Integrating Artificial Intelligence for Academically Challenged Students Education and Health

Abstract

Students with Intellectual and Developmental Disabilities (ID/DD) often experience overlapping medical and cognitive challenges that affect their academic participation and social interaction. Frequent absences, delayed progress, and limited communication skills highlight the urgent need for an integrated support system. Despite advancements in educational technology, most digital learning tools remain limited in addressing the dual educational and healthcare needs of ID/DD students. This study aims to identify existing gaps and propose a systematic framework for integrating Artificial Intelligence (AI) into education and health systems to enhance personalized learning and well-being for students with ID/DD. The study emphasizes the importance of combining health data with instructional design to achieve inclusive and adaptive learning experiences. A systematic literature review was conducted across multiple databases, including IEEE Xplore, ERIC, ACM Digital Library, and NFER, covering studies published between 2020 and 2025. The review process followed the PRISMA guideline and applied strict inclusion and exclusion criteria to ensure the validity of selected studies. The findings reveal that AI has been used to support ID/DD learners in various contexts, but most implementations remain fragmented, lacking integration between educational and medical data. The proposed AI-based framework connects these domains through data-driven decision-making, adaptive feedback, and intelligent reasoning mechanisms. This study contributes to the development of a holistic AI-driven model that supports individualized learning and health monitoring in line with SDG 3 (Good Health and Well-Being) and SDG 4 (Quality Education). Strengthening collaboration among educators, caregivers, and healthcare professionals can create more inclusive and effective educational ecosystems for ID/DD students.

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