👉 In a controlled test, 27 Instructional Design postgrads at Carnegie Mellon created designs both with & without GPT-4 assistance. 👉 Every design was blind-scored on quality by expert instructors. 👉The result: Design with AI was not not just faster, but produced better quality designs in 100% of the cases. But the detail is where it gets interesting...👇 The research also revealed a "capability frontier"—a clear boundary between where AI helps Instructional Design quality most, and where it might actually compromise it. TLDR: 🚀 USE AI FOR: Designs which use well-established design methodologies, step-by-step processes & widely-discussed topics. ❌ BE MORE CAUTIOUS WHEN USING AI FOR: Designs on niche, novel & complex topics which use less well-established design methodologies. 💡Bonus insight: In line with broader research on the impact of AI on knowledge work, the research also suggests that novice Instructional Designers benefit *most* from AI design assistance (but only when we are strict on what sorts of tasks they use it for). To learn more about the research & what it tells us about how to work with AI in our day to day work, check out my latest blog post (link in comments). Happy innovating! Phil 👋

👉 In a research paper published 3 weeks ago, researchers propose that traditional models like as ADDIE & SAM have severe limitations which have made it difficult to create dynamic, relevant and ultimately high-impact learning. 👉 In its place, they propose a new model, "ADGIE" - a hybrid human + AI re-imagining of the process, with the goal of dramatically increasing the speed, agility & quality of instructional design. Here’s how it works: Analysis: AI analyses data like SME & learner interviews to create learner personas & concepts and skills maps; the Designer validates them. Design: The Designer curates content; AI structures it into a plan in line with the persona & concept & skills map. Generation: AI produces the first draft of learning materials; the Designer refines them. Individualisation: AI adapts learning paths for individuals; the Designer oversees the process. Evaluation: A continuous process where the Designer validates AI outputs and learner feedback improves the system. My take: ADGIE is more than just a new acronym—it’s one example of a practical, forward-looking framework that provides a language to talk about how the profession is changing and captures how Instructional Design is evolving in response to AI. Read more in my latest blog post (link in comments). Happy innovating! Phil 👋 | 28 comments on LinkedIn

After 20+ years of research in instructional design, I'm thrilled to announce Epiphany AI, which I've co-founded with Gianluca Mauro. Together, we're building the world's most powerful AI copilot for instructional design, combining deep pedagogical expertise with cutting-edge technology to transform how online, blended & in-person learning is designed. To learn more about our journey, follow us on LinkedIn at Epiphany AI & check out our website, where you can join the waitlist. Let's do this! Phil 🚀 https://lnkd.in/eH5MYvQW | 60 comments on LinkedIn

Most instructional designers are using AI for content creation & admin tasks - and missing out on AI's full potential. I've identified Six AI Use Case…

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It’s a question many in the industry have been thinking about – myself included. I recently read the…

In this week's blog post I share the findings from the second of three…

🚀 I conducted an experiment with over 200 instructional designers, and the results are in... In this… | 11 comments on LinkedIn