The relationship between fluid intelligence and learning potential: Is there an interaction with attentional control?

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The main aim of the study was to explore the relationship between fluid intelligence (gf), attentional control (AC), and learning potential (LP), and to investigate the interaction effect between gf and AC on LP. The sample comprised 210 children attending the fourth grade of a standard elementary school. It was hypothesized that the extent of the association between gf and LP depends on the level of attentional control, so that a low level of AC would weaken or possibly break that link, while a high level of AC would facilitate the employment of fluid general ability in learning situations. The results show that there was a moderate relationship between the measures of gf and LP, while gf was not found to be related to AC. Regarding the hypothesized interaction effect, the data suggested that the relationship between learning potential and fluid intelligence is invariant regarding the level of attentional control in the sample. Possible reasons for the lack of a moderation effect are discussed.

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  • Ackerman P. Beier M. & Boyle M. (2005). Working memory and intelligence: The same or different constructs? Psychological Bulletin 131(1) 30-60.

  • Aiken L. S. & West S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park: Sage.

  • Alloway T. P. (2009). Cognitive training: Improvements in academic attainments. Professional Association for Teachers of Students with Specific Learning Difficulties 22 57-61.

  • Alloway T. P. (2010). Working memory and executive function profiles of students with borderline intellectual functioning. Journal of Intellectual Disability Research 54(5) 448-456.

  • Alloway T. P. & Alloway R. G. (2010). Investigating the predictive roles of working memory and IQ in academic attainment. Journal of Experimental Child Psychology 106(1) 20-29.

  • Anderson V. Jacobs R. & Anderson P. J. (Eds.). (2008). Executive functions and the frontal lobes: A lifespan perspective. NY: Psychology Press.

  • Baddeley A. D. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences 4(11) 417-423.

  • Baddeley A. D. & Hitch G. (1974). Working memory. In G.H. Bower (Ed.) The psychology of learning and motivation: Advances in research and theory (Vol. 8 pp. 47-89). New York: Academic Press.

  • Banich M. T. Milham M. P. Atchley R. Cohen N. J. Webb A. & Wszalek T. (2000). fMRI studies of Stroop tasks reveal unique roles of anterior and posterior brain systems in attentional selection. Journal of Cognitive Neuroscience 12(6) 988-1000.

  • 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) 109-160.

  • Brydges C. R. Reid C. L. Fox A. M. & Anderson M. (2012). A unitary executive function predicts intelligence in children. Intelligence 40 458-469.

  • Budoff M. (1987). The validity of learning potential assessment. In: C. S. Lidz (Ed.) Dynamic assessment: An interactional approach to evaluating learning potential (pp. 53-81). New York NY: Guilford Press.

  • Carlson J. S. & Wiedl K. H. (1979). Toward a differential testing approach: Testing- -the-limits employing the Raven matrices. Intelligence 3(4) 323-344.

  • Carter C. S. Mintun M. Cohen J. D. (1995). Interference and facilitation effects during selective attention: An (H2O)-O-15 PET study of Stroop task performance. Neuroimage 2(4) 264-272.

  • Cattell R. B. (1971). Abilities: Their structure growth and action. Boston: Houghton Mifflin.

  • Chuderski A. (2014). Which working memory components predict fluid intelligence. Psychology 5(5) 328-339.

  • Chuderski A. Taraday M. Nęcka E. & Smoleń T. (2012). Storage capacity explains fluid intelligence while executive control does not. Intelligence 40(3) 278-295.

  • Colom R. Rebollo I. Palacios A. Juan-Espinosa & M. Kyllonen P. (2004). Working memory is (almost) perfectly predicted by g. Intelligence 32(2004) 277-296.

  • Conway A. R. A. Cowan N. Bunting M. F. Therriault D. J. & Minkoff S. R. (2002). A latent variable analysis of working memory capacity short-term memory capacity processing speed and general fluid intelligence. Intelligence 30(2002) 163-183.

