That Neuroscience Guy - Neuroscience in Education Part 2- Measuring Learning with Dr. Kent Hecker

Episode Date: July 23, 2024

In this week's episode of That Neuroscience Guy, we welcome guest speaker Dr. Kent Hecker - a professor in Neuroscience at the University of Calgary. We discuss how neuroscience gives insight into how we learn and how we can better measure if someone is learning. 

Hi, my name is Ola Kirk-Olson, and I'm a neuroscientist at the University of Victoria. And in my spare time, I'm that neuroscience guy. Welcome to the podcast. Today, we're diving back into the field of neuroeducation, the role of neuroscience and education. And as a part of that, we're going to be talking to someone I've known that since I was five years old, Dr. Kent Hecker from the university of Calgary. Kent, welcome to the podcast.

Hi, well, thanks for having me. Hey, not a problem, man. I guess the question, like the reason we're having this conversation is, is literally the reason you and I reconnected, which is what is the role of neuroscience and education? And I guess we can start broad and then we can dial into specifics, but like why neuroscience and education? Like what is neuroeducation? Well, I think, you know, it's an interesting question. And this really gets back to when we reconnected maybe 10 years ago or so, where we were and what my background is, is actually psychometric. So I'm really

interested in understanding the science of learning. And how we look at that how we measure that is usually through performance performance on a test,, whether on some type of performance metric that we're talking about is the application of neuroscience to really think about and investigate how teaching practices and educational interventions impact brain function and structure or more maybe to the point, do they impact brain function and structure? And can we actually measure those in order to understand how we can better implement our educational practices for the development of of competence or expertise in any number of different educational settings you know it's obviously i knew you were going to say something along those lines because we've been talking about this, as you said, for over 10 years. Like this is how I dove back into this.

Right. Like in the sense that I went to grad school, I was a high school teacher. I was teaching physics and I was teaching phys ed and I was coaching basketball. And I went back to school and there was this course about neuroscience and there was a little blurb about learning in the brain. And I went, well, hey, if I'm going to teach people or coach people, maybe this is something that I should know, right? But if we're being a bit specific, like, you know, what kind of changes are we looking at? Like, what is the expectation? Yeah, and actually, for me, that's a really interesting question.

A lot of people have proposed, based upon the basic neuroscience of learning the stuff that you've worked on, various different, whether if we're taking a look at EEG, various changes in that electrical activity as people go through a process, or even in the study that we use using functional magnetic resonance imaging, taking a look at novice expert differences in clinical decision making. differences in clinical decision-making. If we use the fMRI piece as an example, what we showed was obviously with novices, which is expected, I would think, and as I understood and read more about it, that there would be greater prefrontal cortex activity, which means greater cognitive abilities brought to bear by novices on those problems. What was really interesting is, again, within the fMRI studies, was that there were hemispheric differences associated with that.

And it really came down to the conversations with you and others and reading some of the work that's been done in the literature. It comes back to that idea that expertise is the result of the experiences that people had. And what we were observing in the brain, actually, with experts was that there was, that the experts were actually recalling their experiences and bringing those experiences to bear on those respective clinical problems. And more importantly, the difficult clinical problems. So there's a couple of different components that we have to look at, Ola, and this is where I leverage off your expertise and others' expertise is we have to be specific with what

we are asking within this idea of neuroeducation. I don't think we can necessarily go into it just going, what is occurring? There has to be some background theory that is being built off of the work that you and others have done. And then we have to be very mindful of the types of questions that we're asking and the interpretations of what we think we're seeing within the brain activity, whether through EEG or fMRI. So I think that's what you're trying to get at was just a couple of exemplars of some of the work that we've done in an applied space and some of the preliminary studies that we've performed over

the last few years. Well, yeah, obviously it's a bit of a loaded question because this is something that we researched together. I think one thing that people might be interested in, in something you hit on perfectly, is that we assume experts are better. And, you know, that makes sense. You know, the definition, you know, of the whole concept, I guess. But when you typically measure experts, you see less brain activity. So do you want to, can we just talk about that a little bit? And like we did in our study, right? The study we did together, but like novices have more brain activity, which is kind of like, like it's almost counterintuitive, right? Like if someone gets stronger physically you assume more strength

