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Biological evolution and human cognition are analogous information processing systems

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Juan Castro discusses why the mechanisms that govern biological evolution and human cognition are analogous, as both follow the same principles of natural information processing systems.

Image courtesy of interviewee. April 30, 2024

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This video video discusses the application of evolutionary theory principles to cognitive processes, particularly in learning and education. It begins by acknowledging the extensive research surrounding evolutionary theory and aims to draw analogies with less explored areas like cognitive and evolutionary psychology. The authors emphasize that their approach is not original, as even Charles Darwin suggested that cultural phenomena could undergo evolutionary processes.

The paper outlines five key principles that underpin both evolutionary development and cognitive learning:

1. **Randomness as Genesis Principle**: Learning often involves trial and error, where individuals explore various approaches randomly until they find one that works.
2. **Borrowing and Reorganizing Principle**: Learning can be more efficient when students observe and replicate methods from teachers or peers rather than struggling through problems independently.
3. **Narrow Limits of Change Principle**: The process of learning typically requires small, gradual changes rather than dramatic modifications, which could overwhelm limited working memory.
4. **Information Store Principle**: In cognition, long-term memory serves as the repository for acquired knowledge, much like the genome in biological evolution.
5. **Environmental Organizing and Linking Principle**: Learning is influenced by contextual cues from the environment, which help to retrieve and integrate information from long-term memory.

The authors argue that instructional methods should align with these principles, particularly emphasizing the value of explicit instruction over discovery learning for novice students. They suggest that teachers should be aware of their students' prior knowledge to facilitate learning effectively. Overall, the paper promotes a structured approach to education, leveraging principles of evolution to enhance cognitive understanding.

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We know that evolutionary theory, it's rich.

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So it has, it has been researched for about

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150 years or something like that, even more.

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So we wanted to, okay, let's, let's take this,

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this evolutionary theory, let's use this richness

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of information, and why don't we, we try to build analogies

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with other less research areas.

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For example, cognitive psychology, evolutionary psychology.

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So that was kind of the, the approach that we took

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to make this analogy.

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It's important to to mention

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that the analogy is not original for us.

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So we are not doing something original.

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By making this analogy.

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Even Darwin, Charles Darwin, the, the father

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of evolutionary theory, he also suggested that other

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phenomena such as learning culture also have this type of

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evolutionary process.

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So that something, it's invented if you, if if you,

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if you may, something is created, it's tried,

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and if it were works, it, it's prolonged in generations.

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And, and if it doesn't work, you have

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to try other approaches.

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So it's kind of random and then test.

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And then if it works, it goes, it reproduces

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for generations, for example.

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That that will be kind of, the,

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the basic idea of evolution.

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And in this paper, we want to take that idea of evolution,

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that processes, and see how in learning

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or in solving cognitive problems

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or solving problems with, with, with your mind, you kind

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of do similar, similar things.

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These five principles, they are shared.

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So in evolutionary biology, so systems, evolutionary,

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species, so species, biological species,

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they develop or they are created

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following these five principles.

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So we are making the point that also in cognition,

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when you're learning something new,

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you also follow these five principles.

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The, the tricky thing about this analogy is

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that evolution takes millions of years

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and learning takes seconds.

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So that's kind of tricky thing.

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So in this paper, our

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or original approach was to try to make it a little simpler.

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So the analogy I, I mentioned that was already, eh,

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eh, was already suggested by Darwin.

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But we want to make the point that, okay, let's, let's try

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to refine the analogy

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and let's try to use simpler examples

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to explain the analogy.

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So in this case, in in the paper, we are using bacteria,

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which is the simplest possible living organism.

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So let's have a look at what happens inside the bacteria,

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these genetic and evolutionary processes,

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and let's try to do analogies with what, what would be to

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Learn.

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So the first two principles are the randomness

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as genesis principle and the borrowing

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and reorganizing principle,

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and I'm going to describe them a little bit,

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but only considering the cognitive aspect, not, not

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as much the evolutionary

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because it gets a little more complicated.

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And, and basically our paper

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and our research is about education.

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So I'm going to focus more on education.

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So randomness as genesis principle means that, for example,

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when you're trying to solve a problem,

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maybe a teacher gave you a problem to solve.

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If you don't know anything about the problem, you'll have

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to, you, you have to, to see what's the goal stage,

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where, where do you want, want to go?

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So what's the final answer that you want to, to pursue?

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And then try to see how steps from there, how to approach.

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So in what stage are you now?

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How can you progress a little bit, then a little bit.

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And each of these steps is random.

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So you, you try an approach.

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If it doesn't work, you discard it, you try another one.

