For this week’s reflection, I want to discuss universal design for learning (UDL) in the context of educational technology, especially generative AI. I am already quite familiar with UDL – from my background as an educational assistant, as well as from our PDPP courses thus far (e.g., ED-D 301: Learners and Learning Environments). So, what we’ve been covering is mostly review / consolidation. That is, except for the ways that we can use new tech to UDL-ify our practice. I’ve been loving considering UDL in the context of AI, so, the theme of this reflection is…

Employing AI to reach students of diverse abilities and interests

Photo from https://www.cast.org/resources/course/prek-12-artificial-intelligence-for-udl-self-directed-2025/. CAST (the gold standard of UDL) actually offers mini workshops on how to turn “artificial intelligence into assistive intelligence” (and boy, do I love that slogan!).

I’ve previously mentioned that I am SUPER EXCITED about the potential UDL applications of generative AI. Differentiating lessons and materials can be a huge hurdle, especially for early career teachers. I want to be able to meet every student where they’re at, and provide the optimal challenge that they need to learn and thrive. I think that AI could help.

I thought it would be a fun exercise to take the UDL checklist that was linked in this week’s course materials, and brainstorm/test out ways that generative AI could be used to fulfill it. I also included some prompts you could use as inspiration.

Universal Design for Learning Checklist

Make Expectations (objectives, rubrics, grading) explicit from the start

  • Use AI to rewrite objectives in student-friendly language
  • Example: Ask ChatGPT, Claude, or Gemini, “Rewrite this learning objective in simple grade 3 student-friendly language”

Multiple means of engagement

  • Use AI to personalize activities and texts to student interests
  • Example: “Rewrite these math word problems to feature characters from the popular Netflix original, KPOP Demon Hunters”

Multiple means of representation

  • Use AI to create concept maps, analogies, and story-style explanations. I recently discovered NapkinAI, which is great at creating visual concept maps (sometimes ChatGPT sucks at this – it still struggles with generating text and images together).
  • Example: “Explain photosynthesis three ways: a story, a diagram description, and a sports analogy.”

Include alternatives to the text (e.g. website, article, video, audio summary, or lower reading-level text

  • NotebookLM makes great podcasts/audio summaries from written texts. It could be a great resource for kids who struggle to decode or tackle big blocks of words.
  • In my AI Workbook assignment, I tried out using ChatGPT to translate a text into a lower reading level. This is an area where it thrives.
  • MagicSchool also has a text leveller tool.
  • Example: “Rewrite this article at a grade 4 reading level and include key vocabulary definitions.”
How to use MagicSchool text leveller feature: https://youtu.be/nU8QG6eLhvQ?si=gwbu-PzrtN9iAjaA

Include checks for understanding to shape instruction

  • Use AI to create exit tickets, poll questions, and think-pair-share prompts.
  • KahootAI makes great quick quizzes to check student understanding.

Provide access to class notes in various formats (e.g. outline, graphic, study cast)

  • Use AI to convert notes into Cornell notes, graphic organizers, study guides, and flash cards.
  • Tools like Quizlet use generative AI to transform notes from and into many forms!

Thanks for reading!