How to Learn Really Hard Subjects Easily

In this video, I'm going to teach you how to learn any hard concept intuitively and easily. It's a skill that I mastered in uni going through medical school, and it's something that I use constantly whether I'm learning about business or AI or learning science. As a result, instead of banging my head against a topic for 3 or 4 hours like I used to, I can now understand the same amount of content in less than one hour. I've taught this skill to thousands of students and professionals over the years and today I want to share it with you too so that you can spend less time on reading and researching and more time actually working towards your goals and solving problems. So I'm going to cover three main points in this video. The first thing is what makes a topic hard in the first place. I used to think that some topics are just difficult to learn for some people. That's not true. The second point is what actually happens in our brain when we're getting stuck on a difficult concept because that is the part that actually slows us down. And then finally, what can you do to get unstuck quickly when your brain is in that situation? This is the part that turns that hard topic into something that feels simple and easy to understand. So the first thing is what actually makes something hard or difficult to understand in the first place? Well, the easier way to understand this is to actually flip that and ask ourselves, what is it that makes something easy or intuitive to understand? And I think the simplest and most accurate definition is that something is intuitive when it fits a pattern that we're used to. So if I say that there's three ways of thinking about something before, during and after that should feel intuitive for us because we have an existing pattern of understanding how chronology can be divided into before, during, and after. If I throw this pen in the air, intuitively we understand that it's going to fall down because we have an existing pattern that we built up from when we were 2 years old throwing spaghetti on a wall. Uh that gravity is a thing. And this cause and effect relationship is something that we're familiar with. So we build up all of these different patterns both in early childhood and also through schooling that give us different ways of thinking about information. And these patterns of thinking are everywhere. Like when you do your mathematics and you're young learning your basic arithmetic that 1 plus 1 equals 2, 2 plus 2= 4, you kind of memorize all of those different patterns that allows you to have an intuitive way of thinking about arithmetic from that point on in your life. And intuitive doesn't necessarily mean that it has to be simple like 1 plus 1 equals 2. You can have a pattern form from really quite advanced specific knowledge. Like you can learn about the properties of a specific type of cell in the human body that behaves a certain way and now you have an intuitive understanding about how that cell might behave when it responds to certain diseases. That is highly specific information. But as long as you can see a pattern that allows predictability, that becomes intuitive. Likewise, if that pattern is violated and broken, something goes against the pre-established pattern that feels counterintuitive. This is a reason why things feel less intuitive as they get more complex because we have fewer patterns that we can apply to that complex topic. For example, it's a lot harder to apply the pattern of how 1 + 1 equals 2 when you're learning advanced calculus. And so whether something is intuitive or easy to understand or not is less about the specific information or how complicated it is and more about how many patterns [snorts] you are familiar with that you can apply in that situation. And so this concept that I'm talking about which is basically pattern matching. I'm going to give this a different term which is a little bit more scientifically valid, more what we talk about in learning science which is schema fit. Schema is basically talking about the different types of patterns of thinking, the patterns and structure of knowledge and the fit is just the matching part. And so understanding that making something easy to understand and intuitive is all about creating schema fit is an important frame shift on how we think about learning because this opens up a whole new set of techniques and tools that we can start applying whenever we feel we're getting overwhelmed or this thing is you know too complicated to wrap our head around. And the way we do this is by understanding what contributes to schema fit. So there's there's two different ways that we can think about this. One way is the schemas that we have pre-existing. Now, as a little meta point, it's intuitive probably for you to feel that if one way of thinking about it is in terms of pre-existing schemas, then the other way of thinking about it might be new schemas and that actually that is correct. So, the other way of thinking about it is new schemas that we are creating that we didn't have pre-existing. In learning science, the way that these terms might have been introduced is that there is something called schema assimilation and then schema accommodation. But you can see how unless you're really wellversed in learning science, these two categories, even though they actually kind of mean the same thing as pre-existing and new, it feels much less intuitive for you to learn. So if I had introduced this to you in a way that said, hey, there's two ways