Computational Thinking

What Computational Thinking covers

Computational Thinking is examined in Paper 1, Principles of Computer Science. It covers decomposition, abstraction and subprograms, algorithms, flowcharts and pseudocode, operators and trace tables, logic errors, test data and efficiency, searching and sorting algorithms and truth tables.

The 6 subtopics

Each one has its own page.

• Decomposition, abstraction and subprogramsDecomposition and abstraction with worked examples from maps, games and school reports, and how subprograms save time, simplify testing and maintenance, and can be reused.Open →
• Algorithms, flowcharts and pseudocodeAlgorithms and informal pseudocode, the six flowchart symbols, sequence, selection, repetition and iteration, input, processing and output, variables, constants, arrays and records.Open →
• Operators and trace tablesModulus, integer division and exponentiation with worked values, the order of operations, relational and logical operators in conditions, and trace tables for short algorithms.Open →
• Logic errors, test data and efficiencySyntax, logic and runtime errors, finding and fixing logic errors in algorithms, normal, boundary and erroneous test data, and judging efficiency by compares, passes and memory.Open →
• Searching and sorting algorithmsLinear and binary searches traced through short lists, worst-case compares, and bubble and merge sorts worked step by step, with when each is the better choice.Open →
• Truth tablesAND, OR and NOT, truth tables with up to three inputs, worked values of combined expressions, and alarm and heating problems solved with logic.Open →

What you need to know

Answer each one before you reveal it.

Take Computational Thinking further

The same content, four other ways.

Commonly confused

Pairs that lose marks when they are blurred together.

• Decomposition vs Abstraction

  Decomposition: breaking a problem down into smaller, more manageable sub-problems. Abstraction: removing unnecessary detail so that only the essential features remain.

• Linear search vs Binary search

  Linear search: checking each item in turn from the start of a list until the target is found. Binary search: repeatedly comparing the middle item of a sorted list and discarding half of it.

• Bubble sort vs Merge sort

  Bubble sort: repeatedly swapping adjacent items that are out of order until a pass makes no swaps. Merge sort: splitting a list into single items and then combining them back together in order.

Questions from this topic

Each one with the model answer underneath.

1. 1

   Define decomposition.

   Model answer

   Decomposition is breaking a problem down into smaller sub-problems. Each sub-problem is simple enough to understand and solve on its own.

2. 2

   Define abstraction.

   Model answer

   Abstraction is removing detail that does not matter to the problem being solved. Only the features needed for the solution are kept.

3. 3

   Why does decomposition make a large problem easier to solve?

   Model answer

   A small sub-problem is easier to understand than the whole problem at once. Each part can be solved, written and tested separately.

4. 4

   Explain how decomposition helps a team of programmers.

   Model answer

   Different sub-problems can be handed to different programmers. The team can then work on several parts at the same time.

5. 5

   A map of a railway network shows the stations and the lines between them but not the real distances. Which technique does the map use, and why?

   Model answer

   The map is an abstraction of the real network. A passenger only needs the order of stations and the connections, so the rest is left out.

6. 6

   A program models a game of noughts and crosses. Which details of a real game would abstraction remove?

   Model answer

   Abstraction would remove the pen, the paper and the players’ appearance. The model keeps only the 3 × 3 grid, the marks and whose turn it is.

What is inside Levo

Six ways to work the same material.

Computational Thinking revision questions

What does Computational Thinking cover in Edexcel GCSE Computer Science?

6 subtopics: decomposition, abstraction and subprograms, algorithms, flowcharts and pseudocode, operators and trace tables, logic errors, test data and efficiency, searching and sorting algorithms and truth tables. Each one has its own page with questions and model answers.

How is Computational Thinking organised?

By the Edexcel 1CP2 specification, subtopic by subtopic, so it matches the order you are taught it in.