Computational thinking is the framework computer scientists use to examine problems whose solutions can be represented computationally. It rests on four fundamental concepts: abstraction, algorithmic design, decomposition and pattern recognition. This unit defines each one and shows how they work together across real computer science domains. (B1 is common to SL and HL, with no AHL-only material.)
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What computational thinking is
It is a way of thinking about problems where solutions can be represented computationally, and it helps you analyse how systems with many components work together.
It rests on four key ideas: abstraction, algorithmic design, decomposition and pattern recognition.
It does not necessarily involve programming. The guide describes it as a toolkit of problem-solving techniques.
Practising it makes you a better problem solver in computer science and in other disciplines.
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1. Which fundamental concept of computational thinking is defined as filtering out unnecessary detail to focus on the essential features of a problem?
2. A developer breaks a large customer relationship management system into separate modules such as lead tracking and customer management, aiming for each module to have one clear responsibility. Which concept is being applied?
3. Looking at the sequence 2, 4, 6, 8 and noticing that each term is 2 greater than the one before, so the next term can be found with next = current + 2, is an example of which concept?
4. Which statement about computational thinking is correct according to the IB guide?
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