From Early Detection to Lifelong Inclusion: Artificial Intelligence-Supported Identification and Intervention for Dysgraphia
Year: 2026
Type: article
Abstract: Dysgraphia, characterized by persistent difficulties in handwriting fluency, spelling, and written expression, continues to be among the least systematically identified learning disabilities within mainstream and inclusive educational settings, especially in India, where delayed identification exacerbates academic disadvantage and undermines learner confidence. This study systematically reviews the research literature and emerging technology platforms worldwide to explore AI based technologies for the early detection and structured intervention of dysgraphia. This study reviews AI powered assessment systems such as machine learning models, smart pen sensors, deep learning diagnostics and handwriting analytics as well as AI supported intervention ecosystems providing adaptive learning environments, real time feedback and personalised skill development pathways using a qualitative, review based methodology. The results indicate that AI identification tools can improve the objectivity, accuracy and timeliness of dysgraphia detection, moving from reactive deficit assessments to proactive, evidence-based screening embedded in educational routines. AI-assisted interventions also demonstrate consistent promise in improving writing outcomes, engagement, and self-efficacy, via developmentally calibrated learning pathways. The study points out major lacunae in the use of AI in the Indian educational context and the importance of culturally responsive, multilingual and ethically-grounded tools that are in alignment with the RPwD Act, 2016 and NEP, 2020. Responsible AI integration has huge potential for reducing educational exclusion and for promoting equitable, sustainable participation across the lifespan.
Authors: Sadaf Iqbal, DR. R. Jamuna
Institution: Jamia Millia Islamia
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7203637577