Cat 0:00

I held myself back from saying,"I'm not your mom," though. I'm not your mom, you figure it out.

Ashley 0:04

You figure out when you're overdoing it.

Cat 0:06

You can be hard on yourself if you want. There's this really fun stuff in psychology about why people give up on their goals, and how so many people set a goal, and one of the reasons you give up on goals is because they are under-articulated. Just like the illusion of explanatory depth, the theme of this episode is your mind likes heuristics.

Ashley 0:36

So I feel like we've talked about metacognition multiple times on this podcast because as it turns out, it is maybe the biggest tool you can have in your toolbox in terms of how to learn new things. And Cat gave some thought to this recently. You gave a presentation to a company about things they've maybe misunderstood or have mislearned about the learning process itself. So what we wanted to share with you today was some of those insights and really tackle this question of how do you learn new things as an adult, right? As a, as a fully formed human being, how do we learn things out in the world? How do we become experts, even more specifically? Yeah. I think one

Cat 1:18

I think, I like to think of it as getting better at your strategies of, like, quickly gaining expertise and evaluating how it's all going. These are misconceptions that all of us have, and, and they happen for really interesting reasons because we're kind of operating, uh, you know, when we think about whether we're learning or not, we're usually using a lot of surface-level cues. Like, does something feel like it's coming easily to me? Do I feel like I can quickly access this information? But there's actually some really interesting paradoxical effects about learning, and once you start to track how well your strategies are working over time, you start to reveal these effects. I also really like this stuff because it is-- sort of shifts your perspective away from thinking,"Oh my gosh, am I good at this or bad at that?" And towards the realm that I really like in psychology, which is, how can I get the absolute most with whatever I was born with? And that's actually a big contribution of the field of metacognition. You know, if you want to explain a large percent of the variance in some of the achievement outcomes that happen for, you know, relatively similar levels of ability. So say everybody gets through, you know, school and they achieve a certain professional career path, there's sort of-- you've already selected a lot of people who have cleared some threshold of ability. So what is it that really starts to make the difference at those levels of performance? It starts to be these metacognitive strategies. And that is, like, a very robust finding, which is really fun and exciting because it's actually something we can do and change in our own lives.

Ashley 3:01

and change behavior. Yeah, I love that. And it was really fun looking through the slides that you used to give this talk, because as I was looking at them, I was realizing how much we've come to this topic from kind of two different angles, right? Like, I've gone through several different forms of, like, teacher training to learn how to be in front of a classroom and work with students and encourage learning. And you have come through the, you know, more of the lens of, like, skill-based learning for employees, and also you're a learning scientist, so you've thought about this in terms of psychology and, like, the rich research history behind that. So yeah, this was just, like, really fun to think about, and, and I'm excited that we get to share today some, some concrete things. Like, some concrete things that we really think anybody can do regardless of the thing you are trying to learn, uh, in, in your life. And I think that this will be really helpful for that. So should we dig in?

Cat 3:55

No pressure. That was a, that was a meta lead in. Yeah. Okay. Let's dig in. There are these... I like to organize this, like there, there are a couple big misconceptions that people often have about how their learning works. So the first one is that when you're learning stuff in the world, your head is just this empty bucket that you fill up with content. So you're a little kid at school, your bucket is empty. You go to school, you fill it with the ABCs. You get older, you're filling on top of that, you're layering like how to read Shakespeare or whatever, reading"The Grapes of Wrath." You know, you get to college, you, you have another layer right on top of that, that's sort of the, the, you know, layer of whatever people do in, you know, freshman literature. And throughout your life, it's just this bucket, and maybe you forget stuff, and that's stuff falling out of the bucket. Um, and you wanna keep trying to cram as much stuff in the bucket as possible. Um, and when you are performing in the world, you are just sort of pulling content out of this bucket and projecting it on like a screen projector. Like,"Here it is. I'm playing back the thing I know." So that is your head is an empty bucket that you fill, is how I describe it.

Ashley 5:11

Yeah.

Cat 5:12

this come up for you?

Ashley 5:13

my bucket is filled with, like, 50 Cent lyrics and, like, kinda weird basketball tricks that, like, you know, I learned as a kid. Um, it's, it's a mix of motor learning and, and some cognitive learning.

Cat 5:24

Yeah. And you, you hear people say like,"I have wasted so much brain space on learning these lyrics. Why is that in here? There's no room for like the new stuff." From a neuroscience point of view, what's your take on that?

Ashley 5:36

brain space for these new things. Why is it weird? Certainly... Okay, so we're, we're gonna, we're gonna take apart the bucket analogy. But yeah, thinking about, like, the brain as a bucket that you just store things in that has a limited capacity is flawed, I think. Although it's not to say that there isn't a capacity, right? You only have so many neurons, and perhaps more importantly, you only have so much attention to give to any number of things at a given time. And so, you know, there are some limits we're working up against. But it's not as if the memory of a fact of, like, what's the capital of Kansas, for example. It's not like the memory of that fact takes up one bit in your brain, and then you're gonna have, like, all the other bits filled by other things. It's that that memory is represented in populations of neurons, and some of those neurons in that population are also serving other memories, so there's, there's overlap. This is, like, how biological memory works. So yeah, it's, it's not a bucket. We're not, like, just tossing things in the bucket. Like

Cat 6:44

It's like complex dynamic processes. Yeah. So from the learning science point of view, we would say this is mostly a myth. Like, thinking about your brain as this empty bucket that you fill is really not accurate to the complex patterns of learning, and we have a name for it. Um, actually, learning scientists call this the tape recorder myth. So this myth that you are like this blank tape recorder, you hit record, you know, and then when you're kind of regurgitating information, you just hit play, and it just plays it back. So there's a couple different, like, things involved there. Like, right, you just described that memory is actually a lot more complicated than playing it back out of nothing. But for a long time, that was how people conceived of it. They just thought accurate reproduction of what you experienced is what, you know, retrieving things from your memory is. Um, and actually, we've learned that retrieval is really generative, so you actually are kind of like reconstructing the world when you pull out your memories, right? And this is an interesting thing about learning because when you, like, sit down and take a test and retrieve information, like, you are kind of creating the mental model for the schema, the set of things you're-- the concept you're trying to learn. And there's actually a lot of ways in which forgetting enhances your learning. So this is one reason that, like, sitting down and testing yourself, even if you fail and you don't retrieve the information, can actually help you encode information, like, more deeply, um, as long as you kinda keep working at it. And this is also something that trips people up because they sort of think,"If I'm not successfully a- you know, answering the, the questions on the test, then I'm not learning." Um, and so they give up. They stop doing things like testing themselves.

