Computational Thinking
Computational Thinking (CT) : It is all of the processes that involve problem solving by expressing the solutions of problems algorithmically and systematically.
Except that it can be used to solve any problem in an IT project, it includes steps that we can use to solve a problem in our daily life, just like in algorithm definition and use.
When the literature on Computational Thinking skill is examined, it is observed that it is important for a person to receive programming training in the process of acquiring this skill.
Computational thinking generally happens as follows:
- The problem is broken down into parts,
- The separated parts are brought face to face so that they can be solved in a similar way to the problems encountered before,
- Information that is not relevant to the problem that has arisen is excluded from the work.
- Steps are created to solve the problem and the resulting solution is used in the most efficient way.
Since not every complex problem can be solved in the same way, the path to be followed while applying computational thinking may vary according to the problem.
In a joint study of ISTE (International Society for Technology in Education) and CSTA (Computer Science Teachers Association), computational thinking is defined as a thinking method that includes the following features:
- Formulating problems so that they can be solved with the help of computers or other tools,
- Organizing and analyzing data logically,
- Presenting data with abstractions such as models and simulations,
- Automating solutions through algorithmic thinking,
- Identifying, analyzing and implementing possible solutions in order to achieve the most efficient and effective combination of steps and resources,
- Transferring and generalizing the found solution process to different problems (ISTE & CSTA, 2011).
Components of Computational Thinking
Computational thinking has four components, including Decomposition, Pattern Recognition, Abstraction, and Algorithm Design.
Decomposition
It is the stage in which a complex problem we encounter is made more manageable by breaking it down into parts with algorithmic thinking. It is a must-have method in the first step to solve large and complex problems cleanly.
Pattern Recognition
As a term meaning, it can be expressed as defining the pattern, rule between the data in a series. In computational thinking, on the other hand, the similarities in the problem are identified and it is determined at this stage whether there is a similarity with a problem that has been encountered before or that has been determined in the sub-parts of the problem at hand. If a similarity is detected, using the predetermined solution techniques in this problem will make our work easier and save us time in approaching the solution. This component is an important step in producing effective solutions to the problems encountered.
Abstraction
Abstraction focuses on the most essential and most needed components of the solution. By ignoring the details, attention is drawn to only the important elements, in order to isolate everything that will not lead us to a solution. Thanks to this step, our focus is only on the solution process of the identified problem, and it accelerates the problem solving process by separating it from the details and making it simple.
Algorithm Design
It is the final component of computational thinking. In this step, it is determined how the problem will be solved step by step. While designing the algorithm that will lead us to the solution, attention should be paid to the determination of the solution that will be realized with the shortest path.
We can say about debugging as another component that we can consider in the algorithm design step. Debugging helps us to improve our algorithm by correcting the possible errors that we determine by testing the algorithm we designed.
Conclusion
- Computational Thinking is a problem-solving approach that involves expressing solutions algorithmically and systematically. It can be used to solve any problem, not just IT-related ones, and involves breaking down the problem into parts, identifying similarities with previously encountered problems, excluding irrelevant information, and creating steps for the solution.
- The four components of Computational Thinking are Decomposition, Pattern Recognition, Abstraction, and Algorithm Design.
- Decomposition involves breaking down a complex problem into manageable parts, Pattern Recognition involves identifying similarities between the problem and previously encountered ones, Abstraction involves focusing on essential elements and ignoring irrelevant details, and Algorithm Design involves determining how the problem will be solved step by step, with attention to the shortest path. Debugging is another component that can be considered during Algorithm Design to correct any possible errors in the algorithm.
