The Contribution of Executive Functions, Visual Processing and Reading Skills to the Performance in the Colored Raven Progressive Matrices Test: A Predictive Study among First-to-Fourth Grade Arabic-Speaking Children
In this study, the
objective was to assess the extent to which EFs and visual processing,
especially visual attention, contribute to children’s performance in the
Colored Progressive Matrices of Raven (CPM), a test generally used between 5 - 11
years. For this purpose, we tested children from first grade to fourth grade in
a battery that included the different sub-domains of EFs and visual processing
tests. We hypothesized that links will be found between the performance in CPM,
executive functions performance and visual/attentional processes. In addition,
we hypothesized that EFs, in particular, working memory (WM) and
shifting/updating, will explain variance in the performance in the CPM. At the
same time, on the basis of findings showing a link between reading skills and
performance in the RAVEN, we collected reading accuracy and fluency measures to
assess the extent to which EFs and visual processing explain variance in the
performance of RAVEN beyond reading accuracy. At the behavioral level, we found
a grade effect in almost all the measures collected. Also, we found significant
but still weak correlations between the performance in the CPM and almost all EFs,
VP and reading measures (accuracy and fluency). The highest and most
significant correlations were found between the CPM and Color Trail test (part
B), which measures mental flexibility and shifting (r = .35) with reading
accuracy (r = .38). Regression models conducted separately to assess the
contribution of VP, EFs and reading showed first that VP explained 16% of the
variance in the CPM, but only the Color Trail (Part A) was a significant
predictor of the Raven’s scores. EFs explained 18% of the variance in the
performance in the CPM, with Color Trail (Part B) measuring shifting being the
strongest and significant predictor and then the Digit Span. Finally, a
step-wise regression model showed that reading accuracy alone explained 15% of
the variance in CPM, and with EFs and VP, additional 6% were provided (total
21%) by the Color Trail B. In spite of its limitations (the size of the sample
groups), this study points to several new and important areas of inquiry for
future research. For one, we noticed that not only does general ability
correlate with reading, but reading, as a complex skill that includes many
sub-skills, correlates with performance in non-verbal tests such as the CPM. In
this regard, one can ask whether or not the school system should consider
taking general ability and high-order thinking skills such as strategies and
making connections into account as part of the
References
[1]
Abdel-Khalek, A. M., & Raven, J. (2006). Normative Data from the Standardization of Raven’s Standard Progressive Matrices in Kuwait in an International Context. Social Behavior and Personality, 34, 169-179. https://doi.org/10.2224/sbp.2006.34.2.169
[2]
Ackerman, P. L., Beier, M. E., & Boyle, M. O. (2005). Working Memory and Intelligence: The Same or Different Constructs? Psychological Bulletin, 131, 30-60. https://doi.org/10.1037/0033-2909.131.1.30
[3]
Adams, M. J. (1990). Beginning to Read. MIT Press.
[4]
Adot, A. (2014). A Standardization Study of the Raven’s Colored Progressive Matrices in Ghana. Ife Psychologia, 22, 27-35.
[5]
Alvarez, J., & Emory, E. (2006). Executive Function and the Frontal Lobes: A Meta-Analytic Review. Neuropsychology Review, 16, 17-42. https://doi.org/10.1007/s11065-006-9002-x
[6]
Ardila, A. (2008). On the Evolutionary Origins of Executive Functions. Brain and Cognition, 68, 92-99. https://doi.org/10.1016/j.bandc.2008.03.003
[7]
Asadi, I. A., Khateb, A., Ibrahim, R., & Taha, H. (2017). How Do Different Cognitive and Linguistic Variables Contribute to Reading in Arabic? A Cross-Sectional Study from First to Sixth Grade. Reading and Writing, 30, 1835-1867. https://doi.org/10.1007/s11145-017-9755-z
[8]
Baddeley, A. D. (2000). The Episodic Buffer: A New Component of Working Memory? Trends in Cognitive Science, 4, 417-423. https://doi.org/10.1016/S1364-6613(00)01538-2
[9]
Baddeley, A. D. (2007). Working Memory, Thought and Action. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780198528012.001.0001
[10]
