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‘Children at Risk’ of Poor Educational Outcomes: Insights from a (Neuro-)Cognitive Perspective

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Abstract

Taking a (neuro-)cognitive perspective, this article deals with preconditions of successful learning and maladaptive developmental processes related to deficient learning processes and poor educational outcomes. Three strands of research are focused that have made significant contributions to the understanding of (neuro-)cognitive risks for poor educational outcomes: intelligence research, research on working memory, and research on attentional processes. Selected examples from these areas of research are provided with a summary of main conclusions. In addition, we highlight current research gaps by arguing that there is a specific need for (a) future research focusing on the interactions between the (neuro-)cognitive functions described, as well as for (b) integrating results from the (neuro-)cognitive perspective into a broader conceptual framework of risk factors. A claim is made that more research is needed linking insights from different scientific perspectives and methodological traditions to generate approaches that successfully contribute to a substantial reduction of the percentage of students with poor educational outcomes.

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References

  • 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). doi:10.1016/j.jecp.2009.11.003.

  • Alloway, T. P., Gathercole, S. E., Adams, A. M., Willis, C., Eaglen, R., & Lamont, E. (2005). Working memory and other cognitive skills as predictors of progress towards early learning goals at school entry. British Journal of Developmental Psychology, 23, 417–426.

    Google Scholar 

  • Alloway, T. P., & Gathercole, S. E. (2006). How does working memory work in the classroom ? Educational Research and Reviews, 1(4), 134–139.

    Google Scholar 

  • Awh, E., Vogel, E. K., & Oh, S.-H. (2006). Interactions between attention and working memory. Neuroscience, 139(1), 201–208. doi:10.1016/j.neuroscience.2005.08.023.

    Google Scholar 

  • Baddeley, A. D. (1986). Working memory. Oxford: Oxford University Press.

    Google Scholar 

  • Baddeley, A. D. (2007). Working memory, thought and action. Oxford: Oxford University Press.

    Google Scholar 

  • Baddeley, A. (2012). Working memory: theories, models, and controversies. Annual Review of Psychology, 63(1), 1–29. doi:10.1146/annurev-psych-120710-100422.

    Google Scholar 

  • Barkley, R. A., Fischer, M., Edelbrock, C. S., & Smallish, L. (1990). The adolescent outcome of hyperactive children diagnosed by research criteria: an 8-year prospective follow-up study. Journal of the American Academy of Child and Adolescent Psychiatry, 29(4), 546–557.

    Google Scholar 

  • Barkley, R. A. (1997). ADHD and the nature of self-control. New York: Guilford Press.

    Google Scholar 

  • Biederman, J. (1998). Resolved: mania is mistaken for ADHD in prepubertal children. Journal of the American Academy of Child & Adolescent Psychiatry, 37(10), 1091–1099.

    Google Scholar 

  • Biederman, J., Newcorn, J., & Sprich, S. (1991). Comorbidity of attention deficit hyperactivity disorder with conduct, depressive, anxiety, and other disorders. American Journal of Psychiatry, 148(5), 564–577.

    Google Scholar 

  • Biederman, J., Faraone, S., Milberger, S., Guite, J., Mick, E., Chen, L., et al. (1996). A prospective 4-year follow-up study of attention-deficit hyperactivity and related disorders. Archives of General Psychiatry, 53(5), 437–446. doi:10.1001/archpsyc.1996.01830050073012.

    Google Scholar 

  • Binet, A., & Simon, T. (1916). The development of intelligence in children. Baltimore: Williams & Wilkens (E. S. Kite, Trans.).

  • Breslau, J., Miller, E., Breslau, N., Bohnert, K., Lucia, V., & Schweitzer, J. (2009). The impact of early behavior disturbances on academic achievement in high school. Pediatrics, 123(6), 1472–1476. doi:10.1542/peds.2008-1406.

    Google Scholar 

  • Buehner, M., Krumm, S., Ziegler, M., & Pluecken, T. (2006). Cognitive abilities and their interplay. Journal of Individual Differences, 27(2), 57–72. doi:10.1027/1614-0001.27.2.57.

