That Neuroscience Guy - The Neuroscience of Improving Learning

Episode Date: June 20, 2022

We have spent a lot of time discussing how we learn, and what happens in the brain when we do it. But we can also improve that learning! In today's episode of That Neuroscience Guy, we discuss the neuroscience behind different methods we know to improve our learning. 

Hi, my name is Olof Kregolsen, and I'm a neuroscientist at the University of Victoria. And in my spare time, I'm that neuroscience guy. Welcome to the podcast. Have you ever tried to learn something new? Like imagine you were learning to play the guitar or you were trying to learn a new language. On this podcast, I've told you a lot about what's going on in the brain when people learn. Hebbian learning, you know, learning through repetition and the changes that occur at that level when that's happening. Basically neurons that fire together,

wire together. And we've talked about dopamine and prediction errors and reinforcement learning. But one thing we haven't talked about is how can we improve learning? Now, if we want to learn more efficiently, what does neuroscience tell us about how we can improve learning? So on today's podcast, the neuroscience of improving learning. So we're going to talk about three things, and I'm going to talk about them separately. The first of which is the concepts of masked and distributed practice. Masked practice is essentially practicing something, say the guitar, for extended periods of time, many days in a row, or many hours on end. And distribution of practice basically means that you're going to space that out some more. So maybe you take some days off or you don't practice for four hours in a row, but you do two two-hour chunks. So let's just work through this with some examples.

In terms of mass practice, just going with what I've already said, you could imagine that you're learning to play the guitar and you decide you're going to practice every day of the week. So you're going to put in some time every single day. Now that's a mass practice schedule because you're practicing every single day. On a distributed practice schedule, you'd have some days off in between. You might practice Mondays, Wednesdays, Fridays, and Saturdays. So a distributed practice schedule between days means you're spacing things out. And a mass practice schedule means you're doing it every day. Now there's one thing I'm going to emphasize right here. Distributed practice does not mean less practice. Less is never more when it comes to learning. But it just means you're

spacing things out. Now, there's another way you can distribute practice as well. You can distribute practice, say, within a day. So imagine it's Thursday today, and I'm going to decide to learn to play the guitar, and I'm going to put in four hours of practice. Well, I could do one four-hour chunk, which would be mass practice, or I could do two two-hour practice sessions,, I could do one four-hour chunk, which would be mass practice, or I could do two two-hour practice sessions, or I could do four one-hour practice sessions. I guess I could even push it and do eight 30-minute practice sessions. So those are examples of distribution of practice. Now, one question that I'm sure is going to run through your minds is, how much distribution should I do?

Well, there's no right answer. It comes down to the individual, their experience, and the skill they're trying to learn. But if you ever find yourself practicing the same thing for hours on end, you're probably better to space it out. Now, the literature is pretty clear here. Distributed practice is better than mass practice. There is not a single study that I'm aware of, with maybe one exception I'll mention in a few minutes, that shows that distribution is worse than mass practice. But the question is in the brain. Why does it work? Why is distributing practice better for learning? Well, there's a couple of theories about this. The first is the concept of neural rest.

If you're doing something every single day or you're doing it for long periods of time within a single day, your brain just gets tired of doing the same thing over and over again. And by taking a little bit of time off, your brain can recover and is ready to try learning a little bit more. There's another possible explanation, which is the idea that distribution of practice promotes recall. If you are trying to do something and you haven't done it for a while, your brain is forced to recall from long-term memory to working memory what you're trying to do.

And that very active recall helps learning. So distribution promotes recall, which should enhance learning. And finally, a bit of research from my own lab, we've published a paper on this. We found that under a distributed practice schedule, we saw larger prediction errors. Remember with dopamine and reinforcement learning, we talked about this idea of expectancy and how expectancy drives learning. Well, we found that on a distributed practice schedule, we saw larger prediction errors, and we saw that in terms of a brainwave response.

So the science is pretty clear here. Distributed practice is better than mass practice, and there's reasons within the brain why it works. Now, that's number one. Here's number two, a different thing to consider when you're thinking about learning something new, the concepts of blocked versus random practice. Now, to understand blocked and random practice, you have to switch this up a bit and imagine you're learning two skills. Now, for the sake of

this, let's say the forehand and backhand in tennis, and those are two separate skills. So, you're learning a sport, tennis, but you're learning two skills, forehand and backhand. So you're learning a sport, tennis, but you're learning two skills, forehand and backhand. In a blocked practice example, you would learn the forehand or practice the forehand, say for 30 minutes, and then you would switch and practice the backhand for 30 minutes. So it's kind of similar to the idea of mass practice, but we call it blocked because it's within a session and we're talking about two or more skills. So blocked would be practicing the forehand for 30 minutes and then practicing the backhand for 30 minutes. In a random practice schedule, you would practice both skills within 60

minutes. So you might do the forehand on one repetition and the backhand in the next and the backhand on the next and the forehand on the next. And the name gives it away. The person learning the skill doesn't know what they're doing next. So this usually involves a coach or just playing in a game. Hence the name random practice. Now, you wouldn't want to use 60 minutes, of course, because the rules of distribution are still true. But you can have distributed random practice.

So you can put the two things together. Now, why does random practice work? And again, the behavioral research is clear. Random practice is better than blocked practice. So you're better to alternate between two skills, assuming you're learning two skills, than practicing one for a blocked period of time and the other for a blocked period of time. But what's going on in the brain? Well, the classic theory of this is contextual interference.