Baddeley, A. D., & Hitch, G. J. (1974). Working Memory. In G. A. Bower (Ed.), Recent Advances in Learning and Motivation (Vol. 8, pp. 47-89). Academic Press. https://doi.org/10.1016/S0079-7421(08)60452-1
[11]
Baker, S. C., Rogers, R. D., Owen, A. M., Frith, C. D., Dolan, R. J., Frackowiak, R. S. J., & Robbins, T. W. (1996). Neural Systems Engaged by Planning: A PET Study of the Tower of London Task. Neuropsychologia, 34, 515-526. https://doi.org/10.1016/0028-3932(95)00133-6
[12]
Barbey, A. K., Colom, R., & Grafman, J. (2013). Dorsolateral Prefrontal Contributions to Human Intelligence. Neuropsychologia, 51, 1361-1369. https://doi.org/10.1016/j.neuropsychologia.2012.05.017
[13]
Belacchi, C., Carretti, B., & Cornoldi, C. (2010). The Role of Working Memory and Updating in Colored Raven Matrices Performance in Typically Developing Children. European Journal of Cognitive Psychology, 22, 1010-1020. https://doi.org/10.1080/09541440903184617
[14]
Blair (2003). Behavioral Inhibition and Behavioral Activation in Young Children: Relations with Self-Regulation and Adaption to Preschool in Children Attending Head Start. Developmental Psychobiology, 42, 301-311. https://doi.org/10.1002/dev.10103
[15]
Bryan, J., & Luszez, M. A. (2000). Measurement of Executive Function: Considerations for Detecting Adult Age Differences. Journal of Clinical and Experimental Neuropsychology, 22, 40-55. https://doi.org/10.1076/1380-3395(200002)22:1;1-8;FT040
[16]
Carpenter, P. A., Just, M. A., & Shell, P. (1990). What One Intelligence Test Measures: A Theoretical Account of the Processing in the Raven Progressive Matrices Test. Psychological Review, 97, 404-431. https://doi.org/10.1037/0033-295X.97.3.404
[17]
Carretti, B., & Cornoldi, C. (2010). The Role of Working Memory and Updating in Coloured Raven Matrices Performance in Typically Developing Children. European Journal of Cognitive Psychology, 22, 1010-1020. https://doi.org/10.1080/09541440903184617
[18]
Carroll, J. B. (1993). Human Cognitive Abilities: A Survey of Factor-analytic Studies. Cambridge University Press. https://doi.org/10.1017/CBO9780511571312
[19]
Collette, F., & Van der Linden, M. (2002). Brain Imaging of the Central Executive Component of Working Memory. Neuroscience and Biobehavioral Review, 26, 105-126. https://doi.org/10.1016/S0149-7634(01)00063-X
[20]
Collette, F., Hogge, M., Salmon, E., & Van der Linden, M. (2006). Exploration of the Neural Substrates of Executive Functioning by Functional Neuroimaging. Neuroscience, 139, 209-221. https://doi.org/10.1016/j.neuroscience.2005.05.035
[21]
Collette, F., Van der Linden, M., Laureys, S., Delfiore, G., Degueldre, C., Luxen, A. et al. (2005). Exploring the Unity and Diversity of the Neural Substrates of Executive Functioning. Human Brain Mapping, 25, 409-423. https://doi.org/10.1002/hbm.20118
[22]
Crawford, J. D. (1991). The Relationship between Tests of Sustained Attention and Fluid Intelligence. Personality and Individual Differences, 12, 599-611. https://doi.org/10.1016/0191-8869(91)90257-C
[23]
Dagher, A., Owen, A. M., Boecker, H., & Brooks, D. J. (1999). Mapping the Network for Planning: A Correlational PET Activation Study with the Tower of London Task. Brain, 122, 1973-1987. https://doi.org/10.1093/brain/122.10.1973
[24]
Deliyianni, E., Monoyiou, A., Elia, I., Georgiou, C., & Zannettou, E. (2009). Pupils’ Visual Representations in Standard and Problematic Problem Solving in Mathematics: Their Role in the Breach of the Didactical Contract. European Early Childhood Education Research Journal, 17, 95-110. https://doi.org/10.1080/13502930802689079
[25]
Diamond, A., Carlson, S. M., & Beck, D. M. (2005). Preschool Children’s Performance in Task Switching on the Dimensional Change Card Sort Task: Separating the Dimensions Aids the Ability to Switch. Developmental Neuropsychology, 28, 689-729. https://doi.org/10.1207/s15326942dn2802_7
[26]
Diamond, A., Kirkham, N., & Amso, D. (2002). Conditions under Which Young Children Can Hold Two Rules in Mind and Inhibit a Prepotent Response. Developmental Psychology, 38, 352-362. https://doi.org/10.1037/0012-1649.38.3.352
[27]
Duncan, J., & Owen, A. M. (2000). Common Regions of the Human Frontal Lobe Recruited by Diverse Cognitive Demands. Trends in Neuroscience, 23, 475-483. https://doi.org/10.1016/S0166-2236(00)01633-7
[28]
Ehri, L. C., & Snowling, M. J. (2004). Developmental Variation in Word Recognition. In B. Shulman, K. Apel, B. Ehren, E. Silliman, & C. Stone (Eds.), Handbook of Language and Literacy Development and Disorders (pp. 433-460). Guilford.
