitive abilities from social interactions with adults or older children and people. He distinctly defines this as the Zone of Proximal Development. Older people provide scaffolding, or tools that help children improve their cognitive abilities. Successful intelligence incorporates the socio-cultural environment and people’s ability to be successful in the environment and in their personal standards (Steinberg & Grigorenko, 2004). Different cultures value different things and have different experiences. This will greatly influence what they need to succeed in their world.
Sternberg (2004) discusses a study where they tested children in a village in Kenya on their knowledge of natural herbal medicine. Many in this area of Kenya do not have Westernized schooling or strive for a Westernized education. Therefore, Sternberg (2004) found that they had great knowledge of their herbal medicines, but they scored lower on vocabulary tests. They also discuss how Western children may have knowledge of the herbal medicines, but it would not be as extensive as the Kenyan children’s knowledge (Sternberg et al., 2001). This demonstrates different forms of intelligence in different contexts. One is not better than the other, and the type of knowledge that these children have is beneficial for their environment. Intelligence is moldable by culture.
When we combine intelligence and the sociocultural influence, we see that culture has a significant impact on cognitive development and thus school and learning. Siegler and Alibali (2005) gave examples of this from other studies where they found that children of different cultures spend their time participating in different activities. For example, the Korean and American children spent less of their time in formal and informal lessons and work than those in Russia and Estonia (Tudge et al., 1999). In addition, the book continues to discuss cultural norms influence child development and their abilities to perform certain tasks. This can also apply to intelligence in a school and learning context if culture is truly influential. Stevenson and colleagues’ (1986) study supports this assumption. They examined Japanese, Taiwanese, and American mothers’ different values and beliefs about their children’s education. The children took reading and mathematical tests, and the United States children performed worse than the Taiwanese and Japanese children. Researchers found that the mothers’ attitudes about school influenced achievement. For example, the Asian mothers were more likely to help them with their homework. Therefore, definitions and the value of intelligence can be different across cultures. Several other studies explore and define the relation between intelligence and culture. The first study by Greenfield and Quiroz (2013) explored the differences between Latino immigrant parents and European American parents. More specifically, they examined how the different culture valued personal achievement for their children. Their research found that Latino families had more familistic values, family before outsiders, whereas European Americans had more individualistic values. The interviews consisted of conflict scenarios about family reactions school performance and the importance of family. There were 74% of Latino parents that believed the child should be able to leave school to care for his brother at home and only 31% of European American parents believed this. These results imply that there are differences in values of family life and culture that influence children’s view on education and thus intelligence.
The second study conducted by Brooks-Gunn and colleagues (1996) looked at IQ score difference among black and white children and their home environment, birth weight, and financial situation. The main point was that maternal education influences this difference. People in poverty are less likely to have a degree from higher education. The children will only learn from their environment and interactions with people in their neighborhood and family members. This creates a cultural difference in the value of intelligence and education. Brooks-Gunn and colleagues (1996) pointed out that the learning experience in the home of the black children was very different or was not as valued as the experience in white children’s homes.
The Jose and Bellamy (2011) article examined students in the US, New Zealand, China, and Japan and the different ways that parents influenced their children’s persistence. The results indicated that US parents valued incremental theory of intelligence the most, Chinese parents encouraged their kids the most and were most persistent, and New Zealand parents had more significant levels of frustration. The more parents supported incremental learning the more the children were persistent on the task. The main claim that the researchers made was that Asian parents motivate their children to learn in a different way than Western parents do. This study was not so much about levels of intelligence than the way that culture shapes learning and intelligence. It, evidently, varies across cultures. Lastly, Wentzel (1998) conducted a study also assessing how parents shape children’s ways of learning and motivation to learn. Parents and culture had an influence on children’s value of intelligence and learning and motivation. The main idea was that parents set their expectations for their children through their confidence in them, the nature of children’s intelligence, and achievement-related values.
Researchers can not particularly assign intelligence to one culture over another. Additionally, the studies imply that socio-culture plays one of the biggest roles in school achievement, educational motivation, learning abilities, and thus intelligence. That is, these children value what their parents, community, or culture values. This also shapes the way that they learn, the way that they approach problems, and how they value learning and certain educational skills. The main findings are that the way children learn, and thus their intelligence, is shaped by their culture and environment.
- Outline of human intelligence
- Active intellect
- Intelligence (journal)
- Neuroscience and intelligence
- Passive intellect
- Self-test of Intelligence
- Intelligence Quotient
- Theory of multiple intelligences
- 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. doi:10.1037/0003-066X.51.2.77. Article in Wikipedia: Intelligence: Knowns and Unknowns
- Maich, Aloysius (1995). "A Hobbes Dictionary". Blackwell: 305
- Nidditch, Peter. "Foreword". An Essay Concerning Human Understanding. Oxford University Press. p. xxii
- English, and Latin version.
