The Definition of Computational thinking
As previously mentioned, computational thinking can be broken down into the following 4 parts.
decomposition-breaking down a complex problem or system into smaller, more manageable parts.
pattern recognition-looking for similarities among and within problems.
abstraction-focusing on the important information only, ignoring irrelevant detail.
algorithms-developing a step-by-step solution to the problem, or the rules to follow to solve the problem.
Phonebook
A phone book would contain names and telephone numbers.
To use it, would require looking up a name in an alphabetically sorted list.
The list would be broken down across pages.
The process of looking up a name is what we know in CS as Binary Search.
THEME PARK QUEUE
You and a friend are visiting a theme park for the day.
There are 4 ticket booths, with separate queues for each.
The process mirrors that of Parallel Processing in CS
Computational thinking is an essential skill that does not only belong to computer scientists. We can extend it to a wider field and apply them in many more ways.
Mathematics
For example, Machine learning, as an application of computational thinking, has already transformed statistics. In terms of mathematical scale and dimensionality, the scale at which statistical learning is used for all kinds of problems was unimaginable only a few years ago. And Computer scientists have been hired in the statistics departments of various organisations.
Biology
What's more, computational biology is changing the way biologists think. Computer scientists are increasingly interested in the biological sciences and want data structures and algorithms that represent the structure of proteins in ways that reflect their functions.
Other fields
Computational game theory is changing the way economists think.
Nano computing is changing the way chemists think
Quantum computing is changing the way physicists think.
Understanding
Computers are boring and repetitive, whereas the human mind is full of enthusiasm and imagination. But we can solve problems through computational thinking. As mentioned above, computer thinking is being used in all areas of life.
If we want a hot cup of tea, we can divide it into preparatory steps and practical steps. First prepare the tea bags, tea cups, kettle, and water. Then boil the water, put the tea bags into the cups and finally pour in the boiling water. This straightforward process demonstrates computational thinking.
In our future studies and work, we can all apply this kind of thinking to solve problems, transforming difficult problems into small, solvable steps.
In our future studies and work, we can apply this kind of thinking to solve problems, transforming difficult problems into small, solvable steps. Then looking for commonalities in these types of questions. Ignoring the useless details and creating a flow chart like the one on the homepage. Follow the logic, execute it step by step and then finally accomplish our goal.
Essentially, We can use this method to build our problem-solving system and integrate computational thinking into our lives so that when we encounter a difficult problem, we can come up with a solution instead of being stagnant.