Ashley 8:40

Yeah. Yeah.

Cat 8:41

It's a little niche, but...

Ashley 8:42

No, I think that's, that's helpful. I do-- I wanna go back to the bucket, and I, and I wanna ask, like, if it's not an empty bucket, what is it?

Cat 8:52

I think that it is, like, a really constructive process when you're encountering information in the world. So you're, like, sort of selectively encoding what you are getting exposed to in the world, right? Rather than, like, it's all just being passively happening to you. You-- Like, you mentioned attention. Like, you're choosing what you attend to and how you sort of bring it into your mind and how you're remembering it. And so this is actually something that if when you do a psychology study and you wanna talk about differences between experts and beginners, one thing we have some neat findings on is experts, you show them new information in their domain, they tend to immediately start encoding structural features about the thing that they're looking at. Whereas beginners are just, they don't know what to pay attention to. They're looking at surface features. They don't know how to organize those features. Experts are kind of pulling things into these mental maps and schemas where they have this sort of deeper concept knowledge. Beginners are just like,"I'm drowning in information,"

Ashley 9:57

Yeah. So when we, so when we talk about this, like in, in sort of pedagogical training, we talk about scaffolds. And, and I love that as a visual because, you know, I think that the thing you build as a learner throughout your life, maybe in specific fields, are scaffolds for those fields. And like, if it's computer science, you're building a scaffold of like how computers talk to each other or how different parts of code talk to each other, and like even like what the rules are about what that might be. And then when you learn new rules, you know kinda where to slot it onto the scaffold. And in biology, it's a little bit more about core concepts in terms of like,, okay, structure is a thing that, uh, restricts the function of biological systems as one rule that applies to various different examples of biological systems, right? Like, this is always true. Structure determines function to some degree. And I think like, yeah, I think this point about like you're not, you're not just encountering stuff in the world without those scaffolds. You are always walking into the room with things you believe about it. And this starts really early, right? This is like one of the reasons we probably rely so heavily on stereotypes, not only like in a human sense, but also in a way that we like categorize objects. Like, we have like an idea for what an object is, right? We come in with kind of like preconceived notions about what this can do, what it's for. Yeah, we have heuristics. Exactly. Exactly. And that those heuristics are scaffolding that we hang stuff on as we go about the lear- uh, the world and we learn things.

Cat 11:34

I mean, something truly exceptional about human learning is that we learn from a relatively tiny number of examples. And if you think about it from a species level, you know, point of view, like tiny human babies are exceptional learners. This is like one of the absolute defining characteristics of human cognition. And like we don't value it because we just take it for granted, and we don't realize how much it defines us. But if you think about the incredible array of things that a baby has to learn about their culture to communicate with other people, and they learn it from a very small number of examples, and they generalize and kind of test those examples. And this goes to kind of, there's people like Alison Gopnik who sort of put out this idea of like the child as scientist, and babies are kind of doing this like, you can think of it like they're doing hypothesis testing, and the most vital thing they have to hypothesis test is what does it mean to belong and be accepted and, you know, thrive and be safe in the community of other people. So we have a lot of stuff devoted to social cognition for a lot of people. So that means, you know, you think about a baby learning to interact with an iPad, which they can learn immediately without needing to know what computers are or what code is or all of this stuff, and yet they have this incredible facility to understand tools. And I love that, and I love to kind of suggest to people in tech that we can look at tool use as this thing that includes computers. Um, yeah. And so this is like a clue to how our learning is so interesting and how we are constantly trying to figure out what is the larger category that like this set of things belongs to. So it... You can bring that to your own practice in whatever domain you're trying to work in. And some ways that I suggest doing it are like, you know, try to think, what do I think is the mech- of this thing that I'm gonna work on? Say you're writing code. Can I predict the effect that's gonna happen if I implement this solution? And even if you have basically no idea, which is, which is gonna be the case a lot of the time when you're an early learner and it feels really uncomfortable, do it. Like write down a one-line prediction. Keep a notepad by your desk and do it, and see if it holds. And develop this habit of like what we call pre-testing yourself, where you force yourself to just push a little bit further than you actually understand and say,"Well, why, why do I think this is true?" Or,"Is this implementation a version of this other category?" Um, and starting to do that is really helpful practice for people.

Ashley 14:18

this pattern of like mental piece testing where you force yourself to just push a little bit further than you actually think you can. So w-why might I be doing that? Or is this simply my brain's version of this other- Yeah, yeah starting to do that? Yeah, and I love that because what you're doing is you're acknowledging the fact that you have ideas about how things work. Like you, you're able to make a prediction. You could be totally wrong, but you're coming into the room with stuff in your scaffold, and so you have the ability to make some prediction based on that. And, and I totally agree. I think it's a amazing strategy for learning and something I have my students do. Like, and I really, really try to underscore this with students, and I say like,"Look, you know, I'm gonna ultimately give you the answer, and you have the internet at your fingertips, so you can like go look it up." But like that's not the point. Like the point is you need to think about it first and try to predict what's gonna happen or what the answer might be, and I think that that's really, really important. And I think about it too from a neuroscience perspective because the brain fundamentally is a prediction machine. And so much of what we understand about the brain now, and the benefit of the prediction is that like what it allows you to do is it allows you to move quickly. Because if you're correct 95% of the time, you know, the, the, the cost of that 5% where, you know, it's a visual illusion that caught your visual predictions off and, you know, s-so maybe it

Cat 15:36

your brain wants you to survive a tiger attack, and the moments where it wasn't really a tiger, uh, it's, that's fine. That's fine if we make some mistakes, but we don't want to fail to predict the tiger.