- This paragraph almost verbatim from Goldstein, Sam; Princiotta, Dana; Naglieri, Jack A., Eds. (2015). Handbook of Intelligence: Evolutionary Theory, Historical Perspective, and Current Concepts. New York, Heidelberg, Dordrecht, London: Springer. p. 3. ISBN 978-1-4939-1561-3.
- S. Legg; M. Hutter. "A Collection of Definitions of Intelligence". 157: 17–24.
- Gottfredson 1997777, pp. 17–20
- Gottfredson, Linda S. (1997). "Mainstream Science on Intelligence (editorial)" (PDF). Intelligence. 24: 13–23. doi:10.1016/s0160-2896(97)90011-8. ISSN 0160-2896.
- Neisser, Ulrich; Boodoo, Gwyneth; Bouchard, Thomas J.; Boykin, A. Wade; Brody, Nathan; Ceci, Stephen J.; Halpern, Diane F.; Loehlin, John C.; Perloff, Robert; Sternberg, Robert J.; Urbina, Susana (1996). "Intelligence: Knowns and unknowns" (PDF). American Psychologist. 51: 77–101. doi:10.1037/0003-066x.51.2.77. ISSN 0003-066X. Retrieved 9 October 2014.
- Binet, Alfred (1916) . "New methods for the diagnosis of the intellectual level of subnormals". The development of intelligence in children: The Binet-Simon Scale. E.S. Kite (Trans.). Baltimore: Williams & Wilkins. pp. 37–90. Retrieved 10 July 2010.
originally published as Méthodes nouvelles pour le diagnostic du niveau intellectuel des anormaux. L'Année Psychologique, 11, 191-244
- Wechsler, D (1944). The measurement of adult intelligence. Baltimore: Williams & Wilkins. ISBN 0-19-502296-3. OCLC 219871557. ASIN = B000UG9J7E
- Humphreys, L. G. (1979). "The construct of general intelligence". Intelligence. 3 (2): 105–120. doi:10.1016/0160-2896(79)90009-6.
- Burt, C. (1954). "The Differentiation Of Intellectual Ability". The British Journal of Educational Psychology.
- Frames of mind: The theory of multiple intelligences. New York: Basic Books. 1993. ISBN 0-465-02510-2. OCLC 221932479.
- Gottfredson, L. (1998). "The General Intelligence Factor" (pdf). Scientific American Presents. 9 (4): 24–29. Retrieved 2008-03-18.
- Sternberg RJ; Salter W (1982). Handbook of human intelligence. Cambridge, UK: Cambridge University Press. ISBN 0-521-29687-0. OCLC 11226466.
- Feuerstein, R., Feuerstein, S., Falik, L & Rand, Y. (1979; 2002). Dynamic assessments of cognitive modifiability. ICELP Press, Jerusalem: Israel; Feuerstein, R. (1990). The theory of structural modifiability. In B. Presseisen (Ed.), Learning and thinking styles: Classroom interaction. Washington, DC: National Education Associations
- Spearman, C. (1904). “General intelligence” objectively determined and measured. American Journal of Psychology, 15, 201–293. (K. R-26)
- S. Legg; M. Hutter (2007). "Universal Intelligence: A Definition of Machine Intelligence". Minds & Machines. 17 (4): 391–444. doi:10.1007/s11023-007-9079-x.
- "TED Speaker: Alex Wissner-Gross: A new equation for intelligence". TED.com. Retrieved 2016-09-07.
- Glick (1975) reported in Resnick, L. (1976). The Nature of Intelligence. Hillsdale, New Jersey: Lawrence Erlbaum Associates.
- Coren, Stanley (1995). The Intelligence of Dogs. Bantam Books. ISBN 0-553-37452-4. OCLC 30700778.
- Reader, S. M., Hager, Y., & Laland, K. N. (2011). The evolution of primate general and cultural intelligence. Philosophical Transactions of the Royal Society B: Biological Sciences, 366(1567), 1017-1027.
- Kamphaus, R. W. (2005). Clinical assessment of child and adolescent intelligence. Springer Science & Business Media.
- Trewavas, Anthony (September 2005). "Green plants as intelligent organisms". Trends in Plant Science. 10 (9): 413–419. doi:10.1016/j.tplants.2005.07.005. PMID 16054860.
- Trewavas, A. (2002). "Mindless mastery". Nature. 415 (6874): 841. doi:10.1038/415841a. PMID 11859344.
