The University of Pennsylvania — Computational Thinking for Problem Solving — Week One
An Introduction to the four methods for problem-solving.
The University of Pennsylvania has a course dedicated to problem-solving and how to think about problems you face. This topic is quite interesting and embodies exactly what someone should learn. Learning how to think is, in my opinion, the most important thing that someone could learn. It is a powerful skill that is so frequently glossed over. The first week of this course tackles the skill of how to think by breaking it down to four different steps.
Step 1 — Decomposition
Decomposition is the act of taking a problem and breaking it down into simple steps. By tackling each step one at a time, eventually, the problem gets solved as a whole. This method is incredibly useful for tackling problems that seem too large are on their own.
Step 2 — Pattern Recognition
Once a problem has been decomposed, it becomes easier to see the repetitive steps. This part of problem-solving has to do with recognizing these patterns and how to build the most efficient algorithm to solve them.
Step 3 — Data Representation and Abstraction
This part deals with defining what the most efficient data is for the problem that is being solved. It deals with abstracting away the parts of the problem that is not absolutely necessary to know in order to find a solution.
Step 4 — Algorithms
This step has to do with taking each of the three previous steps and combining them together to build an algorithm. To do this, it is necessary to know each subpart of a problem, what data is necessary, and what patterns appear. Once you organize each part accordingly, you can then proceed to follow a step by step guide to solving your particular problem.
I am looking for week 2! Stay tuned!
Thank you for reading!
