I. Connotation of Computational Thinking

Computational Thinking is a problem-solving method that involves decomposing complex problems into smaller, more manageable parts (decomposition), identifying and describing patterns in the problems (pattern recognition), identifying general solutions to the problems (abstraction), and designing simple steps or rules to solve the problems (algorithm design) (Wing, 2006). This way of thinking is not only applicable to computer science but also to many areas of our daily lives.

II. Importance of Computational Thinking in Academia and Career

Computational Thinking plays a significant role in my study program as it forms the basis for understanding and applying computer science concepts. Whether it’s programming, data analysis, or artificial intelligence, computational thinking is required to solve problems and innovate.

In my current and future career, Computational Thinking is equally important. In a world that is increasingly dependent on technology, the ability to understand and apply computational thinking is a valuable skill. It can help me solve problems more effectively, understand and utilize technology better, and think more innovatively.

III. Detailed Understanding of Computational Thinking

According to Sengupta, P., Dickes, A., & Farris, A.V. (2018), Computational Thinking is defined as a thought process involved in formulating problems and their solutions so that the solutions can be executed by a computer. The importance of this way of thinking lies in its ability to help us understand and apply the knowledge and practices in Science, Technology, Engineering, and Mathematics (STEM). Furthermore, Computational Thinking can help us understand the uncertainty and subjectivity in STEM, which is essential for the sustainable and long-term curricular integration of Computational Thinking.

In addition, Sengupta et al. emphasized the importance of Computational Thinking in trans-disciplinary representational and epistemic practices such as design and modeling, and its role in computational modeling. They also proposed reframing coding and modeling as designing for an authentic audience, and the importance of using both visual and text-based programming languages for long-term curricular integration.

Therefore, Computational Thinking is not just about mastering computational logic and symbolic forms, but it is a more complex experience. It should be viewed as a discursive, perspectival, material, and embodied experience that includes but is not limited to the use and production of computational abstractions.

IV. Conclusion

In conclusion, Computational Thinking is a powerful tool that can help us better understand and solve problems, whether in academic research or in our careers. By learning and practicing Computational Thinking, we can better utilize technology.

References:

• Sengupta, P., Dickes, A., & Farris, A.V. (2018). Toward a Phenomenology of Computational Thinking in K-12 STEM. In: Khine, M.S., (Ed). Computational Thinking in STEM Discipline: Foundations and Research Highlights. Springer.
• Wing, J. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35.