Microlearning Under the Microscope
Of late, there's been a flurry of attention to the term 'microlearning'. You see it in magazine articles, conference talks, and of course vendor ads. And it has been portrayed as everything from the latest fad to the solution to all ills.
The real task is to first separate the wheat from the chaff. Just what is microlearning? And then, what are the possible solutions microlearning provides? Is there any 'there' there?
It turns out that the answer is complex, but the opportunities and applications are real. So let's go through the definitions, the opportunities, and the entailed design constraints.
The first potential answer is 'just in time' learning. And that's a great thing, but...that isn't what they really mean. Instead they mean something else. Something good, but it's not learning.
You've probably found a video on YouTube to assist you in something you needed to do. Maybe glue something together, or trouble shoot and or repair something. I did; I fixed my dryer. Here's the thing: I learned nothing. If the same thing went wrong, I'd have to see the video again. And that's ok! I don't need to learn it, I just needed to do it right. And the typical type of such support makes it unlikely that learning will occur. You may remember something about the adhesive, for instance, but that is not the way to bet.
And that's the mistake that many are making, they are confounding performance support with learning. And that may be good for marketing (would that it were not), but it's actually an important distinction. Because you design them differently!
Performance support is all about helping us succeed in the moment. It's about overcoming our cognitive limitations by putting information in the world. For example, checklists and lookup tables overcome our lack of good rote memory and scaffold it.
The design solution is about understanding the context, and finding the minimum information that will scaffold success. Minimal is important (what I call 'the least assistance principle'), additional info only gets in the way.
So, performance support is good. Making it available when and where necessary is great. And it's not learning, so it's not microlearning. I implore you to use it (er, well), as in many cases it is a better solution than a learning approach. You can call it what you will, but it's not legitimately microlearning.
The second notion of microlearning is learning that's chunked up and dribbled out. And again, this is a good thing! But I want to suggest it's not microlearning. This is a more complex story, so bear with me.
Think about some hobby, craft, or sport you're engaged in. How do you learn and improve? If you're like most of us, you participate in clubs, attend events, take some lessons maybe. However, most importantly, you practice.
What you do is engage, again and again, over time. And this is good. More importantly, it aligns with how our brains learn. At the neural level, what's happening is that you're reactivating patterns that represent the elements, and strengthening the links between the neurons that make the pattern. There's a catch, however. The links can only be strengthened so much in any one day before you literally need sleep.
The way learning really works is that you strengthen the links a little bit each time each day you practice. (This is why the 'event' model is broken.) It's what I call 'slow learning', but technically is termed "spaced learning". And it's good. But, it's not trivial, and that's the problem.
What people are suggesting in this approach is to break your content down into small chunks and distribute them a chunk a day or so. Which sounds good, but misses nuances. There's some likelihood that the content has 'degraded' since the last presentation, and you need to revisit a few times. And most microlearning models don't do this. It's all about taking your existing (ineffective) content and chunking it up. And that's better, but it is unlikely to achieve the learning goals you think are being achieved.
What you need to do to really make spaced learning work is a bit more complex. Here you have to figure out how complex the concept is, and how frequently needed, to make a determination of just how much development and practice is required. Then you need to break it down to the amount to deliver on a day, and how much repetition to build in along with elaboration to ensure that that learning gets developed to both be retained until needed and transfer to all appropriate situations (and no inappropriate ones). And it doesn’t have to be every day, but the degradation needs to be figured in. Simplistic approaches with simple formulas aren’t likely to capture the needed rigor. The 70:20:10 model should be considered here as well, looking at other ways to reactivate including coaching and stretch assignments.
So this form of microlearning is really 'spaced learning', and it's more than a trivial exercise on existing content. Done right, again, it's a good thing, but whether you consider it microlearning is a matter of definition.
Ok, I've been criticizing the most common and popular definitions of microlearning, so what do I think microlearning really is? It actually goes back to performance support, with a twist. Here you're supporting execution in the moment, but also working to ensure there's some learning going on as well. The goal is to develop someone's understanding while in the context. And this has some entailments, but also some advantages.
In formal learning, we typically recreate a learning context. We will run role-plays around interpersonal relations, or we will provide simulations of devices or environments (if we're doing it right). But if we have real contexts, couldn't we wrap learning around them?
What I suggest could and should be meant by microlearning is providing learning on top of an existing context. It can be minimal (read: micro), because there's already a context to leverage.
Which still isn't trivial. What do you need in the moment? I argue that you need conceptual models that explain why it is done this way. And, possibly, examples to support transfer. The context makes these meaningful.
So, to me, microlearning is contextualized just-in-time learning. One other thing...
Many of the pitches around microlearning argue that it's about mobile. And I disagree. Don't get me wrong, I'm a fan of mobile (heck, I wrote two books about mLearning). But microlearning isn't inherently mobile.
You can do contextualized performance support or learning at the desktop. You can wrap it around your software as much as around anything else. It's about supporting the task in the moment and/or developing the person over time. While doing performance support or microlearning makes a lot of sense, it's not inherent. Microlearning is about context, wherever that may be, and it can be browser- or app-based.
Performance support, spaced learning, or just-in-time learning are all great things. You can relabel whichever you wish as microlearning. However, they're not the same thing (they're not even all learning). You should be clear about what your needs are, and do the right match to the situation. Then do the right design for the need. So here's to supporting success!