Encoding, Media and Compression
Explaining how characters, images and sound become bit patterns and how sampling, colour depth, resolution and compression affect quality and size.
How to study A-level Computer Science
Define the problem and representation, trace the state change, justify the algorithm or architecture, then test the result against requirements, evidence and constraints.
Core concepts
Concept 1
An encoding maps symbols or measurements to bit patterns according to an agreed standard.
Exam cue: Use dimensions, bit depth, sampling rate and duration with consistent units in size calculations.
Concept 2
Sampling rate, sample resolution, image dimensions and colour depth influence fidelity and storage requirements.
Exam cue: Separate representation parameters from compression ratio or file-format overhead.
Concept 3
Lossless compression preserves all information; lossy compression discards selected information to reduce size further.
Exam cue: Judge compression by the intended use, tolerated loss and resource constraint.
Risk pitfalls and guardrails
Assuming a displayed character has one universal byte representation.
Guardrail: Do not substitute a memorised definition or generic advantage until you have identified the input, state, stakeholder and constraint in the task.
Confusing image resolution with colour depth.
Guardrail: Do not substitute a memorised definition or generic advantage until you have identified the input, state, stakeholder and constraint in the task.
Calling compressed data encrypted.
Guardrail: Do not substitute a memorised definition or generic advantage until you have identified the input, state, stakeholder and constraint in the task.
Memory anchors
Character Encoding
A character encoding maps characters to numeric codes and bit patterns.
Sampling Rate
Sampling rate is the number of samples taken per unit time.
Sample Resolution
Sample resolution is the number of bits used for each sampled value.
Lossless Compression
Lossless compression allows the original data to be reconstructed exactly.
Lossy Compression
Lossy compression removes information judged less important for the intended use.
Checkpoint rule
Do the check-up only after you can summarize each concept in one sentence and identify one dangerous pitfall from memory.
Knowledge Check (after reading)
Short check-up to confirm understanding of this module.
Check-up Questions
Why is Unicode needed in addition to early ASCII?
What does a character encoding define?
Answer all questions to submit.
Next step personalized recommendations
Continue learning
Move forward only after this module is stable.
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