Recap
Teaching with Purpose in the GenAI Era: Lessons from the Science of Learning
As generative AI continues to reshape higher education, educators face an important question: How can we use these tools to support meaningful learning without losing sight of the principles that make teaching effective?
In our recent webinar, Teaching with Purpose in the GenAI Era: Lessons from the Science of Learning, we welcomed Dr. Lew Ludwig, (Chair of Mathematics, Denison University; Co-Director, Consortium for Teaching and Learning), and Dr. Todd Zakrajsek,(Director, International Teaching and Learning Cooperative). Drawing from their book, The Science of Learning Meets AI, we explored how educators can use established learning science frameworks to guide thoughtful, purposeful AI integration.
Moderated by Alchemy’s Dr. Brett Christie, the session offered practical approaches to using AI to strengthen teaching and learning, rather than simply adopting technology for its own sake.
Key Takeaways
1. Start With Learning, Not Technology
One of the session’s central messages was that effective AI integration begins with understanding how students learn.
As Todd explained, completing a task isn’t necessarily the same as learning. Productive effort, critical thinking, and opportunities to work through challenges remain essential to developing understanding.
Rather than asking what AI can do, educators should consider how AI can support student learning. The goal is to reduce unnecessary barriers without removing the productive struggle that helps students grow.
2. Use Established Learning Frameworks to Guide AI Integration
AI may be new, but the principles of effective teaching are not.
Lew and Todd explored how educators can apply familiar instructional frameworks to strengthen their use of generative AI:
- Backward Design: Start with learning outcomes, then align assessments and instructional activities to those goals.
- Bloom’s Taxonomy: Support students as they progress from foundational knowledge toward application and higher-order thinking.
- Transparency in Learning and Teaching (TILT): Make assignment purpose, tasks, and success criteria clear to students.
- Universal Design for Learning (UDL): Identify and reduce barriers to create more accessible, inclusive learning experiences.
These frameworks provide a foundation for evaluating where AI can meaningfully improve course design and student learning.
3. Take an Incremental Approach With the ACE Model
Educators don’t need to redesign an entire course to begin integrating AI effectively.
Lew and Todd introduced their ACE Model, which offers three approaches to incorporating AI into teaching:
- Adapt: Use AI to improve an existing lesson, assignment, or instructional activity.
- Create: Develop new learning experiences or activities with AI support.
- Embed: Integrate AI directly into learning activities or ongoing instructional workflows.
The model encourages educators to start with what they’re already doing and identify opportunities for thoughtful improvement.
4. Small Changes Can Make a Meaningful Difference
Throughout the session, Lew and Todd shared practical examples of how AI can support educators, from reviewing assignments for clarity and alignment to identifying accessibility barriers and creating opportunities for individualized practice.
The discussion reinforced that meaningful innovation doesn’t always require a complete course redesign. Sometimes, the most valuable starting point is improving one assignment, refining one activity, or making instructions more accessible to students.
Moving Forward: Keep Learning at the Center
As AI tools continue to evolve, the science of learning offers educators a reliable foundation for making instructional decisions.
The key takeaway? Tools may change, but the principles behind how students learn remain essential.
A huge thank you to Dr. Lew Ludwig and Dr. Todd Zakrajsek for sharing their expertise, and to everyone who joined us and contributed their perspectives and experiences.
Want to explore these ideas further? Watch the full webinar recording to hear Lew and Todd’s examples, explore the ACE Model, and discover practical ways to apply learning science principles to AI-supported teaching.
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