Ashley 15:49

Yeah. Yeah, exactly. Like you see a stick in the grass, and you think it's a snake, but it's not, and that's fine. You know? We could deal with that. So like the brain is predictive. That's a really, really cool thing about it. And I think that like taking advantage of that and sort of tapping into that really intentionally actually is really engaging. Like it, it really means you're using your brain. You're using your brain for what it was built to do, which is like predict how things are gonna go in the world.

Cat 16:18

And your brain responds to the feedback. I mean, at, at the end of the day, s- I say the word learning like a bazillion times in my, in my life, and then sometimes I find myself just sort of like,"Wait, what is learning?" You know? It's like the capacity to take in feedback and change from it, you know? And take in information and change from it. And, and whether you're actually getting that information accurately is a big question. And, um, you know- There's a lot of implicit sort of things that you can try to bring to the explicit level. So I remember there was a concept inventory work that people had done about biology actually, and like what are the most common sort of those core concepts? Where do people learn really persistent, robust misconceptions? Um, I think one classic one is evolution, right? People have this difficulty understanding the way that randomness can be a part of a process that results in like very non-random things, right? And that's because selection pressure is not random. Like selection pressure in many ways is very systemic, but we have this randomness, uh, you know, in... You, you check me. I, I think it's random, right? Like a mutation randomness that then results in these kind of like over time adaptive things. This was a big struggle for humanity to wrap its heads around, right? And when-- It's funny because sometimes when you measure this stuff with students, you almost find like historical misconceptions, right? Like, yeah, 100 years ago we thought that, and this is also what pretty much every junior high school student has a misconception about because they're falling into the same h- heuristic way of thinking about it that's not quite accurate, you know?

Ashley 18:07

Mm-hmm. Yeah, there's some really good work about this with things like genetics and probability, and like, you know, people underestimate how genetically similar humans are, for example. Like, you know, and it's really interesting because we have these built-in ideas that from lots of systemic racism and other things that, like, we're really different from other humans. And actually, but like if you look genetically, we're extremely similar to other humans, right? And it's just a f- a handful of genes that change your skin color and things like that. So I think that you're totally right. These things are pervasive in a lot of different fields and, and for interesting reasons.

Cat 18:47

This makes me think of the cognitive biases where, you know, depending on how something is framed to you, like if you hear,"Oh, this thing detects 60% of the problems," you're like,"Amazing. Let's get it." And then if you hear,"Oh, this thing misses 40% of the problems," you're like,"Well, it's terrible." You know? The, um, the famous ground beef experiments I wanna say that they did with this where they framed it either as like this is 2% fat beef or like 98% lean beef or something like that. Um, I wanna say that's an example of this. Yeah. We're-- Again, we operate with these very efficient heuristics, but they can pile up on us and steer us wrong, and developing better meta- metacognition, I think it forces you to puncture some of those illusions.

Ashley 19:34

Mm, mm. Yeah, I love that. Let's

Cat 19:37

about a second illusion because this is the second big one that I often talk about with people, and it's the idea that The more you're learning, um, your learning is best measured by performance. So, you know, you are just gonna see performance go up, and you're gonna see learning go up, and they're gonna be a nice, perfect correlation, single line going up to the right.

Ashley 20:01

you learn and what your performance is? Mm-hmm. So if I continue to test myself and I continue to score better and better, why am I not learning? Why is that not evidence for learning? The

Cat 20:13

So it's evidence for a kind of learning, but it's not evidence for whether that learning will last and whether that learning is particularly good retention. So to, again, break it down into, like, this is actually a lot more complicated, there are conditions that raise your short-term performance and depress your long-term performance, and vice versa, there are conditions that actually depress your short-term performance, force you to make a lot more errors, but in the long term, we measure far better lasting retrieval. So one of the things that learning scientists really care about is they're kinda like,"All right. Whatever your performance in the moment, sure." Like, everybody has pretty amazing memory for, like, the lecture they just went to, but what we care about are things like long-term encoding of information. Can you transfer it to other domains? So transfer of learning is also a big problem that doesn't often happen, and this is something that's very interesting. Like, you can be quite good at a set of things in a certain domain and just not have really figured out how to transfer it to another domain. And so folks who become very expert are usually really good at this sort of transfer. So let me give you, like, a really tangible example. I probably talked about this on the pod before, but cramming, like cramming for a test, exposing yourself to tons of information, binging on a coding session, deep dive YouTube video land, I'm up all night, you know, learning something. you will learn some stuff from that, but it will not lead to the same kind of lasting retention and performance as you often wanna have.

Ashley 22:02

So

Cat 22:02

like, enjoy your YouTube binges, but if you want to do serious skill building,

Ashley 22:08

building. You

Cat 22:09

often actually want to be spacing out when you're getting exposed to information. And I think this kind of pulls to some of the biological threshold and, like, ceilings that you're talking about, you know, where we have certain limits about our attention, about how efficiently we're encoding information, and it's really interesting. Like, a cl- this classic example is that students will cram for a test the next day. They'll stay up all night and do it. They will perform pretty well on that test, but you follow those students over time and ask them a month later, they retain almost none of that information So it can actually be, in fact, this really negative relationship between short-term performance and long-term performance. In my, in my book, um, about software teams, I call this the brittle productivity trap, because there are a lot of things that look like they are paying off in the short term that actually decrease our chances of getting the long-term performance. And it's so scary to commit to that. It's so hard to believe it, but, like, over and over and over again, we measure this. If you take a three-month look at people or a six-month look at people, it is really different than if you look at them for only one day or one session.

Ashley 23:23

So the question this raises for me is how to incentivize this kind of long-term, more productive learning process for students, right? I think this is a little bit of an easier sell for, for professionals who know that, you know, if the thing you wanna do is be able to, like, I don't know, make ceramics or something, right? Then maybe you need to, like, watch some YouTube videos, go try it, watch some more videos, kinda like over time, like, we have an understanding of this, right? But for my students, I don't know. This-- Most of them are just trying to get through their midterms, and so they're cramming and

Cat 23:55

students... I have two challenges to that. Do you think students don't wanna learn things for the sake of learning? And do you think that professionals don't have short-term performance pressures?

