Desirable difficulties

Desirable difficulties are things that make it harder, or at least, slower to learn things, but improve the depth of understanding and retention. In other words, they reduce the quantity but increase the quality of learning. If done correctly, however, quantity actually grows exponentially over time beating those who don’t use certain desirable difficulties effectively.

Interleaved practice
So what are some examples of desirable difficulties? The most effective one so far, for me, has been interleaved practice, which means switching between different subjects or exercises. Why does this improve learning? Because it not only makes you learn how to do certain things but also when.

An example is when learning mathematics, students these days learn one method at a single time before going to the next one. They learn how to solve certain math problems but will not learn when to use certain methods to solve math problems. By mixing up the exercises each with their own methods to solve the problems, you can learn when to use certain methods. This is one of the benefits of interleaved practice.

The next benefit of interleaved practice, is that it also requires the usage of more advanced brain parts, like the prefrontal cortex. And even if it doesn’t, one can imagine how practicing different things requires the usage of many different brain regions, making them much more interconnected. So interleaved practice also increases your understanding of things.

The segmenting principle
The segmenting principle is an element in the so-called E-learning (theory), see: https://en.wikipedia.org/wiki/E-learning_(theory)

It is also somewhat similar to incremental learning, see: https://supermemo.guru/wiki/Incremental_reading — Incremental reading, SuperMemo Guru

Essentially, you are learning in small portions. This enables you to make more and stronger neural connections while simultaneously applying spaced repetition. So when learning a certain math technique, you can try to solve 50% of the problems requiring that technique, go to a different math problem requiring a different technique (interleaved practice), and then solving the other 50% like a day later (spaced repetition).

Think before you learn or read the answer
This might seem an obvious one, like when learning math, but it can be applied to many more things than just math, like when reading a book. For example, I am reading this book currently, called The Extended Phenotype: The Long Reach of the Gene by Richard Dawkins and I have this chapter called ‘Constraints on Perfection’, essentially the limiting factors why organisms are not or cannot perfectly adapt to their environment. So what I am doing before reading the chapter, is that I ask myself “Can I perhaps name some constraints myself?” or “What does this remind me of?” and so on.

What this essentially allows, is making more and stronger neural connections in and with other related things, which accelerates your learning of this chapter. According to some books and articles, this method also allows pre-learning hippocampal neurogenesis, meaning that your brain is literally preparing to acquire new data. This way, your brain is able to fill those “empty” neurons much quicker allowing you, again, to learn faster and with more depth.

And of course by thinking before reading, you indirectly apply spaced repetition, namely by asking questions such as “What does this remind me of?”