AQA A-Level Computer Science Paper 2, June 2025: Question 10
4 marks ยท Medium difficulty ยท Short Answer
State two reasons why data is compressed, and explain why run length encoding (RLE) is more suitable for compressing images while dictionary-based compression is better suited for text.
Practise this questionQuestion
Question text
10.1 State two reasons why data is often compressed.
[2 marks]
Reason 1
Reason 2
10.2 Two different methods of compressing data are run length encoding (RLE) and
dictionary-based methods.
Explain why RLE is more suitable for compressing images and dictionary-based
methods are more suitable for compressing text.
[2 marks]
Mark scheme
Show the mark scheme
Total
Qu Pt Marking guidance
marks
10 1 Marks are AO1 (understanding) 2
Less storage space required;
A. less memory required
A. reduce file size
NE. less space required
Data can be transmitted more quickly // in less time;
A. less bandwidth required to transmit data
A. reduces cost of sending using a metered connection
NE. easier to transmit
More data/files can be fitted on a storage device with a given capacity (A. size);
A. examples of devices and capacities
A. data/file can be used on a service with a size limit eg email attachments
Max 2
Total
Qu Pt Marking guidance
marks
10 2 Marks are AO1 (understanding) 2
RLE suitable for images (1 mark):
In (some) images it is likely that adjacent pixels will be the same colour;
A. likely to be multiple pixels of same colour in a row as BOD
NE. adjacent values are likely to be the same
Dictionary based suitable for text (max 1 mark):
Repetition will be of words/groups of character/sequences of symbols/substrings;
The repeating data is likely to be spread throughout the text;
A. repeating data is unlikely to be adjacent identical characters/words/groups of
characters
A. never/rarely more than two adjacent letters/words that are the same
How to answer it
Data Compression: Purpose, RLE, and Dictionary Encoding
This question assesses fundamental AO1 knowledge of lossless data compression:
- The practical advantages of reducing file size (storage efficiency, transmission speed, and bandwidth consumption).
- How structural differences between media types (adjacent repeated pixels in images vs. repeating words/patterns spread across text) determine the suitability of Run Length Encoding (RLE) versus Dictionary-based compression.
Reasons Why Data is Compressed
State two reasons why data is often compressed.
โ Acceptable Answers (Any Two)
- Storage reduction: Takes up less storage space / less memory / reduces overall file size.
- Faster transmission: Data can be transmitted more quickly / in less time across a network.
- Bandwidth efficiency: Uses less network bandwidth / lowers transmission costs on metered connections.
- Device/Service capacity: Allows more files to fit on a fixed-capacity drive, or allows files to meet size limits (e.g. email attachment limits).
โ Common Errors & Vague Language
- "Less space required" – Not Enough (NE). You must state storage space, memory, or file size.
- "Easier to transmit" – Not Enough (NE). Too vague; explain why (e.g. "faster transmission", "uses less bandwidth").
- Confusing compression with encryption (e.g. claiming it makes data more secure).
๐ง Exam Technique: The Two Pillars of Compression
Whenever an exam asks why compression is used, always separate your thoughts into Storage and Transmission:
- Storage: Smaller footprint on secondary storage (SSD, HDD).
- Transmission: Less time and less bandwidth required over a network.
Suitability: RLE for Images vs. Dictionary for Text
Explain why RLE is more suitable for compressing images and dictionary-based methods are more suitable for text.
โ Mark Scheme Criteria
- RLE for images (1 mark):
In images, it is common to have runs of adjacent pixels that are the same colour (multiple consecutive pixels of identical value). - Dictionary methods for text (1 mark):
In text, repetition consists of recurring words, sequences of characters, or substrings that are spread throughout the document (rarely consecutive/adjacent).
๐ก Why the Algorithms Work This Way
- RLE (Run Length Encoding): Stores a data value alongside a count of consecutive occurrences (e.g. 5 Blue, 12 Red ). If adjacent values are not identical, RLE can actually increase file size due to storing count overheads.
- Dictionary (e.g. LZW): Builds an indexed table of repeated tokens (words/phrases) and replaces occurrences anywhere in the file with compact numerical codes.
โ Common Errors in 10.2
- Omitting "Adjacent" / "Consecutive": Saying "images have lots of pixels the same colour" is insufficient without noting they occur in contiguous runs (side-by-side).
- Forgetting "Pixels": Writing "adjacent values are the same" without context was rejected. Always contextualise to pixels and colours.
- Failing to contrast text structure: Overlooking that English text rarely has consecutive identical words (e.g. you rarely write "the the the"), meaning RLE would fail, whereas dictionary methods locate identical tokens separated across paragraphs.
๐ง Top-Scoring Model Answer
"Images frequently contain large blocks of identical, adjacent pixels of the same colour, which allows RLE to encode them efficiently as single count-colour pairs."
"In contrast, text contains repeating words and substrings distributed throughout the text rather than next to each other, making dictionary methods ideal as they substitute recurring non-adjacent patterns with short pointers."
Topics
4.5 Fundamentals of data representation ยท 4.5.6 Representing images, sound and other data
Question and mark scheme from the AQA A-Level Computer Science examination, Paper 2, June 2025. QuestionVault is an independent revision resource; questions remain the copyright of the awarding body.