Ashley 24:06

two

Cat 24:06

Because they sure do.

Ashley 24:09

Have you noticed students don't remember things from the past? And do you think that professionals- Um make sure they do? Yes, of course, they do. So absolutely. Um, for the question about students, I think that it is a privilege to want to learn and have the space to learn, um, that many students either don't have or don't feel that they have or haven't set themselves up for that, right? Like, they're taking as many classes as they can. They're like, you know, maybe setting themselves up for situations where like they are cramming last minute, um, because... And also because you get rewarded, right? Like, if you are the kind of person who can cram and can do well on the exam the next day, you get rewarded for that. There's no--

Cat 24:50

Uh,

Ashley 24:50

Seemingly, there's no downside to having forgotten in a year from now.

Cat 24:54

I could describe the exact same thing for professionals. They are under constant short-term performance evaluation, sometimes e-incredibly explicitly. Whole organizations will say,"All that matters is hitting our OKRs right now." You know, all that matters that, you know, we have systems that don't always check what the long-term degradation costs are. But I would argue that the long-term degradation costs are visible once you look. And that happens for you as an individual because you will achieve less. It's very measurable. I wouldn't be saying that these effects matter if we hadn't tested them on the long-term performance scale.

Ashley 25:32

term. Hmm.

Cat 25:33

performance is still in the equation.

Ashley 25:35

because- Hmm. Performance is really the- Yeah, yeah.

Cat 25:36

other, the other, like, argument from, and I talk about this too in my book, I have this chapter in my book called"The Performance Paradox," which is basically about how we can try to navigate these tensions.

Ashley 25:47

about how we

Cat 25:48

And one thing that defaulting to these short-term strategies does is it burns you out, and so you start to avoid moments where you think you can't demonstrate your performance to other people. And so you take on less challenge, you take on less performance, and you become a lower achieving person.

Ashley 26:06

who are just- Mm-hmm.

Cat 26:07

Paradoxically, because you've committed, you say,"Oh, I really, all that I care about is..." If you say all that you care about is performance, it will lead you down this path of becoming what we call performance avoidance, um, oriented. And that is a devastating trap for a lot of people. Like, think about the high-achieving high schooler who got all A's and was like,"I'm gonna be perfect," and they hit college, and somewhere in the middle of college, the bottom drops out of their motivation, and they're like,"Where did it go? I don't even know," right? Like, a lot of people have had this. If you don't fill your little Sims needs meters, the system does break. So, and I, I would say we could say this is true on the level of organizations and, and the function of products in the world too, but...

Ashley 26:53

all professions, professionals Yeah. Well, I, yeah, totally take your point about professionals. That makes, that makes total sense. I think it, It makes me wonder if the thing you need to put in front of people is more long-term metrics, right? Like, and more feedback on whether or not over the long term they've achieved and not just these, like, short-term,

Cat 27:12

have to do that. You

Ashley 27:13

you say? OKR? I don't even know what that is. Oh,

Cat 27:17

Oh, bless. I don't even wanna tell you

Ashley 27:19

Such an academic.

Cat 27:20

why should you have to know? It's, um, uh, it's, uh, objectives and key results, and it's the, it's, like, organizational goal setting. So let's talk about... I,'cause I actually think there are ways to bring your attention to whether you're measuring these more sustainable problem-solving patterns. And I bet, that it's probably a lot of the stuff that you do think about in teaching. Like, if you are doing project-based work and you're getting rewarded for the effort that you put into things, not just summarizing the right answer in a multiple choice question. We have these more complex ways we can look at behavior, and I think that is metacognition nurturing. Like, it, it makes you think about the process you're using. Um, active learning as kind of a movement in education, a lot of it is about trying to reward people for the way they are thinking and the way they are trying. Um, I think forms of measurement that sort of take into account where you started from, so if you are someone who has a significantly different entry point, like you've never coded before, whatever, and you get rewarded for the amount of, gain that you made relative to your starting point, which we can do in more complex psych, you know, psychometrics, we can do this in more complex testing. Um, you know, that's a really good way to do it. Um, I think that,

Ashley 28:46

I think that in,

Cat 28:47

the workplace, I see this too when teams really start to understand and value the people who are driving forward, shared knowledge. Our tech lead, for instance, was really concerned about making sure that the innovation we came up with on one team actually transferred to another team and got, you know, we had this innovation in one part of the code base that got, moved to another part of the code base because somebody thought critically about, how to get those two components to take advantage of each other. You know, there are, like, organizations that you know, I've talked to and I think there's a much better metacognitive ecosystem happening in this organization, and the reason it's happening is because people are paying attention to these long-term effects.

Ashley 29:34

Yeah. Yeah. So I hear you saying two things. Like, one is, like, you have to be testing yourself, and that's kind of, like, where the active learning idea comes in. And this actually relates to a conversation I had with a student this past week who hadn't done as well on, their first quiz and was kind of asking me, like,"Uh, I don't understand. Like, I, I watched the lectures, and then I sat down for the quiz, and I was overwhelmed immediately. I couldn't do anything." And yeah, like,"I thought I got it, but the problem is..." And they had done the homework assignments and everything, but they hadn't actually tested themselves in, in any way. They hadn't considered edge cases, right? And especially for something like programming, this is my programming class, you know, it's not gonna suffice that you understand what we've already done. You need to actually know that you understand the rules, and the only way to know that you understand the rules is to test the rules against a million other cases and in different situations. And that was really

Cat 30:31

people. It doesn't have to be a million. It doesn't have to be a million.

