Artificial Intelligence in Chemistry Education for Students with Disabilities: A Scoping Review of Applications Supporting Inclusive Teaching Practices

Abstract

Objective: To map evidence on AI applications in chemistry education for students with disabilities and identify outcomes and barriers for inclusive teaching.

Methods: A scoping review was conducted following Arksey & O’Malley’s framework and PRISMA-ScR. Scopus and Google Scholar were searched. Eligible studies were thematically analyzed.

Results: Five studies were included. AI applications were mainly supportive (animation tools, translation systems, computer-assisted instruction, teacher training, LLM evaluation). Evidence was mostly descriptive, showing perceived benefits in accessibility and engagement but limited learning outcome data. Key barriers included low teacher readiness, infrastructure gaps, and limited reliability of generative AI.

Conclusion: AI in inclusive chemistry education remains early-stage, with emphasis on accessibility rather than adaptive pedagogy. Stronger empirical evidence is needed.