Fluid and crystallized intelligence
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According to the theory published in 1963 by the psychologist Raymond Cattell, general intelligence (g) is subdivided into fluid intelligence (gf) and crystallized intelligence (gc). Fluid intelligence is the ability to solve novel reasoning problems and is correlated with a number of important skills such as comprehension, problem solving, and learning. Crystallized intelligence on the other hand is the ability to deduce secondary relational abstractions by applying previously learned primary relational abstractions.
Fluid intelligence depends on working memory capacity, which is localized in the prefrontal cortex. This region degenerates faster than other cortical regions in the course of aging and encephalopathies. Fluid intelligence peaks at around age 20 and then gradually declines.
Fluid and crystallized intelligence are constructs originally identified as elements of a theory developed by Raymond Cattell. The concepts of fluid and crystallized intelligence were further developed by Cattell's student, John L. Horn.
Some researchers have linked the theory of fluid and crystallized abilities to Piaget's theory of cognitive development. Fluid ability and Piaget's operative intelligence both concern logical thinking and the eduction of relations. Crystallized ability and Piaget's treatment of everyday learning reflect the impress of experience. Like fluid ability's relation to crystallized intelligence, Piaget's operativity is considered to be prior to, and ultimately provides the foundation for, everyday learning.
Fluid versus crystallized
- Fluid intelligence involves inductive and visuospatial abilities.
- Crystallized intelligence involves deductive, verbal, and numerical abilities.
Each type of ability subsumed under crystallized intelligence is relatively independent of the other. For example, increasing a student's proficiency in Latin does not increase the student's proficiency in algebra. But the abilities subsumed by crystallized intelligence are dependent on the individual's fluid intelligence. For example, students proficient in Latin also tend to be proficient in algebra because people with a high gf tend to acquire more gc. In other words, individuals high in gf acquire more knowledge and at faster rates; their acquisition of knowledge also depends less on the quality of the learning environment (e.g., the quality of available books). Psychologist Geoffrey Miller has argued that human intelligence and capacities for the cultural universals of language, music, and art are unnecessarily sophisticated with regard to the survival needs of hunter-gatherers. Miller instead argued that the evolution of general intelligence occurred by sexual selection rather than natural selection. Philosopher Denis Dutton also argued that the human capacity for aesthetics evolved by sexual selection.
Fluid intelligence generally correlates with measures of abstract reasoning and puzzle solving. Crystallized intelligence correlates with abilities that depend on knowledge and experience, such as vocabulary, general information, and analogies. Paul Kline identified a number of measures that correlated at least r = .60 with gf and gc. Induction, visualization, quantitative reasoning, and ideational fluency correlated .60 or more with gf. Verbal ability, language development, reading comprehension, sequential reasoning, and general information correlated 0.6 or more with gc. It is possible that intelligence tests may not truly reflect levels of fluid intelligence. Some authors have suggested that unless an individual is truly interested in a problem presented on an IQ test, the cognitive work required to solve the problem to may not be performed owing to a lack of interest. These authors contended that a low score on tests which are intended to measure fluid intelligence may reflect more a lack of interest in the tasks themselves rather than any sort of inability to complete the tasks successfully.
Measurement of fluid intelligence
Various measures have been used to assess fluid intelligence. The Cattell Culture Fair IQ test, the Raven Progressive Matrices (RPM), and some of the subscales that contribute to Performance IQ on the WAIS are thought to measure of gf. The RPM is one of the most commonly used measures of fluid ability. It is a non-verbal multiple choice test. Participants have to complete a series of drawings by identifying relevant features based on the spatial organization of an array of objects, and choosing one object that matches one or more of the identified features. This task assesses the ability to consider one or more relationships between mental representations or relational reasoning. Propositional analogies and semantic decision tasks are also used to assess relational reasoning.
Standardized IQ tests such as those used in psychoeducational assessment also include tests of fluid intelligence. In the Woodcock-Johnson Tests of Cognitive Abilities, gf is assessed by two tests: Concept Formation (Test 5) in the Standard Battery and Analysis Synthesis (Test 15) in the Extended Battery. On Concept Formation tasks, the individual has to apply concepts by inferring the underlying "rules" for solving visual puzzles that are presented in increasing levels of difficulty. Individuals at the preschool level have to point to a shape that is different from others in a set. As the level of difficulty increases, individuals increasingly demonstrate an understanding of what constitutes a key difference (or the "rule") for solving puzzles involving one to one comparisons, and on later items identifying common differences among a set of items. For more difficult items, individuals need to understand the concept of "and" (e.g., a solution must have some of this and some of that) and the concept of "or" (e.g., to be inside a box, the item must be either this or that). The most difficult items require fluid transformations and cognitive shifting between the various types of concept puzzles that the examinee has worked with previously.
