At a conference earlier this year, one of my Learning and Development idols, JD Dillon, said something along the lines of, “In L&D, we are notoriously bad at defining our own terms.” When he said that to an auditorium of a hundred or so of us, I wanted desperately to shout, “Amen, brother!” but it didn’t seem like that kind of crowd.
I’ve explored in some previous posts what terms like “blended learning” mean to me and the journey to occupational enlightenment that came with it. And it will always be that – a journey and an evolution. But on the lips of everyone concerned with training and development today seems to be “adaptive learning”, which is quite a natural progression from the tenets of blended learning. So let’s be the change we wish to see and start with a definition.
Adaptive learning is a method of on-demand instruction that orchestrates artificial intelligence and sophisticated algorithms to present the next appropriate action, based on what it knows about each unique learner.
I chose my words carefully here (emphasis on the “artificial intelligence and sophisticated algorithms” part). It’s been encouraging to see some training in recent years dip its proverbial toes into this concept by presenting content in such a way that it appears to adapt – if you meet X criteria or select Y, we will show you Z. But this seems more like improved UX than “adaptive” learning. I purposefully use the word “orchestrates” in the definition of adaptive learning because it feels like just that <places nerd hat firmly on head>, a symphony of unique parts working in concert to produce something that just feels… right, natural, and <I should probably stop now> beautiful.
Training masterfully tailored to the individual.
Improvements in algorithms mean that adaptive learning not only allows for micro-refinements in the experience of acquiring new knowledge, but also in the way that concepts are re-introduced for retention, all while zeroing in on a learner’s “sweet spot,” so learners remain confident and engaged.
If you need further proof,
Adaptive learning levels the “gateway learning” playing field, freeing up instructors to focus on more complex concepts.
Adaptive learning’s strongest use case is within a blended learning model. When students are given the opportunity to learn foundational knowledge — or “gateway learning” — using adaptive learning modules before traditional instructor-led training, instructors no longer have to spent time getting less-experienced students up to speed. Everyone comes to class on an even playing field, which means instructors have more time to devote to learning tasks that humans do best — explaining complex concepts, mentoring, coaching, and motivating.
My initial foray with true adaptive learning was jarring at first. It asked me to rate myself, presented questions, and wanted to know how I felt about my answer before knowing if I’d selected the right one. I didn’t like the feeling of being tested before I even knew what was going on. It was backwards dangit and it rubbed me that way! But I’ve come to appreciate that that was exactly the point. The process of content followed by user input means you may be consuming content you never needed. With the paradigm flipped, the AI can work its magic much more efficiently, which means learners are on the path to mastery faster than ever before. And, not that anyone needed the reminder, but efficiency – good, inefficiency – bad.
Now that I’ve started writing content for adaptive learning and working with teams that do so, it’s changed the way I think about instructional design. I’m much more focused on the objective and less concerned with telling a (perhaps unnecessary) story to reach it. Again, the paradigm has shifted.
If you haven’t had the chance to explore adaptive learning, I certainly encourage you to. Read about it for yourself, sample some when you can, and most importantly, prepare to marvel at the difference it can make for your unique learning needs. If you’ve made it this far into the article, perhaps you’re willing to give it a try even right now. Which you can do for free here with some modules on Microsoft Project:
Play with it, flip it upside down, inside out, tell me (and the AI via the CHALLENGE US button) what you liked and hated. As always, I’d love to hear from you.
 The Equity Equation White Paper, McGraw-Hill 2019