Volume 10 -                   MEJDS (2020) 10: 199 | Back to browse issues page

XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Yazdani S, Arjmandnia A, Nejati V, Hassanzadeh S, Fathabadi J. A Comprehensive Investigation of Eight Components of Visual-Spatial Ability in Children with Mathematics Learning Disorder. MEJDS 2020; 10 :199-199
URL: http://jdisabilstud.org/article-1-1783-en.html
1- Faculty of Psychology, Department of Psychology, Tehran University
2- Faculty of Psychology and Education of Exceptional Children, Department of Psychology, Tehran University
3- Faculty of Psychology, Department of Psychology, Shahid Beheshti University
Abstract:   (2187 Views)
Background & Objectives: Mathematics Learning Disorder (MLD) is a neurodevelopmental condition. MLD refers to conditions where children with basically healthy Intelligence Quotient (IQ) lag behind children of the same age or grade in mathematics, due to some deficits in mathematics learning ability. MLD is associated with deficits in cognitive functions. Brain imaging studies confirmed that similar areas are activated when individuals process spatial and number tasks. It has been revealed that the parietal lobe plays an essential role in the processing of spatial information. The Visual-Spatial Ability (VSA) is an umbrella term that refers to the skill in representing, transforming, generating, and recalling symbolic and nonlinguistic data. Evidence for the role of visual–spatial processing in MLD remains contradictory. Therefore, the present study aimed to explore differences in SA factors in children with and without MLD.
Methods: In total, 128 children aged 9–12 years have participated as two Typically Developing (TD) and MLD groups in this cross–sectional study, in 2018. Moreover, 64 children in the MLD group were selected by purposive sampling method from learning disorder centers in Tehran City, Iran. The TD group comprised 64 children who were selected by a multi–stage sampling approach from two elementary schools. The inclusion criteria for the MLD group were obtaining IQ scores of >85 in the Wechsler Intelligence Scale for Children–Fourth Edition (WISC–IV, 2003), and achieving a score of <80 in the Key–Mat (Cannolly et al., 1988). In the TD group, the Colorado Learning Disability Questionnaire (Wilcott et al., 2011) was used to ensure the absence of learning disabilities. The inclusion criterion for the TD group was receiving a score of <40 in the aforementioned questionnaire. The study participants were excluded from both groups in case of experiencing bioneurological disabilities. VSA was measured with a computerized tasks battery of spatial ability (solouki et al., 2020). This battery included 8 factors of VSA, including the Flexibility of Closure (FC), Closure Speed (CS), Perceptual Speed (PS), Visualization (VIS), Spatial Relations (SR), Spatial Orientation (SO), Spatial-Temporal (ST) ability, and Way Finding (WF). Subjects in both research groups were individually assessed concerning the 8 components of SA by the aforementioned battery. All 8 spatial ability tasks were presented to each subject on 15–inch computers, using E–Prime 2 and Unity software. The study subject was placed 60 cm away from the screen. The battery of spatial ability tasks was performed in two 45–minute sessions. The obtained data were analyzed by descriptive statistics, such as mean and standard deviation as well as inferential statistics using the Mann–Whitney U test in SPSS at a significance level of 0.05.
Results: The collected data suggested that the MLD group, compared to the TD group obtained a lower accuracy score in the tasks of FC (p<0.001), CS (p<0.001), PS (p<0.001), VIS (p<0.001), SR (p<0.001), SO (p<0.001), ST (p<0.001), and in the memory of landmark phase of WF task (p=0.002). Furthermore, the number of trials in the learning path (p<0.001) and walked path in the short distance phase of the WF task was higher in the MLD group, compared to the controls (p=0.003). The current research results also revealed that the two groups were significantly different in the mean score of reaction time in VIS (p<0.001), SR (p<0.001), and SO tasks (p<0.001).
Conclusion: The present study results demonstrated that children with MLD have defects in all 8 components of VSA.
Full-Text [PDF 603 kb]   (871 Downloads)    
Type of Study: Original Research Article | Subject: Psychology

References
1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-5. 5th ed. Washington, D.C: American Psychiatric Association; 2013.
2. Soares N, Evans T, Patel DR. Specific learning disability in mathematics: a comprehensive review. Transl Pediatr. 2018;7(1):48–62. [DOI]
3. Price G, Ansari D. Dyscalculia: characteristics, causes, and treatments. Numeracy. 2013;6(1):Article 2. [DOI]
4. D’Oliveira TC. Dynamic spatial ability: an exploratory analysis and a confirmatory study. The International Journal of Aviation Psychology. 2004;14(1):19–38. [DOI]
5. Kong L, Michalka SW, Rosen ML, Sheremata SL, Swisher JD, Shinn-Cunningham BG, et al. Auditory spatial attention representations in the human cerebral cortex. Cereb Cortex. 2014;24(3):773–84. [DOI]
6. Carroll JB. Human cognitive abilities: a survey of factor-analytic studies. Cambridge ; New York: Cambridge University Press; 1993.