Ashley 30:34

Well, no, no, sorry. But, like, you know, a good, healthy set of

Cat 30:38

Yeah. Yeah! Right. We have a name for this. We call this the illusion of explanatory depth, and this is a learning illusion, and it is this situation where you think that you understand a complex system more than you do. And I think it's really, really classic in programming. Um, and one thing that's super interesting from a psychology point of view about the illusion of explanatory depth is we actually struggle with this specifically for mechanistic understanding, for, like, causal connections between things. So, um, again, what our cognition has optimized for being dropped in the world and, like, moving on heuristics might sometimes make it slow us down or trip us up when we are trying to deal with the, the level of complexity of the systems that we've built. So, you know, it is fixable, and I think that it's just really good to know you can have this illusion if you are not puncturing it. And so active learning practices will puncture this illusion, which is really, really cool. It's, like, a reason they work. So some of those, just to get specific, are like, do I understand boundary conditions? Do I understand... Am I noticing irregularities? Am I... Is there, like, grit in this little, this nice, fluent, beautiful thing that seems like it's working? Is there, like, an irregularity I need to pull out of my mind and test what, what it is? And then also another thing I give people advice to is, do is, like, think about interactions between components and, like, these three things: boundary conditions, irregularities, interactions between components. These all give us clues to when we have the wrong mental model. So testing will often reveal that, and that's probably what your student wasn't doing, right?

Ashley 32:29

Mm-hmm. Yeah. Yeah, and I feel like there's another thing I would add to the list here too, which is, like, asking what happens if, you know? Like, what happens if we do this thing and then that thing? Like, there's a little bit of experimentation that you have to do in large systems of cause and effect to understand whether something causes something else, right? You have to, like, do the things out of order or do something else, and I think that that kind of experimentation is really necessary to make sure you understand how the thing works.

Cat 32:58

I agree completely. And, you know, we're circling around this thing that I'm gonna name as well, which is the concept of deliberate practice. And if you Google, like, the psychology of expertise or how do I become an expert or what do psychologists say about learning, like, deliberate practice will probably be the top result because that is essentially the set of strategies we recommend. And doing deliberate practice was really famously, um, came out of some of the Ericsson work

Ashley 33:28

by Ericsson.

Cat 33:29

the 10,000 hours rule... Yeah. Which he always hated, so, like, Malcolm Gladwell, uh, made this 10,000 hours, um, sort of claim based on this original work from Ericsson. Um, and just so you can know, Ericsson hated that. He has his own book. Um, but

Ashley 33:48

himself didn't call it 10,000 hours?

Cat 33:51

didn't, propose that there was this magical rule about a threshold of a... And, and the idea kind of became as long as you put in these hours, it became the tape recorder

Ashley 34:01

myth again.

Cat 34:01

It was like it became as long as you put in these hours, you'll just get there magically, automatically, and that is not the case. Like, his work was all about how people on the path to expertise actually practice deliberately, and that a lot of practice was wasteful, and that you could really waste your time if it doesn't have these features. So features of deliberate practice are it's outside of your comfort zone, but it's not so far outside of your comfort zone that you're getting lost. So you have to be getting pretty immediate feedback.

Ashley 34:35

Not so far from You... have to be getting pretty immediate- It's

Cat 34:37

It's the zone of proximal development,

Ashley 34:39

proximity or something. Like, isn't there a... Thank you. I was like,"Oh, it's

Cat 34:42

Yeah, zone of proximal development is very related idea that, like, too much challenge, you're just lost. Too little challenge, you're not learning. Um, another characteristic he talks about is you are breaking skills down into their subcomponents, and you are kind of deliberately working on each one and building them up together into a whole skill. And this is why the feedback is important because you need to know if you've got that subcomponent or not. You're building on a house of sand. And I would add, like, an affective dimension to this. You know, men in psychology, they hate feelings, so they're always like, This is equations of motivation."

Ashley 35:20

And then

Cat 35:21

There's-- We have learned that emotions matter too, and, um, I think you have to be meaningfully rewarded. You have to be feeling, like, this quality of mastery that you have talked about and that it's, like, integrated with your sort of deeper goals as a lear- you know, and this is meaningful to you. And we just see over and over and over again, like- People can't go their whole lives with these brittle performance-focused... You can claim you're gonna do it, but, like, almost nobody adheres to that

Ashley 35:53

tools people feel You can

Cat 35:54

we like to be motivated and we like meaning, you know?

Ashley 35:57

Yeah. Yeah, and I feel like that really, like, brings us back to the, the second point you made earlier about measuring your own performance over time, and I think, being able to see that and feel the reward from that is really important, and it's really a way for you to build your own self-efficacy, not just around the thing you are learning, but also as a learner, right? That you actually can learn new things, and I think that that's really cool, and I think really important motivationally. Like, we don't...

Cat 36:27

Mm-hmm.

Ashley 36:29

demotivating to try and try and not feel like anything is working, and, you know, very few of us, are gonna, like, put ourselves through that. Um, but, you know, most of us want some feedback, and I mean, this must come up all the time in your work with organizations, right? Where, like, people aren't getting that kind of positive feedback, I would imagine. I just would venture, I guess.

Cat 36:53

You know what I think is funny is it's like we think we're getting feedback, and then if you really ask, you're like,"Are you really, really ever getting to talk about this thing you figured out today?" Or, like, on good teams and good cultures, this starts to happen naturally, sort of built in, where there are people who are really, like, mindful and aware of it maybe. But, you know, I've worked with so many organizations that essentially just do, have you hit these organizational criteria for performance? All they're ever doing is a performance conversation, and perhaps some managers in the organization have come to one of my talks and therefore are, like, trying to be a mentor and they're providing some feedback. But, you know, I think you can take some charge of it yourself. I tell people I, I think you can give yourself tools to assess what you don't know and also assess what you do know and have learned, which we can lose track of very easily. And we, we acclimate Almost immediately to what we can do, and a lot of us think that's, that doesn't mean anything anymore. It's not rewarding anymore because we're really not keeping track of what a beautiful gain it is. So I talk to people about things like, have you ever thought about keeping track of like the comprehension that you have built about this code base? Con- concept areas. If you're a visual person, put it on a whiteboard, put it on a corkboard, make a couple Post-it Notes. This does not have to be fancy. Just even sit down for 15 minutes and just give yourself this little bit of metacognitive hug

Ashley 38:33

with

Cat 38:34

and say,"Hey, I know this part really well, and I don't know that part really well, and maybe I can like go spelunking off into that part of the code base for like 10 minutes today, and then I can take a note of like a new concept that came up, and then I can learn about it." I, I'm not trying to be cheesy, but like these very small behavioral moves really add up for people and really do matter. And these like even like 15 minutes a day or something like that is really effective and can be very different from someone who doesn't ever put that knowledge work in.

