Exploring AI Technology in Grammar Performance Testing for Children with Learning Disabilities
The study explores the application of artificial intelligence (AI) in addressing grammar challenges among children with learning disabilities, aiming to assess the efficacy of an AI-driven tool for personalized interventions. A sample of 100 children aged 8–12, diagnosed with learning disabilities,...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Education Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7102/15/3/351 |
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| Summary: | The study explores the application of artificial intelligence (AI) in addressing grammar challenges among children with learning disabilities, aiming to assess the efficacy of an AI-driven tool for personalized interventions. A sample of 100 children aged 8–12, diagnosed with learning disabilities, was recruited from special education programs. Participants were divided into an experimental group (n = 50), which used an AI-based grammar assessment tool with personalized feedback, and a control group (n = 50), which completed conventional paper-based grammar tests without feedback. The AI tool administered adaptive grammar tasks, including sentence correction and verb conjugation, and performance was evaluated over four weeks using pre-test and post-test measures. A quasi-experimental design and statistical analyses, including <i>t</i>-tests and repeated-measures ANOVA, revealed a significant improvement in grammar performance for the experimental group (M = 78.5, SD = 5.6) compared to the control group (M = 70.2, SD = 6.1; <i>p</i> < 0.001), with a large effect size (Cohen’s d = 0.84). Participants and educators reported high engagement and usability of the tool. The findings underscore AI’s potential to provide tailored learning experiences, addressing individual needs more effectively than conventional strategies. Further research should examine long-term outcomes and broader educational applications to maximize its impact. |
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| ISSN: | 2227-7102 |