A-Level Computer Science

Course Overview

A-Level Computer Science combines rigorous theoretical study with practical programming and problem-solving skills. It covers a broad range of topics from low-level computer architecture and data representation to high-level programming paradigms, algorithms, databases and networking — preparing students thoroughly for degree-level Computer Science and related disciplines.

Students receive 3 sessions of 2 hours per week — 6 contact hours every week — covering both examined theory and the non-examined assessment (NEA) programming project. Dedicated NEA support sessions ensure students develop a high-quality, well-documented project that can account for up to 20% of their final grade.

3

Sessions per week

2 hrs

Per session

6 hrs

Contact time per week

20%

NEA project weighting

Weekly Lesson Schedule

Session 1 (2 Hours)

Theory & Computer Systems

Theoretical content taught and reinforced through structured notes, diagrams and exam-style questions. Covering computer architecture, data representation, networking, databases and computational thinking.

0:00–0:45 New theory content with examples · 0:45–1:20 Exam-style questions and mark scheme review · 1:20–2:00 Q&A and homework set

Session 2 (2 Hours)

Programming & Algorithms

Practical programming in Python and pseudocode. Algorithm design, tracing and analysis. Students write, test and debug programs with tutor guidance and code review.

0:00–0:30 Algorithm review and trace tables · 0:30–1:30 Programming tasks in Python · 1:30–2:00 Code review and debugging

Session 3 (2 Hours)

NEA Project or Mixed Exam Practice

Alternating between dedicated NEA development sessions (planning, coding, testing and documentation) and mixed past paper practice covering all exam board topics.

NEA session — Project development, testing and write-up · Exam session — Past paper questions and mark scheme review

NEA Project

The Non-Exam Assessment (NEA) is an independent programming project worth up to 20% of the final A-Level grade.

1

Project Selection & Analysis

Choosing a suitable real-world problem, defining the scope, identifying stakeholders, and producing a detailed requirements specification with clear success criteria.

2

Design Documentation

Producing algorithms using flowcharts and pseudocode, designing data structures and file formats, planning the user interface and system architecture.

3

Programming & Implementation

Writing well-structured, commented code in Python or another appropriate language. Implementing features iteratively with regular testing and debugging.

4

Testing & Evaluation

Producing a comprehensive test plan with normal, boundary and erroneous test data. Evaluating the solution against the original success criteria and suggesting improvements.

Year 12 — AS Level Content

Sept–June, 3×2hrs/week

Programming Fundamentals

Data types: integer, float, Boolean, string, char
Variables, constants and assignments
Sequence, selection (if/elif/else) and iteration (for, while)
Subroutines: procedures and functions
Parameter passing: by value and by reference
Recursion: base case, recursive case, call stack
File handling: reading, writing and appending

Data Structures

Arrays: 1D and 2D
Records and tuples
Stacks: push, pop, peek, isEmpty
Queues: enqueue, dequeue, circular queues
Linked lists: nodes, pointers, insertion and deletion
Binary trees: traversal (in-order, pre-order, post-order)

Algorithms

Sorting: bubble, merge, insertion, quick sort
Searching: linear and binary search
Pathfinding: Dijkstra's algorithm
Big-O notation: O(1), O(n), O(n²), O(log n)
Trace tables and algorithm analysis
Writing algorithms in pseudocode

Computer Systems 1

CPU architecture: ALU, control unit, registers, buses
Fetch-decode-execute cycle
Primary and secondary storage
Data representation: binary, denary, hexadecimal
Binary arithmetic and two's complement
Character encoding: ASCII and Unicode
Image and sound representation

Software & Operating Systems

Types of software: system and application
Operating system functions: process, memory and file management
Scheduling algorithms: round robin, FCFS, SJF
Interrupts and interrupt handling
Virtual machines and emulators
Programming language translators: compiler, interpreter, assembler

Databases & SQL

Relational databases: tables, fields, records, keys
Entity-relationship diagrams
SQL: SELECT, FROM, WHERE, JOIN, INSERT, UPDATE, DELETE
Normalisation: 1NF, 2NF, 3NF
ACID properties and transactions
Client-server databases

Year 13 — A2 Level Content

Advanced Programming Paradigms

Object-oriented programming: classes, objects, methods
Encapsulation, inheritance and polymorphism
Functional programming: pure functions, immutability, higher-order functions
List comprehension and map/filter/reduce
Event-driven programming principles

Networks & Web Technologies

Network topologies: bus, star, mesh, ring
LAN, WAN, internet and intranet
TCP/IP protocol stack and OSI model
IP addressing: IPv4 and IPv6, subnetting
HTTP, FTP, DNS, SMTP protocols
Cybersecurity: encryption, firewalls, authentication

Computational Thinking & Theory

Abstraction, decomposition and pattern recognition
Finite state machines (FSMs) and transition diagrams
Regular expressions and formal languages
Turing machines: theory and significance
Limits of computation: halting problem
Classifying problems: tractable and intractable

Advanced Algorithms & Complexity

Graph theory: nodes, edges, directed and weighted graphs
Depth-first and breadth-first search
Minimum spanning trees: Prim's and Kruskal's algorithms
Dynamic programming
Heuristic methods and optimisation
Comparing algorithm efficiency with Big-O

Legal, Ethical & Cultural Issues

Data Protection Act 2018 and UK GDPR
Computer Misuse Act 1990
Intellectual property and copyright law
Ethical implications of AI and automation
Environmental impact of computing
Digital inclusion and accessibility

NEA Project (Year 13 Completion)

Final implementation and code completion
Comprehensive testing against success criteria
User testing and feedback incorporation
Final evaluation write-up
Documentation review and submission preparation

Exam Preparation

Weekly Past Paper Questions

Theory and programming exam questions from AQA, OCR and Edexcel past papers tackled every week, covering all specification areas.

NEA Project Support

Dedicated NEA sessions every fortnight with tutor guidance on analysis, design, coding, testing and evaluation — helping students maximise the 20% project marks.

Pseudocode & Trace Tables

Writing accurate pseudocode and completing trace tables are key skills for the exam papers, practiced regularly throughout the two-year programme.

Termly Mock Exams

Full mock papers under timed exam conditions each term with detailed written feedback and personalised grade targets for university applications.

Careers

Software Engineering

Full-stack development, mobile apps, game development and enterprise software all build directly on the programming and algorithmic thinking developed at A-Level.

Artificial Intelligence & Data Science

Machine learning, neural networks and big data analysis all require the mathematical and computational thinking foundations laid at A-Level Computer Science.

Cybersecurity

Network security, ethical hacking, cryptography and digital forensics are rapidly growing fields that draw directly on A-Level networking and theory content.

Computer Science Degree

A-Level Computer Science is the ideal preparation for a Computer Science degree at university, covering the theory and programming skills expected at entry level.

Engineering & Robotics

Embedded systems, control systems and robotics all combine computing with engineering principles, building on the hardware and systems content of A-Level CS.

Finance & Fintech

Algorithmic trading, blockchain, financial modelling and banking technology all recruit heavily from Computer Science graduates.

A-Level Computer Science