Technology-Enhanced Education for Neurodiverse Learners: A Bibliometric Approach to Reducing Educational Inequalities

Background/purpose. Neurodiversity, including ASD, ADHD, and dyslexia, has a powerful impact on the learning processes and interaction with education. As fairness issues are growing in technology-enhanced learning (TEL), it is high time to trace research trends and critical contributors, as well as release new themes in this area. This paper examines the current scholarship on neurodiversity and education in the world over the period of 2010 to 2025 to illuminate intellectual frameworks and new trends.

Materials/methods. The bibliometric analysis concerned 336 articles obtained from Scopus. VOSviewer was used to map co-authorship, co-citation, and keyword co-occurrence. Analyses focused on academic production, country leadership, institutions, and thematic areas informing the world of research.

Results. The results indicate a gradual increase in publications over the last decade, with significant contributions from the United States, United Kingdom, and Italy. Harvard University and Vanderbilt University became the top institutions. Three key research clusters were found: (1) Cognitive and Psychological Studies, which centered on the idea of executive functioning and learning difficulties in neurodiverse students; (2) Educational Technology and Learning Strategies, which centered on the concept of adaptive systems and approaches to dealing with the neurodiversity issue; and (3) Assistive Technology and Artificial Intelligence, which revolved around the idea of AI and virtual reality in supporting the neurodiversity issue. Despite advances, obstacles persist in terms of access and socio-economic disparities.

Conclusion. Technology-based learning helps in meeting UN Sustainable Development Goal 4 (Quality Education), yet needs more policy changes, wider access to AI tools, and training of specific teachers to provide equal opportunities. Future research should focus on longitudinal assessments of TEL interventions and address ethical issues related to the use of AI in learning.

Keywords: Neurodiversity, Technology-Enhanced Learning, Bibliometric Analysis, Inclusive Education, Equal Opportunities

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