Leveraging Artificial Intelligence to Support Language Processing in Children With Dyslexia and Dysgraphia: A Design-Based Study
DOI:
https://doi.org/10.17507/jltr.1703.15Keywords:
inclusive classroom, artificial intelligence, dyslexia and dysgraphia, special educational needs, design-based researchAbstract
This study examines the use of artificial intelligence (AI) in designing inclusive classrooms to support elementary school students with special educational needs (SEN), particularly those with dyslexia and dysgraphia, in Semarang, Indonesia. Using a design-based research (DBR) approach, the study was conducted in 15 elementary schools, involving 15 classroom teachers and their students identified as having literacy-related learning difficulties. Various AI-based tools, such as text-to-speech applications, digital writing assistants, and adaptive learning platforms, were integrated into the classroom learning process to enhance accessibility and personalize learning experiences. Data were collected through classroom observations, teacher interviews, student assessments, and system analytics generated during two iterative design and implementation cycles. Results indicate that AI integration contributed to improvements in students’ reading fluency, spelling accuracy, and written expression. Teachers reported increased capacity for implementing differentiated learning, a better real-time understanding of student learning progress, and greater confidence in managing inclusive learning. This study offers a practical and replicable model for integrating AI into inclusive classroom design, demonstrating its potential to bridge the learning gap for students with specific literacy challenges and empower teachers in inclusive education practices.
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