Speaker
Description
When AI can generate an answer in seconds, what should students still be learning? As generative AI reshapes education, teachers have an opportunity not to replace learning with technology, but to redesign learning for deeper thinking. By leveraging AI to support routine cognitive tasks, classroom time can be redirected toward the higher-order thinking that students need most.
This workshop introduces *the 3–3 AI-Bloom Framework*, a practical approach to integrating AI with Bloom's Taxonomy. Participants will first explore how AI can effectively support the first three levels of Bloom's Taxonomy—Remember, Understand, and Apply—through retrieval practice, concept explanations, worked examples, adaptive practice, and immediate feedback. Rather than treating AI-generated content as the end of learning, participants will discover how it can become the starting point for deeper thinking.
Building on this framework, participants will experience and design classroom activities that intentionally promote Analyze, Evaluate, and Create. Through practical lesson redesign, they will learn how to engage students in critiquing AI-generated responses, comparing multiple AI outputs, identifying misconceptions, defending ideas with evidence, refining AI prompts, and creating authentic products through collaborative problem-solving and project-based learning. These activities demonstrate how AI can shift classroom time away from routine tasks and toward richer discussion, deeper reasoning, and meaningful knowledge construction.
By the end of the workshop, participants will leave with the 3–3 AI-Bloom Framework and a collection of classroom-ready activities for deciding what AI should do—and what students must still do. Rather than replacing thinking, AI becomes a catalyst that frees teachers to design learning experiences where students think critically, creatively, and independently.
