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

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Title: IEPs in the Age of AI: Examining IEP Goals Written with and without ChatGPT
Language: English
Authors: Danielle A. Waterfield (ORCID 0009-0008-1677-3135), Olivia F. Coleman, Nathan P. Welker (ORCID 0009-0001-9387-9565), Michael J. Kennedy, Sean D. McDonald, Bryan G. Cook
Source: Journal of Special Education Technology. 2026 41(1):57-71.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 15
Publication Date: 2026
Sponsoring Agency: Office of Special Education Programs (OSEP) (ED/OSERS)
Contract Number: H325D210027
Document Type: Journal Articles
Reports - Research
Education Level: Elementary Secondary Education
Descriptors: Individualized Education Programs, Students with Disabilities, Special Education, Educational Objectives, Special Education Teachers, Teacher Attitudes, Artificial Intelligence, Technology Uses in Education, Faculty Workload, Elementary Secondary Education
DOI: 10.1177/01626434251324592
ISSN: 0162-6434
2381-3121
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 = 0.67) 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.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1496954
Database: ERIC
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  Data: IEPs in the Age of AI: Examining IEP Goals Written with and without ChatGPT
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  Data: <searchLink fieldCode="AR" term="%22Danielle+A%2E+Waterfield%22">Danielle A. Waterfield</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0008-1677-3135">0009-0008-1677-3135</externalLink>)<br /><searchLink fieldCode="AR" term="%22Olivia+F%2E+Coleman%22">Olivia F. Coleman</searchLink><br /><searchLink fieldCode="AR" term="%22Nathan+P%2E+Welker%22">Nathan P. Welker</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0001-9387-9565">0009-0001-9387-9565</externalLink>)<br /><searchLink fieldCode="AR" term="%22Michael+J%2E+Kennedy%22">Michael J. Kennedy</searchLink><br /><searchLink fieldCode="AR" term="%22Sean+D%2E+McDonald%22">Sean D. McDonald</searchLink><br /><searchLink fieldCode="AR" term="%22Bryan+G%2E+Cook%22">Bryan G. Cook</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Special+Education+Technology%22"><i>Journal of Special Education Technology</i></searchLink>. 2026 41(1):57-71.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: <searchLink fieldCode="EL" term="%22Elementary+Secondary+Education%22">Elementary Secondary Education</searchLink>
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  Data: 10.1177/01626434251324592
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  Data: 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 = 0.67) 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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  Data: 2026
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  Data: EJ1496954
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      – SubjectFull: Elementary Secondary Education
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