    Google Scholar 

  • Bull, R., Johnston, R. S., & Roy, J. A. (1999). Exploring the roles of the visual-spatial sketchpad and central executive in children’s arithmetical skills: views from cognition and developmental neuropsychology. Developmental Neuropsychology, 15, 421–442.

    Google Scholar 

  • Bull, R., Espy, K. A., & Wiebe, S. A. (2008). Short-term memory, working memory, and executive functions in preschoolers: longitudinal predictors of mathematical achievement at age 7 years. Developmental Neuropsychology, 33, 205–228. doi:10.1080/87565640801982312.

    Google Scholar 

  • Bull, R., & Scerif, G. (2001). Executive functioning as a predictor of children’s mathematics ability: inhibition, switching, and working memory. Developmental Neuropsychology, 19(3), 273–293.

    Google Scholar 

  • Cattell, R. B. (1943). The measurement of adult intelligence. Psychological Bulletin, 40, 153–193.

    Google Scholar 

  • Cattell, R. B. (1963). Theory of fluid and crystallized intelligence: a critical experiment. Journal of Educational Psychology, 54(1), 1–22.

    Google Scholar 

  • Carroll, J. B. (1993). Human cognitive abilities. Cambridge: Cambridge University Press.

    Google Scholar 

  • Colom, R., Escorial, S., Shih, P. C., & Privado, J. (2007). Fluid intelligence, memory span, and temperament difficulties predict academic performance of young adolescents. Personality and Individual Differences, 42(8), 1503–1514. doi:10.1016/j.paid.2006.10.023.

    Google Scholar 

  • Conway, A. R. A., Cowan, N., Bunting, M. F., Therriault, D. J., & Minkoff, S. R. B. (2002). A latent variable analysis of working memory capacity, short-term memory capacity, processing speed, and general fluid intelligence. Intelligence, 30(2), 163–183.

    Google Scholar 

  • Corbetta, M., & Shulman Gordon, L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3(3), 201–215. doi:10.1038/nrn755.

    Google Scholar 

  • Corkum, P., McGonnell, M., & Schachar, R. (2010). Factors affecting academic achievement in children with ADHD. Journal of Applied Research on Learning, 3, 1–14.

    Google Scholar 

  • Cowan, N. (1995). Attention and memory: an integrated framework. Oxford psychology series, No.26. Oxford University Press.

  • Daley, D., & Birchwood, J. (2010). Child: impact on academic performance and what can be. Child: Care, Health and Development, 36(4), 455–464. doi:10.1111/j.1365-2214.2009.01046.x.

    Google Scholar 

  • D’Amico, A., & Guarnera, M. (2005). Exploring working memory in children with low arithmetical achievement. Learning and Individual Differences, 15(3), 189–202. doi:10.1016/j.lindif.2005.01.002.

    Google Scholar 

  • Davidson, J. E., & Kemp, I. A. (2011). Contemporary models of intelligence. In R. J. Sternberg & S. B. Kaufman (Eds.), The Cambridge handbook of intelligence (pp. 58–84). New York: Cambridge University Press.

    Google Scholar 

  • Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and educational achievement. Intelligence, 35(1), 13–21. doi:10.1016/j.intell.2006.02.001.

    Google Scholar 

  • DeStefano, D., & LeFevre, J.-A. (2004). The role of working memory in mental arithmetic. European Journal of Cognitive Psychology, 16, 353–386.

    Google Scholar 

  • Duncan, G. J., Magnuson, K., Pagani, L. S., Engel, M., Feinstein, L., Brooks-Gunn, J., Sexton, H., et al. (2007). School readiness and later achievement. Developmental Psychology, 43(6), 1428–1446. doi:10.1037/0012-1649.43.6.1428.

    Google Scholar 

  • Eden, G. F., & Stein, J. F. (1995). Verbal and visual problems in reading disability. Journal of Learning Disabilities, 28(5), 272–290.

    Google Scholar 

  • Engel, P. M. J., Heloisa Dos Santos, F., & Gathercole, S. E. (2008). Are working memory measures free of socio-economic influence? Journal of Speech, Language, and Hearing Research, 51, 1580–1587. doi:10.1044/1092-4388.

