S1E2: Rethinking Learning Goals in the AI Era

If AI can now complete our assignments, does AI change our learning goals? In this episode of the AI for Educators Design Lab podcast, Jennifer Maddrell, PhD, explores how AI not only makes assignments more vulnerable but also prompts a review of traditional learning goals. AI isn't just changing what students can produce. It's also revealing that some of our legacy learning goals were written for a time when recall and reproduction were the dominant aims and indicators of learning. Using her own literature review assignment as an example, Jennifer considers what students should learn when AI can quickly tackle many learning tasks. She walks through five design questions to help you audit whether your current learning goals are still relevant, sufficient, and aligned with what learners need in a world shaped by human-AI collaboration, and concludes with a preview of Episode 3 on AI literacy coming in April. Do your learning goals prioritize content coverage or cognitive capability? Does AI support or undermine the learning goal? Do your learning goals reflect what authentic, discipline-specific performance looks like when AI is available? Do your learning goals encourage metacognitive awareness? What is the best way to make learning visible? Check out our other free resources for educators: 🎙️Next Path Design Podcast Library: https://nextpathdesign.com/podcast 🔗 Design Brief Library as a podcast supplement: https://nextpathdesign.com/designbrief 📬 Next Path Insights Newsletter: https://nextpathdesign.com/newsletter 00:00 Welcome Back 00:25 Why Learning Goals Shift 2:21 Lit Review Wake Up Call 04:56 Five Design Questions 06:03 Coverage vs Capability 07:55 When AI Helps or Hurts 09:46 Authentic Practice Today 11:28 Metacognition with AI 14:14 Evidence Beyond Products 15:51 Wrap Up and Next Steps 17:49 Design Brief and Episode Three 18:54 Final Thoughts and Thanks