access and opportunity will grow.
Research-Based Practices for Teaching Students with Moderate to Severe Intellectual Disability.
2. Centering Student Voice Through the IEP An IEP is most effective when it clearly connects a student’s needs to specific supports, including AI- enhanced AAC. Documenting Present Levels, goals, and training ensures technology is used consistently and meaningfully. Limiting students to preselected words or yes/no responses restricts their authorship; embedding AI-enhanced AAC into the IEP allows them to expand ideas, build vocabulary, and participate fully across settings. This keeps their voice at the center of their learning. The next IEP meeting is the right time to start. 3. Thoughtful Integration With Guardrails AI in AAC must be implemented with care, training for staff, clear expectations for use, and safeguards for privacy, accuracy, and bias are essential. Moving forward doesn’t mean rushing; it means building a plan that protects student agency while expanding opportunities for meaningful writing. Teachers, therapists, administrators, and families share the responsibility to ensure equitable access so every student’s voice is heard and valued. CONCLUSION True writing instruction is about empowering students to construct and share their own ideas, not simply producing marks on a page. For students who use AAC, achieving this requires both intentional IEP goals and equitable access to the tools their peers already use. When we expand our definition of “writing” beyond handwriting and spelling, and embrace technology, including AI, as a legitimate means of authorship, we give every student the chance to develop a genuine voice. NEXT IN OUR SERIES: We’ll explore the critical role educators play in supporting students who use AAC to ensure their voices are heard and their authorship remains their own. From fostering independence to guiding ethical and effective AI use, we’ll look at practical strategies that keep student agency at the center of learning. Note: ChatGPT and Grammarly were used by the authors to organize and edit this article. REFERENCES Beukelman, D. R., & Light, J. C. (2020). Augmentative and alternative communication: Supporting children and adults with complex communication needs (5th ed.). Baltimore, MD: Paul H. Brookes Publishing.
Griffiths, Tom & Slaughter, Rohan & Waller, Annalu. (2024). Use of artificial intelligence (AI) in augmentative and alternative communication (AAC): community consultation on risks, benefits and the need for a code of practice. Journal of Enabling Technologies. 10.1108/JET-01-2024-0007. Lahm, E. A., Bausch, M. E., Hasselbring, T. S., & Blackhurst, A. E. (2001). National Assistive Technology Research Institute. Journal of Special Education Technology, 16(3), 19-26. https://doi.org/10.1177/016264340101600302 (Original work published 2001) Light, J. C., & McNaughton, D. (2014). Communicative competence for individuals who require augmentative and alternative communication: A new definition for a new era of communication? Augmentative and Alternative Communication, 30(1), 1–18. https://doi.org/10.3109/0743 4618.2014.885080 Lorah ER, MacNeil S, Zimmerman T, Rackensperger T, Holyfield C, Caldwell N, Dragut EC, Vucetic S. Spurring Innovation in AAC Technology through Collaborative Dreaming and Needs Finding with Individuals with Developmental Disabilities Who Use AAC. Semin Speech Lang. 2024 Nov;45(5):461-474. doi: 10.1055/s-0044-1791789. Epub 2024 Oct 15. PMID: 39406366. McNaughton, David & Rackensperger, Tracy & McLemore, Lance. (2025). Supporting meaningful participation in society by adults with developmental disabilities who need and use AAC: lived experiences, key research findings, and future directions. Augmentative and alternative communication (Baltimore, Md. : 1985). 41. 1-14. 10.1080/07434618.2025.2504497. Nica, E., Sabie, O. M., & Oaia, D. C. (2024). Artificial intelligence– assisted education technology, personalized learning algorithms, and sustainable academic performance in digital classrooms. Journal of Educational Technology and Innovation, 5(1), 11. https://doi.org/10.3390/educ5010011 Rashid, M. M., Atilgan, N., Dobres, J., Day, S., Penkova, V., Küçük, M., Clapp, S. R., & Sawyer, B. D. (2024). Humanizing AI in Education: A Readability Comparison of LLM and Human-Created Educational Content. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 10711813241261689. https://doi. org/10.1177/10711813241261689
Jimenez, B., Courtade, G., & Fosbinder, J. (2024). Leveraging Artificial Intelligence to Enhance Implementation of
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