of thinking about it, assimilation versus accommodation, you will feel that this topic is harder for you to understand. So little bit of like a meta example, but coming back to the point. So these two parts pre-existing and new, they basically just reflect the schemas that you have available to match something with and the schemas that you are hypothesizing within the new content. So whenever you're learning something new, you don't know what pattern exists there. There is some kind of pattern cuz the information is going to connect together. The facts are not completely isolated like they have meaning in and of itself. However, you don't know what that meaning is. And this is the part that can be overwhelming for learning because there are so many different ways that it could connect and you don't know which pattern is going to fit. And so what your brain does as a shortcut is it looks at the different patterns you already have and tries to match them. It says this topic feels like it's kind of similar to this other thing that I've already learned about in the past. Is it similar or not? And it tries to see if there is a fit. And if there is a fit and if that fit is very closely tied together, it's going to make it much faster and easier for you to understand it. But if there's no fit, then that's when you feel like this is difficult, very different to what you're used to. But what's the point of actually knowing about this? Well, now that you know about the two different aspects of creating schema fit, we can explore what your brain is trying to do to achieve schema assimilation and accommodation. And to create that schema fit and we can actually boost those processes up actively. Basically, your brain automatically is going to try doing this, but it does it at like two or three out of 10. If you can increase that, forcibly increase your brain's activation, so it does those same processes at 7 or 8 out of 10, it's going to dramatically boost how quickly you're able to turn something that's complicated into something that's intuitive. And when you don't do this, and you just let your brain do it at a 2 or a 3 out of 10, which is what it will normally automatically do, this is when you get stuck. So let's look at what your brain is doing already by default. New information is going to come into your brain. So let's say that there's these new uh nodes of information. Each of these circles represents a concept or a fact. And these concepts and facts are integrated and and related to each other in a variety of different ways. Uh and our brain is basically trying to figure out how it all connects together. But at the moment when that new information first comes in, we don't know. And at this point, what you're going to feel is just a sensation that there is a lot to learn here. There's a lot of different pieces of information. You might feel that sensation like, I'm about to forget this, which is your brain indicating, hey, all of these pieces of information are all very isolated and they're very fragmented together. I don't see how it fits together. There is no schema fit that I'm seeing. I'm about to bin all of this and forget it because I don't I don't see why it's worth holding on to in my memory. And so what your brain is going to do is going to look for a schema of fit. And so inside your existing set of knowledge, uh you will have certain patterns that you've picked up that you've learned before. Like for example, the before, during, after might be one pattern that you are used to or it could be a very specific pattern for that topic, right? It it doesn't have to be general. It can be, you know, very technical and very specific. And so it's going to have, let's say, a couple of these patterns. To keep it simple, let's use a very simple pattern of before, during, and after. uh and another pattern of cause and effect and maybe another one. Let's say this is the pattern of drivers, actions, consequences. And so we're going to now look at this information, this new body of information, and we're going to ask ourselves, do these things connect together? Can I group these in a way that allows me to see that this is really just before, during, and after? So, we might say, okay, these two things here, these are kind of things that happen before. Uh maybe this stuff is something that maybe happens during an event, but this is definitely not after. So, we would look at this pattern and say, okay, it does not fit this pattern very cleanly. So, now we might try the other one, cause and effect. Okay, if I think about it as cause and effect, then perhaps okay, these things could be considered causes and this is really the effect, but these two again they don't fit anywhere else. So again, you know, we would say this one is not a a good pattern. There's no schema fit there. And so we might try the same thing here. Drivers, actions, and consequences. Does it fit that pattern? Yes or no. And again, if our brain is generating, let's say, three different ones and it's generating it very very quickly and it's going to test to see if there's schema fit early on. If the answer is yes, there is schema fit, then we're just going to feel that this is intuitive to begin with. We're not going to run into a situation where we feel that this is complicated in the first place. What happens is that when we do this and we consistently find no it is not a good fit then this is where we typically get stuck and we don't know what to do to resolve this situation. This is where we get the feeling this is difficult