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Computational thinking
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Computational thinking is a way of solving problems so that a person or a computer can carry out the solution. It has four main parts.
The four parts
Decomposition: breaking a big problem into smaller problems that are easier to solve.
Pattern recognition: spotting things that are the same or similar, so you can reuse a solution.
Abstraction: removing details that do not matter, to focus on what does.
Algorithms: writing step-by-step instructions to solve the problem.
Pattern recognition: spotting things that are the same or similar, so you can reuse a solution.
Abstraction: removing details that do not matter, to focus on what does.
Algorithms: writing step-by-step instructions to solve the problem.
Abstraction in real life
The London Underground map is a famous abstraction. It leaves out real distances, streets and bends.
It keeps only what a passenger needs: the stations, the lines and where to change.
A football video game does not model every blade of grass, but it keeps the ball, the players and the rules.
It keeps only what a passenger needs: the stations, the lines and where to change.
A football video game does not model every blade of grass, but it keeps the ball, the players and the rules.
Decomposition example
Problem: make a quiz game.
Decompose it: ask a question, check the answer, keep the score, show the final score.
Each small part can now be solved, and even shared between people in a team.
Decompose it: ask a question, check the answer, keep the score, show the final score.
Each small part can now be solved, and even shared between people in a team.
You are planning a school trip. Show decomposition and abstraction.
- Decomposition: split the trip into transport, cost, permission letters, timetable and lunch.
- Abstraction: for the coach booking, keep the number of people and the date. The colour of the coach does not matter.
Answer: Decomposition splits the trip into smaller tasks; abstraction keeps only the details each task needs.
Decomposition breaks a problem down, pattern recognition spots similarities, abstraction removes unnecessary detail, and an algorithm gives step-by-step instructions.
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