    Google Scholar 

  • Farah, M. J., Shera, D. M., Savage, J. H., Betancourt, L., Giannetta, J. M., Brodsky, N. L., et al. (2006). Childhood poverty: specific associations with neurocognitive development. Brain Research, 1110(1), 166–174. doi:10.1016/j.brainres.2006.06.072.

    Google Scholar 

  • Fergusson, D. M., & Horwood, L. J. (1995). Early disruptive behavior, IQ, and later school achievement and delinquent behavior. Journal of Abnormal Child Psychology, 23(2), 183–199.

    Google Scholar 

  • Fergusson, D. M., Lynskey, M. T., & Horwood, L. J. (1997). Attentional difficulties in middle childhood and psychosocial outcomes in young adulthood. Journal of Child Psychology & Psychiatry, 38(6), 633–644.

    Google Scholar 

  • Forness, S. R., Youpa, D., Hanna, G. L., Cantwell, D. P., & Swanson, J. M. (1992). Classroom instructional characteristics in attention deficit hyperactivity disorder: comparison of pure and mixed subgroups. Behavioral Disorders, 17, 115–125.

    Google Scholar 

  • Frazier, T. W., Youngstrom, E. A., Glutting, J. J., & Watkins, M. W. (2007). ADHD and achievement: meta-analysis of the child, adolescent, and adult literatures and a concomitant study with college students. Journal of Learning Disabilities, 40(1), 49–65. doi:10.1177/00222194070400010401.

    Google Scholar 

  • Gathercole, S. E., Alloway, T. P., Willis, C., & Adams, A.-M. (2006). Working memory in children with reading disabilities. Journal of Experimental Child Psychology, 93, 265–281. doi:10.1016/j.jecp.2005.08.003.

    Google Scholar 

  • Geary, D. C. (2011). Cognitive predictors of achievement growth in mathematics : a 5-year longitudinal study. Developmental Psychology, 47(6), 1539–1552. doi:10.1037/a0025510.

    Google Scholar 

  • Geary, D. C., Hoard, M. K., Byrd-Craven, J., & Desoto, M. (2004). Strategy choices in simple and complex addition: contributions of working memory and counting knowledge for children with mathematical disability. Journal of Experimental Child Psychology, 88, 121–151. doi:10.1016/j.jecp.2004.03.002.

    Google Scholar 

  • Geary, D. C., Brown, S. C., & Samaranayake, V. A. (1991). Cognitive addition: a short longitudinal study of strategy choice and speed- of-processing differences in normal and mathematically disabled children. Developmental Psychology, 27, 787–797.

    Google Scholar 

  • Geary, D. C., Hamson, C. O., & Hoard, M. K. (2000). Numerical and arithmetical cognition: a longitudinal study of process and concept deficits in children with learning disability. Journal of Experimental Child Psychology, 77, 236–263.

    Google Scholar 

  • Geary, D. C., Hoard, M. K., & Hamson, C. O. (1999). Numerical and arithmetical cognition: patterns of functions and deficits in children at risk for a mathematical disability. Journal of Experimental Child Psychology, 74, 213–239.

    Google Scholar 

  • Geary, D. C., Hoard, M. K., & Nugent, L. (2012). Independent contributions of the central executive, intelligence, and in-class attentive behavior to developmental change in the strategies used to solve addition problems. Journal of Experimental Child Psychology, 113, 49–65.

    Google Scholar 

  • Glutting, J. J., Youngstrom, E. A., & Watkins, M. W. (2005). ADHD and college students: exploratory and confirmatory factor structures with student and parent data. Psychological Assessment, 17(1), 44–55. doi:10.1037/1040-3590.17.1.44.

    Google Scholar 

  • Goldstein, H. S. (1987). Cognitive development in low attentive, hyperactive, and aggressive 6-through 11-year-old children. Journal of the American Academy of Child and Adolescent Psychiatry, 26, 214–218.

    Google Scholar 

  • Gordon, M., Thomason, D., & Cooper, S. (1990). To what extend does attention affect K-ABC scores. Psychology in the Schools, 27, 144–147.

    Google Scholar 

  • Heiligenstein, E., Guenther, G., Levy, A., Savino, F., & Fulwiler, J. (1999). Psychological and academic functioning in college students with Attention Deficit Hyperactivity Disorder. Journal of American College Health, 47, 181–185.

