[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit ::
:: Volume 7, Issue 3 (Summer 2019) ::
Shefaye Khatam 2019, 7(3): 32-41 Back to browse issues page
The Study of Automatic and Controlled Data Processing Speed Based on the Stroop Test in Students with Math Learning Disability
Esmaeil Soleymani, Mehran Alipour *, Mehran Soleymani
Department of Educational Sciences, Uimia University, Urmia, Iran , hiva838@gmail.com
Abstract:   (1585 Views)
Introduction: The study of individual differences in information processing in order to predict the academic achievement of students with math disability is of great importance. The purpose of this study was to study automatic and controlled data processing speed based on the Stroop test in students with math learning disability. Materials and Methods: This descriptive study was causal-comparative. The study population consisted of students in district 6 education in Tehran city. The sample consisted of 36 students with and without learning disability in mathematics (18 students with Math Learning Disability and 18 normal students), selected by systematic random sampling from the list of statistical populations (specific learning problems center) and matching method (normal group). The data were collected by demographic questionnaire, Raven's Progressive Matrices, Keymaths math test and Stroop test and analyzed by multivariate analysis of co-variance, Shapiro-Wilk test, Box and Levin tests. Results: The findings showed that automatic and controlled information processing in students with and without a math learning disability are significantly different. The mean of reaction time and number of errors in students with math learning disability is significantly higher than students without learning disability is math. Conclusion: According to the results of this study the speed of automatic and controlled information processing in students with math learning disability is weak (low) and educators should pay attention to this problem.
Keywords: Students, Individuality, Learning
Full-Text [PDF 916 kb]   (355 Downloads)    
Type of Study: Research --- Open Access, CC-BY-NC | Subject: Cognitive Neuroscience
1. Horowitz SH, Newman L, Kaye HS. The state of learning disabilities: facts, trends and emerging issues. 3nd ed. New York: National Center for Learning Disabilities. 2014.
2. Passolunghi MC, Siegel LS. Working memory and access to numerical information in children with disability in mathematics. J Exp Child Psychol. 2004; 88(4): 348-67. [DOI:10.1016/j.jecp.2004.04.002]
3. Dowker A. Individual differences in arithmetic: implications for psychology, neuroscience and education. New York: Psychology Press. 2005. [DOI:10.4324/9780203324899]
4. Geary DC. Mathematical disabilities: reflections on cognitive, neuropsychological, and genetic components. Learn Individ Differ. 2010; 20(2): 130-133. [DOI:10.1016/j.lindif.2009.10.008]
5. Passolunghi MC, Lanfranchi S. Domain-specific and domain-general precursors of mathematical achievement: a longitudinal study from kindergarten to first grade. Br J Educ Psychol. 2012; 82(1): 42-63. [DOI:10.1111/j.2044-8279.2011.02039.x]
6. Price GR, Ansari D. Dyscalculia: characteristics, causes, and treatments. Numeracy: Advancing Education in Quantitative Literacy. 2013; 6(1): 37-56. [DOI:10.5038/1936-4660.6.1.2]
7. Moll K, Gobe SM, Snowling MJ. Basic number processing in children with specific learning disorders: Comorbidity of reading and mathematics disorders. Child Neuropsychol. 2015; 21(3): 399-417. [DOI:10.1080/09297049.2014.899570]
8. American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-5, 5th ed. 2013. [DOI:10.1176/appi.books.9780890425596]
9. Kaplan H, Saduk B. Synopsis of clinical psychiatry. Tehran: Arjmand Publication. 2015.
10. Sohrabi F, Mikaeilimonie F, Alipour M. The prevalence of learning disabilities in elementary school students in West Azarbaijan. Contemporary Psychology, Biannual Journal of the Iranian Psychological Association. 2010; 5: 446-9.
11. Mogasale VV, Patil VD, Patil NM, Mogasale V. Prevalence of specific learning disabilities among primary school children in a south indian city. Indian J Pediatr. 2011; 79(3): 342-7. [DOI:10.1007/s12098-011-0553-3]
12. Fougnie D. The relationship between attention and working memory. New Research on Short-Term Memory. Nova Science Publishers, Inc. 2008.