to understand. Basically your brain is saying I don't know how to think about this. It doesn't match the patterns I'm familiar with. And if we don't know how to resolve this issue then we just stay stuck. we use much less effective ways of processing this information. For example, just trying to individually wrote memorize each individual fact because we don't have any other way to keep it in our long-term memory and that is extremely timeconuming uh and also just a terrible experience of learning and so what we need is to boost these default processes. So remember what I've just explained here which your brain is doing normally. This is your brain doing it at a two or three out of 10. So we can take these exact same processes and now that we are aware of it, we can consciously do it faster and better than your brain is doing it by default. So what does that look like? Here's what you should do. Once you get the sensation, hey, I'm starting to feel stuck. Aka, I've lucked out on my existing patterns here. There are two possible ways that we can boost this. Number one, we can boost it on this side or we can boost it on this side. Boosting this part of it means that instead of just generating a few different patterns that come to mind automatically, we deliberately think about other patterns of thinking that we may have that we can try to apply. So this part is about generating more patterns. So maybe when we look at this list, we had before, during, after, we had cause and effect, we had drivers, actions, consequences. Maybe we can also think of one that's like left, middle, right, maybe, you know, top, middle, down, or below or significant, moderate, mild, right? These are all different types of patterns that maybe uh we can apply and find a match for in this new information. Now, this is going to be more effective. Uh starting and boosting on this side is going to be more effective when you already have a pretty good amount of prior knowledge about this overall topic. So you may not know much about this specific set of facts, but these facts are going to sit within a network of a much larger topic. So if you already are pretty deep in a certain topic or a domain, then you're probably also going to have a lot of other patterns that you can apply. So if you have more knowledge in the field, it means that the patterns you think of are more likely to be accurate rather than sort of just random guesses. And you're going to have just a bigger library of patterns to draw off of. This is a less effective strategy if you are really new to that discipline. And so for those types of situations, you want to more actively find patterns. So remember how I said that there's all this new information and you don't exactly know how it comes together, but it does fit. There is some kind of pattern there. And we know there's some kind of pattern there because the information is going to be connected. Each fact is probably going to have some kind of influence and relationship and connection to the other facts and concepts. But while your brain is pretty good at figuring out some existing patterns and seeing if they match, it's not as good at actually finding new patterns in this new information. And specifically, there are four things that make it much harder for your brain to find patterns in this new information. And when we're able to address these four things, it becomes much easier to turn that overwhelming concept into something that's much easier to understand. And these four things are number one, interference. Number two, element interactivity. Number three, overload. And number four, abstractness. Number four, abstractness. Now, one thing I'm trying to do when I'm teaching you all of this stuff is I want to present learning science and learning research in a way that actually makes sense for you and is practical. If you were to go through, dive head first into learning science research, read through hundreds of articles, it's actually it's pretty confusing. It's not laid out in a way that's easy for someone to read, understand, see the implication of it across all the other learning science articles out there and then turn that into an actual practical improvement that you can make. And so for the last decade, more than a decade, one of my personal focuses has been on bridging that gap between the research and the practice. And the reason that I do think it's important to understand a little bit about the learning science and how it impacts you is that it makes it much easier for you to know how to think about learning. So if you're having an issue at work, you're feeling overwhelmed in a meeting or it's taking you so long to get through, you know, all the new material that you need to keep up with. It's really difficult to know what to do about that if you don't actually know how learning works, right? It's like trying to fix a car without understanding how the engine works. And that is actually an example of this pattern interaction. By teaching you a little bit more about how learning works, I'm trying to give you patterns and perspectives so that you know how to think about learning. And the next time you have a problem with learning or your retention or how long it takes you to cover something, you know how to think about that problem in a productive way. And so I firmly believe that knowing how to think about a problem is 80% of the way to solving that problem. And the one thing that you should do to know how to think about learning is to join my free newsletter. In a way, you could