Novice Special Educators Using GenAI to Support Specially-Designed Instruction

Ann Jolly

Special Education, Specially-Designed Instruction, Co-Teaching

As a university supervisor supporting student teachers entering the field of special education, I have modeled how GenAI can support their work by providing quality specially designed instruction (SDI) across diverse learners and grade levels. Recognizing the significant time demands inherent in individualizing instruction, particularly with substantial caseloads, I demonstrated how GenAI could support their planning and progress monitoring, leaving more time for instruction.

I actively integrated GenAI as a hands-on strategy in special education student teaching seminars. We began by deconstructing grade-level standards using GenAI. Students learned to prompt the AI to “task analyze” standards for learners with specific disabilities (SWD), revealing potential learning barriers and informing an initial draft of individualized objectives. We discussed the importance of Human Intelligence with Artificial Intelligence, due to biases, hallucinations, and other challenges with AI. I also emphasized that they never enter student identifying information or data into a chatbot. Focusing on the grade-level standards ensures that SWD are receiving instruction that is grade-level aligned.  

Next, we explored GenAI’s capacity for differentiation. I presented student profiles with varied learning strengths and needs, and students prompted the AI to generate multiple versions of instructional activities. The rapid generation of diverse options, from visual aids to adapted text, demonstrated AI’s potential to save significant planning time and offer a broader range of accessible materials. We also investigated AI’s role in progress monitoring. Students learned to input IEP goals, prompt the AI to suggest measurable objectives, and create basic data sheet templates. The emphasis remained on teacher expertise in selecting and adapting these suggestions, ensuring alignment with individual student needs and effective data collection for informed instructional adjustments, a critical aspect of SDI monitoring.

GenAI enables special education teachers to efficiently a) differentiate tasks, b) analyze tasks that we want to be explicit about, teach students with disabilities, c) differentiate tasks to align with student assets, and d) monitor progress, using monitoring tools that students and teachers can use to track progress towards goals. An example of this feature is the prompt: “What is a common IEP goal for a 5th grader with organization challenges?” The chatbot could tell me the goal and specific objectives towards the goal. After selecting one of the objectives, I prompted “Create a student-friendly data sheet to monitor the goal: The student will independently use a planner or organizational tool to record homework assignments, project due dates, and important dates for at least 90% of assigned tasks.” The chatbot generated instructions and a chart for the student to self-monitor their progress toward the goal. In another example, I provided the prompt, “Generate a three-point rubric in table form to assess a student’s understanding of standard W. 4.2 Write informative /explanatory texts to examine a topic and convey ideas and information clearly.” I then showed how we could select one rubric component to teach and monitor explicitly using transition words (always, never, sometimes) to scaffold and build toward mastery. 

I also modeled how GenAI could support co-teaching, maximizing efficient planning to brainstorm lesson ideas, generate lesson plans, adapt resources, generate strategies to increase student engagement, and teach and manage behaviors, leading to a safe and productive learning environment. In addition to chatbots they were familiar with from their school districts, I also introduced Poe Ludia (https://poe.com/Iudia), a chatbot that incorporates the Universal Design for Learning principles.

My students’ feedback was overwhelmingly positive. They recognized GenAI’s potential to save planning time, generate diverse instructional ideas, and facilitate the creation of accessible materials. Importantly, they understood that GenAI could free them to focus more on direct student interaction and tailoring instruction based on individual needs.