A Level Computer Science Topics by Exam Board: Full List

If you’re studying A Level Computer Science, the three main exam boards to deliver the qualification are: OCR, AQA, and CIE.

But how are they different? In this article, we will show you which topics each exam board covers and how they are grouped in assessment. By the end, you will know exactly what topics to revise, and discover high-quality revision resources to support you.

OCR A Level Computer Science Topics

1. Characteristics of contemporary processors, input, output, and storage devices

This topic explores the essential components of a computer system, including processors, input/output devices, and storage technologies. You’ll delve into how processors execute instructions through the fetch-decode-execute cycle and how factors like clock speed, cache, and cores impact performance. 

For example, have you ever wondered why your phone’s performance improves with each new model? This section explains the technology behind such improvements. 

You’ll also examine different processor architectures and storage types, gaining insights into real-world applications like GPUs in gaming and beyond.

Topics include:

• Structure and function of the processor

• Types of processor

• Input, output, and storage
  

2. Software and software development

This topic introduces you to the inner workings of software and the methods used to develop it. You’ll explore how operating systems manage resources, including how they handle multitasking, memory, and interrupts. 

Imagine your computer juggling multiple tasks, like streaming music while running a game – this section explains how that happens. 

You’ll also learn about software development methodologies, such as agile and waterfall, and when each is most effective. Plus, you’ll uncover the crucial role of translators like compilers and interpreters, which make programming languages usable by computers.

Topics include:

• Systems software

• Applications generation

• Software development

• Types of programming language
  

3. Exchanging data

This topic examines how data is exchanged between systems, focusing on compression, encryption, databases, and networking. 

Have you ever wondered how messages travel securely across the Internet? In this course, you’ll learn about encryption techniques, such as symmetric and asymmetric encryption, that make this possible. 

This section also covers relational databases, including SQL and normalisation, and explores network technologies such as the TCP/IP stack and protocols like HTTP and HTTPS. You’ll even get to understand how search engines rank web pages using algorithms like PageRank.

Topics include:

Compression, encryption, and hashing

• Databases

• Networks

• Web technologies
  

4. Data types, data structures, and algorithms

This topic examines how data is represented, organised, and manipulated within computer systems. You’ll learn about data types such as integers, floating-point numbers, and Boolean values, as well as complex structures like stacks, queues, and binary trees. 

For instance, did you know that social media apps use algorithms to decide what posts you see first? This section explains how such algorithms work, from sorting and searching data to manipulating Boolean expressions.

Topics include:

• Data types

• Data structures

• Boolean algebra
  

5. Legal, moral, cultural, and ethical issues

This topic examines the broader societal implications of digital technology. You’ll explore key legislation like the Data Protection Act and the Computer Misuse Act and their role in safeguarding personal information. Ethical debates around topics such as artificial intelligence and automated decision-making are also covered. 

For example, what happens when algorithms used in job recruitment show bias? This section encourages you to think critically about such challenges and the responsibilities of technologists in shaping the future.

Topics include:

• Computing-related legislation

• Moral and ethical issues
  

6. Elements of computational thinking

This topic introduces the foundational principles of computational thinking, equipping you with the skills to break down complex problems and design effective solutions. 

You’ll explore the importance of abstraction, preconditions, and reusable program components, and learn how to think procedurally, logically, and concurrently to approach problems from different angles. For example, you’ll practise identifying the steps needed to solve problems and evaluate the benefits of concurrent processing.

Topics include:

• Thinking abstractly

• Thinking ahead

• Thinking procedurally

• Thinking logically

• Thinking concurrently
  

7. Problem solving and programming

This topic focuses on how computers can solve problems and how programming techniques can bring solutions to life. You’ll learn key constructs like sequence, iteration, and recursion while exploring modular programming, parameter passing, and the use of an integrated development environment (IDE). 

Object-oriented programming techniques will also be covered, giving you a well-rounded toolkit to tackle complex challenges. Additionally, you’ll delve into computational methods like divide and conquer, heuristics, and data mining to address real-world problems effectively.

Topics include:

• Programming techniques

• Computational methods
  

8. Algorithms

This topic examines the role of algorithms in solving problems and explores standard algorithms used across computing. You’ll learn to analyse and design algorithms, evaluate their efficiency using Big O notation, and compare their complexity. 

Practical applications include implementing and optimising algorithms for data structures like stacks, queues, and trees, as well as understanding traversal techniques. You’ll also study standard algorithms like bubble sort, quick sort, and Dijkstra’s shortest path to understand their practical use cases.

Topics include:

• Analysis and design of algorithms

• Algorithm efficiency and complexity

• Algorithms for data structures

• Standard algorithms

What is Covered in OCR A Level Computer Science Assessment?

Revision Resources for OCR A Level Computer Science

For high-quality revision resources for the OCR A Level Computer Science exam, visit the OCR homepage for access to:

• Revision notes

• Exam questions

• Past papers

AQA A Level Computer Science Topics

1. Fundamentals of programming

This topic focuses on the essential concepts and techniques for programming. You will explore data types such as integers, floats, Booleans, strings, and arrays, as well as user-defined types. 