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So it's randomness.

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So it's ge generating these new steps, but it's random.

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You don't have much clue where to go in opposition.

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The borrowing and recognizing principle means

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that you see some, someone else doing the, these,

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these steps to solve things and you just copy them.

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So for example, a teacher, a competent peer, a student,

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a com, a better student than you

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or a older student, can model

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the steps, can show you the steps.

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They can give you a text with the instructions to, to,

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to do the steps to solve and to get into the solution.

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So this approach is much more effective.

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You, you copy what has already been done before.

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So maybe those experts were

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in the first stages doing themselves,

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they were doing this randomness,

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they eventually got the solution,

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and they, they give you the solution to you.

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You just copy that. So that's much easier, more effective.

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Narrow limits of change principle is the third principle.

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It means how these changes happen.

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So either you do it yourself

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or you see somebody, somebody else doing it.

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You try to do it, you try to learn for, for that.

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But that learning is usually, very,

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you don't learn a lot of information at the same time is

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usually very narrow.

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So the change has to be small and maybe,

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and in, in the, in the case of learning,

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when we talk about working memory, so

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that would be our processor in our mind that allow us

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to learn and process information.

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So our working memory is limited.

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So sometimes we can see this as a disadvantage. Okay?

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It's bad that we have such a limited working memory,

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so we can't learn a lot of information at the same time.

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But in, in the paper, we are also suggesting

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that this could be an advantage and it works for bacteria.

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So changing things little by little, not very broad changes.

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And also in working memory

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that you have a limited working memory

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that doesn't allow you to change a lot

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of things at the same time.

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It can be seen as a, a thing

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that slows you down when you're learning.

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But it's also in the, in the overall run, it's good,

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it's advantages because if you already know a lot

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of information, the new things that you need to learn,

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they, they cannot be too disruptive

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to what you already know.

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So for example, I don't know, you are learning about,

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some mathematical problem, how to solve that problem.

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It can't be something too radical that you have

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to discard all of everything

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that you already knew about mathematics before.

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You have to build on what you already have.

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So, so in that sense,

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having this limited working memory is a good thing.

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So the fourth principle is information store principle,

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and that's in, in biological systems is the genome.

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So where it's the information of, of your, of

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how you're going to build your houses, your different,

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different things that you need to, to, to survive

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as a species, as a biological species, in the case

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of learning or cognition is your long-term memory.

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So every, everything that you are learning

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that you're processing in your working memory,

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which is limited then goes into your long-term memory.

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And there you have it forever.

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And you can have a lot, a lot of information in,

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in long-term memory, and you can use it when you need it.

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So that's a, that's the,

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the main reason why these narrow limits of change.

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So everything that that goes into your long-term memory

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and it's going to be stored there permanently has to be

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added in small amount.

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You, you can't add a lot of new information.

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It's going to be detrimental, detrimental if the information

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that you already had allowed you to learn and to survive.

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So you, you don't want to disrupt with too many changes.

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Everything fifth and last principle

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or environmental organizing

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and linking principle, it means that you,

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you get cues from the environment.

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So the environment tells you what what's happening.

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So for example, a teacher that gives you, okay, solve this

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algae bright kick equation,

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and you, if you already know what you need to, to,

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to do there, you take

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that information from your long-term memory.

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So you have learned how to solve these type of problems.

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You take that information from long-term memory,

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you integrate it into your working memory and,

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and then you can solve the problem

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because you already learn how to solve similar problems.

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So you have that information stored

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via the information store principle

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before, for example, if,

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if we think about in instructional implications, we can,

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we can take that first two principles.

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So, and compare them so random

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as genesis principle versus borrowing

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and reorganizing principle.

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And as I already mentioned, doing this thing randomly trying

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to solve something randomly without knowing

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what direction to take, what to do.

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So it's kind of random that consume that takes a lot

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of time is very inefficient versus

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being given the instructions how

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to do things is much more effective.

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So this can apply to, to these kind

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of fights happening.

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These not, not fight, but these arguments

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or different opinions in education

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that are happening these days.

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Like a pendulum towards, okay, let's give a lot of

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information to students before they can do something.

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So that would be like explicit

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instruction, direct instruction.

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So a teacher or a knowledgeable student

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can teach the less knowledgeable students what

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to do, how to do it.

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So with a, a lot of detail.

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So very explicitly that would be one approach.

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And the other approach is, okay, let's leave these students.

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They can solve these things by themselves.

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Let's, let's make them work by themselves.

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Let's even, don't give them instructions.

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So they should be able to, to sort this out

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by themselves discussing.

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And usually that takes more time.

