Practical Proficiency in Utilizing AI Tools for Accessible Material Creation
Goal: Attendees will gain hands-on awareness of specific AI tools for accessibility.
Applications (Leveraging AI for):
A. Creating alternative text for images.
B. Generating transcripts and captions for audio/video.
C. Simplifying complex text.
D. Offering text-to-speech and speech-to-text functionalities.
Outcome: Participants will leave with initial steps for integrating these tools into their material development workflow.
2. A Deepened Understanding of the UDL Framework Through the Lens of AI
Goal: Participants will learn how to apply AI to embody the three UDL principles strategically.
UDL Principles Emphasized:
A. Multiple Means of Representation
B. Multiple Means of Action and Expression
C. Multiple Means of Engagement
Focus: Emphasizes how AI facilitates the proactive design of flexible learning environments that cater to diverse learner needs from the outset, rather than retrofitting accommodations.
3. Strategies for Efficiently Differentiating Instruction with AI-Generated Resources
Goal: Attendees will acquire actionable strategies for leveraging AI to create differentiated materials.
Differentiation Applications (AI assists in):
A. Generating varied versions of content at different reading levels.
B. Creating personalized practice exercises.
C. Providing tailored feedback.
D. Offering diverse options for students to demonstrate their understanding.
Outcome: Participants will receive a framework for using AI to save time and effort in differentiation while maximizing student engagement and learning outcomes.
This session broadens the view of AI from a fundamental tool to a foundational partner in equity-focused instructional design. By actively aligning AI capabilities with the UDL framework, we shift from reactive accommodation to proactive, inclusive material creation, ensuring technology truly serves the diverse needs of every student and empowers diverse learners worldwide.
After this poster session, participants will be able to
Design accessible learning materials (e.g., alternative text, transcripts, simplified text) by utilizing specific AI-powered tools and platforms.
Apply the three core UDL principles (Representation, Action/Expression, Engagement) by strategically integrating AI to create flexible learning environments proactively.
Differentiate instruction and save time by generating varied content, personalized practice, and tailored feedback using AI-generated resources.
Evaluate their current material creation process and implement initial steps for transitioning from reactive accommodation to proactive, UDL-aligned design using AI.
CAST (2018). Universal design for learning guidelines version 2.2. http://udlguidelines.cast.org
CAST (2020). About universal design for learning. http://www.cast.org/our-work/about-udl.html#. XtuJJ9aSlPY
Desimone, L. M., & Garet, M. S. (2015). Best practices in teacher's professional development in the United States. Psychology, Society & Education, 7(3), 356-369.
International Society for Technology in Education. (2025). ISTE standards for educators. https://www.iste.org/standards/iste-standards-for-teachers
Sewell, A., Kennett, A., & Pugh, V. (2022). Universal Design for Learning as a theory of inclusive practice for use by educational psychologists. Educational Psychology in Practice, 38(4), 364-378. https://doi.org/10.1080/026673.2022.2111677
Tlili, A., Zhang, J., Papamitsiou, Z., Manske, S., Huang, R., Kinshuk, & Hoppe, H. U. (2021). Towards utilising emerging technologies to address the challenges of using Open Educational Resources: A vision of the future. Educational Technology Research & Development, 69(2), 515–532. https://doi.org/10.1007/s11423-021-09993-4
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