Computational thinking

Computational thinking means approaching a problem in a way that can lead to a clear solution a computer can carry out. It includes decomposition, abstraction and algorithmic thinking.

Decomposition breaks a large problem into smaller parts that are easier to understand and solve.

Example: a school lunch-order app

1. Record each pupil's meal choice.
2. Check choices and count meals.
3. Send totals to the kitchen.
4. Show each pupil their order.

Each part can be designed and tested separately, then joined into the complete system.

Abstraction keeps the details needed to solve a problem and ignores irrelevant details.

Example: to plan the shortest walking route between classrooms, a school map needs room locations and paths. It can ignore wall colours, desk positions and the names of pupils. The simplified map is easier to use for route planning.

Algorithmic thinking describes a solution as a precise sequence of steps, including choices and repeats where needed.

Example: count lunch orders

1. Set total to 0.
2. For each order, add 1 to total.
3. Display total.

The steps are in order, and another person could follow them to get the same answer.