Special Education Teachers' Use of Generative AI
A.J. Naatz
About A.J. Naatz
A.J. Naatz is a doctoral candidate at the University of Wisconsin–Madison and a former teacher of students with extensive support needs (ESN). His research focuses on the intersections of innovative technology, teacher preparation, and inclusive education. His scholarship examines how emerging technologies, such as artificial intelligence, can enhance collaborative planning and instructional design for students with ESN. He is committed to advancing fair access to education by bridging research, practice, and teacher development. Through his work, he aims to promote inclusive and innovative learning environments that foster meaningful engagement of all learners.
The problem highlighted in this brief
As generative artificial intelligence (AI) tools rapidly enter educational discourse and policy (e.g., Biden, 2023; Trump, 2025), there remains a significant knowledge gap around how special education teachers are actually using these tools in practice. Despite the potential of AI to enhance IEP goal writing (Rakap, 2023; Waterfield et al., 2025), generate content creation (Waterfield et al., 2025), and streamline administrative work (Goldman et al., 2024), little is known about the frequency, purpose, and conditions under which special education teachers adopt AI, especially for students with extensive support needs. To address this, Naatz and Ruppar (2025) conducted an exploratory survey examining usage patterns and influencing factors among special educators in Wisconsin.
Why does this topic matter to teacher preparation?
Teacher preparation plays a critical role in shaping future educators' understanding of the modern educational landscape and how they can utilize cutting-edge technology to support all students, including those with disabilities. Having a clear picture of how teachers are actually using generative AI for instruction can help researchers and administrators identify barriers and needs related to technology integration, develop effective teacher training, and shape ethical implementation guidelines. Naatz and Ruppar (2025) provide critical implications for teacher preparation programs based on their key findings.
About This Brief
The brief begins with context on the background of AI integration in education, focusing on special education teachers’ early adoption of generative AI tools. Audiences will learn about the current usage patterns among special educators, the factors that influence their decision to use (or not use) AI tools, and the practical implications for professional learning and teacher preparation. Drawing on Naatz and Ruppar’s (2025) exploratory survey, this brief highlights actionable insights for designing ethical, effective, and inclusive AI training that reflects the realities of classroom implementation and supports teachers of students with extensive support needs.
Research and Practice Context
Special Education Teachers’ Use of Generative AI
As AI becomes increasingly embedded in education policy and discourse, there is a limited understanding of how special education teachers are actually engaging with these tools in practice. This brief draws from an interview with A.J. Naatz, a former special educator and current doctoral candidate, whose research explores generative AI adoption among teachers of students with extensive support needs. The study offers timely insights into teacher behavior, decision-making, and implications for inclusive instructional planning.
The following are key insights shared by A.J. Naatz on this research. The interview focused on seven questions about special education teachers’ use of generative AI.
Conversation with A.J. Naatz
Q1: What issues are you trying to address through your work?
Naatz’s study addresses the critical gap between the policy-level enthusiasm for AI and the classroom realities of special education teachers. While AI dominates headlines and guidance documents, little is known about how—and why—teachers actually use these tools. The study aimed to capture both the frequency of generative AI use and the underlying motivations for adoption. These insights are essential for informing professional development, policy recommendations, and ethical guidance around AI integration in special education settings.
Naatz: “We wanted to fill a knowledge gap, primarily around how much teachers are actually using generative AI in classrooms. And then also with that, we wanted to explore why a teacher might adopt these technologies into their planning, into their teaching practices.”
Q2: Can you introduce the theoretical framework that guided your study?
The study combined the Theory of Planned Behavior and the Technology Acceptance Model to explore why special education teachers choose to adopt generative AI. These frameworks help explain how teachers’ attitudes, perceived social expectations, and control over technology use shape their behavior. This theoretical lens not only guided survey design but also helped uncover actionable insights for supporting teacher adoption of AI tools in real-world contexts, particularly by targeting beliefs and external influences.
Naatz: “There were really two key theories that we ended up mashing together, first being the theory of planned behavior, and then we pulled in the technology acceptance model. The theory of planned behavior looks at attitudes, subjective norms, and [behavioral] control. ”
Q3: Can you briefly walk us through your research process and the key findings?
Naatz and Ruppar (2025) conducted an exploratory survey of special education teachers across Wisconsin to capture their frequency of generative AI use and the factors influencing adoption. They found that as of May 2024, 80% of teachers were still in the exploratory phase, rarely using AI in practice. Key predictors of use were teacher attitudes toward AI and contextual factors like administrative support and access to tools. Age also showed a negative correlation with usage, underscoring the need for differentiated support across generations.