Ashley 39:09

what's core? What do you really need to be doing? Hmm. It's like even the things that you do, that is really important. Yeah. So 15 minutes of assessing your own situation.

Cat 39:15

Right. Say at your, it's your active learning time. Maybe it's your lunch hour or something like that, you know. But I mean, when I was the VP of research at Pluralsight, we were really interested in who stuck with learning and who didn't because we had, hundreds of thousands of people on our platform And they were highly motivated, right? Like, if you ta- wanna talk about short-term incentives, these were people who really needed to financially change their lives, like to break into tech careers, right? These were people who understood that, who were like,"I'm trying to learn Python. I'm trying to learn to become a data analyst," you know? And even so, people give up. You'd see people engage with a class and drop out of it and give up. And some of the differences between the people who persisted were that they had the spacing. They weren't doing cramming. They were doing every Friday lunch hour. They were doing 10 minutes a day. They were doing like achievable chunks of deliberate practice. And you would also see that they weren't like flailing around in the content. Like, they were doing some planning and saying,"I'm ma- gonna make small choices that all fit together." And I thought it was a really cool example of deliberate practice, you know. And it makes every like moment of your effort more valuable if it's fitting in with other previous moments

Ashley 40:37

Yeah. I mean, I'm wondering if this kind of like intention setting and really taking time to check in can be good, not only for your motivation, but maybe also for your ability to then decide how to proceed, right? Like for example, to decide like whether you're gonna like spend the next hour troubleshooting, you know, some very specific technical problem, or if you're gonna like offload that or you're gonna like reach out to someone. You know, like does it help us plan our own work? Yeah.

Cat 41:11

You know, it helps us plan and, uh, I also think it helps us actually get out of planning mode and not waste, not constantly burn gas on having to make the decision again and again and again, which is a form of, a form of offloading that's really helpful. Um, so you actually want to sometimes think about this. We could do a whole other episode on goal achievement. But, um, I wrote a Claude skill, which is now my favorite way to try to provide help for people.

Ashley 41:41

decision. I think in business, that can go

Cat 41:45

called Learning Goal.

Ashley 41:46

far. Oh my God. I have

Cat 41:47

And

Ashley 41:48

I can't keep up with your Claude skills. Like it's like you're... Yeah.

Cat 41:52

I know, the overproduction is real. Um, so...

Ashley 41:57

I need, like a whole lesson on Cat's

Cat 42:00

Cat's Claude skills. Yeah, well, if you just do 10 or 15 minutes a day, you could...

Ashley 42:06

No, I don't think that would be enough. That's what I'm saying.

Cat 42:10

so there's this really fun stuff in psychology about why people give up on their goals, and how so many people set a goal, and one of the reasons you give up on goals is because they are under-articulated. So you think, just like the illusion of explanatory depth, the theme of this episode is your mind likes heuristics. Um, so you'll set a goal and you'll think,"All right, um, I'm gonna learn Rust," and you think that you have specified enough about that goal. It feels good. It feels mission-aligned. It's at this high... Like, our minds love to be at this big, high, grand future-thinking level. And then what you haven't done is actually articulate a plan for overcoming specific obstacles. And this, this seems so cheesy, but I swear it really works. We actually tested this intervention, um, at Pluralsight and saw people stick with their intentions to learn longer because of it. So I have written this psychology exercise into a Claude skill, so you, your Claude will force you to do it if you download this skill and use it. Um, and it's called the Mental Contrasting with Implementation Intentions. I'm so terrible, sorry. It's called

Ashley 43:25

Wait, can we make that, like, an acronym? Yeah, the other Men C- MC, the Missy?

Cat 43:28

The MCII is psychologists can't name stuff for shit. Um, so

Ashley 43:36

gotta be a better way to

Cat 43:38

I know. So what you do is you go through what they call mental contrasting. You visualize the outcome, you think about why it matters to you, and you're actually forcing your mind to get specific about it. So instead of just, oh, our minds kinda like to like jump out of the plane, just parachute out, like in free fall. Like, I'll learn Rust because that seems good. Ah. You know,

Ashley 44:03

out of

Cat 44:03

just like kind of... You really... Yeah. So the first thing you do is do mental contrasting. You visualize getting the outcome. You visualize why it will matter to you. When I know- when I'm a developer who knows Rust, I'll do this and this and this. You make it really concrete. Then you think about the obstacle. What is gonna prevent me from learning Rust? I'm gonna... And you really have to be specific. So it's like, I'm gonna do it on a Friday. I'm gonna, I'm gonna imagine that I'm sitting down on a Friday and I'm tired, and what's gonna happen? Like, what is my strategy? And then you make an if-then plan, right? So just like code, you can program your own little mind, and you create really specific if-then plans.

Ashley 44:46

program your own mind and create choices to see how you're gonna do

Cat 44:48

I was just gonna say, this works. Like, we have tested this in psychology interventions, and it really, really does work for people.

Ashley 44:57

in psychology research Okay. So, um, I want you to walk through this with me with a skill I would like to

Cat 45:01

Okay. All right.

Ashley 45:04

about,

Cat 45:05

my, let me open my skill so I have the...

Ashley 45:07

I guess I could do this with Claude, but, you know, it's, uh, let's not remove the human element. Um, so here we are. Uh, I bought a skateboard like six months ago, and I was like,"I'm gonna learn how to skateboard so I can get around campus." And, um, that, that failed because I didn't really have a plan. And, and I think I had a vision in my head of being, you know, maybe the cool professor who can get to class really quickly. And, um, it didn't happen. So, uh, so I'm making a second attempt at it this, this week. And I actually, um, I, I just earlier today, um, bought an electric skateboard for myself because I realized that, I realized that one significant barrier to my learning how to skateboard was the physical effort required.

Cat 45:53

Okay, okay, okay. Stop making the if-then plans already. But I had... This is br- this is brand-new information. I'm finding out about this live.

Ashley 46:01

to do is really look at

Cat 46:02

All right, so this is really good because the first thing you need to do is name the skill, and you wanna connect it to your real life. So instead of just learn to skateboard, it's learn to skateboard so I can look like a really cool, hot professor.

