Understanding of these principles and how they are used to define and refine problems
What you need to know
Computational thinking is a set of problem-solving techniques used in computer science. The three key principles are decomposition (breaking problems into smaller parts), abstraction (removing unnecessary detail to focus on what matters), and algorithmic thinking (creating step-by-step solutions). These principles help programmers define, understand, and solve complex problems systematically.
Key points
Definition:Decomposition: breaking a problem into smaller, manageable parts that can be solved individually.
Definition:Abstraction: removing unnecessary detail to focus on relevant information.
Definition:Algorithmic thinking: identifying the main steps needed to solve the problem and the SEQUENCE that the steps are completed in.
Pattern recognition identifies similarities or recurring features in problems, allowing existing solutions to be reused.
Exam Tip:You must apply these concepts IN CONTEXT. Generic definitions alone will not score marks — explain HOW abstraction or decomposition is used in the given scenario.
Abstraction example: 'storing year groups instead of full dates of birth' or 'showing student IDs instead of full details'.
Decomposition example: 'splitting the program into separate subroutines for each event' or 'breaking the database into separate tables'.
Decomposition makes problems easier to debug, maintain, and split across a team of developers.