but when we talk about brain activity we actually see less brain activity in experts so can you just walk us through like the layman's version of what you think that is well again it's an interesting question i think it's the efficiency of expertise um where as as and there's been some really interesting studies that are out there that are either taking a look at as individuals gather experiences and perform within whatever realm they're working on, you're either seeing this optimization or reorganization of brain activity. And it really comes down to an efficiency component where people don't necessarily have to think as hard as they have had to when they first experienced whatever type of

learning situation, whatever type of, let's say, even within health professions, education, the work that I've been doing, those clinical experiences. There is that expertise piece, that efficiency piece, that experience piece that allows individuals to draw on these resources, which actually is reflected in a decrease in the activity, just what you were mentioning before. So in thinking through it, well, initially it sounds counterintuitive to begin with, but as we work through it and we realize that there really is an efficiency piece that we are actually observing. And that's ultimately what we want our students to gather, to garner, to emulate, if you will, with those expertise. And so the interesting piece is, if there is a difference,

and we've observed some of those differences in terms of efficiency, what's actually the educational intervention that will allow individuals to become and to demonstrate those levels of expertise in the studies that we've been observing? Yeah, well, you nailed it. And that's kind of where I was. I was kind of leading you, but this idea of efficiency, right? Which is experts are more efficient, right? And I was actually, as you're talking about it,

in the back of my mind, I was thinking of like a professional athlete where they move more efficiently. So they actually use less overall energy, but that does equate to better performance, right? Because they're efficient. Well, again, these are leading questions because these are things that we talk about almost every day. But, you know, we did some work with a former student of yours

about anatomy, right? And learning anatomy and looking at what's going on in the brain. Can you tell us a bit about that? Yeah, and that's an interesting question. So Sarah Anderson, former PhD student who is now an instructor and faculty member here at University of Calgary, really had some interesting questions about learning anatomical structures. And again, it comes back to efficiency and process. And the idea really was building off of the work that you've done, taking a look at blobs. And this is actually all of where we got together again. And I read your paper on how you trained individuals to identify different blobs as they went through a process

by observing a diagram of responding either yes or no to the type of blob that was there. My question to you originally was, why is it blobs? Why couldn't it be an anatomical structure? Why couldn't we learn this within the context of, in this case, health professions education? So what Sarah did was really interesting. She took a look at whether or not, first of all, this reinforcement-based learning paradigm that you developed could actually be implemented and used in order to show a performance curve. So would individuals actually begin to recognize these structures more efficiently, effectively, and more consistently over time, which they do based upon the way that the experiment has been set up, which is fascinating. And what she went on to further do in her original studies was to take a look at 2D versus three-dimension objects in terms of anatomical structures. And so she was actually able to show, using a neural signature,

the ability to recognize these anatomical structures. And more importantly, she showed that you were able to learn it through an interleaved process, meaning flipping back and forth, and that you could actually retain that information over time. So she brought individuals back into the lab over a period of time. And it was, we were able to show based upon the paradigm of what those individuals were exposed to, those individuals that were exposed to more of the interleaved process, meaning they were exposed to both two dimension and three dimension diagrams, pictures of the brain, they were able to recognize those anatomical structures. And we actually built on that a little bit too, to address another question that we had subsequently with her and a bunch of pathologists

in taking a look at recognition versus visual expertise. And in this latter study, what we were able to identify that you were also part of was that we actually took novices and experts and showed that while the recognition piece of the novices could mirror the experts over a time period what we observed was the expertise neural signature were significantly different over the entire piece so we were able to tease out some of the pieces that we were interested in, because a lot of the conversations you have, I have had, others have had is this recognition, actually equal expertise. And in that latter study, it actually appears, it appears that there's actually, they're separate, they're different. You need that years in practice,

you need that repetition in various different contexts in order to develop that expertise neural profile you know it i always well one of the things i always liked about the work you've done and we we've done together realistically is is just this application in a real world setting like a lot of the stuff that I did originally was theoretically sound, but it was a very artificial context, right? It was blobs or some other thing that you just learn about that you don't know anything about. But what Sarah did, you know, it made it real, right?