Ashley 46:15

start moving. So instead of just like just skateboard, it's more just like what's the goal? Yeah. I mean, like, like, okay, it's, it's really not about the looks. It's about getting around campus faster. Because I've been taking the trolley more, so I've been, I've been taking the trolley, but the trolley is like a mile from my office, a little more than m- more than a mile. And so, you know, that's like an extra 20 minutes of my commute. If I can get there in five minutes, that's beautiful, which I could do on a skateboard.

Cat 46:36

perfect. So one of the questions of the, this goal exercise is, is there a specific situation where this matters? And you just defined it. So can you put it in one sentence for me, like,"I want to learn to ride this skateboard because..."

Ashley 46:48

that you want to skateboard in? Just like so you can- Um, so that I can get from the trolley to my office in five minutes.

Cat 46:54

Okay. So now we're gonna come up with a SMART goal, um, to think about what success looks like. So do you remember SMART goals?

Ashley 47:04

What successes do you want to see from yourself when you reach

Cat 47:10

specific, measurable,

Ashley 47:13

like attainable... Uh, I forget what

Cat 47:15

achievable.

Ashley 47:17

is. Oh, specific, uh, measurable. A- wait, attainable feels like the same thing. Achievable.

Cat 47:22

Rele- relevant. Really cool.

Ashley 47:24

is R? Really cool. Relevant.

Cat 47:25

time-bound.

Ashley 47:27

Okay. Okay.

Cat 47:29

So, like, we just go... We haven't even gotten to the mental contrasting part, so let's go quickly over this. Come up with a SMART goal about your skateboarding.

Ashley 47:37

So it's more just like- S- um, specifically I, I... Wait, do you want me to do one for each one? Oh, no, a whole goal. No, is

Cat 47:45

a single thing you're going to learn, and then we'll make it a SMART... We'll make sure that it is specific, measurable,

Ashley 47:53

Okay. Well, can we just take what I said earlier? So, so I learn how to skateboard from the trolley, let's say safely skateboard from the trolley to my office.

Cat 48:02

Okay. So what is a specific thing you will actually be learning?

Ashley 48:07

So what I'm asking specifically is what

Cat 48:12

see how mental unpacking is

Ashley 48:14

without dying.

Cat 48:15

What are... Maybe it could be something like, I will learn to balance

Ashley 48:21

successful? Oh, okay. Okay. Well, I think there's a couple things. Yeah. Obviously, there's the, um, standing on the board successfully for this route, but then also I need to determine the best route that feels safe.

Cat 48:35

Okay. So I'm gonna, uh, move us along.

Ashley 48:40

Maybe

Cat 48:41

maybe success looks like, uh, you, you will know that you've achieved this goal when you can skateboard from the trolley stop to your

Ashley 48:50

to work. Mm-hmm.

Cat 48:51

It's measurable in that you won't fall when you do it.

Ashley 48:57

Yeah, I won't have something that I have to come home sheepishly and tell you about. Is this

Cat 49:00

Got it. Is this an achievable first milestone, or does it feel like we need to go smaller? Like,

Ashley 49:07

an

Cat 49:07

you do this in a month,

Ashley 49:10

a

Cat 49:10

to make it that you can skateboard

Ashley 49:14

Okay, so I think this is

Cat 49:15

feet without falling?

Ashley 49:17

this is a valid point. So there's a, there's an easier route, which is from my office to the class that I teach, which has a bike path the whole way. It's very smooth. I actually think this is probably a better first step.

Cat 49:29

I'm liking that. Okay, so let's make it more achievable. We've... And now, um, we already know this is obviously relevant. You're deeply passionate about this. Um, it's

Ashley 49:39

For, like, the past week, I've been deeply passionate.

Cat 49:42

it's related to your role-based identity. Um, just as a note, role-- if you, if you, um, define your goals as, like, should goals, like normative, like,"Oh, I should do this thing," that, those goals tend to lose relative to goals that are want goals. So like,"I want to do X." I... So if you can find a wants component to your should, that helps. Um, okay, so how are you gonna time bound it? What's the timeframe for this?

Ashley 50:11

One, own it. Two, nurture it.

Cat 50:13

Mm-hmm.

Ashley 50:13

Um, okay, so target time for this goal? The board arrives early next week. I think that in a week from then, I should have successfully boarded. Is this, uh, is that the verb? Skateboarded? Can I say boarded? Clearly, I also have some cultural learning to do around this as well. Um, gonna have to talk to some friends or students. Um, okay, yeah. Uh, yeah, in a week, I'll have done from my office to class on the nice bike path.

Cat 50:41

Beautiful. Okay, so we have our learning goal. Now, we're going to enter the realm of the MCII. The first step is to describe a situation where you could realistically face an obstacle along the way of pursuing the goal. So these could be internal, it could be like your reluctance to fall, it could be your motivation, it could be external, it could be time pressure, embarrassment, you know, would be maybe an internal one. Um, so let's imagine a real situation. So imagine it concretely. When would it happen? What time of day? What's happening? What does it feel like? And, um, has it ever happened in the past? Like, in the past, what's happened? Like, have you given up on this goal before?

Ashley 51:22

Yeah, I gave up on the goal because I had a bit of embarrassment because I, took the skateboard that I bought, which is, to be fair, quite small, tiny wheels, hard to ride. Um, but I took it to the parking lot near our house, and I tried it, and it didn't go well. I had, like, skateboarded in high school, and I thought,"Oh yeah, I'll be able to do this." And it, like, it was fine, but I didn't feel as secure as I wanted to feel in order to do this in front of other people, especially students and colleagues. Yeah, so it's like the

Cat 51:51

Hmm. So what's, like, the thought that comes up? If I do this and I fall in front of a student, what?

Ashley 51:57

I will look dumb.

Cat 52:00

Okay.

Ashley 52:01

I'll look like the professor who's trying too hard.

Cat 52:03

Hmm. Okay. So now we're gonna build our if-then plan. We've identified an obstacle to your learning, which is embarrassment, right? It's an internal obstacle. If this situation arises, then I will do what? You have to come up with a specific action

Ashley 52:20

my God. Um.

