Principles of Computational Thinking

It involves three key principles: Abstraction, Decomposition, and Algorithmic Thinking. These principles are used to define and refine problems and are essential for computer programming and system design.

Abstraction

• Definition: Abstraction involves simplifying a problem by focusing only on the important details and ignoring irrelevant information.
• How it's used: When solving a problem, we remove unnecessary complexities to focus on the essential features. For example, when designing a game, you might abstract away the details of how the character walks, focusing only on what direction they should move.
• Purpose: This helps make problems easier to solve by reducing unnecessary details, allowing for more focused problem-solving.

Decomposition

• Definition: Decomposition is the process of breaking a large, complex problem into smaller, more manageable parts.
• How it's used: If you're building a website, you would break the project down into smaller tasks such as designing the layout, writing the code, and managing user interactions.
• Purpose: By breaking down problems, it's easier to solve each part individually, leading to a more efficient and structured approach to problem-solving.

Algorithmic Thinking

• Definition: Algorithmic thinking is the process of creating a step-by-step solution or set of rules to solve a problem.
• How it's used: This involves designing a clear and logical sequence of instructions to complete tasks, such as writing an algorithm to sort a list of numbers or navigating a robot through a maze.
• Purpose: Algorithmic thinking helps ensure that the problem-solving process is repeatable, logical, and efficient, leading to solutions that can be implemented by both humans and computers.