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So they have to discuss a lot, come to a, a,

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a solution maybe doesn't work, try another one.

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So that would be like the other poll would be like a more

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discovery learning or project based learning approach.

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And usually cognitive law theory and our research.

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And in this paper we also make this point that borrowing

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and reorganizing is much more effective.

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So you, you as a teacher should be given the,

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the exact instructions or recommendations

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or suggestions to your students what to do,

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and then they could try to do them.

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And if that works, maybe you, you start to give them less,

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guidance, less feedback.

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But at the beginning,

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especially if there are very novices in the procedures

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or the contents, you need to be there

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explicitly showing them what to do, how to do it.

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So this discovery learning approach, making them okay,

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you, you can solve it by yourself, doesn't work usually.

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And, and usually the, the research, when, when it's,

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experimental, when it controls all the variables, that type

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of research, so that the quality research that we like,

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usually that shows exactly that, that borrowing

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or organizing is much more efficient than

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randomness as genesis.

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So what that would be one instruction applications

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regarding the first two principles,

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if we consider the third principle, narrow limits of change

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and instructional implications, they are all related.

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So this is related to the previous one would be that you

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as a teacher shouldn't be giving a lot of new information

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to your students because they have a limited working memory.

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So they can't process many things

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happening at the same time.

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So for example, you, you shouldn't be giving them an

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animation with a lot

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of information going on at the same time

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or maybe don't talk about a very, complex concept

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or maybe part.

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So not the whole concept, but a part of the concept

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and then another part.

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So maybe split a, a very complex concept

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because they're go, especially if they are novices,

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they don't know anything about the task or the procedure

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or the content you want to teach them, they're going

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to be very limited in, in, in grasping these new things

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and trying to process them

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because they have a, a limited working memory.

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And then, yeah, yeah.

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And then the third,

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third instruction application, considering the last two.

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So information store principle and environmental organizing

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and linking principle would be that this, the,

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the limitations that we see in working memory when you are

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novice kind of disappear when you're an expert.

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Because when you integrate information in your long-term

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memory, that information is integrated and is restructured.

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That's the reorganizing bit of the borrowing

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and reorganizing principal.

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So when you get the information for the first time

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or you see a teacher modeling something to you, it gets

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through through to your long-term memory

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and you accommodate that

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with information that you knew before.

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So, so for example, I can show you something to you

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and I can show you the same thing to another student

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or another human being,

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and you are going to learn it differently

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because you're going to make sense of it

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with the previous information that you already have.

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And it's going to be different

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because you have different experiences, life experiences.

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So you have different long-term memories.

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So you structure that information as a schema.

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We call it schemas or chunks in long-term memory.

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And every schema is going to be different, less

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or more complex depending on what you already knew

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before about that, those type of schemas.

14:44.055 --> 14:48.905
So when you are giving, when you're giving a queue to, to

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what you need to do, if you already know that

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and you have stored in your long-term,

14:53.385 --> 14:57.125
in your long-term memory, you're going to do to attempt

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that task to solve it much more simpler, easily, faster.

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And without this problems of a narrow working memory,

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the working memory becomes kind of, limitless

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when you are dealing with instead of new information,

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what you are dealing with known information

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that you have already stored as schemas.

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So that's basic. So a basic instructional implications will

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be that teachers have to be very vigilant, very observant

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on how much their, the,

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their students already know about the topic.

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So if the, if the students know a lot of the topic,

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you can expect that they will do very well

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with the, with the task.

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And you don't need to worry much about these limits

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of working memory because they're going to be circumvented

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by these schemas that they have.

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But if they're very novices, you have

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to be much more vigilant of these narrow limits

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of change visible and consider

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that they can't process many things at the same time

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because it's all new for them.

00:00 - We know that evolutionary theory, it's rich. So it has, it has been researched for about 150 years or something like that, even more. So we wanted to, okay, let's, let's take this, this evolutionary theory, let's use this richness of information, and why don't we, we try to build analogies

00:21 - with other less research areas. For example, cognitive psychology, evolutionary psychology. So that was kind of the, the approach that we took to make this analogy. It's important to to mention that the analogy is not original for us. So we are not doing something original. By making this analogy. Even Darwin, Charles Darwin, the, the father of evolutionary theory, he also suggested that other

00:49 - phenomena such as learning culture also have this type of evolutionary process. So that something, it's invented if you, if if you, if you may, something is created, it's tried, and if it were works, it, it's prolonged in generations. And, and if it doesn't work, you have to try other approaches. So it's kind of random and then test. And then if it works, it goes, it reproduces for generations, for example.

