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Department of Education, Faculty of Education and Psychology, Semnan University, Semnan, Iran. , stalepasand@semnan.ac.ir
Abstract: (14 Views)
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.
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.
Article number: 9
Type of Study: Research |
Subject:
Special
Received: 2025/06/18 | Accepted: 2026/07/12 | Published: 2026/08/23
Received: 2025/06/18 | Accepted: 2026/07/12 | Published: 2026/08/23
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This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License. |
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)