    Google Scholar 

  • Hitch, G. J., & McAuley, E. (1991). Working memory in children with specific arithmetical learning difficulties. British Journal of Psychology, 82, 375–386.

    Google Scholar 

  • Howes, N., Bigler, E. D., Burlingame, G. M., & Lawson, J. S. (2003). Memory Performance of Children with Dyslexia: a comparative analysis of theoretical perspectives. Journal of Learning Disabilities, 36(3), 230–246.

    Google Scholar 

  • Hoza, B., Pelham, W. E., Dobbs, J., Owens, J. S., & Pillow, D. R. (2002). Do boys with attention-deficit/hyperactivity disorder have positive illusory self-concepts? Journal of Abnormal Psychology, 111(2), 268–278. doi:10.1037/0021-843X.111.2.268.

    Google Scholar 

  • Johnson, W., Deary, I. J., & Iacono, W. G. (2009). Genetic and environmental transactions underlying educational attainment. Intelligence, 37(5), 466–478. doi:10.1016/j.intell.2009.05.006.

    Google Scholar 

  • Kaufman, S. B., Reynolds, M. R., Liu, X., Kaufman, A. S., & McGrew, K. S. (2012). Are cognitive g and academic achievement g one and the same g? An exploration on the Woodcock–Johnson and Kaufman tests. Intelligence, 40(2), 123–138. doi:10.1016/j.intell.2012.01.009.

    Google Scholar 

  • Knudsen, E. I. (2007). Fundamental components of attention. Annual Review of Neuroscience, 30, 57–78. doi:10.1146/annurev.neuro.30.051606.094256.

    Google Scholar 

  • Kibby, M. Y., Marks, W., Morgan, S., & Long, C. J. (2004). Specific impairment in developmental reading disabilities: a working memory approach. Journal of Learning Disabilities, 37(4), 349–363. doi:10.1177/00222194040370040601.

    Google Scholar 

  • Klein, R. G., & Mannuzza, S. (1991). Long-term outcome of hyperactive children: a review. Journal of the American Academy of Child & Adolescent Psychiatry, 3(3), 383–387.

    Google Scholar 

  • Krumm, S., Ziegler, M., & Buehner, M. (2008). Reasoning and working memory as predictors of school grades. Intelligence, 18, 248–257. doi:10.1016/j.lindif.2007.08.002.

    Google Scholar 

  • Lan, X., Legare, C. H., Cameron, C., Li, S., & Morrison, F. J. (2011). Investigating the links between the subcomponents of executive function and academic achievement: a cross-cultural analysis of Chinese and American preschoolers. Journal of Experimental Child Psychology, 108, 677–692. doi:10.1016/j.jecp.2010.11.001.

    Google Scholar 

  • Landerl, K., Bevan, A., & Butterworth, B. (2004). Developmental dyscalculia and basic numerical capacities: a study of 8-9-year-old students. Cognition, 93(2), 99–125. doi:10.1016/j.cognition.2003.11.004.

    Google Scholar 

  • Lu, L., Weber, H. S., Spinath, F. M., & Shi, J. (2012). Predicting school achievement from cognitive and non-cognitive variables in a Chinese sample of elementary school children. Intelligence, 39(2–3), 130–140. doi:10.1016/j.intell.2011.02.002.

    Google Scholar 

  • Lupien, S. J., McEwen, B. S., Gunnar, M. R., & Heim, C. (2009). Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nature Reviews Neuroscience, 10(6), 434–445. doi:10.1038/nrn2639.

    Google Scholar 

  • Luthar, S. S., Cicchetti, D., & Becker, B. (2000). The construct of resilience : a critical evaluation and guidelines for future work. Child Development, 71(3), 543–562.

    Google Scholar 

  • Mackintosh, N. J. (1998). IQ and human intelligence. Oxford: Oxford University Press.

    Google Scholar 

  • Masten, A. S. (2001). Ordinary magic: resilience processes in development. American Psychologist, 56, 227–238.

