مقایسه خرده‌مقیاس‌های نسخه پنجم آزمون هوش استنفورد–بینه در دانش‌آموزان دارای اختلال یادگیری در خواندن و ریاضیات: یک رویکرد شناختی

نویسندگان
بهاره محمدی
یاسمن هاشمی
فاطمه جهانگیریان
عاطفه باتوانی
کارشناسی ارشد روانشناسی تربیتی، دانشکده علوم تربیتی و روانشناسی، دانشگاه خوارزمی، کرج، ایران
چکیده
پژوهش حاضر با هدف مقایسه خرده‌مقیاس‌های شناختی شامل استدلال سیال، حافظه فعال و پردازش دیداری-فضایی در دانش‌آموزان دارای اختلال یادگیری در خواندن و ریاضیات، با تأکید بر رویکرد شناختی انجام شد. این مطالعه از نوع علّی-مقایسه‌ای بود و در ابتدا نمونه‌ای متشکل از ۹۰ دانش‌آموز (۳۰ نفر با اختلال خواندن، ۳۰ نفر با اختلال ریاضی، و ۳۰ نفر بدون اختلال یادگیری به‌عنوان گروه عادی) به روش نمونه‌گیری در دسترس از میان مراجعه‌کنندگان به مراکز مشاوره و کلینیک‌های روان‌شناسی شهر تهران انتخاب شدند. پس از حذف ۱۲ مورد دارای داده‌های ناقص، تحلیل نهایی بر روی ۷۸ دانش‌آموز انجام شد. به‌منظور سنجش مؤلفه‌های شناختی، از آزمون هوش استنفورد–بینه (نسخه پنجم) استفاده گردید و داده‌ها با تحلیل واریانس چندمتغیره و آزمون‌های تعقیبی توکی تحلیل شدند. یافته‌ها نشان داد که عملکرد دانش‌آموزان دارای اختلال یادگیری در خرده‌مقیاس‌های استدلال سیال، حافظه فعال و پردازش دیداری-فضایی به‌طور معناداری پایین‌تر از گروه دانش‌آموزان عادی بود (p<0.05)، در حالی‌که بین دو گروه اختلال خواندن و اختلال ریاضی تفاوت معناداری مشاهده نشد. این نتایج نشان می‌دهد که نارسایی در مؤلفه‌های شناختی مورد سنجش، در هر دو نوع اختلال یادگیری خاص وجود دارد و می‌تواند در تضعیف عملکرد تحصیلی دانش‌آموزان نقش داشته باشد. در مجموع، یافته‌های این پژوهش با تأکید بر نقش خرده‌مقیاس‌های شناختی آزمون هوش استنفورد–بینه در تبیین مشکلات یادگیری، بر ضرورت طراحی مداخلات شناخت‌محور جهت بهبود این مؤلفه‌ها تأکید می‌ورزد؛ مداخلاتی که می‌توانند زمینه ارتقاء عملکرد تحصیلی و کاهش علائم اختلالات خواندن و ریاضی را فراهم سازند.
کلیدواژه‌ها
کارکرد اجرایی
اختلال ریاضی
اختلال خواندن
اختلال یادگیری
نیمرخ هوشی

عنوان مقاله English

Comparison of Stanford–Binet Fifth Edition Subscales in Students with Reading and Mathematics Learning Disabilities: A Cognitive Approach

نویسندگان English

Bahare Mohammadi
yasaman hashemi
Fateme Jahangirian
Atefeh Batwani
چکیده English

The present study aimed to compare cognitive subscales—fluid reasoning, working memory, and visual-spatial processing—among students with reading and mathematics learning disabilities, with an emphasis on a cognitive perspective. This causal-comparative study initially involved a sample of 90 students (30 with reading disability, 30 with mathematics disability, and 30 typically developing students as the control group), selected through convenience sampling from counseling centers and psychological clinics in Tehran. After excluding 12 cases with incomplete data, the final analysis was conducted on 78 students. To assess cognitive components, the Stanford–Binet Intelligence Scales, Fifth Edition (SB5) was used. Data were analyzed using multivariate analysis of variance (MANOVA) and Tukey’s post hoc tests. The findings revealed that students with learning disabilities performed significantly lower than the control group in the subscales of fluid reasoning, working memory, and visual-spatial processing (p < 0.05), while no significant differences were found between the reading and math disability groups. These results suggest that deficits in the assessed cognitive subscales are present in both types of learning disabilities and may contribute to academic underachievement. Overall, the findings highlight the importance of SB5 cognitive subscales in explaining learning difficulties and underscore the need for cognitive-based interventions aimed at strengthening these components to improve academic performance and reduce symptoms in students with reading and math learning disabilities.

