Computational Thinking Skills
Computational Thinking Skills
Introduction to Computational Thinking
- Computational thinking is a problem-solving process.
- It includes formulating problems in a way that a computer can effectively carry out.
- A core set of four skills form the basis of computational thinking: decomposition, pattern recognition, abstraction, and algorithms.
Decomposition
- Decomposition involves breaking a complex problem down into more manageable parts.
- Each part can be addressed individually, making the problem easier to understand.
- Decomposition is essential in developing complex computer programs, it allows different sections of the program to be worked on simultaneously.
Pattern Recognition
- Pattern recognition is the identification of similarities or patterns among small, decomposed problems that can help us solve more complex problems more efficiently.
- In programming, recognising patterns can save time and reduce complexity.
Abstraction
- Abstraction involves filtering out - or ignoring - the unimportant details of the problem, so that you can focus on what really matters.
- This helps in understanding and solving the problem without getting overwhelmed by too much information.
Algorithms
- An algorithm is a step-by-step procedure to solve problems or achieve a specific task.
- Algorithms are used in programming to define a sequence of instructions for the computer to follow.
- Creating algorithms involves sequencing, selection (using IF, ELSE statements) and iteration (using loops like FOR and WHILE).
Applying Computational Thinking in Programming
- Apply decomposition when writing code by breaking it down into functions or methods.
- Use pattern recognition when debugging to identify common errors or to reuse parts of the code.
- Abstraction is useful for managing complexity in large code projects, by focusing on the important parts and ignoring the rest.
- Algorithm design is essential in programming as it involves creating precise instructions for the computer to follow.