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Exploring AI Technology in Grammar Performance Testing for Children with Learning Disabilities

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Publicado en:Education Sciences vol. 15, no. 3 (2025), p. 351
Autor principal: Katsarou, Dimitra V
Otros Autores: Mantsos, Evangelos, Papadopoulou, Soultana, Sofologi, Maria, Efthymiou, Efthymia, Vasileiou, Ilias, Megari, Kalliopi, Theodoratou, Maria, Kougioumtzis, Georgios A
Publicado:
MDPI AG
Materias:
Children with disabilities
Language proficiency
Grammar
Special education
Instructional design
Research design
Greek language
Students with disabilities
Performance evaluation
Personalized learning
Conjugation
Algorithms
Education
Feedback
Learning disabilities
Dyslexia
Artificial intelligence
Attention deficit hyperactivity disorder
Machine learning
Children
People with disabilities
Natural language processing
Adaptive learning
Task performance
Quasi-experimental methods
Efficacy
Tests
Variance analysis
Customization
Disability studies
Teachers
Educational programs
Groups
Error Correction
Academic Achievement
Diagnostic Tests
Access to Education
Error Analysis (Language)
Student Motivation
Language Processing
Learner Engagement
Educational Diagnosis
Educational Strategies
Language Skills
Influence of Technology
Educational Methods
Cognitive Style
Language Impairments
Error Patterns
Educational Facilities Improvement
Educational Needs
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Resumen: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 t-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; p < 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.
ISSN:2227-7102
2076-3344
DOI:10.3390/educsci15030351
Fuente:Education Database