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      Lesson details

      Learning outcome

      I can describe and use Huffman coding to create a compressed representation of data.

      Key learning points

      1. Huffman coding is a lossless compression technique.
      2. Huffman coding assigns shorter bit sequences to more frequent characters and longer sequences to less frequent ones.
      3. A Huffman tree is used to visually represent the encoding scheme to create compressed data.
      4. A Huffman tree sent alongside compressed data adds overhead and can reduce the overall compression efficiency.

      Keywords

      • Huffman tree - a special kind of binary tree used to create short binary codes for data, based on how often each piece of data appears

      • Encoding - putting a sequence of characters into an agreed format

      • Frequency - how often a piece of data appears in a file

      Common misconception

      The Huffman tree is the compressed file.

      The compressed file is a sequence of bits, and the tree is the representation of the coding system.

      Teacher tip

      Break Huffman coding into small, manageable steps and have students practice each one separately. A step-by-step approach reduces cognitive overload, reinforces understanding at each stage, and helps all learners feel successful even with a complex concept like data compression.

      Licence

      This content is © Oak National Academy Limited (2025), licensed on Open Government Licence version 3.0
      except where otherwise stated. See Oak's terms & conditions
      (Collection 2).

      Lesson video

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      Prior knowledge starter quiz

      6 Questions

      Q1.
      What is the purpose of run length encoding?

      Correct answer: to reduce the size of repeating sequences of data
      to increase file size
      to add redundancy to data
      to encrypt data

      Q2.
      What does redundancy in data refer to?

      essential information
      encrypted data
      random patterns in data
      Correct answer: repeated or extra data that isn’t needed

      Q3.
      Which of the following is a characteristic of lossless compression?

      Data is permanently removed.
      Correct answer: Data can be perfectly reconstructed.
      File size is always reduced.
      It works only with images.

      Q4.
      What type of data is best suited for run length encoding?

      randomised data
      encrypted data
      data with no structure
      Correct answer: data with repeating patterns

      Q5.
      Why might run length encoding not always reduce file size?

      It removes all data.
      It adds additional data.
      Correct answer: It depends on the amount of redundancy in the data.
      It works only with text data.

      Q6.
      What does 'lossless' mean in data compression?

      Correct answer: Data is compressed without losing any information.
      Data is encrypted.
      Data is permanently removed.
      Data is randomly altered.

      6 Questions

      Q1.
      What is Huffman coding?

      a method for encrypting data
      a way to create random data
      a lossy compression technique
      Correct answer: a lossless compression technique

      Q2.
      Match each term with its correct description.

      Correct Answer:Huffman tree,a special kind of binary tree used to create short binary codes
      Correct Answer:encoding,changing data into a different format
      Correct Answer:frequency,how often a character appears in data
      Correct Answer:lossless,when data is perfectly reconstructed

      Q3.
      What does a Huffman tree represent?

      the compressed file
      Correct answer: the encoding scheme
      a sequence of bits
      the file size

      Q4.
      Arrange the steps for creating a Huffman tree in the correct order.

      1 - Calculate the frequency of each character.
      2 - Build the tree.
      3 - Assign bit sequences based on the tree structure.

      Q5.
      What is the main purpose of Huffman coding?

      to increase file size
      Correct answer: to compress data efficiently
      to encrypt files
      to remove all data redundancy

      Q6.
      Order the following characters based on their bit sequence length in Huffman coding (shortest to longest).

      1 - C (frequency: 15)
      2 - A (frequency: 10)
      3 - B (frequency: 5)
      4 - D (frequency: 2)

      To help you plan your 10 computer science lesson on: Huffman coding, download all teaching resources for free and adapt to suit your pupils' needs...