Basically, there's a memory trace for each of these two skills. All right, there's a memory trace for the forehand and there's a memory trace for the backhand. And what do we mean by memory trace? It's just the representation in memory. And these two traces basically overlap and compete with each other because they rely on some similar things. And that's what we mean by interference. The two memory traces are literally interfering with each other in contextual because they're both within the same context. Now, why that specifically enhances learning is still a matter of some debate, but the evidence is clear that random practice seems to be better than block practice. And again, it can come back to prediction errors.

Hate to promote my own lab, but more work by the K-Lab has demonstrated that you get larger prediction errors under a random practice schedule than you do under a block practice schedule, and larger prediction errors would be associated with greater learning. Now I'm going to say two things here. First, one weird point. If you do start trying random practice, the typical finding is that you're worse during practice. So you're going to miss more shots and things aren't going to go well. But when it comes to the game, you'll play better. So if you decide to try random practice and it doesn't go well for you, don't be too surprised. That's sort of a classic finding. So there's another thing here. There are a few studies that show that block practice is better than random

practice, but this is typically seen in younger age kids. So if you were teaching, say, tennis to a bunch of grade fours, you might want to start with a block practice schedule as opposed to diving right into random practice. But if you're working with a bunch of high school age kids, you might want to use random practice. And remember, that practice session won't look very pretty, but they'll end up playing better. So that's two. Now the third one I'm going to talk about is the concept of constant versus variable practice. So now you have to think about a single skill, let's say putting a golf ball. Constant practice within the example of putting a golf ball would mean that you practice a bunch of putts from the exact same distance. So you put

a bunch of balls 12 feet away from the hole and you just tap them all in one after the other. Variable practice would mean that on any given putt, you're putting from a new distance. So as opposed to putting your entire container of balls at one location, you might spread them all out over the green and just try putting from a bunch of different locations and a bunch of different distances. So constant is a bunch of repetitions of the same skill from the same distance or with the same criteria. And variable would mean from a bunch of different distances in different locations. And this can also work with time. So if you want to perform a skill at different speeds, constant would be trying at slow, then medium, then fast speeds, and variable would mean

alternating speeds between different repetitions. Now again, the behavioral evidence is pretty clear here. Variable practice is better than constant practice. But in the brain, why does it work? than constant practice. But in the brain, why does it work? Well, this involves the concept of schemas. Now, what's a schema? A schema is essentially what we call a lookup table in the brain. It's a memory of relationships between things. Let's say you want to kick a soccer ball a certain distance from yourself to a teammate. Well, you need to know how much force to apply to have the soccer ball move that distance. The schema is the relationship between force and distance. And for different distances, you need to apply different forces. So you learn this series of relationships. If I want to kick it a short distance, apply this much force. If I want to

kick it a long distance, apply this much force. And why is variable practice better then in terms of the brain? Well, variable practice enhances schemas because you're working the whole schema at different points in time. So as opposed to slowly developing the schema through constant practice, with variable practice, you alternate the schema on a trial-to-trial basis, which results in a stronger schema. Now, all of these things are continuums. There is no such thing really as true mass practice and true distributed practice. It's a continuum. Things fall in between. So you can distribute things more and more and more to the point where it'd be kind of silly if you think back to the start of the podcast with the guitar

example imagine you're going to spend an hour a day practicing guitar well you could do one 60 minute session you could do two 30 minute sessions you could do four 15 minute sessions or you could do 61 minute sessions at some time point it will fall apart because it's just ridiculous. It's going to take you more time to get your guitar out than you have assigned for practice. So you sort of have to work it and accept that it's a continuum. But in terms of distributed versus mass practice, you just got to ask yourself, well, could I break this up into two smaller practice sessions or more? In terms of block

versus random practice, again, it's a continuum. But how random is random? How much do you alternate the two skills? But again, if you find yourself learning two things that are very similar for an extended period of time, then you might want to break that up and alternate the skills at random. And finally, with constant versus variable practice, well, that one's pretty straightforward to assess. If you ever find yourself doing something from the same distance or in the same time criteria over and over and over again, you should probably try and break that up. Now, in some cases, in some sports, this doesn't work. For example, if you're going to shoot a free throw in basketball, well, the distance is always the same. So in that specific instance, maybe constant practice is okay. But if

you talk about shooting a basketball in general, then being variable and developing schemas is better than being constant. Now, I've been using a lot of motor examples here, but this is all true for cognitive skills. So imagine you're trying to learn a new language. Well, under a mass practice schedule, you would practice learning that language for, say, two hours a day. Under a distributed practice schedule, you would break that into four 30-minute chunks. So there are three ways that you can use neuroscience to improve learning. Embrace the concepts of distributed practice, random practice, and variable practice. keep saying this, but we want to know what you want to know about the neuroscience of everyday life. You can also email us, thatneuroscienceguy at gmail.com. There's the website, thatneuroscienceguy.com. We got t-shirts on our Etsy store. You can support us on Patreon. Remember, the money doesn't go to

me. It goes to grad students in the Craig Olson Lab. And finally, of course, thanks for listening to the podcast and please subscribe. My name's Olaf Krigolsen and I'm that neuroscience guy. Thanks so much for listening today and I'll see you on Wednesday for another neuroscience bite.