[29]
Espy, K. A., & Bull, R. (2005). Inhibitory Processes in Young Children and Individual Variation in Short-Term Memory. Developmental Neuropsychology, 28, 669-688. https://doi.org/10.1207/s15326942dn2802_6
[30]
Friedman, N. P., Miyake, A., Corley, R. P., Young, S. E., De Fries, J. C., & Hewitt, J. K. (2006). Not All Executive Functions Are Related to Intelligence. Psychological Science, 17, 172-179. https://doi.org/10.1111/j.1467-9280.2006.01681.x
[31]
Friedman, N. P., Miyake, A., Young, S. E., DeFries, J. C., Corley, R. P., & Hewitt, J. K. (2008). Individual Differences in Executive Functions Are Almost Entirely Genetic in Origin. Journal of Experimental Psychology: General, 137, 201-225. https://doi.org/10.1037/0096-3445.137.2.201
[32]
Frith, U. (1985). Beneath the Surface of Developmental Dyslexia. In K. Patterson, J. Marshall, & M. Coltheart (Eds.), Surface Dyslexia, Neuropsychological and Cognitive Studies of Phonological Reading (pp. 301-330). Erlbaum. https://doi.org/10.4324/9781315108346-18
[33]
Fuchs, L. S., Compton, D. L., Fuchs, D., Paulsen, K., Bryant, J. D., & Hamlett, C. L. (2005). The Prevention, Identification, and Cognitive Determinants of Math Difficulty. Journal of Educational Psychology, 97, 493-513. https://doi.org/10.1037/0022-0663.97.3.493
[34]
Funahashi, S. (2001). Neuronal Mechanisms of Executive Control by the Prefrontal Cortex. Neuroscience Research, 39, 147-165. https://doi.org/10.1016/S0168-0102(00)00224-8
[35]
Hale, J. B., Reddy, L. A., Decker, S. L., Thompson, R., Henzel, J., Teodori, A., Forrest, E., Eusebio, E., & Denckla, M. B. (2009). Development and Validation of an Attention Deficit/Hyperactivity Disorder (ADHD) Executive Function and Behavior Rating Screening Battery. Journal of Clinical and Experimental Neuropsychology, 31, 897-912. https://doi.org/10.1080/13803390802687423
[36]
Harm, M. W., & Seidenberg, M. S. (2004). Computing the Meanings of Words in Reading: Cooperative Division of Labor between Visual and Phonological Processes. Psychological Review, 111, 662-720. https://doi.org/10.1037/0033-295X.111.3.662
[37]
Hirsh-Pasek, K., Golinkoff, R. M., Berk, L. E., & Singer, D. G. (2009). A Mandate for Playful Learning in School: Presenting the Evidence. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195382716.001.0001
[38]
Hughes, C. (2005). Executive Function and Development in B. In Hopkins (Ed.), Cambridge Encyclopedia of Child Development (pp. 313-316). Cambridge University Press.