Programming concepts like variables, constants, iteration, and subroutines are combined to create structured programs. You'll also learn key operations including arithmetic, relational, and Boolean, alongside advanced techniques like recursion and exception handling. 

These foundational skills provide the building blocks for writing efficient, maintainable code.

Topics include:

• Data types and user-defined data types

• Programming concepts and constructs

• Arithmetic, relational, and Boolean operations

• Constants, variables, and exception handling

• Subroutines, parameters, and recursion
  

2. Programming paradigms

This topic introduces you to the characteristics of procedural and object-oriented programming. You will gain experience using hierarchy charts for procedural design and learn about classes, objects, encapsulation, inheritance, and polymorphism in object-oriented programming. 

The focus is on understanding the principles and advantages of each paradigm, with practical application in designing structured, reusable code.

Topics include:

• Procedural programming

• Object-oriented programming concepts and principles
  

3. Fundamentals of data structures

Here, you’ll delve into the use and implementation of data structures like arrays, stacks, queues, graphs, trees, and hash tables. You’ll also explore abstract data types and learn to create and manipulate static and dynamic data structures. 

This section builds a solid understanding of how data is organised, stored, and processed efficiently in programs.

Topics include:

• Abstract data types and data structures

• Single and multi-dimensional arrays

• Operations on queues, stacks, graphs, and trees

• Hash tables, dictionaries, and vectors
  

4. Fundamentals of algorithms

This topic explores algorithm design and analysis. You'll learn to trace and compare algorithms, understand their time complexity using Big-O notation, and apply algorithms like searching, sorting, and optimisation. 

The topic also covers tree and graph traversal methods, as well as Reverse Polish Notation and its practical applications.

Topics include:

• Algorithm design, analysis, and efficiency

• Graph and tree traversal

• Searching and sorting algorithms

• Optimisation algorithms like Dijkstra’s shortest path
  

5. Theory of computation

This section focuses on abstraction and the principles of automating problem-solving. You'll study finite state machines, regular expressions, and the Backus-Naur Form to understand computation limits. 

Key concepts include problem-solving, algorithm correctness, and efficiency, alongside exploring tractable and intractable problems and the Halting problem.

Topics include:

• Abstraction, automation, and procedural decomposition

• Finite State Machines and regular languages

• Computational complexity and limits of computation
  

6. Fundamentals of computer systems

This topic covers the interaction between hardware and software, including the roles of operating systems, utility programs, and translators. You'll learn about system software, machine-code, and assembly language, as well as the principles of logic gates, Boolean algebra, and hardware components.

Topics include:

• Hardware and software relationship

• Operating systems and system software

• Programming languages and translators

• Logic gates and Boolean algebra
  

7. Fundamentals of computer organisation and architecture

This topic explains the structure and functionality of computer systems. You'll study components such as the processor, memory, buses, and I/O controllers, along with von Neumann and Harvard architectures. 

The Fetch-Execute cycle, machine-code operations, and factors affecting processor performance are also covered.

Topics include:

• Internal hardware components and architectures

• Fetch-Execute cycle and processor instruction set

• Machine-code operations and addressing modes

• Factors affecting processor performance
  

8. Consequences of uses of computing

This section examines the ethical, legal, and social impacts of computing. You'll discuss issues like data privacy, intellectual property, and environmental effects, as well as the responsibilities of computer scientists in developing software and algorithms.

Topics include:

• Ethical, legal, and cultural issues

• Impact of computing on society
  

9. Fundamentals of communication and networking

This topic focuses on communication methods, networking principles, and the structure of the Internet. You'll learn about protocols, IP addressing, subnetting, and Internet security. Practical aspects include understanding wireless networking, firewalls, and encryption techniques.

Topics include:

• Communication methods and networking principles

• Internet structure, security, and protocols

• TCP/IP protocol layers and client-server models
  

10. Fundamentals of databases

This section covers database concepts, including relational models, normalisation, and SQL. You'll learn to design and implement relational databases, understand client-server systems, and manage concurrent access to ensure data integrity.

Topics include:

• Relational databases and normalisation

• Structured Query Language (SQL)

• Client-server database systems
  

11. Big Data

This topic introduces the concept of Big Data, including its challenges and opportunities. You'll explore distributed processing, functional programming, and the fact-based model for representing data. Key techniques for analysing unstructured data are also covered.

Topics include:

• Characteristics and challenges of Big Data

• Functional programming for distributed systems

• Fact-based data models and graph schemas
  

12. Fundamentals of functional programming

This section introduces the functional programming paradigm, emphasising higher-order functions, recursion, and immutability. You'll learn to apply functions like map, filter, and reduce, and explore functional approaches to problem-solving.

Topics include:

• Functional programming principles

• Writing functional programs

• List processing and operations
  

13. Systematic approach to problem-solving

This topic provides a structured framework for software development, including analysis, design, implementation, testing, and evaluation. You'll gain practical experience in applying systematic methods to develop robust and efficient solutions.

Topics include:

• Software development life cycle

• Analysis, design, implementation, and testing

• Evaluation of solutions

What is Covered in AQA A Level Computer Science Assessment?