01:20 - That that will be kind of, the, the basic idea of evolution. And in this paper, we want to take that idea of evolution, that processes, and see how in learning or in solving cognitive problems or solving problems with, with, with your mind, you kind of do similar, similar things. These five principles, they are shared. So in evolutionary biology, so systems, evolutionary, species, so species, biological species,

01:55 - they develop or they are created following these five principles. So we are making the point that also in cognition, when you're learning something new, you also follow these five principles. The, the tricky thing about this analogy is that evolution takes millions of years and learning takes seconds. So that's kind of tricky thing. So in this paper, our

02:19 - or original approach was to try to make it a little simpler. So the analogy I, I mentioned that was already, eh, eh, was already suggested by Darwin. But we want to make the point that, okay, let's, let's try to refine the analogy and let's try to use simpler examples to explain the analogy. So in this case, in in the paper, we are using bacteria, which is the simplest possible living organism. So let's have a look at what happens inside the bacteria,

02:52 - these genetic and evolutionary processes, and let's try to do analogies with what, what would be to Learn. So the first two principles are the randomness as genesis principle and the borrowing and reorganizing principle, and I'm going to describe them a little bit, but only considering the cognitive aspect, not, not as much the evolutionary because it gets a little more complicated.

03:17 - And, and basically our paper and our research is about education. So I'm going to focus more on education. So randomness as genesis principle means that, for example, when you're trying to solve a problem, maybe a teacher gave you a problem to solve. If you don't know anything about the problem, you'll have to, you, you have to, to see what's the goal stage, where, where do you want, want to go? So what's the final answer that you want to, to pursue?

03:46 - And then try to see how steps from there, how to approach. So in what stage are you now? How can you progress a little bit, then a little bit. And each of these steps is random. So you, you try an approach. If it doesn't work, you discard it, you try another one. So it's randomness. So it's ge generating these new steps, but it's random. You don't have much clue where to go in opposition. The borrowing and recognizing principle means

04:19 - that you see some, someone else doing the, these, these steps to solve things and you just copy them. So for example, a teacher, a competent peer, a student, a com, a better student than you or a older student, can model the steps, can show you the steps. They can give you a text with the instructions to, to, to do the steps to solve and to get into the solution. So this approach is much more effective. You, you copy what has already been done before.

04:54 - So maybe those experts were in the first stages doing themselves, they were doing this randomness, they eventually got the solution, and they, they give you the solution to you. You just copy that. So that's much easier, more effective. Narrow limits of change principle is the third principle. It means how these changes happen. So either you do it yourself or you see somebody, somebody else doing it.

05:20 - You try to do it, you try to learn for, for that. But that learning is usually, very, you don't learn a lot of information at the same time is usually very narrow. So the change has to be small and maybe, and in, in the, in the case of learning, when we talk about working memory, so that would be our processor in our mind that allow us to learn and process information. So our working memory is limited.

05:47 - So sometimes we can see this as a disadvantage. Okay? It's bad that we have such a limited working memory, so we can't learn a lot of information at the same time. But in, in the paper, we are also suggesting that this could be an advantage and it works for bacteria. So changing things little by little, not very broad changes. And also in working memory that you have a limited working memory that doesn't allow you to change a lot of things at the same time.

06:20 - It can be seen as a, a thing that slows you down when you're learning. But it's also in the, in the overall run, it's good, it's advantages because if you already know a lot of information, the new things that you need to learn, they, they cannot be too disruptive to what you already know. So for example, I don't know, you are learning about, some mathematical problem, how to solve that problem. It can't be something too radical that you have

06:54 - to discard all of everything that you already knew about mathematics before. You have to build on what you already have. So, so in that sense, having this limited working memory is a good thing. So the fourth principle is information store principle, and that's in, in biological systems is the genome. So where it's the information of, of your, of how you're going to build your houses, your different, different things that you need to, to, to survive

07:26 - as a species, as a biological species, in the case of learning or cognition is your long-term memory. So every, everything that you are learning that you're processing in your working memory, which is limited then goes into your long-term memory. And there you have it forever. And you can have a lot, a lot of information in, in long-term memory, and you can use it when you need it. So that's a, that's the, the main reason why these narrow limits of change.

