Introductory guide to Computational Thinking
Computational thinking (CT) is the use of algorithms to define the basic concepts needed to reach transferable solutions to solve real-world problems. (Shute et al. 2017). The definition of computational thinking is “involves solving problems, designing systems, and understanding human behavior, by drawing on the concepts fundamental to computer science”(Wing 2006). Computational thinking is a conceptual approach to solving practical problems in life by correctly and effectively processing information and establishing tasks through computer systems(Lu and Fletcher 2009).
In my opinion, the fundamental purpose of computational thinking is based on solving real problems. By abstracting real problems and converting them into computer language, the data or methods needed to solve the problems can be obtained based on the powerful computing performance of computers.
As for the importance of computational thinking, many researchers and organizations today agree that computational thinking is a universal ability that every young person should possess(Barr and Stephenson 2011).
Computational thinking is partly synonymous with efficiency, which can help us learn more efficiently than just memorizing the operators of the code. In the current learning stage, computational thinking is the basis for later learning computer compilation language, computer composition and other courses. With the help of computational thinking, we can better abstract some practical problems, such as arithmetic summation, with the help of for loop to solve practical problems. Later in my career, there were many projects that were difficult to abstract immediately in computer language. But with the help of mastering computational thinking, it is beneficial for us to disassemble the actual problems and express them in computer language, so as to obtain the data and methods we need.
Barr, V. and Stephenson, C. 2011. Bringing computational thinking to K-12: what is Involved and what is the role of the computer science education community? ACM Inroads 2(1), pp. 48–54. doi: 10.1145/1929887.1929905.
Lu, J.J. and Fletcher, G.H.L. 2009. Thinking about computational thinking. In: Proceedings of the 40th ACM technical symposium on Computer science education. SIGCSE ’09. New York, NY, USA: Association for Computing Machinery, pp. 260–264. Available at: https://doi.org/10.1145/1508865.1508959 [Accessed: 23 October 2023].
Shute, V.J., Sun, C. and Asbell-Clarke, J. 2017. Demystifying computational thinking. Educational Research Review 22, pp. 142–158. doi: 10.1016/j.edurev.2017.09.003.
Wing, J.M. 2006. Computational thinking. Communications of the ACM 49(3), pp. 33–35. doi: 10.1145/1118178.1118215.
