Материал готовится,

пожалуйста, возвращайтесь позднее

пожалуйста, возвращайтесь позднее

What is computational thinking?

Computers can be used to help us solve problems. However, before a problem can be tackled, the problem itself and the ways in which it could be solved need to be understood.

Computational thinking allows us to do this.

Computational thinking allows us to take a complex problem, understand what the problem is and develop possible solutions. We can then present these solutions in a way that a computer, a human, or both, can understand.

The four cornerstones of computational thinking

There are four key techniques (cornerstones) to computational thinking:

decomposition - breaking down a complex problem or system into smaller, more manageable parts

pattern recognition – looking for similarities among and within problems

abstraction – focusing on the important information only, ignoring irrelevant detail

algorithms - developing a step-by-step solution to the problem, or the rules to follow to solve the problem

http://a.files.bbci.co.uk/bam/live/content/zg6bgk7/large

Each cornerstone is as important as the others. They are like legs on a table - if one leg is missing, the table will probably collapse. Correctly applying all four techniques will help when programming a computer.

The four cornerstones of computational thinking are decomposition, pattern, abstraction and algorithms.

Computational thinking in practice

A complex problem is one that, at first glance, we don't know how to solve easily.

Computational thinking involves taking that complex problem and breaking it down into a series of small, more manageable problems (decomposition). Each of these smaller problems can then be looked at individually, considering how similar problems have been solved previously (pattern recognition) and focusing only on the important details, while ignoring irrelevant information (abstraction). Next, simple steps or rules to solve each of the smaller problems can be designed (algorithms).

Finally, these simple steps or rules are used to program a computer to help solve the complex problem in the best way.

Thinking computationally

Thinking computationally is not programming. It is not even thinking like a computer, as computers do not, and cannot, think.

Simply put, programming tells a computer what to do and how to do it. Computational thinking enables you to work out exactly what to tell the computer to do.

For example, if you agree to meet your friends somewhere you have never been before, you would probably plan your route before you step out of your house. You might consider the routes available and which route is ‘best’ - this might be the route that is the shortest, the quickest, or the one which goes past your favourite shop on the way. You'd then follow the step-by-step directions to get there. In this case, the planning part is like computational thinking, and following the directions is like programming.

Being able to turn a complex problem into one we can easily understand is a skill that is extremely useful. In fact, it's a skill you already have and probably use every day.

For example, it might be that you need to decide what to do with your group of friends. If all of you like different things, you would need to decide:

what you could do

where you could go

who wants to do what

what you have previously done that has been a success in the past

how much money you have and the cost of any of the options

what the weather might be doing

how much time you have

Computers can be used to help us solve problems. However, before a problem can be tackled, the problem itself and the ways in which it could be solved need to be understood.

Computational thinking allows us to do this.

Computational thinking allows us to take a complex problem, understand what the problem is and develop possible solutions. We can then present these solutions in a way that a computer, a human, or both, can understand.

The four cornerstones of computational thinking

There are four key techniques (cornerstones) to computational thinking:

decomposition - breaking down a complex problem or system into smaller, more manageable parts

pattern recognition – looking for similarities among and within problems

abstraction – focusing on the important information only, ignoring irrelevant detail

algorithms - developing a step-by-step solution to the problem, or the rules to follow to solve the problem

http://a.files.bbci.co.uk/bam/live/content/zg6bgk7/large

Each cornerstone is as important as the others. They are like legs on a table - if one leg is missing, the table will probably collapse. Correctly applying all four techniques will help when programming a computer.

The four cornerstones of computational thinking are decomposition, pattern, abstraction and algorithms.

Computational thinking in practice

A complex problem is one that, at first glance, we don't know how to solve easily.

Computational thinking involves taking that complex problem and breaking it down into a series of small, more manageable problems (decomposition). Each of these smaller problems can then be looked at individually, considering how similar problems have been solved previously (pattern recognition) and focusing only on the important details, while ignoring irrelevant information (abstraction). Next, simple steps or rules to solve each of the smaller problems can be designed (algorithms).

Finally, these simple steps or rules are used to program a computer to help solve the complex problem in the best way.

Thinking computationally

Thinking computationally is not programming. It is not even thinking like a computer, as computers do not, and cannot, think.

Simply put, programming tells a computer what to do and how to do it. Computational thinking enables you to work out exactly what to tell the computer to do.

For example, if you agree to meet your friends somewhere you have never been before, you would probably plan your route before you step out of your house. You might consider the routes available and which route is ‘best’ - this might be the route that is the shortest, the quickest, or the one which goes past your favourite shop on the way. You'd then follow the step-by-step directions to get there. In this case, the planning part is like computational thinking, and following the directions is like programming.

Being able to turn a complex problem into one we can easily understand is a skill that is extremely useful. In fact, it's a skill you already have and probably use every day.

For example, it might be that you need to decide what to do with your group of friends. If all of you like different things, you would need to decide:

what you could do

where you could go

who wants to do what

what you have previously done that has been a success in the past

how much money you have and the cost of any of the options

what the weather might be doing

how much time you have

Загрузка...

Выбрать следующее задание

Ты добавил

Выбрать следующее задание

Ты добавил