- Goh, C. H.; Nam, H. G.; Park, Y. S. (2003). "Stress memory in plants: A negative regulation of stomatal response and transient induction of rd22 gene to light in abscisic acid-entrained Arabidopsis plants". The Plant Journal. 36 (2): 240–255. doi:10.1046/j.1365-313X.2003.01872.x. PMID 14535888.
- Volkov, A. G.; Carrell, H.; Baldwin, A.; Markin, V. S. (2009). "Electrical memory in Venus flytrap". Bioelectrochemistry. 75 (2): 142–147. doi:10.1016/j.bioelechem.2009.03.005. PMID 19356999.
- Rensing, L.; Koch, M.; Becker, A. (2009). "A comparative approach to the principal mechanisms of different memory systems". Naturwissenschaften. 96 (12): 1373–1384. Bibcode:2009NW.....96.1373R. doi:10.1007/s00114-009-0591-0. PMID 19680619.
- Goebel, Randy; Poole, David L.; Mackworth, Alan K. (1997). Computational intelligence: A logical approach (pdf). Oxford [Oxfordshire]: Oxford University Press. p. 1. ISBN 0-19-510270-3.
- Canny, John; Russell, Stuart J.; Norvig, Peter (2003). Artificial intelligence: A modern approach. Englewood Cliffs, N.J.: Prentice Hall. ISBN 0-13-790395-2. OCLC 51325314.
- Brooks-Gunn, J., Klebanov, P. K., & Duncan, G. J. (1996, April). Ethnic differences in children's intelligence test scores: role of economic deprivation, home environment, and maternal characteristics. Child Development, 67(2), 396-408.
- Greenfield, P.M., Quiroz, B. (2013, February 14). Context and culture in socialization and development of personal achievement values: Comparing Latino immigrant families, European American families, and elementary school teachers. Journal of Applied Developmental Psychology, 34, 108-118.
- Jose, P. E., & Bellamy, M. A. (2011, October 11). Relationships of parents' theories of intelligence with children's persistence/learned helplessness: A Cross-Cultural Comparison. Journal of Cross-Cultural Psychology, 43(6), 999-1018.
- Legg, S., & Hutter, M. (2007, June). A Collection of Definitions of Intelligence. In: Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms, 157, 17-24.
- Siegler, R. S., & Alibali, M. W. (2005). Children's Thinking (4th ed., pp. 107–125). Upper Saddle River, NJ: Prentice-Hall, Inc.
- Sternberg, R. J., Nokes, K., Geissler, P. W., Prince, R., Okatcha, F., Bundy, D. A., & Grigorenko, E. L. (2001). The relationship between academic and practical intelligence: A case study in Kenya. Intelligence, 29, 401–418.
- Sternberg, R. J. (2004, July). Culture and intelligence.
- Sternberg, R.J., Grigorenko, E.L. (2004, August 11). Intelligence and culture: How culture shapes what intelligence means, and the implications for a science of well-being.
- Stevenson, H.W., Lee, S., & Stigler, J.W. (1986, February 14). Mathematics as achievement of Chinese, Japanese, and American children. Science, 231 (4739), 693-699.
- Tudge, J., Hogan, D., Lee, S., Tammeveski, P., Meltas, M., Kulakova, N., Snezhkova, L., Putnam, S. (1999). Cultural heterogeneity: Parental values and beliefs and their preschoolers’ activities in the United States, South Korea, Russia, and Estonia. In A. Göncü (Ed.), Children’s engagement in the world: Sociocultural perspectives. New York: Cambridge University Press.
- Wentzel, K. R. (1998, January). Parents' aspirations for Children's Educational Attainments: Relations to parental beliefs and social address variables. Merrill-Palmer Quarterly, 44(1), 20-37.
- Binet, Alfred; Simon, Th. (1916). The development of intelligence in children: The Binet-Simon Scale. Publications of the Training School at Vineland New Jersey Department of Research No. 11. E. S. Kite (Trans.). Baltimore: Williams & Wilkins. Retrieved 18 July 2010.
- Terman, Lewis Madison; Merrill, Maude A. (1937). Measuring intelligence: A guide to the administration of the new revised Stanford-Binet tests of intelligence. Riverside textbooks in education. Boston (MA): Houghton Mifflin. OCLC 964301.