[39]
Irvine, S. H., & Berry, J. W. (1988). Human Abilities in Cultural Context. Cambridge University Press. https://doi.org/10.1017/CBO9780511574603
[40]
Isquith, P. K., Crawford, J. S., Espy, K. A., & Gioia, G. A. (2005). Assessment of Executive Function in Preschool-Aged Children. Mental Retardation and Developmental Disabilities Research Review, 11, 209-215. https://doi.org/10.1002/mrdd.20075
[41]
Johnson, W., & Bouchard, T. J. (2005). The Structure of Human Intelligence: It Is Verbal, Perceptual and Image Rotation (VPR), Not Fluid and Crystallized. Intelligence, 33, 393-416. https://doi.org/10.1016/j.intell.2004.12.002
[42]
Kafadar, H., & Orhan, I. B. (2016). The Relationship between Wisconsin Card Sorting Test and Raven Standard Progressive Matrices: A Latent Variable Analysis. International Online Journal of Educational Sciences, 8, 48-56. https://doi.org/10.15345/iojes.2016.01.005
[43]
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. https://doi.org/10.1037/0033-2909.131.1.66
[44]
Kirby, J. R., & Bowers, P. N. (2017). Morphological Instruction and Literacy: Binding Phonological, Orthographic, and Semantic Features of Words. In K. Cain, D. Compton, & R. Parrila (Eds.), Theories of Reading Development (pp. 437-462). John Benjamins, Publ. https://doi.org/10.1075/swll.15.24kir
[45]
Leikin, M., Paz-Baruch, N., & Leikin, R. (2013). Memory Abilities in Generally Gifted and Excelling-in-Mathematics Adolescents. Intelligence, 41, 566-578. https://doi.org/10.1016/j.intell.2013.07.018
[46]
Luria, A. R. (1966). Human Brain and Psychological Processes. Harper & Row.
[47]
Luria, A. R. (1969). Frontal Lobe Syndromes. In P. J. Vinken, & G. W. Bruyn (Eds.), Handbook of Clinical Neurology (Vol. 2, pp. 725-757). North Holland.
[48]
Luria, A. R. (1980). Higher Cortical Functions in Man (2nd ed.). Basic Books.
[49]
Lynn, R., Allik, J., Pullman, H., & Laidra, K. (2004). Sex Differences on the Progressive Matrices among Adolescents: Some Data from Estonia. Personality and Individual Differences, 36, 1249-1255. https://doi.org/10.1016/S0191-8869(02)00240-4
[50]
Mackintosh, N. J. (1996). Sex Differences and IQ. Journal of Biosocial Science, 28, 559-572. https://doi.org/10.1017/S0021932000022586
[51]
Mahajna, I. (2012). How Language Influences Numerical Cognition: The Case of Arabic. M.A. Thesis, University of Haifa, Faculty of Education Dept. of Learning Disabilities.
[52]
Maj, M., D’ Elia, L., Satz, P., Janssen, R., Zaudig, M., Uchiyama, C., & Chervisky, A. (1993). Evaluation of Two New Neuropsychological Tests Designed to Minimize Cultural Bias in the Assessment of HIV-1 Seropositive Persons: A WHO Study. Archives of Clinical Neuropsychology, 8, 123-135. https://doi.org/10.1093/arclin/8.2.123
[53]
Martinez, K., Burgaleta, M., Roman, F. J., Escorial, S., Shih, P. C., Quiroga, M. A., & Colom, R. (2011). Can Fluid Intelligence Be Reduced to “Simple” Short-Term Storage? Intelligence, 39, 473-480. https://doi.org/10.1016/j.intell.2011.09.001
[54]
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, 1-10. https://doi.org/10.1016/j.intell.2008.08.004
[55]
Milner, B. (1963). Effects of Different Brain Lesions on Card Sorting: The Role of the Frontal Lobes. Archives of Neurology, 9, 100-110. https://doi.org/10.1001/archneur.1963.00460070100010
[56]
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., &Wagner, 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, 49. https://doi.org/10.1006/cogp.1999.0734
[57]
Norton, E. S., & Wolf, M. (2012). Rapid Automatized Naming (RAN) and Reading Fluency: Implications for Understanding and Treatment of Reading Disabilities. Annual Review of Psychology, 63, 427-452. https://doi.org/10.1146/annurev-psych-120710-100431
[58]
Orton, S. T. (1925). “Word-Blindness” in School Children. Archives of Neurology and Psychiatry, 14, 285-516. https://doi.org/10.1001/archneurpsyc.1925.02200170002001
[59]
Owen, A. M., Doyon, J., Petrides, M., & Evans, A. C. (1996). Planning and Spatial Working Memory: A Positron Emission Tomography Study in Humans. European Journal of Neuroscience, 8, 353-364. https://doi.org/10.1111/j.1460-9568.1996.tb01219.x
[60]
Perfetti, C. A. (2007). Reading Ability: Lexical Quality to Comprehension. Scientific Studies of Reading, 11, 357-383. https://doi.org/10.1080/10888430701530730
[61]
Phillipson, M., Heit, B., Colarusso, P., Liu, L., Ballantyne, C. M., & Kubes, P. (2006). Intraluminal Crawling of Neutrophils to Emigration Sites: A Molecularly Distinct Process from Adhesion in the Recruitment Cascade. The Journal of Experimental Medicine, 203, 2569-2575. https://doi.org/10.1084/jem.20060925