  • Delis D. C. Kaplan E. & Kramer J. H. (2001). Delis-Kaplan executive function system (D-KEFS). San Antonio TX: The Psychological Corporation.

  • Džuka J. & Kovalčíková I. (2008). Dynamické testovanie latentných učebných schopností [Dynamic testing of latent learning abilities]. Československá Psychologie 52(4) 366-377.

  • Elliott J. Grigorenko E. L. & Resing W. C. M. (2010). Dynamic assessment: The need for a dynamic approach. In E. Baker B. McGraw & P. Peterson (Eds.) International encyclopedia of education (3rd ed.). Oxford United Kingdom: Elsevier.

  • Elliot J. & Lauchlan F. (1997). Assessing potential: The search for the philosopher’s stone? Educational and Child Psychology 14(4) 6-16.

  • Engle R. W. & Kane M. J. (2004). Executive attention working memory capacity and a two-factor theory of cognitive control. In B. Ross (Ed.) The Psychology of Learning and Motivation (pp. 145-199). New York NJ: Elsevier.

  • Fabio R. A. (2005). Dynamic assessment of intelligence is a better reply to adaptive behaviour and cognitive plasticity. The Journal of General Psychology 132(1) 41-64.

  • Ferrer E. McArdle J. J. Shawitz B. A. Holahan J. N. Marchione K. & Shawitz S. E. (2007). Longitudinal models of developmental dynamics between reading and cognition from childhood to adolescence. Developmental Psychology 43(6) 1460-1473.

  • Feuerstein R. Rand Y. & Hoffman M. (1979). The dynamic assessment of retarded performers: The learning potential assessment device (LPAD). Baltimore MD: University Park Press.

  • Feuerstein R. Rand Y. Hoffman M. B. & Miller R. (1980). Instrumental enrichment: An intervention program for cognitive modifiability. Baltimore MD: University Park Press.

  • Fiszdon J. M. McClough J. F. Silverstein S. M. Bell M. D. Jaramillo J. R. & Smith T. E. (2006). Learning potential as a predictor of readiness for psychosocial rehabilitation in schizophrenia. Psychiatry Research 143(2-3) 159-166.

  • Freund P. A. & Holling H. (2011). Retest effects in matrix test performance: Differential impact of predictors at different hierarchy levels in an educational setting. Learning and Individual Differences 21(5) 597-601.

  • Friedman N. P. Miyake A. Corley R. P. Young S. E. Defries J. C. & Hewitt J. K. (2006). Not all executive functions are related to intelligence. Psychological Science 17(2) 172-179.

  • Haywood H. C. (1997). Interactive assessment. In R. Taylor (Ed.) Assessment of persons with mental retardation (pp. 103-129). San Diego: Singular Publishing Haywood H. C. & Lidz C. S. (2007). Dynamic assessment in practice: Clinical and educational applications. Cambridge NY: Cambridge University Press.

  • Hornung C. Brunner M. Reuter R. A. P. & Martin R. (2011). Children’s working memory: Its structure and relationship to fluid intelligence. Intelligence 39(4) 210-22.

  • Hotulainen R. Thuneberg H. Hautamäki J. & Vainikainen M-P. (2014). Measured attention in prolonged over-learned response tasks and its correlation to high level scientific reasoning and school achievement. Psychological Test and Assessment Modeling 56(3) 237-254.

  • Jeltova I. Birney D. Fredine N. Jarvin L. Sternberg R. J. & Grigorenko E. L. (2011). Making instruction and assessment responsive to diverse students’ progress: Group-administered dynamic assessment in teaching mathematics. Journal of Learning Disabilities 44(4) 381-395.

  • Jensen A. R. (1998). The g factor: The science of mental ability. Westport CN: Praeger.

  • Kail R. V. (2007). Longitudinal evidence that increases in processing speed and working memory enhance children’s reasoning. Psychological Science 18(4) 312-313.

  • Kane M. J. Hambrick D. Z. Tuholski S. W. Wilhelm O. Payne T. W. & Engle R. W. (2004). The generality of working memory capacity: A latent variable approach to verbal and visuo-spatial memory span and reasoning. Journal of Experimental Psychology: General 133(2) 189-217.

