The session will introduce the use of learner profiles, choice boards, and AI to support personalized learning across subject areas. A visual poster will showcase examples and infographics, with QR codes linking to editable templates, AI prompt banks, and resources. Attendees will explore how learner profiles inform choice board design, see demonstrations of AI-supported differentiation, and leave with strategies and tools ready for immediate use.
Participants will:
Browse interactive visuals and sample choice boards
Scan QR codes to access editable templates and resources
Engage in peer-to-peer conversations about application in their grade or subject
Share challenges and brainstorm AI-supported solutions
Contribute one takeaway idea to a collaborative “ideas wall”
Content is flexible and repeatable, ensuring meaningful engagement whenever participants stop by. A typical interaction cycle might last 15–20 minutes, including an introduction, exploration of learner profiles and choice boards (5–10 minutes), an AI demonstration (5–10 minutes), and a brief takeaway activity.
After this session, participants will be able to design a choice board framework that incorporates learner profiles to support personalized learning, identify ways AI tools can streamline the creation and adaptation of differentiated options, apply strategies to align tasks with standards while accommodating learner variability, and adapt provided templates to create equitable, student-centered learning experiences in their own classrooms.
Büchel, L. L. (2023). Motivated to work: The power of choice boards. English Teaching Forum. U.S. Department of State. https://americanenglish.state.gov/files/ae/resource_files/teaching_techniques_motivated_to_work.pdf
Laak, K.-J., & Aru, J. (2024). AI and personalized learning: Bridging the gap with modern educational goals [Preprint]. arXiv. https://arxiv.org/html/2404.02798v2
Reber, R., Canning, E. A., & Harackiewicz, J. M. (2018). Personalized education to increase interest. Current Directions in Psychological Science, 27(6), 449–454. https://pmc.ncbi.nlm.nih.gov/articles/PMC6715310/
Tucker, C. (2024, April). Designing a standards-aligned choice board (with AI). Catlin Tucker. https://catlintucker.com/2024/04/standards-aligned-choice-board/
Posters in this theme:
Empowering Students Through Sensory Innovation and Inclusive Design
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