Computer Science

Syllabus: AQA A Level Computer Science

1 - Why study  A Level Computer Science?

Computer Science is a rapidly growing field, and students who study it can gain valuable skills and knowledge that are highly sought after in today's job market. A level Computer Science provides a solid foundation in programming languages, algorithms, data structures, and other core computer science concepts that are essential for many careers in technology.

Computer Science can prepare students for further education in computer science-related fields, such as computer engineering, software development, artificial intelligence, and cybersecurity. It also helps students develop critical thinking, problem-solving, and analytical skills that are transferable to many other industries and disciplines.

The subject can help students understand and navigate the complex digital landscape, enabling them to make informed decisions and contribute to the development of innovative solutions that can benefit society as a whole.

2 - What will you study?

Year 12

Paper 1 - Fundamentals of programming
Paper 1 - Fundamentals of data structures
Paper 1 -Theory of computation
Paper 2 - Fundamentals of data Representation
Paper 2 - Fundamentals of computer systems
Paper 2 - Fundamentals of computer organisation and architecture
Paper 2 - Fundamentals of databases
Paper 2 - Consequences of uses of computing

Year 13

Paper 1 - Fundamentals of algorithms
Paper 2 - Fundamentals of communication and networking
Paper 2 - Big Data
Paper 2 - Fundamentals of functional programming
NEA (Non-Exam Assessment – A level programming project) & Systematic approach to problem
Exam preparation

3 - How will you be assessed?

Paper 1: on screen exam, 2:30 hours; 40%
Paper 2: written exam, 2:30 hours; 40%
Non-Examined Assessment (NEA): 20%

3 - What skills will you develop?

  • Programming Skills: Programming using a high-level computing language - writing efficient, bug-free code and understanding programming concepts such as data types, variables, control structures, and functions.
  • Computational Thinking: logically breaking down complex problems into smaller, more manageable parts. Developing algorithms and using data structures to store and manipulate data.
  • Problem-Solving: identifying and solving problems systematically. Applying computational thinking to real-world problems and develop solutions using programming.
  • Data Analysis: how to collect, process, and analyse data using programming, and how to visualize data using graphs and charts.
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