Artificial Intelligence for IEP Development
Authors: Yerin Seung; info@ciddl.org
CIDDL’s latest recorded webinar series highlights researchers integrating artificial intelligence (AI) for Individualized Education Programs (IEPs) development. IEPs are essential for ensuring students with disabilities receive personalized support to succeed, but creating these plans can be a daunting process. Special education teachers often face significant challenges, including navigating extensive documentation, aligning services with individual needs, and managing heavy workloads. These demands can make it difficult to focus on developing meaningful, high-quality plans for each student. By integrating AI into the IEP process, educators can streamline repetitive tasks, access data-driven insights, and allocate more time to thoughtful, individualized planning. This webinar series explores how AI is transforming the way IEPs are developed, offering practical tools and strategies and evidence and insights from empirical studies.
Download the webinar supplemental, a one-page document with links to each video, article citations, and extras provided by the authors (e.g., links to slides and other resources).
Developing Quality IEP Goals in the Age of AI
This webinar, presented by Dr. Chengan Yuan, assistant professor of special education and applied behavior analysis, and Dr. Juliet Hart Barnett, professor of special education both at Arizona State University, highlights how technology, particularly generative AI tools like ChatGPT, Gemini, and CoPilot, is revolutionizing the development of IEP goals based on their article. The speakers discuss the importance of high-quality, SMART (specific, measurable, achievable, relevant, and time-bound) IEP goals, which align with legal and educational standards to address students’ unique needs stemming from disabilities. The webinar introduces six strategies for effectively using AI to create SMART IEP goals, such as crafting clear prompts, incorporating reference texts, and iterative testing. Challenges like safeguarding data, mitigating bias, and ensuring meaningful collaboration with families are also addressed, alongside a call for further research to enhance AI's role in special education.
[embedyt] https://www.youtube.com/watch?v=LKqLRnAdF1U[/embedyt]
Using Generative AI for IEP Goals: Insights and Experiences from Special Education Teachers
Danielle A. Waterfield, alongside Dr. Olivia Fudge Coleman and Nathan (Nate) P. Welker from the University of Virginia, presented their empirical study exploring the potential of generative AI to support the development of high-quality IEP goals. As writing IEP goals remains a challenging and time-intensive task for special education teachers burdened with heavy workloads, the researchers were interested in the potential of generative AI to reduce the cognitive load of special education teachers. They adopted mixed methods to explore the quality of AI-generated IEP goals and special education teachers' experiences. Quantitative findings revealed that AI-generated goals were comparable in quality to teacher-written ones. At the same time, qualitative data highlighted AI’s potential to reduce workload, though human expertise remains crucial for refining outputs. The team emphasized the importance of professional development for teachers regarding AI use and called for further research to expand the understanding of AI’s role in special education.
[embedyt] https://www.youtube.com/watch?v=epN_SKgYgVo[/embedyt]
Prototyping a Multi-Agent System for IEP Development: CoIEP
Dr. Ling Zhang from the University of Wyoming, Dr. Haidee Jackson from the University of Texas Permian Basin, and Dr. Sohyun Yang from Fort Hays State University introduced an innovative AI-powered multi-agent system to streamline IEP development. Recognizing the complexities and workload challenges associated with creating high-quality IEPs, the team developed an AI-human collaboration model to enhance efficiency and accuracy. Unlike single-agent systems, their multi-agent system assigns specific roles to three AI agents, including generating Present Levels of Academic Achievement and Functional Performance (PLAAFP) statements, crafting SMART-aligned IEP goals, and recommending individualized support and services based on evidence-based practices. The system emphasizes collaboration between AI and educators, allowing for iterative refinement while maintaining privacy and personalization. Although still a prototype, this system shows promise in reducing teacher workloads, improving IEP quality, and supporting special education services with structured, evidence-based tools.
[embedyt] https://www.youtube.com/watch?v=MGcMTy9JsFU[/embedyt]
[embedyt] https://www.youtube.com/watch?v=cuxVJl6NDbE[/embedyt]
Join the conversation in our community!
CIDDL is committed to providing high-quality resources to support the increasing knowledge, adoption, and use of a range of educational technologies that can be used for educators, related services, or leadership preparation programs. For more resources, including videos and blogs, subscribe to our newsletter and follow us on YouTube, Facebook, and LinkedIn. The most important part of our CIDDL community is YOU. Join our community and share the innovative ways you are using technology, ask a question about technology integration, or participate in our bi-weekly live AI Community Chats.
We look forward to seeing you in our community!