AI in the classroom only works when it deepens student thinking instead of replacing it. In this hands-on workshop, we will use the 5 E model (Engage, Explore, Explain, Empower, which is our version of Elaborate, and Evaluate) to design AI-integrated lessons that are technically sound and culturally grounded. You will see how AI can support inquiry, computational thinking, debugging, and project-based learning, without doing the thinking for your students. You will walk out with a draft lesson plan or project that is standards-aligned, ethically sound, and connected to who your students actually are: their voice, their identity, their community.
As AI shows up in more classrooms, most educators are handed a list of tools and left to figure out the rest. What they actually need is an instructional design model: a way to decide what students should learn, where AI belongs in the curriculum, and how to teach it ethically and well. This workshop gives them just that.
Participating educators will design culturally relevant AI lessons using the 5 E instructional model: Engage, Explore, Explain, Empower (our take on Elaborate), and Evaluate. The 5 E model builds student understanding through curiosity, investigation, direct instruction, application, and reflection. We rename the application phase "Empower" on purpose. That is the moment students take a concept and make it their own, digging into the work without being walked through every step, and that ownership is where real confidence and capability get built. Paired with culturally responsive CS instruction, the model helps teachers design lessons that are technically rigorous and connected to students' lives, identities, communities, and futures.
The main work is student-facing, anchored by one standard: AI should deepen student thinking, not replace it. Using the 5 E model, participants design AI-integrated CS lessons and projects where students explore AI concepts, evaluate AI outputs, question bias and data, use AI tools responsibly, and apply computational thinking to problems that matter to them. The session also makes room for a secondary move: how teachers can use AI as a planning assistant to brainstorm, differentiate, and strengthen their lessons, without letting it replace their instructional expertise. In both cases, AI stays a tool inside sound instruction rather than a gimmick bolted on top.
The session includes sample AI lesson structures, culturally responsive planning questions, and classroom activities built around prompt development, code review, bias analysis, data conversations, digital citizenship, and human-centered design. Participants will also work through the real responsibilities of AI integration: privacy, bias, hallucinations, academic integrity, accessibility, and student agency.
Throughout, participants use a guided planning template to draft or redesign an AI-integrated CS lesson. They will name the lesson goal, relevant standard, student task, AI tool or concept, cultural connection, instructional strategy, assessment approach, and ethical considerations, with time built in to collaborate, give and receive feedback, and refine.
Participants leave with a draft lesson or project plan ready to adapt to their own classroom. The goal is to move educators from "AI matters" to "I know exactly how to teach this responsibly, meaningfully, and sustainably."