    Google Scholar 

  • Mayes, S. D., & Calhoun, S. L. (2007a). Learning, attention, writing, and processing speed in typical children and children with ADHD, autism, anxiety, depression, and oppositional-defiant disorder. Child Neuropsychology, 13(6), 469–493. doi:10.1080/09297040601112773.

    Google Scholar 

  • Mayes, S. D., & Calhoun, S. L. (2007b). Wechsler Intelligence Scale for Children-Third and -Fourth Edition predictors of academic achievement in children with attention-deficit/hyperactivity disorder. School Psychology Quarterly, 22(2), 234–249. doi:10.1037/1045-3830.22.2.234.

    Google Scholar 

  • McEwen, B. S. (2000). The neurobiology of stress: from serendipity to clinical relevance. Brain Research, 886(1–2), 172–189.

    Google Scholar 

  • McGee, R., Prior, M., Willams, S., Smart, D., & Sanson, A. (2002). The long-term significance of teacher-rated hyperactivity and reading ability in childhood: findings from two longitudinal studies. Journal of Child Psychology & Psychiatry, 43(8), 1004–1017. doi:10.1111/1469-7610.00228.

    Google Scholar 

  • McGrew, K. S. (1997). Analysis of the major intelligence batteries according to a proposed comprehensive Gf-Gc framework. In D. P. Flanagan, J. L. Genshaft, & P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (pp. 151–179). New York: Guilford Press.

    Google Scholar 

  • McGrew, K. S. (2005). CHC theory of cognitive abilities. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (2nd ed., pp. 136–181). New York: Guilford Press.

    Google Scholar 

  • McGrew, K. S. (2009). Editorial 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.

    Google Scholar 

  • McLean, J. F., & Hitch, G. J. (1999). Working memory impairments in children with specific arithmetic learning difficulties. Journal of Experimental Child Psychology, 74(3), 240–260. doi:10.1006/jecp.1999.2516.

    Google Scholar 

  • Menghini, D., Finzi, A., Carlesimo, G. A., Foundation, S. L., & Vicari, S. (2011). Working memory impairment in children with developmental dyslexia : Is it just a phonological deficity ? Developmental Neuropsychology, 36(2), 199–213. doi:10.1080/87565641.2010.549868.

    Google Scholar 

  • Merkt, J., Singmann, H. Bodenburg, S., Goossens-Merkt, H., Kappes, A., Wendt, M., & Gawrilow, C. (2012). Flanker performance in female college students with ADHD: a diffusion model analysis. ADHD, 5, 321–341. doi: 10.1007/s12402-013-0110-1

  • Michalczyk, K., & Hasselhorn, M. (2010). Woking memory in developmental psychology. In H. P. Trolldenier, W. Lenhard, & P. Marx (Eds.), Brennpunkte der Gedächtnisforschung (pp. 87–100). Göttingen: Hogrefe.

    Google Scholar 

  • Miyake, A., & Shah, P. (1999). Toward unified theories of working memory: Emerging general consensus, unresolved theoretical issues, and future research directions. In A. Miyake & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 442–482). New York: Cambridge University Press.

    Google Scholar 

  • Naglieri, J. A., & Bornstein, B. T. (2003). Intelligence and achievement: just how correlated are they? Journal of Psychoeducational Assessment, 21(3), 244–260. doi:10.1177/073428290302100302.

    Google Scholar 

  • OECD (2010). PISA 2009 Results: Learning trends: Changes in student performance since 2000 (Volume V) http://dx.doi.org/10.1787/9789264091580-en.

  • O’Shaughnessy, T. E. O., & Swanson, H. L. (1998). Do immediate memory deficits in students with learning disabilities in reading reflect a developmental lag or deficit? A selective meta-analysis of the literature. Learning Disability Quarterly, 21(2), 123–148.

    Google Scholar 

  • Palmer, S. (2000). Phonological recoding deficit in working memory of dyslexic teenagers. Journal of Research in Reading, 23(1), 28–40. doi:10.1111/1467-9817.00100.

    Google Scholar 

  • Passolunghi, M. C. (2006). Working memory and arithmetic learning disability. In T. P. Alloway & S. E. Gathercole (Eds.), Working memory and neurodevelopmental disorders (pp. 113–138). Hove: Psychology Press.

