#2: Learning Strategies For Complex Topics

I’ve only relatively recently begun devoting some measure of thought to the most effective strategies to learn about (more specifically, to gain an intuitive understanding of) complex subjects.

The Indian education system I grew up studying within had a pretty rigid prescription for how subjects would be taught and knowledge would be tested: rote memorization, set-in-stone definitions, dont-question-a-damn-thing mindsets, regurgitate-the-textbook-on-paper examinations. That’s not to say that I didn’t have some good teachers, but rather that even the best among them were hamstrung by the limits of the system.

When I began studying at TCU, I received my first dose of a different approach to learning. My professors engaged us in conversations rather than merely telling us what was right and wrong. Over the years, I came to believe I preferred a spoken voice walking me through a complex subject rather than reading paragraphs in a book. We all our special in our own way, after all, and my snowflake brain was built to gain knowledge through my ears rather than my eyes.

I now believe I was wrong back then. Over the last two or three years, my approach has started focusing on a different theory of learning—one that Elon Musk laid out in a Reddit AMA. To quote him: “Frankly, though, I think most people can learn a lot more than they think they can. They sell themselves short without trying. One bit of advice: it is important to view knowledge as sort of a semantic tree — make sure you understand the fundamental principles, ie the trunk and big branches, before you get into the leaves/details or there is nothing for them to hang on to.”

Contextualizing the process of learning with the analogy of a tree was a real eye-opener for me. I’ve tried to approach any new learning challenge (for example, learning to code with C#/.NET for work a few months ago) with this perspective in mind. It seems so obvious now.

To this end, I’ve tried to be as fluid as possible in the media I consume and methods I practice to gain this knowledge. Returning to the topic of learning C#/.NET, I combined watching YouTube tutorial videos, reading Microsoft’s developer documentation, reviewing pre-existing code from the team, and plain old trial and error to complete the tasks I was assigned.

Earlier, I was listening to Tim Ferriss’ excellent interview with Tim Urban. Wait But Why is a downright excellent publication by Tim Urban, having been really helpful in teaching me about brain-computer interfaces, the Fermi Paradox and more. He absolutely nails the tree-building approach to helping his readers gain an understanding of these very complex topics.

In the aforementioned interview, Tim Urban lays out his approach to researching topics. In essence, he starts with Wikipedia to gain a rough overview of a topic and idea of where the “walls” are for related information. He then proceeds to do general searches around the topic, reading, watching, listening to or otherwise consuming as many search results as possible. Through this approach, he grows and re-enforces his understanding of the topic by hearing different explanations, perspectives and opinions. Some of the sources he stumbles upon may provide incomplete or inaccurate information, but even these help him gain an insight into the kinds of conversations that exist around the topic.

It’s fascinating to hear this approach to researching and learning about complex topics, especially since the end results are so startlingly good. Further, hearing this from Tim Urban in the interview gives us a well fleshed-out idea of how to approach building our semantic trees of knowledge.