say that each of my newsletters is trying to teach you one of these different patterns. And at the end of each newsletter, I also give you a practical takeaway. Like here's what you should try to focus on for the next week to use and get used to this pattern of thinking. Each newsletter is carefully crafted by myself directly that I write. I sit there in a room, this room actually, close my eyes. I think about what would be the most valuable thing for me to communicate to this person and I write this email. Each email takes about three to five minutes to read. It's sent into your inbox for free every week. If you're interested in that, I'll leave a link for you to sign up in the description below. Anyway, back to the four factors. So as a recap, if we can overcome each of these four barriers, it means that our brain will be able to find the pattern within this new piece of information so that even if you don't have a lot of pre-existing knowledge about it, you will still be able to make it more intuitive and easier to understand. So let's start with this first one, which is interference. Interference is an interesting barrier because the way that this stops your brain from finding a pattern is by giving your brain the wrong pattern. This is something called negative transfer. It's when your brain does this automatic process of finding patterns and seeing if there's a fit and it says, "Hey, there is a fit, but it's wrong." And so you intuitively, very easily understand this new concept incorrectly. The problem with this and the the real danger is that you don't know what you don't know. So, you usually don't realize that this was an example of negative transfer until hours, maybe days, weeks later. Usually, when you test your knowledge in a certain way and you realize something doesn't quite make sense, you discover a new fact or a new concept that you know is true because you're learning about it. But if this was true, it means that something else that you learned before must be wrong. And honestly, this phenomenon is to some extent unavoidable if you're studying something for a long enough period of time. This feeling that I understand it, I really get it and then I realized I was completely wrong has happened to me when I was learning about learning science like dozens of times over the years. But just because it's unavoidable doesn't mean that we shouldn't try to avoid it because it is undesirable and it is going to waste a lot of time. And the way that we can avoid this and protect ourselves against the risk of interference and negative transfer is by actually challenging the schemas that we think fit. So if we think it fits a certain type of pattern, don't just say yes, I feel like this makes sense, this is logical, this is intuitive, and then just run with it. Deliberately take the time to pause and then challenge whether this way truly makes sense. A good way of doing this is to think about the topic in the way that you think makes sense and then create a conclusion or a hypothesis based on that. Okay, if these things fit together in this way, therefore, if that's true, then this also must be true. This is a process that's called generative reasoning. And what you're doing with generative reasoning is that you're creating a chain of logic that must be true based on how you have understood it based on the pattern you think the schema you think makes sense. If A is true and B is true then C must be true. It gives us a tangible concrete thing for us to validate where if this is wrong the way you've understood it must be either incorrect or incomplete. Whereas if C is true, then it means that the way that you've understood A and B is more likely to be correct. Now, professionally speaking, one of the greatest advantages I've noticed of having this habit of constantly challenging the schema fits and using generative reasoning is that you can spot when other people have generated the wrong schema. So, someone could be explaining something to you and saying, "Hey, this is how this topic works. Here's how it makes sense to me." And then you can actually challenge that in a productive way and find gaps in the way that they have understood it. And then that might translate into better problem solving or more accurate decision-m or better solution design. So that's the first barrier interference which is where your brain is giving you a pattern that it thinks is right but it's actually wrong. But what if there is no pattern that it thinks will fit? Well then naturally what you'd have to do is look through this information and then see how all of these things might be related together. Try to create a pattern. Try to group certain ideas together in a way that you think is meaningful and then see if you can create an intuitive, logical pattern out of it. And if you've ever tried to do this, then you will realize that it can be very overwhelming because there are so many possible relationships. There are so many ways that you can group this information and there seems to be an infinite number of patterns that you can pick from. How do you know what makes sense and how do you know what is correct? And if you have felt that before, you've actually already felt the second barrier, which is element interactivity. Element interactivity is basically a fancy way of saying that there is too much going on. Your brain is only capable of processing so much. And if you've got 19 different concepts and facts and keywords that you're trying to see how it all fits together, and there's 400 permutations