Concept Formation tasks assess inductive reasoning ability. In the Analysis-Synthesis test, the individual has to learn and orally state the solutions to incomplete logic puzzles that mimic a miniature mathematics system. The test also contains some of the features involved in using symbolic formulations in other fields such as chemistry and logic. The individual is presented with a set of logic rules, a "key" that is used to solve the puzzles. The individual has to determine the missing colors within each of the puzzles using the key. Complex items present puzzles that require two or more sequential mental manipulations of the key to derive a final solution. Increasingly difficult items involve a mix of puzzles that require fluid shifts in deduction, logic, and inference. Analysis Synthesis tasks assess general sequential reasoning.
In the Wechsler Intelligence Scale for Children-IV (WISC IV), the Perceptual Reasoning Index contains two subtests that assess gf: Matrix Reasoning, which involves induction and deduction, and Picture Concepts, which involves induction. In the Picture Concepts task, children are presented a series of pictures on two or three rows and asked which pictures (one from each row) belong together based on some common characteristic. This task assesses the child's ability to discover the underlying characteristic (e.g., rule, concept, trend, class membership) that governs a set of materials. Matrix Reasoning also tests this ability as well as the ability to start with stated rules, premises, or conditions and to engage in one or more steps to reach a solution to a novel problem (deduction). In the Matrix Reasoning test, children are presented a series or sequence of pictures with one picture missing. Their task is to choose the picture that fits the series or sequence from an array of five options. Since Matrix Reasoning and Picture Concepts involve the use of visual stimuli and do not require expressive language, they are considered to be non-verbal tests of gf.
Within the corporate environment, fluid intelligence is a predictor of a person's capacity to work well in environments characterised by complexity, uncertainty, and ambiguity. The Cognitive Process Profile (CPP) measures a person's fluid intelligence and cognitive processes. It maps these against suitable work environments according to Elliott Jacques Stratified Systems Theory.
Development and physiology
Fluid intelligence, like reaction time, typically peaks in young adulthood and then steadily declines. This decline may be related to local atrophy of the brain in the right cerebellum. Other researchers have suggested that a lack of practice, along with age-related changes in the brain, may contribute to the decline. Crystallized intelligence typically increases gradually, stays relatively stable across most of adulthood, and then begins to decline after age 65. The exact peak age of cognitive skills remains elusive, since it depends on both the skill measurement as well as on the survey design. Cross-sectional data shows typically an earlier onset of cognitive decline in comparison with longitudinal data. The former may be confounded due to cohort effects while the latter may be biased due to prior test experiences.
Improving fluid intelligence with training on working memory
According to David Geary, gf and gc can be traced to two separate brain systems. Fluid intelligence involves both the dorsolateral prefrontal cortex, the anterior cingulate cortex, and other systems related to attention and short-term memory. Crystallized intelligence appears to be a function of brain regions that involve the storage and usage of long-term memories, such as the hippocampus.
Some researchers question whether the results of training interventions to enhance gf are long-lasting and transferable, especially when these techniques are used by healthy children and adults without cognitive deficiencies. A meta-analytical review published in 2012 concluded that "memory training programs appear to produce short-term, specific training effects that do not generalize."
In a series of four individual experiments involving 70 participants (mean age of 25.6) from the University of Bern community, Jaeggi et al. found that, in comparison to a demographically matched control group, healthy young adults who practiced a demanding working memory task (dual n-back) approximately 25 minutes per day for between 8 and 19 days had significantly greater pre-to-posttest increases in their scores on a matrix test of fluid intelligence.
Sternberg drew attention to the limitations of the above study. He commented that "it is unclear to what extent the results can be generalized to other working-memory tasks." He went on to state that "it would be useful to show that the training transfers to success in meaningful behaviors that extend beyond the realm of psychometric testing." Sternberg underlined other limitations as well. He indicated that the researchers (a) probably did not conduct the study with participants who represented a wide range of ability levels and (b) did not assess the durability of the results.