[62]
Plaut, D. C., McClelland, J. L., Seidenberg, M. S., & Patterson, K. (1996). Understanding Normal and Impaired Word Reading: Computational Principles in Quasi-Regular Domains. Psychological Review, 103, 56-115. https://doi.org/10.1037/0033-295X.103.1.56
[63]
Plaza, M., & Cohen, H. (2007). The Contribution of Phonological Awareness and Visual Attention in Early Reading and Spelling. Dyslexia, 13, 67-73. https://doi.org/10.1002/dys.330
[64]
Prabhakaran, V., Narayanan, K., Zhao, Z., & Gabrieli, J. D. E. (2000). Integration of Diverse Information in Working Memory within the Frontal Lobe. Nature Neuroscience, 3, 85-90. https://doi.org/10.1038/71156
[65]
Prabhakaran, V., Smith, J. A. L., Desmond, J. E., Glover, G. H., & Gabrieli, J. D. E. (1997). Neural Substrates of Fluid Reasoning: An fMRI Study of Neocortical Activation during Performance of the Raven’s Progressive Matrices Test. Cognitive Psychology, 33, 43-63. https://doi.org/10.1006/cogp.1997.0659
[66]
Raven, J. (2000a). Manual for Raven’s Progressive Matrices and Vocabulary Scales. Research Supplement No. 3{2nd Ed.): A Compendium of International and North American Normative and Validity Studies Together with a Review of the Use of the RPM in Neuro-Psychological Assessment, by Court, Drebing, & Hughes. Harcourt Assessment.
[67]
Raven, J. (2000b). The Raven’s Progressive Matrices: Change and Stability over Culture and Time. Cognitive Psychology, 41, 1-48. https://doi.org/10.1006/cogp.1999.0735
[68]
Raven, J. (2008). The Raven Progressive Matrices Tests: Their Theoretical Basis and Measurement Model. Uses and Abuses of Intelligence: Studies Advancing Spearman and Raven’s Quest for Non-Arbitrary (pp. 17-68).
[69]
Raven, J. (2009). The Raven Progressive Matrices and Measuring Aptitude Constructs. The International Journal of Educational and Psychological Assessment, 2, 2-38.
[70]
Raven, J. C., Court, J. H., & Raven, J. (1990). Manual for Raven’s Colored Progressive Matrices. Oxford Psychologists Press.
[71]
Raven, J., Raven, J. C., & Court, J. H. (1998, Updated 2003). Manual for Raven’s Progressive Matrices and Vocabulary Scales. Section 1: General Overview. Harcourt Assessment.
[72]
Roca, C., Cuesta, J. A., & Sánchez, A. (2009). Effect of Spatial Structure on the Evolution of Cooperation. Physical Review E, 80, Article ID: 046106. https://doi.org/10.1103/PhysRevE.80.046106
[73]
Rockstroh, S., & Schweizer, K. (2001). The Contributions of Memory and Attention Processes to Cognitive Abilities. Journal of General Psychology, 128, 30-42. https://doi.org/10.1080/00221300109598896
[74]
Rohde, T. A., & Thompson, L. A. (2007). Predicting Academic Achievement with Cognitive Ability. Intelligence, 35, 83-92. https://doi.org/10.1016/j.intell.2006.05.004
[75]
Rouinfar, A., Agra, E., Larson, A. M., Loschky, L. C., & Rebello, N. S. (2014). Linking Attentional Processes and Conceptual Problem Solving: Visual Cues Facilitate the Automaticity of Extracting Relevant Information from Diagrams. Frontiers in Psychology, 5, Article No. 1049. https://doi.org/10.3389/fpsyg.2014.01094
[76]
Schweizer, K., & Moosbrugger, H. (2004). Attention and Working Memory as Predictors of Intelligence. Intelligence, 32, 329-347. https://doi.org/10.1016/j.intell.2004.06.006
[77]
Schweizer, K., Zimmermann, P., & Koch, W. (2000). Sustained Attention, Intelligence and the Crucial Role of Perceptual Processes. Learning and Individual Differences, 12, 271-286. https://doi.org/10.1016/S1041-6080(01)00040-1
[78]
Seidenberg, M. S., & McClelland, J. L. (1989). A Distributed, Developmental Model of Word Recognition and Naming. Psychological Review, 96, 523-568. https://doi.org/10.1037/0033-295X.96.4.523
[79]
Senn, T., Espy, K., & Kaufmann, P. (2004). Using Path Analysis to Understand Executive Function Organization in Preschool Children. Developmental Neuropsychology, 26, 445-464. https://doi.org/10.1207/s15326942dn2601_5
[80]
Smidts, D., Jacobs, R., & Anderson, V. (2004). The Object Classification Task for Children (OCTC): A Measure of Concept Generation and Mental Flexibility in Early Childhood. Developmental Neuropsychology, 26, 385-401. https://doi.org/10.1207/s15326942dn2601_2
[81]
Stein, J., & Walsh, V. (1997). To See But Not to Read: The Magnocellular Theory of Dyslexia. Trends in Neurosciences, 20, 147-152. https://doi.org/10.1016/S0166-2236(96)01005-3
[82]
Strauss, E., Sherman, E. M., & Spreen, S. (2006). A Compendium of Neuropsychological tests: Administration, Norms, and Commentary (3rd ed., pp. 32-37). Oxford University Press.