And I guess just for the people listening, just a reminder, like we're saying reinforcement learning. And, you know, if you are really technically, it's a operant conditioning. But we're really just talking about trial and error learning, right? Like, you know, like you try something, you find out if you're right or wrong. If you're right, guess what? You do it again. If you're wrong, you try something different. And that is how a big part of how we learn.

You know, you touched on something and it's kind of something we've never officially studied, but there's been a popular push that repetition is not a great idea in terms of learning, right? But I think both you and I as former basketball players know that repetition is a key part of the process. Can you just comment on that? Like, we need repetition and learning, right? I would argue that, yes, you definitely need repetition and learning. And again, you touched on that we're former basketball players. Well, in terms of a game situation, you never just go and play the game.

You break that game down into its component parts in terms of a game situation, you never just go and play the game. You break that game down into a good component parts in terms of practice. You build up and stack basically your abilities as you move through into a game like situation and eventually back into the game. So I would argue that repetition is very, very important. Now, repetition solely for expertise? No, and this gets back to the conversation we've had over the years and my questions is when, how best, where, and when can all of these pieces be studied,

looked at, and optimized in order for either the demonstration of expertise for game-like performance or appropriate decision-making within a clinical environment. So I will air my bias. I'm a big fan of that repetition, but it's got to be, I would argue,

guided and deliberate as you move through. And a big component that we've been talking about and that we're still trying to work on is where does that idea of feedback actually come in and what does feedback look like and how does that affect performance but also can that affect our changes within our brains as we take a look at these performance types of criteria that we're asking our participants to, to, uh, uh, to, to look at and to be part of. Well, yeah, yeah, I agree. Like, you know, I, uh, the, the idea of repetition obviously makes tons of sense and we obviously need feedback at the same time, which is, you know, at the end of the day, it's a key part of these studies that we run. I do think that's the interesting future study or studies or entire

program of research, which is when do you provide feedback, right? Like, like what is, like, we all know the basic principles. You need feedback. You shouldn't give feedback every trial. Feedback probably decreases with expertise or at least the need for feedback. But I'd like to think that that is something that we have to look at moving ahead, right? Which is this whole concept of when do we give feedback? Yeah, and just to echo off that, in all the work that we've been doing here at University of Calgary, and all of the performance metrics that we collect on people as they go through professional education programs, we continually talk about providing feedback, but we never really articulate what that looks like, how best to provide it. it and important like there there we we we believe we think it's an important component of it and yes i would argue that it is um but just just when how bare how best and where to provide feedback i think are are ripe for study and i think we can take a look at it through a number of different

measures not only behavioral but but neuroly as well. Well, I guess that's why we're working together. And I guess we may as well share it with the world. Tell me about the famous picture of you and I. You know, you share it at every conference and every presentation. You say it like it's a bad thing. So, yeah, the famous picture is of Olive and I, and I think we're about seven years of age. Hey, Olive. I'd say, well, I think I'm a

little bit younger than you. Not much, but a little bit. Oh yeah, a couple of months, but we're seven years of age in a kiddie pool, and it's you and I and my sister, of all things, because we hung out a fair bit when we were kids. I still have a picture of you and your dog at our beach too. And Sam and arm of all places. So I haven't pulled that one out yet, but, but maybe I'll put that one into a, uh, into a presentation at some point in time. Well, Kent said, thanks for being on the podcast. You know, like, uh, the listeners want to know about the neuroscience of everyday life and, you know, neuro education and neuroscience and learning to me is a part of everyday life.

So thanks for being on the podcast. Yeah, thanks for having me. And I look forward to the future conversations all of them doing all the research that we're doing. Well, I look forward to them as well, obviously. Don't forget, everyone, you can check us out at that neuroscience guy dot com. There's links to Etsy and Patreon, different ways to support us. Of course, you can find us on threads or X at that neuroscience guy. We really do want to know what you want to know about the neuroscience of everyday life.

So please send us ideas about what you want us to talk about. And of course, the podcast itself. Thank you so much for listening and thanks for the support. My name is Olaf Kerr-Golson and I'm that neuroscience guy. I'll see you soon for another episode of the podcast.