The results of a second study, which was conducted at the University of Technology in Hangzhou, China, was consistent with Jaeggi et al.'s results. After student subjects were given a 10-day training regimen based on the dual n-back working memory theory, the students were tested on Raven's Standard Progressive Matrices. Their scores were found to have increased significantly.
Two later n-back studies did not support the findings of Jaeggi et al. Although participants' performance on the training task improved, these studies showed no significant improvement in the mental abilities tested, especially fluid intelligence and working memory capacity.
- 21st century skills
- CHC theory
- Deeper learning
- General intelligence factor
- John L. Horn
- Malleability of intelligence
- Outline of human intelligence
- Raymond Cattell
- Spatial intelligence (psychology)
- Three stratum theory
- Cattell, R. B. (1963). "Theory of fluid and crystallized intelligence: A critical experiment". Journal of Educational Psychology. 54: 1–22. doi:10.1037/h0046743.
- Sternberg, Robert J. Handbook of Human Intelligence. CUP, 1982, p. 75.
- Cattell, R. B. (1971). Abilities: Their structure, growth, and action. New York: Houghton Mifflin. ISBN 0-395-04275-5.
- Unsworth, Nash; Fukuda, Keisuke; Awh, Edward; Vogel, Edward K. (2014). "Working memory and fluid intelligence: Capacity, attention control, and secondary memory retrieval". Cognitive Psychology. 71: 1–26. doi:10.1016/j.cogpsych.2014.01.003. PMC 4484859. PMID 24531497.
- Cattell, R. B. Intelligence: Its Structure, Growth and Action. Elsevier, 1987.
- Kyllonen, Patrick C.; Christal, Raymond E. (1990). "Reasoning ability is (little more than) working-memory capacity?!". Intelligence. 14 (4): 389–433. doi:10.1016/S0160-2896(05)80012-1.
- Dehn, Milton J. Long-Term Memory Problems in Children and Adolescents John Wiley & Sons, 2010, p. 69
- Fuster, Joaquin. The Prefrontal Cortex Elsevier, 2008, p. 44
- Cacioppo, John T.; Freberg, Laura. Discovering Psychology: The Science of Mind. Cengage Learning, 2012, p. 448
- Papalia, D.; Fitzgerald, J.; Hooper, F. H. (1971). "Piagetian Theory and the Aging Process: Extensions and Speculations". The International Journal of Aging and Human Development. 2: 3–20. doi:10.2190/AG.2.1.b.
- Schonfeld, I.S. (1986). "The Genevan and Cattell-Horn conceptions of intelligence compared: The early implementation of numerical solution aids". Developmental Psychology. 22: 204–212.
- Rogers, Barrie. Human Personality: Towards a Unified Theory Vantage Press, 1972, p. 96
- Sternberg, Robert J. The Nature of Human Intelligence CUP, 2018, p. 39
- Kassin, Saul M. Psychology Prentice Hall, 1998, p. 424
- Sternberg, Robert J. Encyclopedia of Human Intelligence Vol. 1, Macmillan, 1995, p. 1107
- Miller, Geoffrey F. (2000). The Mating Mind: How Sexual Choice Shaped the Evolution of Human Nature (1st ed.). New York: Doubleday. ISBN 978-0385495165.
- Dutton, Denis (2009). The Art Instinct: Beauty, Pleasure, and Human Evolution. New York: Bloomsbury Press. pp. 135–163. ISBN 978-1596914018.
- Kline, P. (1998). The new psychometrics: Science, psychology and measurement. London: Routledge.[page needed]
- Messick, Samuel (1989). "Meaning and Values in Test Validation: The Science and Ethics of Assessment". Educational Researcher. 18 (2): 5–11. doi:10.3102/0013189X018002005. JSTOR 1175249.
- Raven, J.; Raven, J. C.; Court, J. H. (2003) . "Section 1: General Overview". Manual for Raven's Progressive Matrices and Vocabulary Scales. San Antonio, TX: Harcourt Assessment.[page needed]
- Bornstein, Joel C.; Foong, Jaime Pei Pei (2009). "MGluR1 Receptors Contribute to Non-Purinergic Slow Excitatory Transmission to Submucosal VIP Neurons of Guinea-Pig Ileum". Frontiers in Neuroscience. 3: 46. doi:10.3389/neuro.21.001.2009. PMC 2695390. PMID 20582273.
- Wright, Samantha B.; Matlen, Bryan J.; Baym, Carol L.; Ferrer, Emilio; Bunge, Silvia A. (2007). "Neural correlates of fluid reasoning in children and adults". Frontiers in Human Neuroscience. 1: 8. doi:10.3389/neuro.09.008.2007. PMC 2525981. PMID 18958222.