13. Geary DC. Consequences, characteristics, and causes of mathematical learning disabilities and persistent low achievement in mathematics. J Dev Behav Pediatr. 2011; 32(3): 250-63. [DOI:10.1097/DBP.0b013e318209edef]
14. Soleymani E. Performance comparison of students with and without math learning disorder in tower of london and continuous operation scale. J Learn Disabil. 2015; 3(14): 56-73.
15. Osmon DC, Smerz JM, Braun MM, Plambeck E. Processing abilities associated with math skills in adult learning disability. J Clin Exp Neuropsychol. 2006; 28(1): 84-95. [DOI:10.1080/13803390490918129]
16. Moriguchi Y, Zelazo PD, Chevalier N. Development of executive function during childhood. Front Psychol. 2016. doi 10.3389/978-2-88919-800-9. [DOI:10.3389/978-2-88919-800-9]
17. Schuiringa H, Nieuwenhuijzen M, De Castro BO Matthys W. Executive functions and processing speed in children with mild to borderline intellectual disabilities and externalizing behavior problems. Child Neuropsychol. 2017; 23(4): 442-62. [DOI:10.1080/09297049.2015.1135421]
18. Cragg L, Gilmore C. Skills underlying mathematics: the role of executive function in the development of mathematics proficiency. Trends in Neuroscience and Education. 2014; 3(2): 63-8. [DOI:10.1016/j.tine.2013.12.001]
19. Gomez DM, Jimenez A, Bobadilla R, Reyes C, Dartnell P. The effect of inhibitory control on general mathematics achievement and fraction comparison in middle school children. The International Journal on Mathematics Education. 2015; 47(5): 801-11. [DOI:10.1007/s11858-015-0685-4]
20. Zelazo PD, Müller U, Frye D, Marcovitch S, Argitis G, Boseovski J, et al. The development of executive functions in early childhood. Monogr Soc Res Child Dev. 2003; 68(3): 137. [DOI:10.1111/j.0037-976X.2003.00269.x]
21. Issazadegan A, Sheikhi S. Fundamentals of neuropsychology. Tabriz: Ons Publication. 2015.
22. Baddeley AD. Working memory, thought and action. Oxford: Oxford University Press. 2007. [DOI:10.1093/acprof:oso/9780198528012.001.0001]
23. Ahadi H, Kakavand AR. Learning disability (from theory to practice). Tehran: Arasbaran Publication. 2010.
24. Moore A, Malinowski P. Meditation, mindfulness and cognitive flexibility. Conscious Cogn. 2009; 18(1): 176-86. [DOI:10.1016/j.concog.2008.12.008]
25. Sella F, Sader E, Lolliot S, Kadosh RC. Basic and advanced numerical performances relate to mathematical expertise but are fully mediated by visuospatial skills. J Exp Psychol Learn Mem Cogn. 2016; 42(9): 1458-72. [DOI:10.1037/xlm0000249]
26. Schneider W, Shiffrin RM. Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review. 1977; 84(1): 1-66. [DOI:10.1037/0033-295X.84.1.1]
27. Schneider W, Dumais ST, Shiffrin RM. Automatic and controlled processing and attention. Parasuraman R, Davies DR. Varieties of attention. Orlando, FL: Academic Press. 1984; p. 1-27.
28. Narimani M, Soleymani E, Zahed Babolan A, Abolghasemi A. The comparsion the effectiveness of executive functionals and play therapy on improving of working memory, attention care and academic achievement in students with math learning disorder. Journal of Clinical Psychology. 2014; 4: 1-17.
29. Kapoula Z, Lê TT, Bonnet A, Bourtoire P, Demule E, Fauvel C, et al. Poor stroop performances in 15-year-old dyslexic teenagers. Exp Brain Res. 2010; 203(2): 419-25. [DOI:10.1007/s00221-010-2247-x]
30. Sterk V, Spengler K, Babika C, Golden C. Examining the relationship between learning diagnoses and stroop color-word test scores within the luria-nebraska neuropsychological battery. Arch Clin Neuropsychol. 2014; 29(6): 545-55. [DOI:10.1093/arclin/acu038.113]
