AQA A-Level Computer Science
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Course version · 601/4569/9Version from Sept 2015Change version
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Explore your topics
14 topics
Course topics14 topics
- Big Data16 objectives
- Consequences of uses of computing25 objectives
- Fundamentals of data structures51 objectives
- Fundamentals of programming53 objectives
- Fundamentals of computer systems53 objectives
- Fundamentals of data representation46 objectives
- Fundamentals of databases26 objectives
- Fundamentals of communication and networking26 objectives
- Fundamentals of algorithms33 objectives
- Fundamentals of computer organisation and architecture25 objectives
- Systematic approach to problem solving21 objectives
- Fundamentals of functional programming24 objectives
12 of 14 shown
Assessment and exam guidance
What Gets Top Grades
Knowledge & Understanding
Demonstrates comprehensive and accurate knowledge
- Uses correct subject-specific terminology
- Shows detailed understanding of concepts
- Makes accurate connections between topics
- Demonstrates depth beyond surface-level knowledge
Application
Applies knowledge effectively to new contexts
- Selects relevant knowledge for the question
- Adapts understanding to unfamiliar scenarios
- Uses examples appropriately
- Shows awareness of context
Analysis & Evaluation
Develops sophisticated analytical arguments
- Constructs logical chains of reasoning
- Considers multiple perspectives
- Weighs evidence to reach justified conclusions
- Acknowledges limitations and nuances
Key Command Words
Give a single fact or term
Name, select, or recognise
Set out main features briefly
Give an account of what something is like or what happens
Give reasons with developed cause→effect chains
State similarities AND differences (both required)
Examine in detail showing cause→effect→consequence chains
Weigh up BOTH sides, reach JUSTIFIED conclusion
Make judgments about importance with justification
Show formula→substitution→calculation→answer with units
Tips and common mistakes
Common Exam Mistakes
Pitfalls to avoid in your exams
- •Confusing Hadoop with Spark.
- •Not understanding the map and reduce phases.
- •Ignoring fault tolerance mechanisms.
- •Confusing privacy with data security; focusing solely on hacking rather than legal and ethical data handling.
- •Failing to differentiate between government surveillance and corporate data collection, treating them as identical.
- •Presenting a one-sided argument on censorship without considering the complexities of content moderation.
- •Overlooking the global nature of the internet and the jurisdictional challenges in enforcing privacy laws.
- •Confusing predictive and prescriptive analytics: predictive forecasts future events, while prescriptive recommends specific actions to influence those events.
Top Examiner Tips
Expert advice for exam success
- •Use diagrams to explain MapReduce flow.
- •Highlight Spark's in-memory processing advantage.
- •Give real-world examples like log analysis.
- •Include specific, named case studies to ground your arguments (e.g., Edward Snowden, Cambridge Analytica, China's firewall).
- •Structure your response clearly: start with definitions, then present arguments for and against, and conclude with a reasoned judgment.
- •Use terminology accurately: distinguish between 'privacy', 'anonymity', 'confidentiality', and 'security'.
- •When discussing legislation, mention its specific principles (e.g., GDPR's right to be forgotten).
- •Structure responses by clearly addressing each analytics type with a definition, key question, techniques, and a concrete example.
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