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What Has Been Learned from Computational Thinking?

Most of the difficulties and challenges we encounter in daily life can be seen as projects. Computational thinking is essential for planning and time management during these projects. Only by mastering computational thinking can we efficiently address various life challenges. Regardless of the specific problem, we can use the following four steps to formulate a plan:

Learn to apply computational thinking's four steps when facing complex projects. When confronted with an intractable problem, we must solve it using computational thinking.

First, break down a large project into smaller problems and prioritize them based on importance.

The second step involves utilizing pattern recognition to compare the current problem with past experiences, addressing similar characteristics. If there are similarities, we can refer to past experiences and create a summary for better problem-solving.

The third step is to abstract complex problems into simpler concepts on the to-do list, converting specific requirements into abstract logic to identify the core issues that need solving.

The final step is to devise a solution by referencing the operational logic of computer algorithms and creating a reasonable and feasible plan for problem resolution.

What Impact Will Computational Thinking Have on Other Courses?

In our subsequent courses, we will encounter various fundamental programming courses, such as Python, JavaScript, and databases. As beginners entering the world of computer programming, we will have to learn multiple programming languages simultaneously. This may create significant pressure for students, and the solution is to apply computational thinking to address these challenges. For instance, when learning Python, the learning process can be broken down into distinct stages:

1.List all the key learning points on a whiteboard, spending time brainstorming.

2.Review the general skills acquired while learning other computer-related subjects, including concepts and logic.

3.Utilize abstract methods to transform the learning process into steps, covering basic knowledge, definitions, classes, frameworks, and databases. Understand the most crucial aspects of each step and practice them.

4.Finally, organize your study time according to your plans and future career goals, prioritizing the acquisition of essential knowledge and practical projects. In your spare time, you can revisit other branches of study.

These revisions aim to enhance clarity and readability while maintaining the original content and intent of your text.

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Reference:

• Yadav, A., Stephenson, C. and Hong, H., 2017. Computational thinking for teacher education. Communications of the ACM, 60(4), pp.55-62.
• Repenning, A., Basawapatna, A. and Escherle, N., 2016, September. Computational thinking tools. In 2016 IEEE symposium on visual languages and human-centric computing (VL/HCC) (pp. 218-222). IEEE.