31. Sternberg RJ. Cognitive psychology. Tehran: Samt Publication. 2008.
32. BaysalKırac L, Ekmekci O, Yuceyar N, Sagduyu A. Assessment of early cognitive impairment in patients with clinically isolated syndromes and multiple sclerosis. Behav Neurol. 2014; doi: 10.1155/2014/637694. [DOI:10.1155/2014/637694]
33. Naber M, Vedder A, Brown SB, Nieuwenhuis S. Speed and lateral inhibition of stimulus processing contribute to individual differences in stroop-task performance. Front Psychol. 2016; 7: 822. doi: 10.3389/fpsyg.2016.00822. [DOI:10.3389/fpsyg.2016.00822]
34. Gordon R, Smith-Spark JH, Newton EJ, Henry LA. Executive function and academic achievement in primary school children: the use of task-related processing speed. Front Psychol. 2018; 9: 582. doi: 10.3389/fpsyg.2018.00582. [DOI:10.3389/fpsyg.2018.00582]
35. Delavar A. Practical and theoretical foundations of research in humanities and social sciences. Tehran: Roshd publication. 2005.
36. Mackintosh TNJ, Bennett ES. What do raven's matrices measure? an analysis in terms of sex differences. Intelligence. 2005; 33(6): 663-74. [DOI:10.1016/j.intell.2005.03.004]
37. Sharifi HP. Theory and application of intelligence and personality tests. Tehran: Sokhan Publications. 2003.
38. Abdel-Khalek AM. Reliability and factorial validity of the standard progressive matrices among Kuwaiti children ages 8-15 years. Percep and Motor Skills. 2005; 2: 409-12. [DOI:10.2466/PMS.101.6.409-412]
39. Anastasi A. Psychological testing. Tehran: Tehran University Press. 1985.
40. Baraheni MN. Raven's progressive matrices as applied to Iranian children. Educ Psychol Meas. 1974; 34(4): 983-8. [DOI:10.1177/001316447403400433]
41. Rosli R. Test review: A. J. connolly keymath-3 diagnostic assessment: manual forms A and B. minneapolis, MN: Pearson, 2007. J. Psychoeduc Assess. 2011; 1: 94-7. [DOI:10.1177/0734282910370138]
42. Mohammadesmaeil E, Hooman HA. Adaptation and Standardization of the Iran key-math test of mathematics. Journal of Exceptional Children. 2003; 2(4): 323-32.
43. Demetriou A, Christou C, Spanoudis G, Platsidou M. The development of mental processing: efficiency, working memory, and thinking. Monogr Soc Res Child Dev. 2002; 67(1): 1-155. [DOI:10.1111/1540-5834.671174]
44. Cox WM, Salehi Fadardi J, Pothos EM. The addiction-stroop test: theoretical considerations and procedural recommendations. Psychol Bull. 2006; 132(3): 443-76. [DOI:10.1037/0033-2909.132.3.443]
45. Basharpour S. Determine the speed of information processing, automatic processing and control, and effect of antidepressant drugs on these three variables on depression. MA thesis. Mohaghegh Ardebili University, Ardebil, Iran. 2006.
46. Mashhadi A, Rasoulzadeh Tabatabaie K, Azadfallah P, Soltanifar A. The comparison of response inhibition and interference control in adhd and normal children. Journal of Clinical Psycology. 2009; 1(2): 37-50.
47. Uttl B, Graf P. Color-word stroop test performance across the adult life span. J Clin Exp Neuropsychol. 1997; 19(3): 405-20. [DOI:10.1080/01688639708403869]
48. Tehrani Doost M, Azadi B, Seddigh A, Asharafi MR, Alaghbandrad J. Disorders of executive function in patients with phenylketonuria treated. Advances in Cognitive Science. 2005; 1: 1-9.
49. Hourston Sh. Self-advocacy for People with Learning Disabilities- A Guide for Adult Educators. A publication of the Whole Life Approach to Learning Disabilities in Adult Literacy Settings Project, Canada. 2011; p. 1-57.

XML   Persian Abstract   Print

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

Soleymani E, Alipour M, Soleymani M. The Study of Automatic and Controlled Data Processing Speed Based on the Stroop Test in Students with Math Learning Disability. Shefaye Khatam. 2019; 7 (3) :32-41
URL: http://shefayekhatam.ir/article-1-1945-en.html

Volume 7, Issue 3 (Summer 2019) Back to browse issues page
مجله علوم اعصاب شفای خاتم The Neuroscience Journal of Shefaye Khatam
Persian site map - English site map - Created in 0.06 seconds with 31 queries by YEKTAWEB 4130