How to Use Computational Thinking to Solve Problems Like a Pro

Can thinking like a computer help us solve our most difficult problems? You might wonder ‘what is the point of computational thinking?’ After all, we invented computers to help solve our most difficult problems. Why would we now want to think like them?

Well, there are a few reasons. The first reason is practical. It is not realistic to expect computers to solve every problem. After all, they don’t take into account human emotions or local knowledge.

The second reason is a moral one. Perhaps we shouldn’t rely on computers to solve everyday problems. I mean, who hasn’t seen sci-fi films like Terminator or the Matrix? We can’t allow them to have too much power over us.

But this is not the point of my article. My point is how to use computational thinking to help with everyday problems.

What exactly is computational thinking?

You might think that computational thinking is a very longwinded way of solving problems, but actually, we do it every day. Just think about it.

Computational thinking

Computational thinking is exactly what you imagine it to be. It is a way of thinking like a computer. In fact, we already use it in our everyday lives. When we cook a meal or get ready for work. When we budget for the weekly shop or plan a trip to the coast.

Computational thinking just means using a set process in which to break down a complex problem. By using this set process, you follow the set technique and find a solution.

For example, if you were to cook a meal, you wouldn’t just blindly throw lots of ingredients into a pan and hope for the best. You would consult a recipe book, go out and buy the correct ingredients, weigh them and then, following the instructions – cook them in the correct order.

Or say you were planning a holiday abroad. You would research suitable resorts and hotels. If you have children, you may look at child-friendly locations. You will look at the cost of flights and the times of departure and arrival. You’ll budget your expenditure and arrange for pickups to and from the airport. After carrying out all of the above, you’ll make a decision and book your holiday.

These are both examples of computational thinking. There are four steps in computational thinking:

Four steps in computational thinking

1. Decomposition

Taking the problem and breaking it down into smaller components.

2. Pattern recognition

Looking for patterns within these smaller components.

3. Abstraction

Focusing on the important details and leaving out irrelevant distractions.

4. Algorithms

Finding steps to solve the smaller problems which will then lead to a solution for the main problem.

You can use computational thinking in many aspects of your life. However, it is particularly helpful when it comes to solving everyday problems. That’s because it breaks down a complex problem into manageable parts.

For example:

You get in your car one morning and the engine doesn’t start. Obviously, you don’t give up, instead, you try and sort out the problem. So where do you start?

Decomposition

By breaking down the components.

Is it cold outside? Do you need to give the engine some gas? Did you remember to put in the anti-freeze? Is the car in gear? If so put the gear in neutral and try again. Have you run out of petrol? Does the car have oil and water?

Pattern recognition

Now you can see that beforehand we had one main problem – the broken-down car. Now, we are dividing the car into different sections which are easily managed.

We can examine each section without getting overwhelmed at the scale of the problem. By doing this, we can also look for patterns in each section. Have we experienced this before? For instance, did our car fail to start on a previous occasion because we had left it in gear?

Abstraction

When you have one main problem, it is easy to get distracted by all the tiny little irrelevant details. By breaking it down into bitesize manageable portions, you can keep what is important in mind and discard what is not.

So with our car break-down, we won’t be concerned with things like the condition of the tyres or whether the windscreen wash is topped up. We are solely focused on what is causing the car not to work.

Algorithms

Now that we have broken our major problem into more manageable ones, it has become easier to identify what is wrong. We can now address the problem and find a solution.

So with our broken down car, once we have identified what is wrong we can fix the problem.

Why is computational thinking important?

Being able to think in this way is important for a variety of reasons.

We retain control

First of all, solving problems in a logical and measured way allows a person to remain in control of a situation. When we can analyse and predict what is going to happen, we are likely to learn from our experiences.

We become confident

By solving problems we become confident and learn to challenge ourselves. We acquire skills that boost our self-esteem. Every stage of computational thinking is an opportunity for learning, and, as a result, self-improvement.

We are not overwhelmed

By breaking down a complex problem we learn not to be overwhelmed by a seemingly insurmountable task. Then we start to recognise patterns once we have broken the task down. This comes with experience. Experience also teaches us what to discard and what is important in solving this problem.

All of these steps are vital life lessons that are useful in our everyday lives.

Final thoughts

Computational thinking isn’t really about programming people to think like a computer. It is about teaching people the four fundamental steps to solve our everyday problems. Why not try it next time you are faced with a complex problem and let me know how you get on?

References:

1. royalsocietypublishing.org
2. www.researchgate.net

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