Skip to main content
Online ISSN: 2622-5506
Articles

WISC-V cognitive indicators of mathematical learning disabilities in elementary school students: A case-control study

DOI: https://doi.org/10.33292/petier.v8i2.317

Abstract

Mathematical learning disabilities (MLD) involve persistent and heterogeneous difficulties in acquiring age-appropriate mathematical skills, requiring assessment through both cognitive and classroom-based indicators. This study examined whether WISC-V profiles differentiate elementary students with MLD from typically developing peers and support an integrated classification model. A case-control design involved 120 students aged 8–12 years, comprising 60 students formally identified with MLD and 60 age-matched controls. Participants completed the WISC-V Chinese Edition and a Mathematical Achievement Test, while teachers completed the Teacher Questionnaire on Mathematical Performance. Data were analyzed using t tests, effect sizes, correlations, discriminant analysis, and ROC analysis. Students with MLD scored significantly lower on all WISC-V primary indices, particularly Working Memory (d = 2.10) and Processing Speed (d = 1.60). Quantitative Reasoning showed the strongest ancillary-index separation (d = 3.03). Arithmetic, Digit Span, and Figure Weights were the most discriminating subtests. MAT deficits were greatest in word problems (d = 3.29) and mental computation (d = 3.03). QRI correlated most strongly with MAT total score (r = .84, p < .001), and the combined model achieved 89.2% accuracy and AUC = .986. QRI, WMI, Arithmetic, Digit Span, word problems, and mental computation are promising screening indicators for MLD, pending external validation.

References

  1. American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders (5th ed., text rev.). American Psychiatric Association Publishing. https://doi.org/10.1176/appi.books.9780890425787
  2. Becker, A., Daseking, M., & Kerner auch Koerner, J. (2021). Cognitive profiles in the WISC-V of children with ADHD and specific learning disorders. Sustainability, 13(17), 9948. https://doi.org/10.3390/su13179948
  3. Butterworth, B., Varma, S., & Laurillard, D. (2011). Dyscalculia: From brain to education. Science, 332(6033), 1049-1053. https://doi.org/10.1126/science.1201536
  4. De Smedt, B., Janssen, R., Bouwens, K., Verschaffel, L., Boets, B., & Ghesquiere, P. (2009). Working memory and individual differences in mathematics achievement: A longitudinal study from first grade to second grade. Journal of Experimental Child Psychology, 103(2), 186-201. https://doi.org/10.1016/j.jecp.2009.01.004
  5. Ding, Y., Xiao, F., Fan, Z. H., & Zhang, D. K. (2016). A brief introduction to the performance of the Wechsler Intelligence Scale for Children-Fifth Edition in the United States. Chinese Journal of Special Education, 7, 18-25.
  6. Geary, D. C. (2004). Mathematics and learning disabilities. Journal of Learning Disabilities, 37(1), 4-15. https://doi.org/10.1177/00222194040370010201
  7. Geary, D. C. (2011). Cognitive predictors of achievement growth in mathematics: A five-year longitudinal study. Developmental Psychology, 47(6), 1539-1552. https://doi.org/10.1037/a0025510
  8. Geary, D. C. (2013). Early foundations for mathematics learning and their relations to learning disabilities. Current Directions in Psychological Science, 22(1), 23-27. https://doi.org/10.1177/0963721412469398
  9. Kucian, K., & von Aster, M. (2015). Developmental dyscalculia. European Journal of Pediatrics, 174, 1-13. https://doi.org/10.1007/s00431-014-2455-7
  10. 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. https://doi.org/10.1006/jecp.1999.2516
  11. Morsanyi, K., van Bers, B. M. C. W., McCormack, T., & McGourty, J. (2018). The prevalence of specific learning disorder in mathematics and comorbidity with other developmental disorders in primary school-age children. British Journal of Psychology, 109(4), 917-940. https://doi.org/10.1111/bjop.12322
  12. Peng, P., Namkung, J., Barnes, M., & Sun, C. (2016). A meta-analysis of mathematics and working memory: Moderating effects of working memory domain, type of mathematics skill, and sample characteristics. Journal of Educational Psychology, 108(4), 455-473. https://doi.org/10.1037/edu0000079
  13. Raghubar, K. P., Barnes, M. A., & Hecht, S. A. (2010). Working memory and mathematics: A review of developmental, individual difference, and cognitive approaches. Learning and Individual Differences, 20(2), 110-122. https://doi.org/10.1016/j.lindif.2009.10.005
  14. Schuchardt, K., Maehler, C., & Hasselhorn, M. (2008). Working memory deficits in children with specific learning disorders. Journal of Learning Disabilities, 41(6), 514-523. https://doi.org/10.1177/0022219408317856
  15. Soares, N., Evans, T., & Patel, D. R. (2018). Specific learning disability in mathematics: A comprehensive review. Translational Pediatrics, 7(1), 48-62. https://doi.org/10.21037/tp.2017.08.03
  16. Szucs, D., Devine, A., Soltesz, F., Nobes, A., & Gabriel, F. (2013). Developmental dyscalculia is related to visuo-spatial memory and inhibition impairment. Cortex, 49(10), 2674-2688. https://doi.org/10.1016/j.cortex.2013.06.007
  17. Watkins, M. W., Kush, J. C., & Glutting, J. J. (1997). Discriminant and predictive validity of the WISC-III ACID profile among children with learning disabilities. Psychology in the Schools, 34(4), 309-319. https://doi.org/10.1002/(SICI)1520-6807(199710)34:4<309::AID-PITS2>3.0.CO;2-G
  18. Wechsler, D. (2014). Wechsler Intelligence Scale for Children-Fifth Edition: Technical and interpretive manual. Pearson.