  • Kovalčíková I. (2009). Dynamic testing and assessment of latent learning capacities. Sosyal Bilimler Araştırmaları Dergisi 1 47-53.

  • Kovalčíková I. (Ed.). (2010). Kognitívna stimulácia individuálnych edukačných potrieb žiaka zo sociálne znevýhodňujúceho prostredia [Cognitive stimulation of individual The Relationship Between Fluid Intelligence And Learning Potential: Is There An Interaction... 3 9 educational needs of pupils from socially disadvantaging environments]. Prešov Slovakia: Vydavateľstvo Prešovskej univerzity.

  • Lee K. Pe M. L. Ang S. Y. & Stankov L. (2009). Do measures of working memory predict academic proficiency better than measures of intelligence? Psychology Science Quarterly 51(4) 403-419.

  • Lehto J. E. Juujärvi P. Kooistra L. & Pulkkinen L. (2003). Dimensions of executive functioning: Evidence from children. British Journal of Developmental Psychology 21(1) 59-80.

  • Lidz C. (2000). The Application of Cognitive Functions Scale. In C. S. Lidz & J. G.

  • Elliott (Eds.) Dynamic Assessment: Prevailing models and applications. Amsterdam: JAI/Elsevier Science.

  • MacDonald A. W. Cohen J. D. Stenger V. A. & Carter C. S. (2000). Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science 288(5472) 1835-1838.

  • Mackey A. P. Hill S. S. Stone S. I. & Bunge S. A. (2011). Dissociable effects of reasoning and speed training in children. Developmental Science 14(3) 582-590.

  • MacKinnon D. P. (2008). Introduction to Statistical Mediation Analysis. New York: Erlbaum.

  • McCandliss B. Beck I. L. Sandak R. & Perfetti C. (2003). Focusing attention on decoding for children with poor reading skills: Design and preliminary tests of the word building intervention. Scientific Studies of Reading 7(1) 75-104.

  • Milham M. P. Erickson K. I. Banich M. T. Kramer A. F. Webb A. Wszalek T. & Cohen N. J. (2002). Attentional control in the aging brain: Insights from an fMRI study of the Stroop task. Brain and Cognition 49(3) 277-296.

  • Miyake A. Friedman N. P. Emerson M. J. Witzki A. H. Howerter A. & Wager T. D. (2000). The unity and diversity of executive functions and their contributions to complex “Frontal Lobe” tasks: A latent variable analysis. Cognitive Psychology 41(1) 49-100.

  • Posner M. I. & Dehaene S. (1994). Attentional networks. Trends in Neuroscience 17(2) 75-79.

  • Primi R. Ferrão M. E. & Almeida L. S. (2010). Fluid intelligence as a predictor of learning: A longitudinal multilevel approach applied to math. Learning and Individual Differences 20(5) 446-451.

  • Resing W. C. M. (2013). Dynamic testing and individualized instruction: Helpful in cognitive education? Journal of Cognitive Education and Psychology 12(1) 81-95.

  • Resing W. C. M. Stevenson C. & Bosma T. (2012). Dynamic testing: Measuring inductive reasoning in children with developmental disabilities and mild cognitive impairments. Journal of Cognitive Education and Psychology 11(2) 159-178.

  • Ropovik I. (2014). Do executive functions predict the ability to learn problem-solving principles? Intelligence 44 64-74.

  • Schweizer K. (2010). The relationship of attention and intelligence. In A. Gruszka G. Matthiews & B. Szymura (Eds.) Handbook of individual differences in cognition: Attention memory and executive control (pp. 247-262). New York: Springer.

  • Sergi M. J. Kern R. S. Mintz J. & Green M. F. (2005). Learning potential and the prediction of work skill acquisition in schizophrenia. Schizophrenia Bulletin 31(1) 67-72.

  • Spearman C. (1904). “General Intelligence” objectively determined and measured.

