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Computer Science

Computer Science
Type of Qualification:
A Level
Exam Board:
Grade 6 GCSE Computer Science and GCSE Maths

Course Content

Computer Systems will cover the characteristics of contemporary systems architecture and other areas including the following:

  • The characteristics of contemporary processors, input, output and storage devices
  • Software and software development
  • Exchanging data
  • Data types, data structures and algorithms
  • Legal, moral, cultural and ethical issues.


Algorithms and Programming will cover computational thinking:

  • Elements of computational thinking
  • Programming and problem solving
  • Pattern recognition, abstraction and decomposition
  • Algorithm design and efficiency
  • Standard algorithms

Style Of Assessment

Year 12 Internal Assessments

Computing Principles: 1 hour 15 minute exam

Algorithms and Problem Solving: 1 hour 15 minute exam
A Level Papers & NEA
A Level Paper 1: Computer Systems (2.5 hours) 40% of the final mark

A Level Paper 2: Algorithms and Programming (2.5 hours) 40% of the final mark
Non-examined Assessment: 20% of the final mark

Whose kind of course?

A Level Computer Science is for you if you are interested in developing your skills in Computing after GCSE. It expands on topics from GCSE, going in to more depth (e.g. in Logic Gates we look at more different types of gates and combining more gates together). New material includes looking at State Machines

Programming will continue focusing on developing skills in Python, or learning a new language such as Visual Basic or C# (a language commonly used by today’s software engineers). New concepts are introduced, such as Object Oriented Programming in both languages.

Career Prospects

The content taught and the transferable problem solving skills acquired in Computer Science are highly sought after across the world of work. They would also help you to continue with further studies in both Engineering & Computer Science at university.

Competence in computer programming is especially useful in any data-oriented profession.