Computational thinking is an article titled "Computational Thinking" published by American computer scientist, Professor Jeannette M. Wing of Carnegie-Mellon University in 2006. The way of thinking based on its limitations - computational thinking. For evaluation, calculation, simulation. Simply put, it is to let humans imitate the thinking mode of computers.

However, abstraction and automation are at the heart of computer thought. Designing time and space that do not exist in reality and simulating these elements constitutes the first abstraction. The outcomes will be superior to practise, despite the fact that this is frequently easier and less expensive. An algorithm, for instance, is described as "a step-by-step process abstraction that accepts input and produces some desired result."(Wing, 2018).

Using the reduction, embedding, transformation, and simulation thinking processes, we can reinterpret a problem that appears to be tough into a challenge that we are familiar with solving (Heintz, Mannila and Farnqvist, 2016). However, layers are introduced throughout the abstraction process, and the calculation is further complicated by the layers. These layers can aid in the system's ability to construct larger, more complex, and deeper system structures as well as more precise calculations and quantification. Data analysis, automation, and optimization are other tasks that fall under the umbrella of computer thinking, and they all work together to increase productivity and produce the best results. Since project estimates are a requirement for genuine projects, data gathering and analysis have become crucial building blocks for forecasting the future (Wing, 2018).

Like other sciences, computational thinking has its formal underpinnings in mathematics and is fundamentally descended from mathematical thought. Second, because building is a system that can communicate with the outside world, computational thinking is also derived from engineering thought. Humans can do deeper and more sophisticated spatial calculations and constructions thanks to the system created in the manner previously indicated, which allows them to transcend the limitations of the physical universe (Shute , Sun and Ashell-Clark, 2017).

Apply to the computer industry for your future education or profession. Computer programmes require a variety of technical techniques to communicate thought; for this reason, formal language theory, compilation theory, testing theory, and optimization theory have all been established. Computational thinking's fundamental ideas are based on these theories and technology. Computational thinking has been thoroughly investigated and developed due to the advancement of computer science, which has helped to define and explain computational thinking. the development of computer science. Problem solving based on constraints and computational models (environments) is at the heart of computational thinking.

The study of computing models, computing system design, and efficient computing system usage for information processing and engineering applications are all topics covered in the field of computer science. It entails the study of fundamental models, the creation of hardware and software systems, and research into technology that is application-focused.

Jeannette M Wing Published:31 July 2008https://doi.org/10.1098/rsta.2008.0118

Demystifying Computational Thinking Valerie J. Shute Florida State University Chen Sun Florida State University Jodi Asbell-Clarke TERC

F. Heintz, L. Mannila and T. Färnqvist, "A review of models for introducing computational thinking, computer science and computing in K-12 education," 2016 IEEE Frontiers in Education Conference (FIE), 2016, pp. 1-9