AI-Assisted Creation of Educational Contents for Children with Special Needs

Creating specialized educational materials for children with diverse cognitive, sensory, or developmental needs is often a resource-intensive process that can be difficult for educators to sustain through traditional manual methods. AI-assisted content creation offers a transformative approach by automating the generation of personalized visual, auditory, and linguistic supports, thereby reducing systemic barriers to learning. This study explores the effectiveness of Generative Artificial Intelligence (AI) in reshaping educational content for children with special needs. It is grounded in the principles of Universal Design for Learning (UDL) and Social Constructivism, particularly the Zone of Proximal Development (ZPD), which advocate for multiple means of representation in learning. Adopting a qualitative thematic analysis, the research investigates the perceptions and lived experiences of educators transitioning from manual “retrofitting” to AI-supported content adaptation. Findings indicate that AI-driven tools, including automated text simplifiers, social story generators, and high-interest visual aids, enhance pedagogical effectiveness and learner engagement. Beyond efficiency gains, the study demonstrates that AI-assisted strategies, when guided by human expertise, can transform instruction into a more responsive and equitable experience. The study concludes by recommending a “human-in-the-loop” framework to ensure the meaningful integration of AI-assisted content, positioning technology as a bridge to active participation for diverse learners.