of relationships, your brain is not going to be able to process that. you're going to feel overwhelmed and you won't be able to find meaningful patterns because your brain has entered into cognitive overload. It's basically on fire and it's not working anymore. And the way we overcome this is very simple. All we have to do is start small. So if we had let's say let's say we've just got these six points and we're trying to see the relationships between these six points. So even with just six different points, trying to think of all the different relationships and seeing if it all makes sense, this is getting overwhelming very very fast. Instead, by starting small, we say, "Okay, we've got this point and then this point. Is there a relationship between these two?" Yes or not, we just add one more. Cool. We've got three things now. What's the relationship between these three things? Can I group these in a certain way? We deal with just the three and then we add just the one more onto that and then we add just one more and then we add just one more. And the reason this works is because when we start with for example just these three and we realize hey these two are kind of in one group then instead of being two things it just becomes one group and then one factor here. And when we add this next piece on, we might say, "Hey, this actually fits inside this group." So now this becomes one group with three parts in it. And then this one, maybe this adds on to this. So now we have two groups. And then this one, maybe it's a it's another thing that, you know, just sits to the side. So we've ended up with maybe something that looks like this, right? We've got a total of still six points, but it's only two groups and one extra fact, which is still only three things in total. And this is really the way that the brain processes things. By grouping information together, it's able to reduce the amount of working memory it needs to hold on to that information. This is a process called chunking, where you take multiple pieces of information and you group them together. It's like if you've got lots of different files sitting on your desktop and you put them into folders, and then you put those folders into folders. It makes it much easier to organize. The same thing actually happens in your brain. And it's much easier to organize your photos when you're only giving it one new thing at a time rather than here's 40 different things, find the best folder structure for all of them. Now, sometimes you'll be trying to do this. You're trying to start small. You're just taking a few words and you're grouping them together and you realize you can't even do it for like two or three words because the words themselves are so complicated. You don't even know what they mean. This is an example of the third barrier which is overload. And overload typically happens when there is too much jargon or technical language being used. Technical language or terminology is an interesting thing because even though it's technically only one word, that piece of jargon actually represents an entire concept that was so important and so interrelated that someone decided we need to give this whole set of ideas a label and that became the terminology. And so, especially if you're reading specialist documentation, uh, you know, highly technical sources, there's going to be a lot of jargon in there. And that jargon may put you into that cognitive overload very quickly. And it takes so much of your mental effort to just unpack what each piece of terminology means that it can't actually look for the relationships. Every time it thinks, hey, is A connected to B? It has to say, wait, what did A actually mean again? Wait, what did B actually mean again? And by the time you finished that, you've kind of forgotten what you were trying to think about. And so what we can do in this situation is to deliberately go through and then dejargonize as much as we can. So, put everything into layman's terms. A really easy way of doing this now is just you put that term into chatbt or whatever AI you want to use and just say, "Hey, turn this turn these into layman's terms for me." And then we'll just give it to you in simple language that requires very little processing power to understand, which means you can now just use that processing power instead for finding the actual patterns, which is the thing that's going to make it more intuitive. But another way, and I actually think that this is more powerful in some situations, is instead of just trying to turn it into layman's terms, look for visualisations or diagrams. In short, just use a Google image search. So sometimes if I know that what I'm trying to learn about is a new piece of terminology, I'll put it into Google. I'll search for the terminology and I will immediately just go to images. And this is now leveraging off of three advantages. The first is that your visual processing speed is tens of thousands of times faster than your written language processing speed. So I'm going to be able to process this visual information much faster than if I were to read paragraphs and paragraphs trying to explain it. The second advantage is that allows me to use visual patterns. So just like we have conceptual patterns like before, during and after. Like if I see that a concept is represented in a diagram that looks like this. That tells me something about the concept compared to if the concept is visualized like this or like this or like this. In each of these examples, there are four things going