We are not taught how to learn optimally. Since most things in life flow from our ability to learn, you would think that learning would be a foundational course. This is not the case.
Many think that learning is just something for the naturally gifted or it is too convoluted or time consuming to get right. They may be partially right because there is a vast amount technique and information that goes into a proper learning method. In the end, it makes people think that there is no way to move the needle for their learning and they end up wasting a lot of time. While I don’t intend a full survey of learning theory here in this article, I do want to point out a stark, useful, and uplifting truth about learning which is this: it looks very much the same no matter what you are learning. This means that learning how to learn can effect every space in which you need to learn efficiently. These techniques are worth your time, so here is what we mean by saying it’s the same everywhere.
Math
Let’s start with everyone’s favorite subject, Math. Within formal mathematical systems, to expand your knowledge (i.e. learn) you start with what are called axioms that you then combine to create ever more complex conclusions through proof. Complexity arises from simplicity in a beautiful way. In school, you do not start with the advanced, you begin with the basics and work your way up. Everything builds on what came before. You learned Algebra, if indeed you learned it, before you went to Calculus, because Calculus is mostly Algebra with some interesting infinities thrown in. There is an unbroken chain between where you are now and where you started. If you struggle with math, start from the beginning, find out what your comfort limit is, then start to connect new ideas to that limit point by asking, how does this build on what I know already?
Science
Science progresses in a similar way. Explanations invoke and build on each other and predictions are made. Sometimes these predictions do not match with our observations, and we have to go back to the drawing board. We do however go one step at a time. The book Where Good Ideas Come From by Steven Johnson calls this the Adjacent Possible, the space of possible conjectures that are immediately next to our current point in our search space. When we conjecture new theories, these always build on what we know with reasonable certainty. Like Isaac Newton said, we stand on the shoulders of giants.
Making connections
In the same way that an entire field grows, so does the knowledge in your head. An optimal strategy starts to become apparent. Whenever you are learning something new…try to connect it to what you already know. Using analogies and poking into why something makes sense based on what you already know is the best way to encode the data so that it sticks in your head. This involves a lot of what Daniel Kahnemann calls System 2 thinking. This type of thinking is deliberate, cyclic, and generally takes more energy which is exactly why we don’t do it. We are lazy! But like your father told you, you must put in the work to reap the rewards.
Systems 1/2 and Language
It’s interesting to note that the two systems of learning are very different in action but still are subject to the same constraints, i.e. connecting to what is already known. System 1 does this intuitively and is the system for language acquisition (up next). System 2 does it more deliberately but has more involvement with logical/mathematical learning. If you try to learn a language with the System 2 approach, then it will take longer if you let System 1 build your language skill.
Our language classes in high school growing up were usually boring. We studied a language for 4 years and couldn’t speak it fluently when we graduated. Language learning doesn’t have to be painful but it often is. This is why people believe that adults have a harder time learning languages than children. At a structural level, I don’t believe this is true. Here’s why.
The fastest way to learn languages has been shown to be one method called Comprehensible Input. In short, you learn language automatically when you understand messages being conveyed. Children do this automatically because of two things
- They learn from context around them. They observe adults talking to them and each other and based on the context, they can start to build a representation of the language
- The sheer amount of talking they are exposed to means they receive a lot of input and then can begin speaking without really having to practice, though in actuality we see babies mimicking sounds all the time. Children do not need to study grammars or memorize vocabulary lists. They don’t even have to consciously think about the language. The context does the work for them because they have representations for what the things in their environment are, starting from simple things like food or hugs to something more abstract like love and hard work. But like math or science, the language learning builds on what came before.
Final Tip
One final comment. I believe that motivating WHY someone should learn something is important because of the same mechanism that we have been discussing. By connecting the learning motivation to a goal you already have, preparing for your career or because it sets the foundations for further study, you solidify in your mind that this is worth your time and are more likely to stick with it.
Hopefully by this point, the main takeaway is clear. Knowledge grows by connection to what came before, what you already know. So take advantage of this. How? It can start as simply as asking the equation, is this similar to anything I know already? Then go from there. You can dive deeper here with excellent work from Justin Sung on Bloom’s Taxonomy, a powerful framework for learning. Also start motivating your learning before starting to increase the likelihood that you stick with it.