Naatz: “We designed an exploratory survey structured into kind of five categories aligned with our theoretical framework. We looked at the frequency of how frequently they're using [AI]. 80% of the respondents either have never used it, have used it once or twice, or use it monthly. Attitudes and contextual factors emerged as significant predictors. Another factor, as teachers get older, less likely to use and adopt AI.”
Q4: How do these findings inform the teacher preparation program?
Naatz emphasized that teacher preparation programs must move beyond bans and instead offer structured opportunities for exploration and ethical use of AI tools. Positive attitudes, administrative support, and access to professional development are critical. If teachers lack ethical guidance or contextual understanding, they may still use AI, but without intention or accountability. This finding calls for intentional training that helps both pre-service and in-service teachers understand how to use AI effectively, responsibly, and in alignment with instructional goals.
Naatz: “Teachers need structured time to explore these tools and to build positive attitudes around them. If it's not ethical, or teachers don't think it's ethical, that's going to impact their attitudes about it. If we just put a hard ban on it, teachers are still going to probably use it, but they're not going to use it ethically, or they're not going to be trained on how to use it.”
Q5: What gaps and opportunities do you see for future research, and what are some questions we might be asking?
Naatz identifies a critical gap in understanding the actual impact of AI on teaching and learning, particularly for students with extensive support needs. He calls for future research to examine whether and how students should use generative AI, balancing the risks (e.g., diminished critical thinking) with the potential benefits for accessibility and autonomy. He urges scholars to center teacher and student voices in AI research to ensure that future implementations are ethical, human-centered, and contextually appropriate.
Naatz: “These tools have amazing capabilities in providing access and accommodations to students with extensive support needs. How can we leverage these tools to help students succeed, not only in the classroom, but in employment, in independent living? I'm also a believer that we need research that centers teacher and student voices in what we do.”
Q6: What else should teacher preparation programs consider moving forward?
Q7: What resources, tools, or networks would you recommend for rural educators who want to explore technology innovations?
Naatz emphasizes that teacher preparation programs must adapt to the reality that AI is already embedded in pre-service teachers' learning habits. Instead of banning AI, programs should rethink course structures and focus on building core teaching skills, such as creativity, adaptability, and classroom management, over procedural tasks that AI can replicate. Strategies like flipped classrooms, real-time case studies, and in-person collaboration can promote authentic learning and professional identity development in an AI-rich educational environment.
Naatz encourages educators to begin exploring AI tools through playful, low-pressure activities, starting with general-purpose large language models like ChatGPT, Gemini, and Claude. He recommends collaborative exploration, trying tools with a peer, and sharing discoveries as a way to spark ideas and reduce apprehension. For a deeper understanding, he suggests accessible resources like Co-Intelligence by Ethan Mollick and diverse perspectives from podcasts such as TED Tech and Better Offline, which offer both optimistic and critical lenses on AI use across fields, including education.
If you are interested in learning more, please read the article Special Education Teachers’ Use of Generative Artificial Intelligence (AI): An Exploratory Survey of Frequency and Factors Influencing Adoption in the Journal of Special Education Technology.
Resources and References
Biden, J. (2023). Executive order on the safe, secure, and trustworthy development and use of artificial intelligence [Executive Order No. 14110]. The White House. https://www.whitehouse.gov/ briefing-room/presidential-actions/2023/10/30/executive-orderon-the-safe-secure-and-trustworthy-development-and-use-ofartificial-intelligence
Goldman, S. R., Taylor, J., Carreon, A., & Smith, S. J. (2024). Using AI to support special education teacher workload. Journal of Special Education Technology, 39(3), 434–447. https://doi.org/10.1177/01626434241257240
Rakap, S. (2023). Chatting with GPT: Enhancing individualized education program goal development for novice special education teachers. Journal of Special Education Technology, 39(3), 339-348. https://doi.org/10.1177/ 01626434231211295
Trump, D. (2025). Executive order on advancing artificial intelligence education for American youth [Executive Order No. 14277]. The White House. https://www.whitehouse.gov/ presidential-actions/2025/04/advancing-artificial-intelligenceeducation-for-american-youth/
Waterfield, D. A., Coleman, O. F., Welker, N. P., Kennedy, M. J., McDonald, S. D., & Cook, B. G. (2025). IEPs in the age of AI: Examining IEP goals written with and without ChatGPT. Journal of Special Education Technology, 01626434251324592. https://doi.org/10.1177/01626434251324592
Suggested Citation
Seung, Y., Naatz, A. J., & the CIDDL Team. (2025). Special Education Teachers’ Use of Generative AI. The Center for Innovation, Design, and Digital Learning.
This work is licensed under a Creative Commons Attribution 4.0 International License.