کلیدواژه‌ها English

executive function
math disorder
reading disorder
learning disorder
intelligence profile
Akar, G. K., Zembat, İ. Ö., Arslan, S., & Thompson, P. W. (Eds.). (2022). Quantitative Reasoning in Mathematics and Science Education. Springer.
Bühner, M., Kröner, S., & Ziegler, M. (2008). Working memory, visual–spatial-intelligence and their relationship to problem-solving. Intelligence, 36(6), 672-680.
Connors, K. H., Guertin, E. L., Nichol, M., Bosson-Heenan, J. M., Gruen, J. R., & Frijters, J. C. (2025). Specificity, Co-Occurrence, and Growth: Math and Reading Skill Development in Children With Learning Disabilities. Journal of Learning Disabilities, 00222194241312189.
Crisci, G., Caviola, S., Cardillo, R., & Mammarella, I. C. (2021). Executive functions in neurodevelopmental disorders: Comorbidity overlaps between attention deficit and hyperactivity disorder and specific learning disorders. Frontiers in human neuroscience, 15, 594234.
Dutta, D. (2017). Developing an Intelligent Chat-bot Tool to assist high school students for learning general knowledge subjects. Georgia Institute of Technology, 13.
Español-Martín, G., Pagerols, M., Prat, R., Rivas, C., Ramos-Quiroga, J. A., Casas, M., & Bosch, R. (2023). The impact of attention-deficit/hyperactivity disorder and specific learning disorders on academic performance in Spanish children from a low-middle-and a high-income population. Frontiers in psychiatry, 14, 1136994.
Farid, A., Habibi-Kaleybar, R., & Moshtary E Sahneh, B. (2021). Comparison of the effectiveness of play therapy and neurofeedback on the executive functions of primary school female students with learning disabilities. Psychology of Exceptional Individuals, 11(43), 175-206.
Goycolea, R., Castro-Alonso, J. C., & Dörr, A. (2021). Visuospatial processing decline due to cannabis consumption in nondependent high school students. Educational psychology review, 33(2), 619-635.
Hamidi, F., Soleymani, S., Dazy, S., & Meshkat, M. (2024). Teaching Mathematics Based on Integrating Reading Strategies and Working Memory in Elementary School. Athens Journal of Education, 11(1), 9-22.
Hwang, H. (2020). Early general knowledge predicts English reading growth in bilingual and monolingual students throughout the elementary years. The Elementary School Journal, 121(1), 154-178.
Kerrigan, S. T. (2023). Modeling Middle Grade Students' Algebraic and Covariational Reasoning using Unit Transformations and Working Memory.
Kim, S. J., & Park, E. H. (2018). Relationship of working memory, processing speed, and fluid reasoning in psychiatric patients. Psychiatry investigation, 15(12), 1154.
Kretzschmar, A., & Nebe, S. (2021). Working memory, fluid reasoning, and complex problem solving: Different results explained by the Brunswik symmetry. Journal of Intelligence, 9(1), 5.
Little, C. W., Lonigan, C. J., & Phillips, B. M. (2021). Differential patterns of growth in reading and math skills during elementary school. Journal of educational psychology, 113(3), 462.
Martin, A. J., Ginns, P., & Collie, R. J. (2023). University students in COVID-19 lockdown: The role of adaptability and fluid reasoning in supporting their academic motivation and engagement. Learning and Instruction, 83, 101712.
Mkhatshwa, T. P., & Doerr, H. M. (2018). Undergraduate students’ quantitative reasoning in economic contexts. Mathematical Thinking and Learning, 20(2), 142-161.
Mnguni, L. (2024). A qualitative description of biochemistry students’ visuospatial reasoning difficulties associated with amino acid models. International Journal of Innovation in Science and Mathematics Education, 32(3).
Muzaini, M., Hasbi, M., Ernawati, E., & Kristiawati, K. (2022). The Empowerment of Problem-Based Learning Models to Improve Students’ Quantitative Reasoning. Formatif: Jurnal Ilmiah Pendidikan MIPA, 12(1).
Nanda, A., & Rani, R. (2025). Exploring the proficiency of basic mathematical facts among primary mathematics teachers. Asian Journal for Mathematics Education, 27527263241307975.
Nooripour, R., Viki, M. G., Ghanbari, N., Farmani, F., & Emadi, F. (2024). Alpha/theta neurofeedback rehabilitation for improving attention and working memory in female students with learning disabilities. OBM Neurobiology, 8(3), 1-20.
Pagani, L. S., Brière, F. N., & Janosz, M. (2017). Fluid reasoning skills at the high school transition predict subsequent dropout. Intelligence, 62, 48-53.
Paz-Baruch, N., & Maor, R. (2023). Cognitive abilities and creativity: The role of working memory and visual processing. Thinking Skills and Creativity, 48, 101294.
Qazizadeh, F. (2022). The functional role of working memory, visual-spatial and processing speed in predicting the academic performance of children with special mathematical learning disorder. Journal of Learning Disabilities, 12(1), 73-84.
Schwaiger, E., & Tahir, R. (2022). The impact of nomophobia and smartphone presence on fluid intelligence and attention. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 16(1).
Singer, Z. (2024). The Predictive Roles of Verbal Comprehension, Visual Spatial, Processing Speed, Fluid Reasoning, and Overall Intelligence in the Performance of Two Working Memory Tasks on the WPPSI-IV (Doctoral dissertation, Saybrook University).
Torppa, M., Aro, T., Eklund, K., Parrila, R., Eloranta, A. K., & Ahonen, T. (2024). Adolescent reading and math skills and self-concept beliefs as predictors of age 20 emotional well-being. Reading and Writing, 37(8), 2075-2099.
Vermeiren, H., Vandendaele, A., & Brysbaert, M. (2023). Validated tests for language research with university students whose native language is English: Tests of vocabulary, general knowledge, author recognition, and reading comprehension. Behavior Research Methods, 55(3), 1036-1068.
Wang, C., & McWatt, S. C. (2023). Visuospatial ability and student approach to learning as predictors of academic performance on written versus laboratory‐based assessments in human anatomy. Anatomical Sciences Education, 16(6), 1187-1199.
Youngstrom, E. A., Glutting, J. J., & Watkins, M. W. (2003). Stanford-Binet Intelligence Scale: (SB4): Evaluating the empirical bases for interpretations. Handbook of psychological and educational assessment: Intelligence, aptitude, and achievement, 217-242.