on. However, the way that it's visually represented leads me to think about the information in a different way. This is also the reason why it's a good practice to try and create visualizations inside your own learning so that even if a diagram or a pattern isn't given to you, you can create your own visual pattern. And the third benefit is that if this is a complicated concept, some expert has already gone through the effort of thinking about how I should best teach this so that it is intuitive for someone else to understand and they've created a diagram for you. And so for complex concepts and new terminology, when you see a diagram or visualization on it, it often highlights the parts that people find tricky about understanding it. Starting straight off the bat with a Google image search to prevent this overload from happening is a technique that I discovered while going through medical school and it is one of the easiest things that anyone can use. It it can cut down the amount of time you need to spend from like 10 minutes of searching and reading stuff to like 45 seconds. Now the fourth and final barrier is abstractness. Abstractness stops you from finding patterns in new knowledge because you are so unfamiliar with the topic and it is so not concrete that you can't relate to it at all. You can't imagine what it means. You can't visualize it. This is really common when people are learning mathematics where the traditional way that maths is taught is very wrote learning uh of behaviors and equations and just using lots and lots of practice questions to get good at executing on them. People don't tend to develop an intuitive way of understanding what these equations or formulas or principles actually mean. And so later when it gets more advanced, they don't have an intuitive way of actually visualizing or understanding what's going on. This is also the reason why again for something like maths which is traditionally taught with numbers and symbols when you then visualize that and then show what that looks like in geometry or shapes or how changing this function changes the shape of this graph it makes it much easier for it to click because we're taking something that was previously very abstract and hard to connect to and we're making it something that's concrete that we can relate to. When something is presented in a way that's very abstract, this uh used to be I I think one of the hardest barriers to overcome because when a topic is presented to you in an abstract way, it's actually hard for you to even know how to make it concrete. You don't know enough about it to think of your own examples. You can't create analogies out of it. Uh you know, if it's not being presented to you in a way that's concrete enough, you just stay confused for a very long time and then you get stuck. Nowadays, it's actually very simple. You just type the thing into AI and you say this is a bit too abstract for me. Give me concrete examples of how this works and it will just give you examples. And so this feels like a bit of a copout in a way, but the the technique that I give you for battling the abstractness here is just get AI to make it concrete. So these are the four different barriers and the ways that you overcome them. So, anytime that you're learning something new and you're feeling like, hey, this is a little bit complicated, I feel like this is hard to wrap my head around, and you get that sensation, hey, I'm starting to feel like I'm stuck, then use these two approaches. If you feel like you've got pretty good prior knowledge about this, you've been studying this for a number of years, see if you can just actively generate some more patterns to try to fit in. Maybe with a little bit more thinking, you have different models that actually make sense for this new information. If not, try to find more patterns. And as you're trying to find patterns, looking for relationships, and grouping things together, be aware of these four barriers that make it very difficult. And then overcome each one with the techniques that I've given. These are techniques that I've used thousands of times and ones that I continue to use regularly to this day. Now, all of this stuff is still just one small aspect of learning. I think there's a lot more to learning than this. And if you want a more comprehensive breakdown of how to think about learning and building a learning system, then check out this video over here where I do just that. Thanks so much for watching and I will see you in the next one.

Join my Learning Drops newsletter (free): https://go.icanstudy.com/newsletter-hardconcepts In this video, I will show you how to learn hard concepts easily and intuitively by using a strategy called Schema-Fitting. Take my Learning Diagnostic Quiz (free): https://go.icanstudy.com/diagnostic-hardconcepts === Guided Training Program === I’ve distilled my 13 years of experience as a learning coach into a step-by-step learning skills program. If you want to be able to master new knowledge and skills in half the time, check out: https://go.icanstudy.com/program-hardconcepts === About Dr Justin Sung === Dr. Justin Sung is a world-renowned expert in self-regulated learning, a certified teacher, a research author, and a former medical doctor. He has guest lectured on learning skills at Monash University for Master’s and PhD students in Education and Medicine. Over the past decade, he has empowered tens of thousands of learners worldwide to dramatically improve their academic performance, learning efficiency, and motivation.