Introductions and Ice-Breaker (14 minutes)
Introduce ourselves and do a quick ice-breaker so that people have some understanding of who is sitting at their table.
Introduce the Co-Lab model with its focus on hands-on exploration and pedagogical discussion, including a demo of how to run through an exploration.
Quick review of AI standards such as removing Personal Information from prompts.
Set the “vibe of the room” guardrails: the focus is on teaching and learning not policies/apps.
Round 1 Exploration (33 minutes)
Frame the Challenge: How can AI help design hands-on activities for the classroom
Individual Exploration: Use provided prompts and follow up questions and guides to generate hands-on lesson ideas
Turn and Talk: Guided by questions on the potential and pitfalls of AI and the pedagogical soundness and use of the exploration.
Brief debrief: Share out to the full room focused on application to teaching practice.
Round 2 Exploration (33 minutes) (same format as round 1)
Frame the Challenge: How do we assess authentically now and in the future?
Individual Exploration: Use provided prompts and follow up questions and guides to generate authentic assessments for the AI age.
Turn and Talk: Focused on how participants modified and tweaked the exploration to benefit their focus.
Brief debrief: Share out to the full room focused on application to teaching practice.
Closing and Reflections (10 minutes)
Reflect on the Co-Lab process itself
Action Planning: what will you try first in your classroom? What will you share with colleagues? What are you still wondering or curious to learn more about?
Share link to resources including sign-up form.
Attendees will create hands-on, student-centered lesson activities for their own classrooms using AI as a planning tool. They will also experience the Co-Lab professional development model firsthand, gaining a framework they can replicate with colleagues to collaboratively explore AI integration while maintaining pedagogical focus. This PD model, which is centered on examining the potentials and pitfalls of AI for teaching and learning, enables participants to enhance their personal AI Literacy, thus allowing them to have better conversations with their students around AI and AI literacy.
The Shift to Student-Led: Reimagining Classroom Workflows with UDL and Blended Learning by Catlin R. Tucker and Katie Novak
Ethan and Lilach Mollick’s work (Assigning AI: Seven Approaches for Students, with Prompts) (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4475995)
Vintage Innovation: Leveraging Retro Tools and Classic Ideas to Design Deeper Learning Experiences by John Spencer
Leading Modern Learning: A Blueprint for Vision-Driven Schools (A Framework of Education Reform for Empowering Modern Learners) by Jay McTighe and Greg Curtis
Elevating Educational Design with AI: Making Learning Accessible, Inclusive, and Equitable by Catlin R. Tucker and Katie Novak
Why AI Literacy is now a Core Competency in Education, by Tanya Milberg (https://www.weforum.org/stories/2025/05/why-ai-literacy-is-now-a-core-competency-in-education/)
Prensky Revisited: Is the Term “Digital Native” Still Applicable to Today’s Learner? By Jennifer Spiegel (https://drive.google.com/file/d/1y6xksPZIgiUib5oJEV_jokmQdpwvmOtY/view)
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