7. Hegarty M, Waller DA. Individual Differences in Spatial Abilities. In: The cambridge handbook of visuospatial thinking. New York, US: Cambridge University Press; 2005. pp: 121–69. [DOI]
8. Uttal DH, Meadow NG, Tipton E, Hand LL, Alden AR, Warren C, et al. The malleability of spatial skills: a meta-analysis of training studies. Psychol Bull. 2013;139(2):352–402. [DOI]
9. Hegarty M. The cognitive science of visual-spatial displays: implications for design. Top Cogn Sci. 2011;3(3):446–74. [DOI]
10. Ekstrom RB, French JW, Harman HH, Dermen D. Manual for kit of factor-referenced cognitive tests: 1976. Princeton N.J.: Education Testing Service; 1976.
11. Yilmaz HB. On the development and measurement of spatial ability. International Electronic Journal of Elementary Education. 2009;1(2):83–96.
12. Halpern DF. Sex differences in cognitive abilities. 4th ed. New York: Psychology Press; 2000.
13. Cheng Y-L, Mix KS. Spatial training improves children’s mathematics ability. Journal of Cognition and Development. 2014;15(1):2–11. [DOI]
14. Peters L, De Smedt B. Arithmetic in the developing brain: A review of brain imaging studies. Dev Cogn Neurosci. 2018;30:265–79. [DOI]
15. Zimmermann M, Kubik V, Persson J, Mäntylä T. Monitoring multiple deadlines relies on spatial processing in posterior parietal cortex. Journal of Cognitive Neuroscience. 2019;31(10):1468–83. [DOI]
16. Koscik T, O’Leary D, Moser DJ, Andreasen NC, Nopoulos P. Sex differences in parietal lobe morphology: relationship to mental rotation performance. Brain Cogn. 2009;69(3):451–9. [DOI]
17. Berteletti I, Prado J, Booth JR. Children with mathematical learning disability fail in recruiting verbal and numerical brain regions when solving simple multiplication problems. Cortex. 2014;57:143–55. [DOI]
18. Ben-Zvi S, Soroker N, Levy DA. Parietal lesion effects on cued recall following pair associate learning. Neuropsychologia. 2015;73:176–94. [DOI]
19. Kolb B, Whishaw IQ. Fundamentals of human neuropsychology. Seventh edition. New York: Macmillian Education Imprint; 2009.
20. Matejko AA, Price GR, Mazzocco MMM, Ansari D. Individual differences in left parietal white matter predict math scores on the Preliminary Scholastic Aptitude Test. Neuroimage. 2013;66:604–10. [DOI]
21. Shafrir U, Siegel LS. Preference for visual scanning strategies versus phonological rehearsal in university students with reading disabilities. J Learn Disabil. 1994;27(9):583–8. [DOI]
22. Share DL, Moffitt TE, Silva PA. Factors associated with arithmetic-and-reading disability and specific arithmetic disability. J Learn Disabil. 1988;21(5):313–20. [DOI]
23. Murphy MM, Mazzocco MMM, Hanich LB, Early MC. Cognitive characteristics of children with Mathematics Learning Disability (MLD) vary as a function of the cutoff criterion used to define MLD. J Learn Disabil. 2007;40(5):458–78. [DOI]
24. Geary DC, Hamson CO, Hoard MK. Numerical and arithmetical cognition: a longitudinal study of process and concept deficits in children with learning disability. J Exp Child Psychol. 2000;77(3):236–63. [DOI]
25. Jordan NC, Levine SC, Huttenlocher J. Calculation abilities in young children with different patterns of cognitive functioning. J Learn Disabil. 1995;28(1):53–64. [DOI]
26. Spellacy F, Peter B. Dyscalculia and elements of the developmental Gerstmann syndrome in school children. Cortex. 1978;14(2):197–206. [DOI]
27. Gunderson EA, Ramirez G, Beilock SL, Levine SC. The relation between spatial skill and early number knowledge: the role of the linear number line. Dev Psychol. 2012;48(5):1229–41. [DOI]
28. Vukovic RK, Siegel LS. Academic and cognitive characteristics of persistent mathematics difficulty from first through fourth grade. Learning Disabilities Research & Practice. 2010;25(1):25–38. [DOI]
29. Huttenlocher J, Newcombe N, Vasilyeva M. Spatial scaling in young children. Psychological Science. 1999;10(5):393–8. [DOI]
30. Wechsler D. Wechsler Intelligence Scale For Children–Fourth Edition (WISC-IV). San Antonio, TX: The Psychological Corporation; 2003.
