Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-15T21:18:41.322Z Has data issue: false hasContentIssue false
  • English
  • Français

The evolution of fluid intelligence meets formative g

Published online by Cambridge University Press:  15 August 2017

Kristof Kovacs  and
Andrew R. A. Conway
Kristof Kovacs
Affiliation:
Eszterházy Károly University, 3300, Eger, [email protected]
Andrew R. A. Conway
Affiliation:
Claremont Graduate University, Claremont, CA [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The argument by Burkart et al. in the target article relates to fluid (not general) intelligence: a domain-general ability involved in complex, novel problem solving, and strongly related to working memory and executive functions. A formative framework, under which the general factor of intelligence is the common consequence, not the common cause of the covariance among tests is more in line with an evolutionary approach.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 40 , 2017 , e208
Check for updates
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bagozzi, R. P. (2007) On the meaning of formative measurement and how it differs from reflective measurement: Comment on Howell, Breivik, and Wilcox (2007). Psychological Methods 12(2):229–37; discussion 238–45. doi: 10.1037/1082-989X.12.2.229.CrossRefGoogle ScholarPubMed
Blair, C. (2006) How similar are fluid cognition and general intelligence? A developmental neuroscience perspective on fluid cognition as an aspect of human cognitive ability. Behavioral and Brain Sciences 29(2):109–25; discussion 125–60. doi: 10.1017/S0140525X06009034.CrossRefGoogle ScholarPubMed
Cattell, R. B. (1971) Abilities: Their structure, growth, and action. Houghton Mifflin. Available at: http://books.google.com/books?id=10EgAQAAIAAJ&pgis=1.Google Scholar
Conway, A. R. A. & Kovacs, K. (2013) Individual differences in intelligence and working memory: A review of latent variable models. In: Psychology of Learning and Motivation, vol. 58, ed. Ross, B. H., pp. 233–70. Academic Press. doi: 10.1016/B978-0-12-407237-4.00007-4.Google Scholar
Duncan, J., Burgess, P. & Emslie, H. (1995) Fluid intelligence after frontal lobe lesions. Neuropsychologia 33(3):261–68. doi: 10.1016/0028-3932(94)00124-8.CrossRefGoogle ScholarPubMed
Engle, R. W. & Kane, M. J. (2004) Executive attention, working memory capacity, and a two-factor theory of cognitive control. The Psychology of Learning and Motivation 44:145–99.CrossRefGoogle Scholar
Flynn, J. R. (2007) What is intelligence? Beyond the Flynn effect. Cambridge University Press. Available at: http://books.google.com/books?hl=en&lr=&id=qvBipuypYUkC&pgis=1.CrossRefGoogle Scholar
Gustafsson, J.-E. (1984) A unifying model for the structure of intellectual abilities. Intelligence 8(3):179–203. doi: 10.1016/0160-2896(84)90008-4.CrossRefGoogle Scholar
Haier, R. J., Colom, R., Schroeder, D. H., Condon, C. A., Tang, C., Eaves, E. & Head, K. (2009) Gray matter and intelligence factors: Is there a neuro-g? Intelligence 37(2):136–44. doi: 10.1016/j.intell.2008.10.011.CrossRefGoogle Scholar
Horn, J. L. & Cattell, R. B. (1967) Age differences in fluid and crystallized intelligence. Acta Psychologica 26:107–29. doi: 10.1016/0001-6918(67)90011-X.CrossRefGoogle ScholarPubMed
Howell, R. D., Breivik, E. & Wilcox, J. B. (2007) Reconsidering formative measurement. Psychological Methods 12(2):205–18. doi: 10.1037/1082-989X.12.2.205.CrossRefGoogle ScholarPubMed
Kane, M. J. (2005) Full frontal fluidity. In: Handbook of understanding and measuring intelligence, ed. Wilhelm, O. & Engle, R., pp. 141–65. Sage.CrossRefGoogle Scholar
Kane, M. J. & Engle, R. W. (2002) The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: An individual-differences perspective. Psychonomic Bulletin & Review 9(4):637–71. Available at: http://www.ncbi.nlm.nih.gov/pubmed/12613671.CrossRefGoogle ScholarPubMed
Kane, M. J., Hambrick, D. Z. & Conway, A. R. A. (2005) Working memory capacity and fluid intelligence are strongly related constructs: Comment on Ackerman, Beier, and Boyle (2005). Psychological Bulletin 131:66–71; author reply 72–5. doi: 10.1037/0033-2909.131.1.66.CrossRefGoogle ScholarPubMed
Kovacs, K. & Conway, A. R. A. (2016) Process overlap theory: A unified account of the general factor of intelligence. Psychological Inquiry 27(3):151–77. doi: 10.1080/1047840X.2016.1153946.CrossRefGoogle Scholar
Kovacs, K., Plaisted, K. C. & Mackintosh, N. J. (2006) Difficulties differentiating dissociations. Behavioral and Brain Sciences 29(02):138–39. doi: 10.1017/S0140525X06349035.CrossRefGoogle Scholar
Krijnen, W. P. (2004) Positive loadings and factor correlations from positive covariance matrices. Psychometrika 69(4):655–60. doi: 10.1007/BF02289861.CrossRefGoogle Scholar
Matzke, D., Dolan, C. V. & Molenaar, D. (2010) The issue of power in the identification of “g” with lower-order factors. Intelligence 38(3):336–44. doi: 10.1016/j.intell.2010.02.001.CrossRefGoogle Scholar
McGrew, K. S. (2009) CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research. Intelligence 37(1):1–10. doi: 10.1016/j.intell.2008.08.004.CrossRefGoogle Scholar
Oberauer, K., Schulze, R., Wilhelm, O. & Süss, H.-M. (2005) Working memory and intelligence—Their correlation and their relation: Comment on Ackerman, Beier, and Boyle (2005). Psychological Bulletin 131:61–5; author reply 72–5. doi: 10.1037/0033-2909.131.1.61.CrossRefGoogle ScholarPubMed
Trahan, L. H., Stuebing, K. K., Fletcher, J. M. & Hiscock, M. (2014) The Flynn effect: A meta-analysis. Psychological Bulletin 140:1332–60.CrossRefGoogle ScholarPubMed
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):842–61. doi: 10.1037/0033-295X.113.4.842.CrossRefGoogle ScholarPubMed
Vicari, S., Bellucci, S. & Carlesimo, G. A. (2007) Visual and spatial working memory dissociation: Evidence from Williams syndrome. Developmental Medicine & Child Neurology 45(4):269–73. doi: 10.1111/j.1469-8749.2003.tb00342.x.Google Scholar
Wang, P. P. & Bellugi, U. (1994) Evidence from two genetic syndromes for a dissociation between verbal and visual-spatial short-term memory. Journal of Clinical and Experimental Neuropsychology 16(2):317–22. doi: 10.1080/01688639408402641.CrossRefGoogle ScholarPubMed