3 Thinking Tools to Understand or Solve Everything: Chunking, Mathematical Reasoning, and Computational Thinking
Everyone’s story is a value depends on how you extract the value of it.
Finally, I start to write in Medium for the sake of learning process that I had. Our story might be related. In my case, I always try to find out the relation of everything and conclude the things as much as possible. I think it’s the basic thing of how knowledge can be built. At least, information. It can make what the thing that you are trying to understand be bold. The wonderful thing of it is it can be almost anything.
Basically, my first step of everything is break and categorize thing into three or five part. Introduction, playground, and conclusion or Introduction, literature review, method, data analysis, and conclusion — those five things is familiar if we can recall our bachelor moment. There are many tool that we can used in between. In this post, I will try to share my three frequently used thinking tools.
Those are chunking, mathematical reasoning, and computational thinking.
Chunking, Mathematical Reasoning, and Computational Thinking
The secret of getting ahead is getting started. The secret of getting started is breaking your complex overwhelming tasks into small manageable tasks, and starting on the first one. ― Mark Twain
We all know everything seems hard if we don’t understand in the first place. But I have belief that everything is actually can be learned or solved if we allocate our time on it and do the thing out in anyway that you can do. It’s obvious that some task need more time than the others. In the very first thing we can do for every object that we want to understand is break it into smaller part, categorize it, assign the level of each category, and connect it.
For example, if we want to understand more about fried rice. We can start from what the thing inside the fried rice. It can be rice, egg, soy sauce, onion, salt, sausage, meatball, chili sauce, etc. Rice is level 1. Salt, onion, and soy sauce is level 2. Egg, sausage, meatball, and chili sauce is level 3. Level 1 is primary, level 2 is secondary, and level 3 is optional. It’s easier if we can break thing into three parts. The rule of three is a gold.
To learn physics, we can also start to break, categorize, leveling, and connect. For some knowledge like this, we are already have the big picture of it. We can try to break this thing using pyramid. The top one is physics itself. Below are classical physics, quantum physics, and relativity. Below classical physics are law of motion, law of gravitation, and waves. Below law of motion are kinematics and dynamics. Below kinematics are velocity and acceleration. Below velocity are distance and time. Below is distance are two positions. In each part, we can try to find the explanation and more understanding.
It is important to view knowledge as sort of a semantic tree — make sure you understand the fundamental principles, i.e. the trunk and big branches, before you get into the leaves/details or there is nothing for them to hang on to. ― Elon Musk
After we break the thing out into smaller part, we can actually start to find a way to solve it. First thing first, we need to know the problem and objective of what we are trying to solve or understand. The more precise we identified the problem, the more precise we conclude the solution. Beside the method that we used to go from problem to conclusion. We can implement the mathematical reasoning here, there are inductive and deductive. Whether we start from a number of observations to general conclusion or from general premise to specific results.
The mathematics are the science of form and quantity; mathematical reasoning is merely logic applied to observation upon form and quantity. ― Edgar Allan Poe
Finally, after we had some smaller detail and connection between the thing that we are trying to understand or solve, we go to the computational thinking: decomposition, pattern recognition, abstraction, and algorithms.
The best part of this last tool is actually computational thinking has some intersection with chunking and mathematical induction. The decomposition part is when you are trying to chunk the thing, where you can break the thing apart. The pattern recognition part is when you are trying to search similarity between those part and make some category from your understanding. The abstraction part is when you are trying to make some connection between the part on decomposing level or pattern recognition, and we can also exclude some point that might not be related too much. The last one, the algorithm is when we try to find a way to go from problem to the solution —using inductive or deductive reasoning . We can make more detail of the thing that we want to do in this part. The possibility of everything that might be occurred.