On Learning – Part 1
Learning is not preparation for life; learning is life. — John Dewey
Making correct predictions in pursuit of a goal is a pretty good definition of “intelligence”. — Steven Pinker
Mistakes are, after all, the foundations of truth, and if a man does not know what a thing is, it is at least an increase in knowledge if he knows what it is not.— Carl Jung
Give me a fruitful error any time, full of seeds, bursting with its own corrections. You can keep your sterile truth for yourself. — Vilfredo Pareto
That which does not kill us makes us stronger. — Friedrich Nietzsche
I have a radical opinion about instructional design: I think it should start from a clear understanding—or at least, a clear theory—of how people learn. This didn’t seem radical to me when I first migrated from my original field of artificial intelligence into training and education, but I quickly discovered that when I nattered on about how learning works in instructional design sessions, people tended to look at me as though I had gone off on a tangent about metaphysics or something. The topic of how people learn just doesn’t come up much in mainstream instructional design, and when it does come up, it is usually indirectly, through rules of thumb like “people learn better when you help them relate your lesson to their experience.”
The main reason, I think, is that instructional design is often seen as a kind of trade, almost like, say, plumbing. No one expects plumbers to be whizzes at hydrostatics. Similarly, a lot of instructional designers seemingly prefer to be left alone to get on with their work without having to be responsible for messy theories of how the brain works.
The problem is that learning is not a solved problem in the sense that building construction is. Following standard practices in the construction industry gets you a building that works; following standard practices in instructional design often gets you a course that doesn’t. To do better, I believe that instructional designers need to develop a better understanding of how learning actually happens, and use this as a guide to produce better designs.
So in this column I want to do my part to to try to make that happen by giving my answer to the question, how do people learn?
I want to begin by considering an example. Because I think discussions like this often go wrong from the start due to a modern tendency to see learning as something that happens in a classroom—and also just for fun–I’ve decided to set my example in a time before formal education. So, for the sake of argument, imagine that you are a homo erectus living in the Indus river valley in, oh, say, about 500,000 BC. Let’s say that you are walking home from the fishing hole in the twilight when suddenly, in a blur of motion, a tiger leaps from the brush directly into your path.
There’s of course a good chance you won’t survive this encounter. In this case the removal of your possibly maladapted genetic strain from the gene pool may help your species adapt through natural selection. It’s cold comfort to you, but over time, as tigers take their toll, the surviving population will come to feature traits that are better adapted to a tiger-rich environment—being able to run fast, say, or being smart enough to avoid tiger-rich places and times.
But let’s be optimistic, and assume you escape. In this case, there is better news: rather than sacrificing yourself to help your species adapt, you will instead get the chance to adapt as an individual. You can’t suddenly get faster, of course, or grow claws or wings, or anything like that. But you will change your behavior. For example, it is more than likely that you won’t dawdle at the fishing hole in the evening any more. You may choose a different path home as well. And so on. This is learning.
The key to learning lies in your ability to remember your experience. You will remember the tiger episode for the rest of your life, and recall it at times when it may help you to make better decisions, like, perhaps, the next time the sun starts going down when you are at the fishing hole. As far as we know, if your brain is healthy, it records every episode that you experience, but only a fraction of those episodes seem to be remembered for the long term. A complete theory of what causes a particular episode to be retained in memory doesn’t exist, but two factors are known to have a big impact: surprise and emotion. Clearly, the tiger episode has plenty of both, which is why we can be certain that you will remember it.
I’ll return to the issue of why surprise matters in a bit, but for now let’s think about why emotion would matter. The best answer seems to be that the things that evoke emotions tend to be things that effect, or threaten to effect, our goals, either positively or negatively. Encountering a tiger generates a lot of emotion because it threatens the goal of self-preservation. It makes sense to remember episodes in which one of your goals was threatened, because those memories can help you identify situations you want to avoid in the future. Likewise, it makes sense to remember episodes in which a goal was furthered—say, for example, a time when you tried a new fishing spot and caught an unusual number of fish—because those memories help you identify situations that you want to recreate.
Now let’s think in more detail about what happens when you remember a past episode. First of all, it is important to note that due to a remarkable property of your memory, you typically recall past situations that are very similar to the one in which you presently find yourself. This matters because—at the risk of stating a tautology—you can expect similar things to happen in similar situations. If you go fishing, it makes sense to expect that it will be like the last time you went fishing; if you are headed down a particular trail it makes sense to expect it to be like the last time you walked down that trail; if you are talking to a particular person it makes sense to expect it to be like the last time you talked to that person; and so on. The notion that you are constantly recalling the last time you did something similar to what you are doing now seems obvious, but when you think about it, it is quite amazing that you are able to do this. Your memory for events is like a version of Google that actually works.
If you observe very young children you’ll notice that they apply expectations from past episodes in a very simple and literal way—they basically expect their second experience in a particular situation to be just like the first. This can create an occupational hazard for parents. When my daughter was young, for example, I used to cringe whenever someone gave her a treat—at the dentists office, say, or at an event at a store or restaurant—because I knew she would expect the same treat the next time, and be unhappy when it wasn’t forthcoming.
As people get older, however, they get more sophisticated about teasing apart the elements of a situation and hypothesizing their individual causes, and this complicates the picture somewhat. For example, if the last time you went fishing it was cold and there was ice on the river, you may be able to reason out that because it is warm this time, you should not expect ice. How exactly people do this sort of reasoning is a big open question—it’s the sort of thing I worked on when I was in artificial intelligence—but this shouldn’t obscure the essential fact that you remember past episodes and extract from them expectations about the present.
Expectations are useful because anticipating something that might happen allows you to take action to ensure that that thing either does or does not actually happen. If you remember that the last time you walked down a particular trail you slipped on a mossy rock, for example, that allows you to step more carefully this time, while if you remember that the last time you went picking strawberries you found some particularly juicy ones in one corner of the patch, you can be sure to go straight to that place the next time. This takes us back to where we started, with encounters with tigers being one of the more obvious sorts of things you might want to avoid.
To be continued…