Mapping the Knowledge Landscape of Artificial Intelligence and Learning Disability Research: A Bibliometric Analysis (2015–2026)

Artificial Intelligence (AI) has emerged as a transformative force in education, healthcare, and assistive technologies, offering significant potential to support individuals with learning disabilities through personalized learning, early identification, and adaptive interventions. Despite the rapid growth of research in this interdisciplinary domain, a comprehensive understanding of its intellectual structure, research trends, and global contributions remains limited. This study conducts a bibliometric analysis of global research on artificial intelligence and learning disability published between 2015 and 2026. Bibliographic data were retrieved from the Scopus database using structured search strategies and analyzed using VOSviewer, Biblioshiny (R package), and Microsoft Excel. The analysis examined publication trends, influential authors, journals, institutions, countries, collaboration networks, keyword co-occurrence, and thematic evolution. The findings reveal a significant increase in research activity after 2020, with Saudi Arabia, the United States, and the United Kingdom emerging as leading contributors. The results also identify key research themes, including inclusive education, assistive technologies, adaptive learning, and machine learning applications. However, collaboration networks remain limited, indicating that the field is still developing. This study provides a comprehensive overview of the knowledge landscape, identifies research gaps, and highlights emerging research directions. The findings contribute to advancing interdisciplinary research, informing educational practices, and supporting the development of AI-driven inclusive educational technologies for individuals with learning disabilities.