IEPs in the Age of AI: Examining IEP Goals Written with and Without ChatGPT

Individualized Education Programs (IEPs) are a core element of special education in the United States. Within IEPs, IEP goals drive the implementation of IEPs and guide measurement of progress for students with disabilities. Yet research indicates that many IEP goals lack sufficient detail, indicating overall low-quality goals. Additionally, special education teachers can feel unsupported in their jobs and struggle with managing their workloads. This convergent mixed methods study explores the integration of artificial intelligence (AI) in special education to address these issues. Specifically, we explored how experienced teachers perceive AI’s role in their practice and compared the quality of AI-generated IEP goals to those written by special education teachers. Quantitative findings show no statistically significant difference ( p = .67) in quality ratings of IEP goals written only by teachers versus AI-generated goals. Qualitative findings depict overall positive perceptions on using AI to facilitate workload. Implications and opportunities for future research and the field centering on continued exploration and training of using generative AI to assist special education teachers are discussed.

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Institutions

Publication Details

Journal
Journal of Special Education Technology
Published
2025-02-28
DOI
https://doi.org/10.1177/01626434251324592
Citations
8
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
5.23

Funders

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article

IEPs in the Age of AI: Examining IEP Goals Written with and Without ChatGPT

Sean M. McDonald, Michael J. Kennedy, Bryan G. Cook, Olivia Fudge Coleman et al.
8 citations
Journal of Special Education Technology
Artificial Intelligence in Healthcare and Education
5.23
article

IEPs in the Age of AI: Examining IEP Goals Written with and Without ChatGPT

Sean M. McDonald, Michael J. Kennedy, Bryan G. Cook, Olivia Fudge Coleman, Danielle A. Waterfield, Nathan P. Welker
article en
8 citations

Abstract

Individualized Education Programs (IEPs) are a core element of special education in the United States. Within IEPs, IEP goals drive the implementation of IEPs and guide measurement of progress for students with disabilities. Yet research indicates that many IEP goals lack sufficient detail, indicating overall low-quality goals. Additionally, special education teachers can feel unsupported in their jobs and struggle with managing their workloads. This convergent mixed methods study explores the integration of artificial intelligence (AI) in special education to address these issues. Specifically, we explored how experienced teachers perceive AI’s role in their practice and compared the quality of AI-generated IEP goals to those written by special education teachers. Quantitative findings show no statistically significant difference ( p = .67) in quality ratings of IEP goals written only by teachers versus AI-generated goals. Qualitative findings depict overall positive perceptions on using AI to facilitate workload. Implications and opportunities for future research and the field centering on continued exploration and training of using generative AI to assist special education teachers are discussed.

Journal of Special Education TechnologyVol. 41(1)
University of Central Florida (US), University of Mary Washington (US), University of Virginia (US)
Office of Special Education Programs, Office of Special Education and Rehabilitative Services
Openalex Percentile: Top 5%
Artificial Intelligence in Healthcare and Education
5.23
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