Cat 52:23

to keep you on the learning path. I'm not allowed to come up with it for you.

Ashley 52:29

I will just look at the student and say,"Get to class."

Cat 52:35

Okay.

Ashley 52:37

No, no. I, um, no, I'll get up and be like,"Oh, I'm just learning, and, um, I'm new to this."

Cat 52:45

Is there a thought that will-- that can accompany that?

Ashley 52:49

What I'll think? I'll think, um,"It's okay. You're, you're learning how to skateboard, and failure is okay."

Cat 52:58

Nice. So now we have an if-then plan for the moment that you're about to give up on this goal'cause you feel embarrassed. Now, y- actually in the exercise, you're supposed to work through several of these, but it will take us 20 years to do that.

Ashley 53:12

it's fine.

Cat 53:13

the last step is you're supposed to go back to your original goal. Think about what it's gonna feel like to be that professor who rides the skateboard, what, what you wanna do here, what you've learned about yourself. Does the goal still feel right? Does the learning goal need to be bigger or smaller? Is there a different first step along the way? Do we need to revisit or adjust the goal?

Ashley 53:38

Hmm. I mean, I think maybe the, the goals need to be a little more granular, you know? Like, some, some smaller steps. But I do think, like, the ultimate goal of being, like, you know, the professors breezing across campus, getting to their meetings, enjoying the nice, like, cool ocean air on their face as they get across the campus, that feels nice.

Cat 54:02

Okay. I have confidence you're gonna do this.

Ashley 54:05

We're gonna have to check back. Oh, my gosh. I can't believe that if we, if we keep this part, I don't know, man. This is, this is a lot. This is putting a really... Like, this is putting a stake in the ground that I don't know if I'm ready to defend.

Cat 54:21

About the fact that you're gonna ride a skateboard?

Ashley 54:23

Yeah.

Cat 54:25

I think it's you being vulnerable, and isn't that what being a good teacher is all about?

Ashley 54:31

I guess so. So, you know, I think this brings me to maybe the last thing that we wanted to talk about today a little bit, which is you know, this is, this is a sort of silly goal, but in a way it's, like, representative of something that, like, someone might back down from. You know, that's like just, a way to make my life a little more joyful, a little easier maybe, but, like, has some, some consequences, right? Like physical or emotional or otherwise, you know? And so I think there's, like, a question

Cat 55:03

can choose challenges

Ashley 55:05

how we choose challenges for ourselves and, like, when are we overdoing it, right? Like y- there's this, like, idea of friction maxing and,

Cat 55:15

Friction naturally exists. That's my term.

Ashley 55:18

That's not just your term. No, I've heard

Cat 55:21

Oh, is it? Okay.

Ashley 55:22

Yeah. No, it exists.

Cat 55:25

common internet word ending.

Ashley 55:27

Yes, yes, yes. Um, you know, and the idea that we should be putting ourselves up to challenges, but of course, there's, there's a way in which this goes too far and we reach burnout and I don't know, like how, how do we know what's the right level of challenge and how frequent and that sort of thing?

Cat 55:43

You know, people love to talk about the, Bjork and Bjork idea of, um, they're-- That's not a, that's not me re-repeating myself. They're both last name Bjork.

Ashley 55:53

And it's not the singer? It's, um, uh, these two learning

Cat 56:00

who do all this metacognition work, and they have this concept of desirable difficulties, which people just love to invoke right now. Absolutely, desirable difficulties are a good thing, they're, they're part of deliberate practice. As we said, you wanna be in that zone of proximal development. I was just reading a paper, and the title of it was"Undesirable Difficulties." And I thought that was great. Like, life is full of undesirable difficulties as well. And I think that friction is a signal, but friction is both a negative and a positive signal about learning, and it depends on what kind of friction, and it depends on what you get to do with it. And so I rarely think it's useful to just pluck out some feeling by itself and say,"Is it good or bad?" Like, is it good or bad to be sad? I mean, if you're sad all the time uncontrollably, that's depression, and we should probably help you. If you're sad because you lost a loved one, that's part of human life, and maybe even something you don't want to medicate away, you know? And these are very, very complex choices for everybody, so I, I don't have the answer to all of this. But

Ashley 57:19

about the answer to

Cat 57:19

to me, it's really, really clear that if we just remove all the context, we entirely lose the meaning of something.

Ashley 57:25

assume it's easy. Hmm.

Cat 57:26

So, you know, I think about where can, where is your friction allowed to go? And the further I've gotten in my life and the more privileged I've gotten in my life, the more my friction has been allowed to go towards, my effort has been allowed to go towards things that actually benefit me and are not just me pulling a bunch of weight in some system for somebody else. And I think that's something to aspire to, is like that your friction really is going towards you.

Ashley 57:57

Hmm. And that's- Hmm. Yeah, so what I hear you saying is like, be aware of the different sources of friction in your life and try to choose ones that feel meaningful to you or maybe towards your own growth and wellbeing.

Cat 58:10

There's the illusions of fluency in learning, and the same people who like to bring those ones up don't always bring up the other side, which is illusions of friction. So, we often end up with learners or people around us who take this cue that because things feel difficult, they're doing the right thing. And you can get really stuck in that. You can almost get kind of addicted to that, and it can feel very rewarding. And it can feel, especially if you live in a world that actually does measure, like, short-term friction I think about Silicon Valley grind culture, that's the perfect example. Does staying up all night actually help you do good work? No. Like, we know this.

Ashley 58:53

me? But Cat, how many startups have started in this way?

Cat 58:57

But it signals that you're willing to do that, and that's the most important message there.

Ashley 59:01

Yeah, totally. It wasn't actually the fact that you did it at night while you were really tired and eating pizza on the floor or whatever.

Cat 59:10

You know, and I think about things like the level of ef- human effort that the washing machine saved in the world was amazing and is a beautiful thing. And, you know, we can, like, honor and value the women in our families who used to wash everybody's clothes

Ashley 59:28

situations.

Cat 59:35

or not, but

Ashley 59:36

Hmm.

Cat 59:37

I think come up with an outcome and test it.