- Ferrer, Emilio; O'Hare, Elizabeth D.; Bunge, Silvia A. (2009). "Fluid reasoning and the developing brain". Frontiers in Neuroscience. 3 (1): 46–51. doi:10.3389/neuro.01.003.2009. PMC 2858618. PMID 19753096.
- Woodcock, R. W.; McGrew, K. S.; Mather, N (2001). Woodcock Johnson III. Itasca, IL: Riverside.[page needed]
- Schrank, F. A.; Flanagan, D. P. (2003). WJ III Clinical use and interpretation. Scientist-practitioner perspectives. San Diego, CA: Academic Press.[page needed]
- Wechsler, D. (2003). WISC-IV technical and interpretive manual. San Antonio, TX: Psychological Corporation.[page needed]
- Flanagan, D. P.; Kaufman, A. S. (2004). Essentials of WISC-IV assessment. Hoboken, NJ: John Wiley.[page needed]
- Lee, Jun-Young; Lyoo, In Kyoon; Kim, Seon-Uk; Jang, Hong-Suk; Lee, Dong-Woo; Jeon, Hong-Jin; Park, Sang-Chul; Cho, Maeng Je (2005). "Intellect declines in healthy elderly subjects and cerebellum". Psychiatry and Clinical Neurosciences. 59 (1): 45–51. doi:10.1111/j.1440-1819.2005.01330.x. hdl:10371/27902. PMID 15679539.
- Cavanaugh, J. C.; Blanchard-Fields, F (2006). Adult development and aging (5th ed.). Belmont, CA: Wadsworth Publishing/Thomson Learning. ISBN 978-0-534-52066-3.[page needed]
- Desjardins, Richard; Warnke, Arne Jonas (2012). "Ageing and Skills" (PDF). OECD Education Working Papers. doi:10.1787/5k9csvw87ckh-en. hdl:10419/57089. Cite journal requires
- Geary, D. C. (2005). The origin of mind: Evolution of brain, cognition, and general intelligence. Washington, DC: American Psychological Association.
- Todd W. Thompson; et al. (2013). "Failure of Working Memory Training to Enhance Cognition or Intelligence". PLoS ONE. 8 (5): e63614. doi:10.1371/journal.pone.0063614. PMC 3661602. PMID 23717453.
- Melby-Lervåg, Monica; Hulme, Charles (2012). "Is Working Memory Training Effective? A Meta-Analytic Review" (PDF). Developmental Psychology. 49 (2): 270–91. doi:10.1037/a0028228. PMID 22612437.
- Jaeggi, Susanne M.; Buschkuehl, Martin; Jonides, John; Perrig, Walter J. (2008). "Improving fluid intelligence with training on working memory". Proceedings of the National Academy of Sciences. 105 (19): 6829–33. Bibcode:2008PNAS..105.6829J. doi:10.1073/pnas.0801268105. JSTOR 25461885. PMC 2383929. PMID 18443283.
- Sternberg, R. J. (2008). "Increasing fluid intelligence is possible after all". Proceedings of the National Academy of Sciences of the United States of America. 105 (19): 6791–6792. Bibcode:2008PNAS..105.6791S. doi:10.1073/pnas.0803396105. PMC 2383939. PMID 18474863.
- Qiu, Feiyue; Wei, Qinqin; Zhao, Liying; Lin, Lifang (2009). "Study on Improving Fluid Intelligence through Cognitive Training System Based on Gabor Stimulus". 2009 First International Conference on Information Science and Engineering. pp. 3459–62. doi:10.1109/ICISE.2009.1124. ISBN 978-1-4244-4909-5.
- Chooi, Weng-Tink; Thompson, Lee A. (2012). "Working memory training does not improve intelligence in healthy young adults". Intelligence. 40 (6): 531–42. doi:10.1016/j.intell.2012.07.004.
- Redick, Thomas S.; Shipstead, Zach; Harrison, Tyler L.; Hicks, Kenny L.; Fried, David E.; Hambrick, David Z.; Kane, Michael J.; Engle, Randall W. (2012). "No Evidence of Intelligence Improvement After Working Memory Training: A Randomized, Placebo-Controlled Study". Journal of Experimental Psychology: General. 142 (2): 359–379. doi:10.1037/a0029082. PMID 22708717.