- Wolman, Benjamin B., ed. (1985). Handbook of Intelligence. consulting editors: Douglas K. Detterman, Alan S. Kaufman, Joseph D. Matarazzo. New York (NY): Wiley. ISBN 978-0-471-89738-5. This handbook includes chapters by Paul B. Baltes, Ann E. Boehm, Thomas J. Bouchard, Jr., Nathan Brody, Valerie J. Cook, Roger A. Dixon, Gerald E. Gruen, J. P. Guilford, David O. Herman, John L. Horn, Lloyd G. Humphreys, George W. Hynd, Randy W. Kamphaus, Robert M. Kaplan, Alan S. Kaufman, Nadeen L. Kaufman, Deirdre A. Kramer, Roger T. Lennon, Michael Lewis, Joseph D. Matarazzo, Damian McShane, Mary N. Meeker, Kazuo Nihira, Thomas Oakland, Ronald Parmelee, Cecil R. Reynolds, Nancy L. Segal, Robert J. Sternberg, Margaret Wolan Sullivan, Steven G. Vandenberg, George P. Vogler, W. Grant Willis, Benjamin B. Wolman, James W. Soo-Sam, and Irla Lee Zimmerman.
- Bock, Gregory; Goode, Jamie; Webb, Kate, eds. (2000). The Nature of Intelligence. Novartis Foundation Symposium 233. Chichester: Wiley. doi:10.1002/0470870850. ISBN 978-0471494348. Retrieved 16 July 2010. Lay summary (16 May 2013).
- Blakeslee, Sandra; Hawkins, Jeff (2004). On intelligence. New York: Times Books. ISBN 0-8050-7456-2. OCLC 55510125.
- Stanovich, Keith (2009). What Intelligence Tests Miss: The Psychology of Rational Thought. New Haven (CT): Yale University Press. ISBN 978-0-300-12385-2. Lay summary (6 November 2013).
- Flynn, James R. (2009). What Is Intelligence: Beyond the Flynn Effect (expanded paperback ed.). Cambridge: Cambridge University Press. ISBN 978-0-521-74147-7. Lay summary (18 July 2010).
- 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).
- Sternberg, Robert J.; Kaufman, Scott Barry, eds. (2011). The Cambridge Handbook of Intelligence. Cambridge: Cambridge University Press. ISBN 9780521739115. Lay summary (22 July 2013). The Cambridge Handbook includes chapters by N. J. Mackintosh, Susana Urbina, John O. Willis, Ron Dumont, Alan S. Kaufman, Janet E. Davidson, Iris A. Kemp, Samuel D. Mandelman, Elena L. Grigorenko, Raymond S. Nickerson, Joseph F. Fagan, L. Todd Rose, Kurt Fischer, Christopher Hertzog, Robert M. Hodapp, Megan M. Griffin, Meghan M. Burke, Marisa H. Fisher, David Henry Feldman, Martha J. Morelock, Sally M. Reis, Joseph S. Renzulli, Diane F. Halpern, Anna S. Beninger, Carli A. Straight, Lisa A. Suzuki, Ellen L. Short, Christina S. Lee, Christine E. Daley, Anthony J. Onwuegbuzie, Thomas R. Zentall, Liane Gabora, Anne Russon, Richard J. Haier, Ted Nettelbeck, Andrew R. A. Conway, Sarah Getz, Brooke Macnamara, Pascale M. J. Engel de Abreu, David F. Lohman, Joni M. Lakin, Keith E. Stanovich, Richard F. West, Maggie E. Toplak, Scott Barry Kaufman, Ashok K. Goel, Jim Davies, Katie Davis, Joanna Christodoulou, Scott Seider, Howard Gardner, Robert J. Sternberg, John D. Mayer, Peter Salovey, David Caruso, Lillia Cherkasskiy, Richard K. Wagner, John F. Kihlstrom, Nancy Cantor, Soon Ang, Linn Van Dyne, Mei Ling Tan, Glenn Geher, Weihua Niu, Jillian Brass, James R. Flynn, Susan M. Barnett, Heiner Rindermann, Wendy M. Williams, Stephen J. Ceci, Ian J. Deary, G. David Batty, Colin DeYoung, Richard E. Mayer, Priyanka B. Carr, Carol S. Dweck, James C. Kaufman, Jonathan A. Plucker, Ursula M. Staudinger, Judith Glück, Phillip L. Ackerman, and Earl Hunt.
|Wikimedia Commons has media related to Intelligence.|
|Look up intelligence in Wiktionary, the free dictionary.|
|Wikiquote has quotations related to: Intelligence|
- Intelligence on In Our Time at the BBC. (listen now)
- APA Task Force Examines the Knowns and Unknowns of Intelligence - American Psychologist, February 1996
- The cognitive-psychology approach vs. psychometric approach to intelligence - American Scientist magazine
- History of Influences in the Development of Intelligence Theory and Testing - Developed by Jonathan Plucker at Indiana University
- The Limits of Intelligence: The laws of physics may well prevent the human brain from evolving into an ever more powerful thinking machine by Douglas Fox in Scientific American, June 14, 2011.
- A Collection of Definitions of Intelligence
Scholarly journals and societies