Computational Thinking (CT), built upon constructionism theory and deeply rooted in computer science, stands as a transferable and enduring skill that enhances individuals' clarity and logical thinking (Beecher 2017). While some people may mistakenly equate CT with programming, I believe that CT essentially involves the systematic structuring of problems using a specialized symbolic language. The CT methodology can be primarily broken down into five fundamental steps:decomposition, pattern recognition, abstraction, and algorithm development.
1.Decomposition
Decomposition refers to breaking a problem into parts that make up its basic structure (Shute et al. 2017).
2.Pattern recognition
Pattern recognition refers to finding the characteristics of things, and then analyzing and summarizing this
characteristic pattern to derive logic (Shute et al. 2017).
3.Abstraction
Abstraction is the removal of the differences found in the previous step (pattern recognition) because they
do not fit the pattern (Shute et al. 2017).
4.algorithm
Algorithm design is the formulation of a solution to a problem or certain rules to be followed (Shute et al.
2017). In
this process, people create a sequence of steps to solve a problem they face.
5.Generalization
Generalization refers to adjusting/optimizing existing models to solve new problems, or a class of problems
(Shute et
al. 2017).
Computational thinking is an invaluable skill in a competitive, ever-changing digital world. CT improves our ability to solve problems, critically analyze, communicate, and think creatively. As students, CT lays the theoretical foundation for our future studies and helps us understand the logic of programming. Furthermore, CT can be applied to almost any job and any industry.For example, the architect Zaha Hadid used computational thinking to design architecture through parametric design, helping architects pave new avenues. In addition, the importance of computational thinking is particularly significant in emerging professional fields, such as data scientists, artificial intelligence engineers, network security experts, etc.As the fields of technology and computing continue to evolve, CT will become the key to career success. People with computational thinking and numeracy skills are more likely to adapt to new technologies and tools, thereby remaining competitive in their careers.Therefore, whether I am an architect or a programmer in the future, computational thinking will help me in my career.
Beecher, Karl. Computational Thinking : A beginner's guide to problem-solving and programming, BCS Learning &
Development Limited, 2017. ProQuest Ebook Central,
https://ebookcentral.proquest.com/lib/Cardiff/detail.action?docID=4871984.
Shute V J, Sun C, Asbell-Clarke J. Demystifying computational thinking[J]. Educational research review,
2017,
22:
142-158.