Computational thinking describes the processes and approaches we draw on when thinking about how a computer can help us to solve complex problems and create systems.
These are the processes involved below;
# Identification
What makes a computer scientist is being able to break down a big problem into the smaller problems that make it up. If you can break down a big problem into smaller problems then you can give them to a computer to solve.
Once the problem is recognised, a pattern would be needed to put it in its simplest terms so that it can be used whenever we need to use it. For example, if you were studying the patterns of how an ATM works, you might need consider to consider the ATM usage rate of highly populated areas.
Once we have our patterns and abstractions, we can start to write the steps that a computer can use to solve the problem. This is done by creating Algorithms. Algorithms aren't actually computer code, but are independent instructions that could be turned into computer code
Computational Thinking is a way of thinking that makes it possible to decipher a problem into several smaller and simpler parts, find patterns in the problem, and develop steps to solve the problem.
The history of Computational Thinking began at least in the 1950s, but most of the ideas were much older. The term Computational thinking was first used by Seymour Papert in 1980. Computational thinking can be used to solve complex algorithmic scale problems, and is often used to realize large efficiency improvements.
Computational Thinking is done on the human side, so it can be used in various fields, not only in the world of computer science. There are four key techniques in Computational Thingking, namely:
Decomposition: Breaking larger / complex problems into smaller / simpler parts into easily manageable tasks. For example, break 'Drive / Directory' in a computer based on its constituent components.
Pattern recognition: Search / find patterns / similarities between problems and in the problem. The ability to see similarities or even differences in patterns, trends and regularities in the data that will later be used in predicting and presenting data.
Abstraction: Focus on important information only, and ignore less relevant details.
Algorithms: Develops the same problem solving instructions step-by-step, step by step, step by step so that others can use the steps / information to solve the same problem.
In solving problems with Computational Thinking, there are aspects that must be done, namely:
Identification comes from the word Identify which means researching, studying. Identification is an activity that seeks, finds, collects, examines, registers, records data and information from the "needs" of the field. The function and purpose of identifying program needs to find out the various problems or program needs that the community wants. To find out various sources that can be used to support the implementation of the program and make it easier to plan the program that will be implemented. The collected data can be used as a basis for program planning that can be influenced by the program manager. As information material for other parties in need.
Analysis is the attitude or attention to something (objects, facts, phenomena) to be able to decipher into parts, and recognize the links between the parts in the whole. Analysis can also be interpreted as the ability to solve or describe a material or information into smaller components so that it is easier to understand. The goal is to find and get a solution from the problems that occur
implmentation can be interpreted as an action or implementation of a plan that has been carefully designed. The goal itself is so that we can produce or get the results we want.
What is Computational Thinking?
Computational thinking describes the processes and approaches we draw on when thinking about how a computer can help us to solve complex problems and create systems.
These are the processes involved below;
# Identification
What makes a computer scientist is being able to break down a big problem into the smaller problems that make it up. If you can break down a big problem into smaller problems then you can give them to a computer to solve.
#Analysis
Once the problem is recognised, a pattern would be needed to put it in its simplest terms so that it can be used whenever we need to use it. For example, if you were studying the patterns of how an ATM works, you might need consider to consider the ATM usage rate of highly populated areas.
#Implementation
Once we have our patterns and abstractions, we can start to write the steps that a computer can use to solve the problem. This is done by creating Algorithms. Algorithms aren't actually computer code, but are independent instructions that could be turned into computer code
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Computational Thinking is a way of thinking that makes it possible to decipher a problem into several smaller and simpler parts, find patterns in the problem, and develop steps to solve the problem.
The history of Computational Thinking began at least in the 1950s, but most of the ideas were much older. The term Computational thinking was first used by Seymour Papert in 1980. Computational thinking can be used to solve complex algorithmic scale problems, and is often used to realize large efficiency improvements.
Computational Thinking is done on the human side, so it can be used in various fields, not only in the world of computer science. There are four key techniques in Computational Thingking, namely:
Decomposition: Breaking larger / complex problems into smaller / simpler parts into easily manageable tasks. For example, break 'Drive / Directory' in a computer based on its constituent components.
Pattern recognition: Search / find patterns / similarities between problems and in the problem. The ability to see similarities or even differences in patterns, trends and regularities in the data that will later be used in predicting and presenting data.
Abstraction: Focus on important information only, and ignore less relevant details.
Algorithms: Develops the same problem solving instructions step-by-step, step by step, step by step so that others can use the steps / information to solve the same problem.
In solving problems with Computational Thinking, there are aspects that must be done, namely:
Identification comes from the word Identify which means researching, studying. Identification is an activity that seeks, finds, collects, examines, registers, records data and information from the "needs" of the field. The function and purpose of identifying program needs to find out the various problems or program needs that the community wants. To find out various sources that can be used to support the implementation of the program and make it easier to plan the program that will be implemented. The collected data can be used as a basis for program planning that can be influenced by the program manager. As information material for other parties in need.
Analysis is the attitude or attention to something (objects, facts, phenomena) to be able to decipher into parts, and recognize the links between the parts in the whole. Analysis can also be interpreted as the ability to solve or describe a material or information into smaller components so that it is easier to understand. The goal is to find and get a solution from the problems that occur
implmentation can be interpreted as an action or implementation of a plan that has been carefully designed. The goal itself is so that we can produce or get the results we want.
Downvoting a post can decrease pending rewards and make it less visible. Common reasons:
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