This study conducts a bibliometric analysis of the scientific literature addressing the intersection between Specific Learning Disabilities (SLDs) and Artificial Intelligence (AI), a field that has been gaining increasing relevance due to the transformative potential of AI-based interventions in education. SLDs, including dyslexia, dysgraphia, and dyscalculia, significantly impact learning processes and academic outcomes, making it crucial to explore innovative approaches for their early identification and personalized support. AI technologies, such as machine learning, natural language processing, and adaptive systems, offer promising tools to enhance educational inclusion and tailor interventions to individual learning needs. By leveraging data-driven methodologies, AI can provide dynamic and responsive learning environments, improving both engagement and outcomes for students with diverse cognitive profiles.
Using data retrieved exclusively from the Scopus database and analysed through the Bibliometrix R package, this research examines publication trends, citation patterns, international collaboration networks, and thematic evolutions within this interdisciplinary domain. The analysis reveals a substantial increase in research output since 2020, highlighting a growing academic and technological interest in leveraging AI to address SLD challenges. Countries such as the United States, Spain, Italy, and India emerge as key contributors, fostering an expanding global collaboration network. These international partnerships reflect a shared commitment to addressing the complex and multifaceted nature of learning disabilities through cross-disciplinary research efforts.
Thematic mapping identifies core topics like dyslexia, machine learning, and personalized learning systems, alongside emerging themes such as contrastive and adversarial machine learning approaches, which represent innovative frontiers for future exploration. In particular, these advanced AI techniques show potential in enhancing diagnostic precision and developing more adaptive educational tools. Despite this promising landscape, the study underscores the need for broader empirical validation and interdisciplinary cooperation involving educators, AI researchers, and healthcare professionals. Meta-analytic evidence also suggests the importance of integrating cross-disciplinary insights when developing AI tools tailored to the needs of students with disabilities (Zhang, Carter Jr., Liu, & Peng, 2024).
The findings emphasize the strategic role of AI in promoting educational equity and suggest future research directions to consolidate and expand this field, ultimately contributing to more inclusive and effective learning environments for individuals with SLDs. Such efforts are essential to bridge existing gaps in access to tailored educational resources, ensuring that technological innovation translates into tangible benefits for learners worldwide.