5 Elements of Effective Thinking (Summary and Application)
Not being able to come up with solutions sucks. When your grade, career, or livelihood is on the line, the stress can be tough to deal with.
Thankfully, I came across this amazing book that teaches you how to think well and come up with answers.
This is a quick summary of the book, 5 Elements of Effective Thinking, along with some of my thoughts and an application at the end.
5 Elements of Effective Thinking Summary and Application
Be relentless in learning the basics
The word “basic” gets equated to “boring” most of the time, but it is by far the most important ingredient in a problem-solving and learning process. Time gets wasted and your experience gets unnecessarily painful if you don’t master the basics.
For example, in order to play an advanced piece with the piano, you first need to master the foundational theories and drills. To learn calculus effectively, you first need to be proficient in algebra. And so on.
See What’s There
Seeing a man rob a store and then thinking the robber did it in desperation to feed his family is weird and is most likely the wrong interpretation. You might be right, but one thing is for sure: he committed a crime.
That might be an extreme example, but it illustrates that the things we see are interpreted by our own perception in life. The keyword here is “perception.” Learn to see things for what they truly are and not what you want them to be (or perceive them to be), because you’ll be dealing with the situation the wrong way.
See What’s Not There
Finding out what’s missing helps you fill-in the gaps in your understanding and gives you a more accurate picture of the problem.
Get into the habit of asking the following questions:
- “What else don’t I know?”
- “What else is missing?”
- “Is there a hidden piece of information I need to know?”
We are conditioned to avoid making mistakes at a young age, which is a tragedy because errors are like bounce boards towards solutions.
When you’re stuck and you don’t know what to do, deliberately give yourself a wrong answer to gain insight for your next course of action.
Embrace failure. Seek mistakes. They are guides towards coming up with answers to tough questions.
Just like making mistakes, asking questions leads you to answers because it unearths hidden aspects of a problem.
Some good questions to ask are the following:
- What are the subparts of this problem if I break it down into smaller chunks.
- How do I patch the hole in my understanding of the problem?
- What if…?
Do Things Differently
When you fail, trying harder is rarely the next best move. Instead, do things differently.
Let’s say you’re not getting the grades you want despite spending hours studying. Instead of cramming harder, you could do the following:
- Pretend you’re the instructor and create a test for the class. This forces you to think which topics are important to know. Then, actually take that test.
- Learn how to use the memory palace (I’ve used this technique to memorize 80 artificial intelligence jargon at one point).
- Write down as many things you can recall about a subject. Then, check what you’ve missed.
Treat Solutions as Starting Points, Not Peaks
If you think you’ve found a solution to a problem, see if you can do better.
For example, people in the past who used rotary phones would’ve thought it was impossible for anyone to carry a communication device without cables. And yet, here we are with our smartphones.
It’s a mistake to consider current solutions as peaks. Instead, they should be treated as valleys with more summits for us to climb.
Before taking a course, reading a book, or learning a skill, make a guess on what you’re going to learn based on the information you know about them.
The satisfaction of being right gives you a jolt of excitement which helps you retain the information.
On the other hand, you’ll get a “yikes” effect when you guess wrong which will let the information sink in your brain.
Application: Intro to Data Analysis Course
I gave up on a data analysis course five years ago because I couldn’t deal with the brain hurt. But after reading the book above, I decided to take the class again to test the concepts I just learned.
The results were amazing! Here’s how I used the things I’ve learned from the book.
1. I made guesses on what to learn and expect
This part of the process felt like a game because I had a guessing match with myself throughout the course.
Here are some of the things I expected:
- I’m going to struggle again (I did but not as much as before).
- I don’t need to review Python (I was wrong).
- I’ll be tempted to look at the answers (I did).
- I’ll be tempted to give up (I did not).
Here are some of the things I thought I was going to learn:
- Numpy and Pandas (I did)
- Statistics (I did not)
- Introduction to regression stuff that I keep hearing about (I did not).
2. I spent a lot of time on the foundation
I barely remembered how to code in python but I started doing the exercises anyway but I ended up wasting a lot of time because I spent more effort fixing my code instead of writing solutions.
So, I reviewed python for a week and then continued the class.
3. I asked questions to get past hard problems
Some of those questions were the following:
- Do I really understand this question? If I do, then why don’t I know how to start solving the problem?
- How do I deconstruct the problem so I could understand it better?
- Is there a formula I should be using which the instructor hasn’t given us (this turned out to be the case. I googled the equation I needed, used it in my code, and viola. I got it right).
4. I deliberately made mistakes when I didn’t know how to start solving the exercises
I wrote a solution that I knew was wrong and then executed it Instead of staring at the screen for a long time. I got a warning from the machine which told me where my error was, but those errors became starting points that eventually led me to answers.
If your default thought process is not yielding satisfactory results, try the principles shared in the book.
You got this.