    Google Scholar 

  • Passolunghi, M. C., & Siegel, L. S. (2001). Short-term memory, working memory, and inhibitory control in children with specific arithmetic learning disabilities. Journal of Experimental Child Psychology, 80, 44–57.

    Google Scholar 

  • Perkins, D. F., & Borden, L. M. (2003). Positive behaviors, problem behaviors, and resiliency in adolescence. In T. M. Millon & M. J. Lerner (Eds.), Handbook of psychology: Developmental psychology (pp. 373–394). Hoboken: Wiley.

    Google Scholar 

  • Pickering, S. J. (2006). Working memory in dyslexia. In T. P. Alloway & S. E. Gathercole (Eds.), Working memory and neurodevelopmental disorders (pp. 7–40). Hove: Psychology Press.

    Google Scholar 

  • Pliszka, S. R. (1998). Comorbidity of attention-deficit/hyperactivity disorder with psychiatric disorder: an overview. Journal of Clinical Psychiatry, 59(2), 50–58.

    Google Scholar 

  • Purvis, K. L., & Tannock, R. (1997). Language abilities in children with attention deficit hyperactivity disorder, reading disabilities, and normal controls. Journal of Abnormal Child Psychology, 25(2), 133–144. doi:10.1023/A:1025731529006.

    Google Scholar 

  • Purvis, K. L., & Tannock, R. (2000). Phonological processing, not inhibitory control, differentiates ADHD and reading disability. Journal of the American Academy of Child and Adolescent Psychiatry, 39(4), 485–494.

    Google Scholar 

  • Reuhkala, M. (2001). Mathematical skills in ninth-graders: relationship with visuospatial abilities and working memory. Educational Psychology, 21, 387–398.

    Google Scholar 

  • Rogers, M., Hwang, H., Toplak, M., & Tannock, R. (2011). Inattention, working memory, and academic achievement in adolescents referred for attention deficit/ hyperactivity disorder (ADHD). Child Neuropsychology, 17(5), 444–458.

    Google Scholar 

  • Rohde, T. E., & Thompson, L. A. (2007). Predicting academic achievement with cognitive ability. Intelligence, 35(1), 83–92. doi:10.1016/j.intell.2006.05.004.

    Google Scholar 

  • Sandson, T. A., Bachna, K. J., & Morin, M. D. (2000). Right hemisphere dysfunction in ADHD: visual hemispatial inattention and clinical subtype. Journal of Learning Disabilities, 33(1), 83–90. doi:10.1177/002221940003300111.

    Google Scholar 

  • Schuchardt, K., Maehler, C., & Hasselhorn, M. (2008). Working memory deficits in children with specific learning disorders. Journal of Learning Disabilities, 41(6), 514–523. doi:10.1177/0022219408317856.

    Google Scholar 

  • Sheehy, K., & Rix, J. (2009). A systematic review of whole class, subject-based pedagogies with reported outcomes for the academic and social inclusion of pupils with special educational needs. In: Research Evidence in Education Library. London: EPPI-Centre, Social Science Research Unit, Institute of Education, University of London.

  • Shonkoff, J. P. (2010). Building a new biodevelopmental framework to guide the future of early childhood policy. Child Development, 81(1), 357–367. doi:10.1111/j.1467-8624.2009.01399.x.

    Google Scholar 

  • Shonkoff, J. P. (2011). Protecting brains, not simply stimulating minds. Science, 333(6045), 982–983. doi:10.1126/science.1206014.

    Google Scholar 

  • Sparfeldt, J. R., Buch, S. R., & Rost, D. H. (2010). Klassenprimus bei durchschnittlicher Intelligenz. [Best in class with average intelligence]. Zeitschrift für Pädagogische Psychologie, 24(2), 147–155. doi:10.1024/1010-0652/a000012.

    Google Scholar 

  • Spearman, C. (1927). The abilities of man. New York: Macmillan.

    Google Scholar 

  • Steinmayr, R., Ziegler, M., & Träuble, B. (2010). Do intelligence and sustained attention interact in predicting academic achievement? Learning and Individual Differences, 20(1), 14–18. doi:10.1016/j.lindif.2009.10.009.