31. Connolly A, Nachtmann W, Prichett E. KeyMath Diagnostic Arithmetic Test-Revised. Circle Pines, MN: American Guidance Service; 1988
32. Willcutt EG, Boada R, Riddle MW, Chhabildas N, DeFries JC, Pennington BF. Colorado Learning Difficulties Questionnaire: validation of a parent-report screening measure. Psychological assessment. 2011 Sep;23(3):778. [DOI]
33. Sadeghi A, Rabiee M, Abedi MR. Validation and reliability of the wechsler intelligence scale for children-IV. Scientific Journal Management System. 2011;7(28):377–86. [Persian] [Article]
34. Mohamadesmail E, Hooman, HA. Adaptation and standardization of Key Math Test. Reasearch on Exceptional Children. 2002;6(4):323-332.[Persian] [Article]
35. Hajloo N, Rezaie Sharif A. Psychometric properties of Colorado Learning Difficulties Questionnaire (CLDQ). Journal of Learning Disabilities. 2011;1(1):24–43. [Persian] [Article]
36. Soluki S, Yazdani S, Arjmandnia A, Fathabadi J, Hassanzadeh S, Nejati V, Jansen P. Comprehensive assessment of spatial ability in children: a computerized tasks battery. Adv Cogn Psychol; 2020. [In Press].
37. Gardner MF. TVPS, test of visual-perceptual skills (non-motor): manual. Hydesville, CA: Psychological and Educational Publications; 1996.
38. Harris J, Newcombe NS, Hirsh‐Pasek K. A new twist on studying the development of dynamic spatial transformations: mental paper folding in young children. Mind, Brain, and Education. 2013;7(1):49–55. [DOI]
39. Wiedenbauer G, Jansen-Osmann P. Manual training of mental rotation in children. Learning and Instruction. 2008;18(1):30–41. [DOI]
40. Hegarty M, Waller D. A dissociation between mental rotation and perspective-taking spatial abilities. Intelligence. 2004;32(2):175–91. [DOI]
41. Sanchez CA, Wiley J. The role of dynamic spatial ability in geoscience text comprehension. Learning and Instruction. 2014;31:33–45. [DOI]
42. Mengue-Topio H, Courbois Y, Farran EK, Sockeel P. Route learning and shortcut performance in adults with intellectual disability: A study with virtual environments. Research in Developmental Disabilities. 2011;32(1):345–52. [DOI]
43. Mix KS, Cheng Y-L. The relation between space and math: developmental and educational implications. Adv Child Dev Behav. 2012;42:197–243. [DOI]
44. Geary DC. Mathematical disabilities: cognitive, neuropsychological, and genetic components. Psychol Bull. 1993;114(2):345–62. [DOI]
45. Arcavi A. The role of visual representations in the learning of mathematics. Educational Studies in Mathematics. 2003;52(3):215–41. [DOI]
46. Hegarty M, Kozhevnikov M. Types of visual–spatial representations and mathematical problem solving. Journal of Educational Psychology. 1999;91(4):684–9. [DOI]
47. Kosslyn SM, Reiser BJ, Farah MJ, Fliegel SL. Generating visual images: units and relations. J Exp Psychol Gen. 1983;112(2):278–303. [DOI]
48. Rieber LP. A historical review of visualization in human cognition. ETR&D. 1995;43(1):45–56. [DOI]
49. Zimmermann W, Cunningham S. Editors’ introduction: What is mathematical visualization? In: Visualization in teaching and learning mathematics. USA: Mathematical Association of America; 1991. pp: 1–8.
50. Clements DH, Battista MT. Geometry and spatial reasoning. In: Handbook of research on mathematics teaching and learning: A project of the National Council of Teachers of Mathematics. England: Macmillan Publishing Co, Inc; 1992. pp: 420–64.
51. Ashcraft MH. cognitive psychology and simple arithmetic: a review and summary of new directions. Mathematical Cognition. 1995;1(1):3–34.
52. Marshalek B, Lohman DF, Snow RE. The complexity continuum in the radex and hierarchical models of intelligence. Intelligence. 1983;7(2):107–27. [DOI]
53. Bull R, Johnston RS. Children’s arithmetical difficulties: contributions from processing speed, item identification, and short-term memory. J Exp Child Psychol. 1997;65(1):1–24. [DOI]
54. Allen GL. Cognitive abilities in the service of wayfinding: a functional approach. The Professional Geographer. 1999;51(4):555–61. [DOI]

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2025 CC BY-NC 4.0 | Middle Eastern Journal of Disability Studies

Designed & Developed by : Yektaweb