Document Type : Original Article


1 Department of Psychology, Roudehen Branch, Islamic Azad University, Roudehen, Iran

2 Department of Assessment and Measurement, Faculty of Psychology and Educational Sciences, Allameh Tabataba’i University, Tehran, Iran

3 Department of psychology, Roudehen Branch, Islamic Azad University, Roudehen, Iran


Children with cognitive disability have a poor performance in all of the visual –motor tests. Therefore, diagnosis and rehabilitation of these learning disabilities seem necessary. The purpose of the present study was to construct and normalize a learning disability test for pre-school students. A researcher-made visual-spatial test was devised consisting of seven sections (symbolization, space status, visual distinction, visual argumentation, visual memory sequence, maze, and rotational form) whose content validity was confirmed by psychology professors and then was performed on a sample of 206 preschool students. The questions were analyzed, and their validity, reliability and cut point were determined. This test showed an acceptable reliability. Then, to determine the construct validity and components of the tests, Varimax normalized method was used. Conformity factor analysis was also used to determine the validity of the factors which confirmed that the structure of questionnaire had an acceptable fitness to the data. Independent t-test demonstrated that there is a significant difference between the average scores of the normal students and those with learning disability. To investigate convergent validity, we used learning disability checklist that was simultaneously completed by the mothers. The results of Chi-Squared test demonstrated that there is a significant relationship between these two variables: the completed checklist by mothers and completed learning disability test by children.Considering the acceptable reliability and validity of the tests, it can be a tool to be used by learning disorders and counseling centers.


  1. Association, A. P. (2013). Diagnostic and statistical manual of mental disorders (DSM-5®). American Psychiatric Pub.
    1. Behpajoh, A., & Salehi, M. (2001). The comparison of nonverbal intelligent  in deaf and normal students at ages 6, 9 and 12 years (Persian). Journal of Psychology and Education, 5(2),95-110.
    2. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. Sage focus editions, 154, 136-136.
    3. Bugden, S., & Ansari, D. (2016). Probing the nature of deficits in the ‘Approximate Number System’in children with persistent developmental dyscalculia. Developmental science, 19(5), 817-833.
    4. Comrey, A. J., & Lee, H. B. (1992).  A first course in factor analyse. Hhillsdale, Nj: Erlbaum
    5. Delavar, A., & Zahrakar, K. (2010). Evaluating and measuring in Psychology, Counseling and Educational Sciences. Arasbaran Publishing.
    6. Ghaem, H., Soleymani, Z., & Dadar, H. (2011). Comparitive study of the role of morphological awareness in accuracy, speed and comprehension of reading in dyslexic and normal children in second grade of primary school. Modern Rehabilitation, 4 (3).
    7. Golamitooranposhti, M., Delavar, A., & Sharifi, H.P. (2017). Construct and normalization of learning disability in children of preschool. PH.D.Thesis.
    8. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling. A Multidisciplinary Journal, 6(1), 1-55.
    9. Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
    10. Kirby, J. R., Parrila, R. K., & Pfeiffer, S. L. (2003). Naming speed and phonological awareness as predictors of reading development. Journal of Educational Psychology,95, 453–464.
    11. Mohammed, A. R., Rashed, A., & Shirmohammadi, S. (2017). A synthetic instrument for diagnosis and performance measurement of Individuals with Visual Sequential Memory Deficit. Paper presented at the Medical Measurements and Applications (MeMeA), 2017 IEEE International Symposium on.
    12. Nandakumar, K., & Leat, S. J. (2008). Dyslexia: A review of two theories. Clinical and Experimental Optometry, 91(4), 333-340.
    13. Ortiz, R., Estévez, A., Muñetón, M., & Domínguez, C. (2014). Visual and auditory perception in preschool children at risk for dyslexia. Research in developmental disabilities, 35(11), 2673-2680.
    14. Pisella, L. (2017). Visual perception is dependent on visuospatial working memory and thus on the posterior parietal cortex. Annuals of physical and rehabilitation medicine, 60(3), 141-147.
    15. Silver, A. A., & Hagin, R. A. (2002). Disorders of learning in childhood. Wiley.
    16. Soleymani, Z., & Barkhordar, A., A, M.(2011). Designing and measuring the validity and reliability of rapid automatized naming test in the first-grade students. Journal of Modern Rehabilitation, 2 (1).
    17. Verhoeven, L., & Perfetti, C. (2008). Advances in text comprehension: Model, process and development. Applied Cognitive Psychology, 22(3), 293-301.
    18. Willcutt, E. G., Petrill, S. A., Wu, S., Boada, R., DeFries, J. C., Olson, R. K., & Pennington, B. F. (2013). Comorbidity between reading disability and math disability: Concurrent psychopathology, functional impairment, and neuropsychological functioning. Journal of learning disabilities, 46(6), 500-516.