    Google Scholar 

  • Strenze, T. (2007). Intelligence and socioeconomic success: a meta-analytic review of longitudinal research. Intelligence, 35(5), 401–426. doi:10.1016/j.intell.2006.09.004.

    Google Scholar 

  • Swanson, H. L. (1993). Working memory in learning disability subgroups. Journal of Experimental Child Psychology, 5(1), 87–114. doi:10.1006/jecp.1993.1027.

    Google Scholar 

  • Swanson, H. L. (1999). Reading comprehension and working memory in learning-disabled readers: is the phonological loop more important than the executive system? Journal of Experimental Child Psychology, 72(1), 1–31. doi:10.1006/jecp.1998.2477.

    Google Scholar 

  • Swanson, H. L. (2006). Working memory and reading disabilities: Both phonological and executive processing deficits are important. In T. P. Alloway & S. E. Gathercole (Eds.), Working memory and neurodevelopmental disorders (pp. 59–88). Hove: Psychology Press.

    Google Scholar 

  • Swanson, H. L. (2011). Working memory, attention, and mathematical problem solving: a longitudinal study of elementary school children. Journal of Educational Psychology, 103(4), 821–837. doi:10.1037/a0025114.

    Google Scholar 

  • Swanson, H. L., Jerman, O., & Zheng, X. (2008). Growth in working memory and mathematical problem solving in children at risk and not at risk for serious math difficulties. Journal of Educational Psychology, 100(2), 343–379. doi:10.1037/0022-0663.100.2.343.

    Google Scholar 

  • Swanson, H. L., & Sachse-Lee, C. (2001). Mathematical problem solving and working memory in children with learning disabilities: both executive and phonological processes are important. Journal of Experimental Child Psychology, 79(3), 294–321. doi:10.1006/jecp.2000.2587.

    Google Scholar 

  • Thurstone, L. L. (1938). Primary mental abilities. Chicago: University of Chicago Press.

    Google Scholar 

  • van der Sluis, S., van der Leij, A., & de Jong, P. F. (2005). Working memory in Dutch children with reading- and arithmetic-related LD. Journal of Learning Disabilities, 38, 207–221.

    Google Scholar 

  • Vellutino, F. R., Fletcher, J. M., Snowling, M. J., & Scanlon, D. M. (2004). Specific reading disability (dyslexia): what have we learned in the past four decades? Journal of Child Psychology & Psychiatry, 45(1), 2–40. doi:10.1046/j.0021-9630.2003.00305.x.

    Google Scholar 

  • Werner, E. E., & Smith, R. S. (1992). Overcoming the odds: High risk children from birth to adulthood. Ithaca: Cornell University Press.

    Google Scholar 

  • Weyandt, L. L., & DuPaul, G. (2006). ADHD in college students. Journal of Attention Disorders, 10(1), 9–19. doi:10.1177/1087054705286061.

    Google Scholar 

  • Willcutt, E. G., DeFries, J. C., Pennington, B. F., Olson, R. K., Smith, S. D., & Cardon, L. R. (2003). Genetic etiology of comorbid reading difficulties and ADHD. In R. Plomin, J. C. DeFries, P. McGuffin, & I. Craig (Eds.), Behavioral genetics in a postgenomic era (pp. 227–246). Washington: American Psychological Association.

    Google Scholar 

  • Wilson, K. M., & Swanson, H. L. (2001). Are mathematics disabilities due to a domain-general or a domain-specific working memory deficit? Journal of Learning Disabilities, 34, 237–248.

    Google Scholar 

  • Wood, F. B., & Grigorenko, E. L. (2001). Emerging issues in the genetics of dyslexia: a methodological preview. Journal of Learning Disabilities, 34(6), 503–511. doi:10.1177/002221940103400603.

    Google Scholar 

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Acknowledgments

The preparation of this paper was funded by the federal state government of Hesse (LOEWE initiative).

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Schmid, J., Hasselhorn, M. ‘Children at Risk’ of Poor Educational Outcomes: Insights from a (Neuro-)Cognitive Perspective. Child Ind Res 7, 735–749 (2014). https://doi.org/10.1007/s12187-014-9260-8

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  • DOI: https://doi.org/10.1007/s12187-014-9260-8

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