07:55 - So everything that that goes into your long-term memory and it's going to be stored there permanently has to be added in small amount. You, you can't add a lot of new information. It's going to be detrimental, detrimental if the information that you already had allowed you to learn and to survive. So you, you don't want to disrupt with too many changes. Everything fifth and last principle or environmental organizing and linking principle, it means that you,

08:28 - you get cues from the environment. So the environment tells you what what's happening. So for example, a teacher that gives you, okay, solve this algae bright kick equation, and you, if you already know what you need to, to, to do there, you take that information from your long-term memory. So you have learned how to solve these type of problems. You take that information from long-term memory, you integrate it into your working memory and,

08:54 - and then you can solve the problem because you already learn how to solve similar problems. So you have that information stored via the information store principle before, for example, if, if we think about in instructional implications, we can, we can take that first two principles. So, and compare them so random as genesis principle versus borrowing and reorganizing principle.

09:19 - And as I already mentioned, doing this thing randomly trying to solve something randomly without knowing what direction to take, what to do. So it's kind of random that consume that takes a lot of time is very inefficient versus being given the instructions how to do things is much more effective. So this can apply to, to these kind of fights happening. These not, not fight, but these arguments

09:49 - or different opinions in education that are happening these days. Like a pendulum towards, okay, let's give a lot of information to students before they can do something. So that would be like explicit instruction, direct instruction. So a teacher or a knowledgeable student can teach the less knowledgeable students what to do, how to do it. So with a, a lot of detail.

10:19 - So very explicitly that would be one approach. And the other approach is, okay, let's leave these students. They can solve these things by themselves. Let's, let's make them work by themselves. Let's even, don't give them instructions. So they should be able to, to sort this out by themselves discussing. And usually that takes more time. So they have to discuss a lot, come to a, a, a solution maybe doesn't work, try another one.

10:49 - So that would be like the other poll would be like a more discovery learning or project based learning approach. And usually cognitive law theory and our research. And in this paper we also make this point that borrowing and reorganizing is much more effective. So you, you as a teacher should be given the, the exact instructions or recommendations or suggestions to your students what to do, and then they could try to do them. And if that works, maybe you, you start to give them less,

11:22 - guidance, less feedback. But at the beginning, especially if there are very novices in the procedures or the contents, you need to be there explicitly showing them what to do, how to do it. So this discovery learning approach, making them okay, you, you can solve it by yourself, doesn't work usually. And, and usually the, the research, when, when it's, experimental, when it controls all the variables, that type of research, so that the quality research that we like,

11:56 - usually that shows exactly that, that borrowing or organizing is much more efficient than randomness as genesis. So what that would be one instruction applications regarding the first two principles, if we consider the third principle, narrow limits of change and instructional implications, they are all related. So this is related to the previous one would be that you as a teacher shouldn't be giving a lot of new information to your students because they have a limited working memory.

12:28 - So they can't process many things happening at the same time. So for example, you, you shouldn't be giving them an animation with a lot of information going on at the same time or maybe don't talk about a very, complex concept or maybe part. So not the whole concept, but a part of the concept and then another part. So maybe split a, a very complex concept

12:54 - because they're go, especially if they are novices, they don't know anything about the task or the procedure or the content you want to teach them, they're going to be very limited in, in, in grasping these new things and trying to process them because they have a, a limited working memory. And then, yeah, yeah. And then the third, third instruction application, considering the last two. So information store principle and environmental organizing

13:24 - and linking principle would be that this, the, the limitations that we see in working memory when you are novice kind of disappear when you're an expert. Because when you integrate information in your long-term memory, that information is integrated and is restructured. That's the reorganizing bit of the borrowing and reorganizing principal. So when you get the information for the first time or you see a teacher modeling something to you, it gets through through to your long-term memory

13:56 - and you accommodate that with information that you knew before. So, so for example, I can show you something to you and I can show you the same thing to another student or another human being, and you are going to learn it differently because you're going to make sense of it with the previous information that you already have. And it's going to be different because you have different experiences, life experiences.

14:24 - So you have different long-term memories. So you structure that information as a schema. We call it schemas or chunks in long-term memory. And every schema is going to be different, less or more complex depending on what you already knew before about that, those type of schemas. So when you are giving, when you're giving a queue to, to what you need to do, if you already know that and you have stored in your long-term, in your long-term memory, you're going to do to attempt

14:57 - that task to solve it much more simpler, easily, faster. And without this problems of a narrow working memory, the working memory becomes kind of, limitless when you are dealing with instead of new information, what you are dealing with known information that you have already stored as schemas. So that's basic. So a basic instructional implications will be that teachers have to be very vigilant, very observant on how much their, the, their students already know about the topic.

15:34 - So if the, if the students know a lot of the topic, you can expect that they will do very well with the, with the task. And you don't need to worry much about these limits of working memory because they're going to be circumvented by these schemas that they have. But if they're very novices, you have to be much more vigilant of these narrow limits of change visible and consider that they can't process many things at the same time

16:03 - because it's all new for them.

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