Revision Resources for AQA A Level Computer Science

For high-quality revision resources for the AQA A Level Computer Science exam, visit the AQA homepage for access to:

• Past papers

CIE A Level Computer Science Topics

1. Information representation

This section explores how data is represented and stored in computer systems, covering binary, hexadecimal, character encoding, and multimedia formats. You’ll also learn about compression techniques for different types of data.

Topics include:

• Binary, denary, hexadecimal, and Binary Coded Decimal (BCD) number systems

• One’s and two’s complement representation and binary arithmetic

• Character encoding standards: ASCII, extended ASCII, and Unicode

• Bitmap and vector graphics

• Sound sampling and file size calculations

• Lossy and lossless compression methods (e.g., RLE)
  

2. Communication

This section covers how networks and the internet enable communication between devices, with a focus on topology, transmission methods, and security. You'll explore the hardware and protocols that underpin networking.

Topics include:

• LANs, WANs, and topologies (bus, star, mesh)

• Client-server vs peer-to-peer networking

• Wireless and wired networks, including Ethernet and CSMA/CD

• Cloud computing: public and private clouds

• IP addresses, subnetting, and DNS

• Network hardware: routers, NICs, WAPs

• Real-time and on-demand bit streaming
  

3. Hardware

This section explains the fundamental hardware components of a computer system and their roles, including input/output devices, memory, and embedded systems. You’ll also explore logic gates and their application in circuits.

Topics include:

• Input, output, and storage devices

• RAM vs ROM, SRAM vs DRAM, and types of ROM

• Embedded systems and monitoring/control systems

• Logic gates: AND, OR, XOR, NAND, NOR, NOT

• Constructing and interpreting logic circuits and truth tables
  

4. Processor fundamentals

This section focuses on CPU architecture, the Fetch-Execute cycle, and assembly language programming. You’ll learn about registers, addressing modes, and bit manipulation.

Topics include:

• Von Neumann architecture and the stored program concept

• Special purpose registers (e.g., PC, ACC, MAR)

• Fetch-Execute cycle and interrupt handling

• Assembly language, addressing modes, and instruction sets

• Bit manipulation: logical, arithmetic, and cyclic shifts

• Use of bit masking to control devices
  

5. System software

This section examines operating systems, language translators, and utility software. You’ll also explore the role of IDEs in software development.

Topics include:

• Operating system functions: memory, file, process, and hardware management

• Utility software: defragmentation, backup, compression

• Assemblers, compilers, and interpreters

• Features of an Integrated Development Environment (IDE)
  

6. Security, privacy, and data integrity

This section covers the methods and tools used to secure data, protect user privacy, and maintain data integrity in computer systems.

Topics include:

• Data security threats: malware, phishing, hackers

• Protection methods: encryption, firewalls, authentication

• Data validation (range checks, presence checks) and verification methods

• Differences between security, privacy, and integrity
  

7. Ethics and ownership

This section explores ethical considerations in computing, including intellectual property rights, professional ethics, and the impact of Artificial Intelligence.

Topics include:

• Professional ethics and organisations (e.g., BCS, IEEE)

• Copyright laws and software licensing

• Applications and implications of Artificial Intelligence (AI)
  

8. Databases

This section covers database concepts, including relational models, normalisation, and SQL. You’ll learn to design and implement relational databases, understand client-server systems, and manage concurrent access to ensure data integrity.

Topics include:

• Relational databases and normalisation (1NF, 2NF, 3NF)

• Structured Query Language (SQL)

• Client-server database systems and concurrent access control
  

9. Algorithm design and problem-solving

This section develops computational thinking skills, focusing on abstraction, decomposition, and algorithm design. You’ll learn to write pseudocode and create flowcharts.

Topics include:

• Abstraction and decomposition

• Writing pseudocode using sequence, selection, and iteration

• Stepwise refinement and structured English
  

10. Data types and structures

This section explores the data types and structures used in programming, including arrays, records, and files. You'll also be introduced to abstract data types like stacks and queues.

Topics include:

• Data types: integer, real, char, string, Boolean, date

• Records and arrays (1D and 2D)

• File handling in pseudocode

• Abstract data types: stack, queue, linked list
  

11. Programming

This section covers the fundamentals of programming, including constructs, structured programming, and the use of procedures and functions.

Topics include:

• Constructs: IF statements, loops, and CASE structures

• Procedures, functions, and parameter passing

• Writing efficient pseudocode
  

12. Software development

This section introduces the program development life cycle and tools used for design and testing. You’ll learn about different life cycle models and techniques for identifying and correcting errors.

Topics include:

• Development life cycle models: waterfall, iterative, RAD

• Analysis, design, implementation, testing, and maintenance

• Structure charts and state-transition diagrams

• Types of testing: dry run, walkthrough, alpha, beta

What is Covered in CIE A Level Computer Science Assessment?

Revision Resources for CIE A Level Computer Science

For high-quality revision resources for the AQA A Level Computer Science exam, visit the CIE homepage for access to:

• Past papers

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Explore Our A Level Computer Science Resources

References

CIE A Level Computer Science Specification

OCR A Level Computer Science Specification

AQA A Level Computer Science Specification