[83]
Stuss, D. T., & Knight, R. T. (2002). Principles of Frontal Lobe Function. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195134971.001.0001
[84]
Stuss, D. T., & Alexander, M. P. (2000). Executive Functions and the Frontal Lobes: A Conceptual View. Psychological Research, 63, 289-298. https://doi.org/10.1007/s004269900007
[85]
Sweet, L. H., Rao, S. M., Primeau, M., Mayer, A. R., & Cohen, R. A. (2004). Functional Magnetic Resonance Imaging of Working Memory among Multiple Sclerosis Patients. Journal of Neuroimaging, 14, 150-157. https://doi.org/10.1111/j.1552-6569.2004.tb00232.x
[86]
Tahan, S., Cline, T., & Messaoud-Galusi, S. (2011). The Relationship between Language Dominance and Pre-Reading Skills in Young Bilingual Children in Egypt [Special Issue]. Reading and Writing: An Interdisciplinary Journal, 24, 1061-1087. https://doi.org/10.1007/s11145-011-9301-3
[87]
Tanji, J., & Hoshi, E. (2008). Role of the Lateral Prefrontal Cortex in Executive Behavioral Control. Physiological Review, 88, 37-57. https://doi.org/10.1152/physrev.00014.2007
[88]
Taub, G. E., Floyd, R. G., Keith, T. Z., & McGrew, K. S. (2008). Effects of General and Broad Cognitive Abilities on Mathematics Achievement. School Psychology Quarterly, 23, 187-198. https://doi.org/10.1037/1045-3830.23.2.187
[89]
Turkeltaub, P. E., Gareau, L., Flowers, D. L., Zeffiro, T. A., & Eden, G. F. (2003). Development of Neural Mechanisms for Reading. Natural Neuroscience, 6, 767-773. https://doi.org/10.1038/nn1065
[90]
Van der Elst, W., Van Boxtel, M. P. J., Van Breukelen, G. J. P., & Jolles, J. (2006). The Stroop Color-Word Test: Influence of Age, Sex, and Education; and Normative Data for a Large Sample across the Adult Age Range. Assessment, 13, 62-79. https://doi.org/10.1177/1073191105283427
[91]
Vanderwood, M. L., McGrew, K. S., Flanagan, D. P., & Keith, T. Z. (2002). The Contribution of General and Specific Cognitive Abilities to Reading Achievement. Learning and Individual Differences, 13, 159-188. https://doi.org/10.1016/S1041-6080(02)00077-8
[92]
Verguts, T., & De Boeck, P. (2002). The Induction of Solution Rules in Raven’s Progressive Matrices Test. European Journal of Cognitive Psychology, 14, 521-547. https://doi.org/10.1080/09541440143000230
[93]
Vincent, K. R., & Cox, J. A. (1974). A Re-Evaluation of Raven’s Standard Progressive Matrices. The Journal of Psychology, 88, 299-303. https://doi.org/10.1080/00223980.1974.9915740
[94]
Wechsler, D. (1998). Manual for the Wechsler Intelligence Scale for Children-Third Edition. The Psychological Corporation. https://doi.org/10.1037/t49755-000
[95]
Zelazo, P. D., Müller, U., Frye, D., & Marcovitch, S. (2003). The Development of Executive Function in Early Childhood. Monographs, Society for Research in Child Development, 68 (3, Serial No. 1).
