By Clark Quinn

It’s easy to categorize. Our brains do it naturally, so whether we create 3 or 7 basic colors, we do lump things together. Red or blue; urban, suburban, or rural; the four horsemen. Similarly, we can try to categorize learning, but as in many cases, the answer isn’t really so simple. So here, I want to talk about the continuum from formal to informal.

First, of course, it helps to have a definition (so that we’ll have something to shoot holes in). I’ve said that informal learning is a situation where the learner doesn’t know the answer (just like formal learning), but in this case there’s no one to provide the answer. You create your best answer, and then test and iterate. Sort of like science!

Which makes sense to me (but then, it’s my definition). Yet, what about situations where the answer is known, but you don’t want to have to reveal what you’re up to by bringing in expertise? Or other situations where there’s a good general principle, but…not for this specific situation?

That’s a lot of learning design, by the way. That is, you have a good basis based upon learning science. However, your situation’s not quite the same: you’ve got your local context – problem complexity, frequency of occurrence, importance, and breadth of application – that doesn’t neatly fit the principle or needs adaptation. Thus, you’ll need to create your first best design, then test and iterate.

That’s the situation in many cases. Someone’s done something similar, and we’re looking to try it out. I don’t like the idea of ‘best practice’, which to me is just copying someone else’s solution. It’s unlikely to work owing to the new context! Instead, I like ‘best principles’, where you know (or determine) what the underlying abstraction or model is, and then contextualize that for the new situation.

Which leads us to the continuum. There are well-defined domains (often ones we’ve defined, e.g. mathematics). There are right answers and wrong answers. Then there are more ill-defined domains (c.f. leadership), where the right decision depends on many factors (e.g. folks may disagree). Someone will determine a good answer, post-hoc, but in the moment you make a best guess and see how it goes. Then it goes out to areas where we don’t have any principles.

I think it’s useful to consider Dave Snowden’s Cynefin framework here. He talks about four quadrants (and a center): the simple, where there’s a right answer; the complicated, where an expert can determine a good answer; the complex, where you work together to find an emergent answer; and the chaotic, where you do something to try to move it to one of the other quadrants. (The center, confusion, is kind of vague, to me.) This is a four part description instead of two, but to me it’s also really a continuum. Still, having those definitions make it easier except at the boundaries.

My simple point is that there’s a continuum from formal to informal. Yet, it’s all learning! Thus, what we know about learning applies. There are useful practices, such as sampling across the range, only varying one thing at a time, effective brainstorming, etc. There are also practices to avoid (e.g. not individual thought before sharing; not tapping into diversity, etc). Those who understand how we think, work, and learn have the advantage in both. I’ve argued before that L&D, who are supposed to be the ones who know this, should be involved in both. We can facilitate along the continuum, and we should.