  • Stanovich K. E. Cunningham A. E. & Freeman D. (1984). Intelligence cognitive skills and early reading progress. Reading Research Quarterly 14 278-303.

  • Stauffer J. M. Ree M. J. & Caretta T. R. (1996). Cognitive-components tests are not much more than g: An extension of Kyllonen’s analysis. Journal of General Psychology 123 193-205.

  • Sternberg R. J. & Grigorenko E. L. (2002). Dynamic testing: The nature and measurement of learning potential. New York NY: Cambridge University Press.

  • Sternberg R. J. Grigorenko E. L. Birney D. P. Fredine N. Jarvin L. & Jeltova I. (2007). Dynamic instruction for and assessment of developing expertise in four ethnic groups. In E. J. Gubbins (Ed.) Research Monograph of the National Research Center on the Gifted and Talented. University of Connecticut. Stevenson C. E. (2012). Puzzling with potential. Dynamic testing of analogical reasoning in children (Doctoral dissertation Leiden University). Amsterdam the Netherlands: Ipskamp Drukkerij.

  • Stevenson C. E. Hickendorff M. Resing W. C. M. Heiser W. & de Boeck P. (2013). Explanatory item response modeling of children’s change on a dynamic test of analogical reasoning. Intelligence 41(3) 157-168.

  • Swanson H. L. & Howard C. B. (2005). Children with reading disabilities: Does dynamic assessment help in the classification? Learning Disability Quarterly 28(1) 17-34.

  • Swanson H. L. & Lussier C. M. (2001). A selective synthesis of the experimental literature on dynamic assessment. Review of Educational Research 71(2) 321-363.

  • Taub G. Floyd R. G. Keith T. Z. & McGrew K. S. (2008). Effects of general and broad cognitive abilities on mathematics. School Psychology Quarterly 23(2) 187-198.

  • Taylor T. R. (1992). Beyond competence: Measuring potential in a cross-cultural situation fairly. Potential in psychometrics. In Congress on psychometrics for psychologists. Megawatt Park Sandton: Eskom and the Society of Industrial Psychology of South Africa.

  • Tillman C. M. Nyberg L. & Bohlin G. (2008). Working memory components and intelligence in children. Intelligence 36(5) 394-402.

  • Tzuriel D. (2000). Dynamic assessment of young children: Educational and intervention perspectives. Educational Psychology Review 12(4) 385-435.

  • Unsworth N. & Engle R. W. (2007). The nature of individual differences in working memory capacity: Active maintenance in primary memory and controlled search from secondary memory. Psychological Review 114(1) 104-132.

  • Unsworth N. & Spillers G. J. (2010). Working memory capacity: Attention memory or both? A direct test of the Dual-Component Model. Journal of Memory and Language 62 392-406.

  • Vygotsky L. S. (1962). Thought and language. Cambridge MA: MIT Press.

  • West R. Alain C. (2000). Effects of task context and fluctuations of attention on neural activity supporting performance of the Stroop task. Brain Research 873(1) 102-111.

  • Wiebe S. A. Sheffield T. Nelson J. M. Clark C. A. Chevalier N. & Espy K. A. (2011). The structure of executive function in 3-year-olds. Journal of Experimental Child Psychology 108(3) 436-452.

  • Wiedl K. H. (1999). Cognitive modifiability as a measure of readiness for rehabilitation. Psychiatric Services 50(11) 1411-1413.

  • Wiedl K. H. (2003). Dynamic testing: A comprehensive model and current fields of application. Journal of Cognitive Education and Psychology 3(2) 93-119. journalofpedagogy1/2015

  • Wiedl K. H. Schottke H. H. & Calero-Garcia D. (2001). Dynamic assessment of cognitive rehabilitation potential in schizophrenic persons and in elderly persons with and without dementia. European Journal of Psychological Assessment 17(2) 112-117.

  • Wiedl K. H. & Wienobst J. (1999). Interindividual differences in cognitive remediation research with schizophrenic patients: Indicators of rehabilitation potential? International Journal of Rehabilitation Research 22(1) 55-59.

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