Discover what computational thinking is and its benefits from childhood to the profession
Posted: Tue Dec 17, 2024 8:37 am
Computational thinking involves solving everyday problems by using the fundamental concepts of computer programming whose solutions can be represented by a series of steps or instructions.
It is more than a problem-solving skill; in many contexts it can be useful both personally and professionally, which is why it is a necessary skill for anyone to develop.
Want to know more about this? Keep reading this article!
What is computational thinking?
Jeannette M. Wing, a professor at the Department of Computer georgia email list 3 million contact leads Science at Carnegie Mellon University in the United States, was one of the first specialists to use the term computational thinking.
He did this by wanting to describe how a computer scientist thinks and how beneficial it is for everyone to think this way.
She defined it as follows:
“…the thought process involved in formulating a problem and its solutions so that they are represented in a form that can be conveyed to an information processing agent.”
In other words, it is the mental process through which a person considers a problem and, for its possible solution, uses a sequence of instructions executed by a computer, a human, or both . In other words, it applies skills inherent to computing and critical thinking.
What are the pillars of computational thinking?
Computational thinking has four principles, which are:
1. Breaking down a problem into smaller phases
It consists of breaking down a complex system or problem into smaller parts so that they are easier to solve.
Each small problem will be solved one after another until the entire system is solved.
2. Recognition of repetitive patterns
Once you have broken down the complex problem into smaller ones, look for common feature standards.
Finding these similarities in small decomposed problems will help you solve the system more efficiently.
3. Abstraction of information irrelevant to the proposed problem
Abstraction refers to focusing on the important information, leaving aside irrelevant and unnecessary features.
But what is important information? In abstraction it is mainly about the general characteristics that are common to each element, rather than specific details .
After having these general characteristics, one must proceed to create a "model" of the problem, which is the general idea of the problem that one is trying to solve.
It is more than a problem-solving skill; in many contexts it can be useful both personally and professionally, which is why it is a necessary skill for anyone to develop.
Want to know more about this? Keep reading this article!
What is computational thinking?
Jeannette M. Wing, a professor at the Department of Computer georgia email list 3 million contact leads Science at Carnegie Mellon University in the United States, was one of the first specialists to use the term computational thinking.
He did this by wanting to describe how a computer scientist thinks and how beneficial it is for everyone to think this way.
She defined it as follows:
“…the thought process involved in formulating a problem and its solutions so that they are represented in a form that can be conveyed to an information processing agent.”
In other words, it is the mental process through which a person considers a problem and, for its possible solution, uses a sequence of instructions executed by a computer, a human, or both . In other words, it applies skills inherent to computing and critical thinking.
What are the pillars of computational thinking?
Computational thinking has four principles, which are:
1. Breaking down a problem into smaller phases
It consists of breaking down a complex system or problem into smaller parts so that they are easier to solve.
Each small problem will be solved one after another until the entire system is solved.
2. Recognition of repetitive patterns
Once you have broken down the complex problem into smaller ones, look for common feature standards.
Finding these similarities in small decomposed problems will help you solve the system more efficiently.
3. Abstraction of information irrelevant to the proposed problem
Abstraction refers to focusing on the important information, leaving aside irrelevant and unnecessary features.
But what is important information? In abstraction it is mainly about the general characteristics that are common to each element, rather than specific details .
After having these general characteristics, one must proceed to create a "model" of the problem, which is the general idea of the problem that one is trying to solve.