Melissa Hanifi Vahed, Siavash Tale Pasand, Shahab Moradi,
Volume 24, Issue 150 (8-2025)
Abstract
Background: Mathematics disorder is a learning disability that makes understanding and performing mathematical calculations challenging for children. Furthermore, numerous gaps exist in domestic studies regarding the identification and classification of the cognitive subtypes of this disorder. This study aims to evaluate general and specific cognitive processing types in children with mathematics disorder.
Aims: The study aimed to identify the cognitive subtypes of mathematics disorder in elementary school students.
Methods: This descriptive-correlational study was conducted with two target populations, the first consisted of all students referred to learning disability centers in Alborz Province diagnosed with poor mathematical performance, and the second comprised all third- to sixth-grade elementary students in Alborz Province during the 2023-2024 academic year. The participants included 96 students diagnosed with mathematics disorder selected through random sampling and 180 typically developing students selected through stratified random sampling. Participants completed twelve cognitive tasks designed using Psychopy software, the Wechsler Intelligence Scale for Children-IV, the Frostig visual perception test, the Wepman auditory perception test, the Iran-Key math test, and the Rutter Behavioral Rating Scale. The data were analyzed using t-test, exploratory factor analysis and cluster analysis spss 24 software was used for data analysis.
Results: The exploratory factor analysis identified six factors: arithmetic cognitive performance, cognitive comparison performance, numerical cognitive processing, cognitive processing speed, arithmetic processing speed, and response accuracy, which together explained 74% of the variance. The cluster analysis revealed six distinct cognitive clusters among children with math disorders: cognitive processing divergence, computation and accuracy with delayed processing, impaired numerical cognition, numerical and accuracy deficits, processing and accuracy deficits, and arithmetic and comparison deficits.
Conclusion: The findings suggest that mathematics disorder is a heterogeneous condition. Therapists and educational systems can use these results to design targeted interventions tailored to the specific subtype of mathematics disorder in children with mathematical difficulties.
Melissa Hanifi Vahed, Siavash Tale Pasand, Shahab Moradi,
Volume 25, Issue 162 (8-2026)
Abstract
Background: Cognitive assessment of mathematical disorders requires the evaluation of multidimensional processes (such as working memory and numerical processing). However, existing Persian tools lack the ability to accurately diagnose these dimensions. This study aims to fill this research gap by designing localized multidimensional tasks to facilitate the identification of subgroups of mathematical disorders. Aims: This research was conducted with the goal of developing and designing a set of cognitive tasks specifically for children with mathematical disorders. Methods: The current study is a developmental-applied design. The statistical population includes third to sixth grade elementary school students from Alborz province in the academic year 2023-2024. The participants comprised 96 students (72 boys, 24 girls) with learning disabilities in mathematics, selected through stratified random sampling. A set of cognitive tasks was identified based on the literature. Participants completed the designed cognitive tasks in the Psycopy software environment. Eleven tasks were included, measured through both the number of correct responses and reaction time. The data analysis utilized item-total correlation, Cronbach's alpha coefficient, and exploratory factor analysis. The data were analyzed using SPSS version 26. Results: The results of the exploratory factor analysis revealed six distinct factors that collectively explained 74% of the variance. The factors identified included cognitive arithmetic performance, cognitive comparison performance, cognitive numerical processing, cognitive processing speed, arithmetic processing speed, and cognitive response accuracy. The reliability coefficients for the tasks ranged from 0.62 to 0.89. Conclusion: The results support the satisfactory construct validity of the designed tasks in assessing children with mathematical disorders, which can aid in the precise identification of cognitive strengths and weaknesses related to mathematical learning