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All Journal Psychology, Evaluation, and Technology in Educational Research
Wang, Bingli
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Computer Science & IT Education Social Sciences

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The effectiveness of AI-assisted instruction for primary school students with mathematics learning disabilities Fangping, Wang; Ratna sari, Nuraeni; Wang, Bingli
Psychology, Evaluation, and Technology in Educational Research Vol. 8 No. 1 (2025)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/petier.v8i1.311

Abstract

Despite the increasing application of artificial intelligence technology in education, research on the effectiveness of AI-assisted instruction systems for primary school students with mathematics learning disabilities remains limited. This study investigated the effects of a customized AI-assisted instruction system on improving academic performance and learning motivation among primary school students with mathematics learning disabilities. Using a quasi-experimental design, 42 third-to-fifth grade students diagnosed with mathematics learning disabilities from three primary schools in Jiangsu Province participated in a 12-week intervention study. The experimental group (n=21) received AI-assisted instruction intervention, while the control group (n=21) received traditional remedial instruction. The study collected data using standardized mathematics tests, learning motivation scales, and classroom observation records. Results showed that students in the experimental group demonstrated significant improvements in both mathematics achievement (Cohen's d=0.89) and learning motivation (Cohen's d=0.76). This article discusses strategies for effectively implementing AI-assisted instruction systems in special education settings.
WISC-V cognitive indicators of mathematical learning disabilities in elementary school students: A case-control study Wang, Fangping; Sari, Nuraeni Ratna; Wang, Bingli
Psychology, Evaluation, and Technology in Educational Research Vol. 8 No. 2 (2026): Article in Press
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/petier.v8i2.317

Abstract

Mathematical learning disabilities (MLD) involve persistent and heterogeneous difficulties in acquiring age-appropriate mathematical skills, requiring assessment through both cognitive and classroom-based indicators. This study examined whether WISC-V profiles differentiate elementary students with MLD from typically developing peers and support an integrated classification model. A case-control design involved 120 students aged 8–12 years, comprising 60 students formally identified with MLD and 60 age-matched controls. Participants completed the WISC-V Chinese Edition and a Mathematical Achievement Test, while teachers completed the Teacher Questionnaire on Mathematical Performance. Data were analyzed using t tests, effect sizes, correlations, discriminant analysis, and ROC analysis. Students with MLD scored significantly lower on all WISC-V primary indices, particularly Working Memory (d = 2.10) and Processing Speed (d = 1.60). Quantitative Reasoning showed the strongest ancillary-index separation (d = 3.03). Arithmetic, Digit Span, and Figure Weights were the most discriminating subtests. MAT deficits were greatest in word problems (d = 3.29) and mental computation (d = 3.03). QRI correlated most strongly with MAT total score (r = .84, p < .001), and the combined model achieved 89.2% accuracy and AUC = .986. QRI, WMI, Arithmetic, Digit Span, word problems, and mental computation are promising screening indicators for MLD, pending external validation.
Co-Authors Fangping, Wang Ratna sari, Nuraeni Sari, Nuraeni Ratna Wang, Fangping