Computational thinking

Abstraction

Ignoring unnecessary information about a problem to focus on the main features of it

Why is abstraction useful?

It is used to help focus on the essential parts of the problem

Decomposition

• Breaking down a complex problem into smaller subproblems

• Can be used to assign tasks to multiple people working on a problem simultaneously

• Can lead to easier debugging

Divide and conquer

A method of continuously decomposing a problem until each subproblem is atomic

Why is decomposition useful?

• Allows concurrent tasks to be identified, hence speeding up time for project execution

• Allows teams to work together more easily

Pattern recognition

• Identifying any form of patterns/correlation within problems

• Can be used to apply similar approaches to different problems

How can pattern recognition be used for drawing an equilateral triangle in Pseudocode?

• An equilateral triangle has 3 equal sides and 3 equal external angles

• So, you can use iteration to repeat one step 3 times

Generalisation

Adapting a solution to a problem to fit for several similar problems

How can you generalise drawing regular polygons in Pseudocode?

• External angles can be calculated using 360/sides

• Use iteration to draw the side lengths and external angles (sides) amount of times

Logical reasoning

Using facts and evidence to reach a valid conclusion

Debugging

Finding the reason why something isn’t working as expected, then fixing it

How is debugging related to computational thinking?

• Abstraction can be used to focus on the main problem

• Decomposition can be used to decompose the problem to simplify a solution

Evaluation

Checking if a solution solves the problem it was designed to solve

What are some factors you should evaluate about a solution?

• If the output is correct

• If the solution works with different types of data

• If there exists another solution which is “better”