In this course, I learned that computational thinking is a fundamental skill everyone should master and that computational thinking is extensive, not just for computer scientists—a deeper understanding of the nature and role of computational thinking. Computer thinking is a way for humans to solve problems, but it does not require humans to think like computers. Computers are dull, humans are intelligent and imaginative, and only by mastering the unique problem-solving methods of computational thinking can we use our wisdom to solve problems that we dare not try before the computing era. In the application process, essential computational thinking mainly reinterprets seemingly complex problems through simulation, transformation, embedding, and reduction and informs how to solve them. Using computational thinking, complex problems can be made more systematic and simplified. In the rest of the courses, computational thinking can help me find a way to deal with problems in messy information, significantly improve the efficiency of problem-solving, improve my agile thinking, and exercise the logic of thinking. At the same time, it affects the way to solve the problem. I know that to be centered on the problem point when analyzing the problem, it is necessary to choose an appropriate method to model some of the critical problems that need to be solved urgently in model design and establishment. It can help me see the problem more directly, which is conducive to promoting application performance improvement. In this process, it will inevitably be accompanied by the use and integration of computational thinking to ensure that the problem can be solved quickly and improve the efficiency of the modeler in analyzing the problem. At the same time, the study of this course stimulated my enthusiasm for exploring computer courses. In the subsequent computer course learning, to cultivate the habit of thinking about problems with computational thinking and the habit of actively practicing programming, and practice more because the way of thinking of computer language is not a sudden mastery. It requires me to continue to explore and practice in the subsequent study, not only in the classroom to accept the teacher's ready-made programs, so in the following course learning, I will write programs according to my ideas, refer to relevant materials, gradually develop the way of thinking required for editing programs, and integrate the necessary skill of computational thinking into the future study, work and life.
1:Anon 2022. Communications of the ACM Volume 49Issue 3March 2006 pp 33–35 [Online].
2:Anon 2022. SIGCSE '07: Proceedings of the 38th SIGCSE technical symposium on Computer science education March 2007 Pages 195–196 [Online].
3:Anon 2022. The Computer Journal ( Volume: 55, Issue: 7, July 2012) [Online].
4:Anon 2022. Barbara Sabitzer,Heike Demarle-Meusel, Maria Jarnig, "Computational thinking through modeling in language lessons", 2018 IEEE Global Engineering Education Conference (EDUCON), pp.1913-1919, 2018. [Online].
5:Anon 2022. STOC '01: Proceedings of the thirty-third annual ACM symposium on Theory of computing July 2001 [Online].
6:Anon 2022. Yao, A.CC. (2009). Communication Complexity and Its Applications. In: Deng, X., Hopcroft, J.E., Xue, J. (eds) Frontiers in Algorithmics. FAW 2009. Lecture Notes in Computer Science, vol 5598.Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02270-8_2 [Online].
7:Anon 2022. Part of the Lecture Notes in Computer Science book series (LNTCS,volume 5598) [Online].