CARDIFF UNIVERSITY

Understanding Computational Thinking

Computational thinking is a way of thinking analytically and a method used to solve problems. Computational thinking is to help us deal with complex issues and develop solutions after understanding the problem. Computational thinking uses basic concepts of computation to understand human behaviour, design systems, and solve problems (Wing, 2006). Computational thinking allows human thinking and problem-solving to be presented to computers. It allows computers to understand human behaviour. It also allows humans to understand the computer's execution logic. In other words, computational thinking is presented in a way that both humans and computers can understand. Nowadays, most of us use computers daily, and successful communication is known as computational thinking, when people understand how to communicate with computers to make efficient use of their capabilities (Shute et al., 2017, pp. 142-158). The efficient use of computers can be referred to as computational thinking. Computational thinking and engineering thinking have something in common in the way we understand intelligence, computability, thinking, and human behaviour in general (Wing, 2008). Computational thinking builds on the capabilities and limitations of computational processes (Shute et al., 2017, pp. 142-158). Nevertheless, computational thinking does not mean thinking like a computer; it can be divided into five steps to solve problems efficiently (Cansu, F.K. & Cansu, S.K., 2019):

1. Analyse the problem - Recompose the problem into multiple problems, each of which is a familiar, solvable problem.

2. Recursion - Use the previous information to begin building the system.

3. Decompose the Problem - Break the problem down into separate units that can be managed individually.

4. Abstraction - Extract the essential details and ignore irrelevant information.

5. Solve - Get a solution for the purpose.

This division of problem-solving allows for human solutions and purposes to be delivered exclusively to computers, which can also understand the information received. When we learn to use computational thinking, we can solve our problems efficiently. Computational thinking is essentially the process of converting confusing, complex, real-world problems into something that a computer can understand and solve. Abstraction is an essential aspect of computational thinking. Abstraction makes problems more straightforward to think about. Abstraction makes it easier to understand by reducing unnecessary details and variables. It can lead to more straightforward solutions.

Importance in learning

Computational thinking is an essential aid and inspiration in learning now and in the future. It can provide a different way of thinking to solve problems. For example, if we are faced with a complex project or an essay in a future subject, we will be able to use computational thinking to solve the problem. We can use computational thinking to solve the problem. Use computational thinking to break down projects into manageable parts. Each part can have its own direction and purpose. This breaks down a complex problem into many small, understandable parts. After that, the problem is abstracted using computational thinking. Abstraction divides the problem into many levels, each of which is connected in some way. Think at multiple levels of abstraction.

Furthermore, ignore irrelevant information through the process of abstraction. Next, pattern recognition identifies and understands the process of patterns, regularities, trends or features in data. Recurring patterns can be reused. Furthermore, using algorithms can connect the steps of problem-solving. The project is more accessible to solve after utilising computational thinking. Going deeper into computational thinking and choosing better and more complex abstractions will allow me to work on more complex problems of larger-scale numbers in the future. Computational thinking is affecting almost all scientific research, including the sciences and humanities (Bungy, 2007). In the future, computational thinking can play a role in solving problems in the computer field. At the same time, computational thinking can be inspiring and helpful to other professions as well. Majoring in computer science and then pursuing careers in medicine, business, politics or even the arts (Wing, 2006). Computational thinking can also be helpful.