a level coursework computer science

All about A level Computer Science – course information

What's a level computer science about.

A level Computer science is split into two complementary sections, programming and theory.  On the programming side of the course, students can learn a programming language (chosen by your teachers from C#, Java, Pascal/Delphi, Python and VB.Net).  You will cover  the fundamentals of programming, data structures, algorithms, and object-orientated programme design.

The theory side of computer science teaches about the internal workings of a computer, right down the basics of how all data is stored using binary, whether that data consists of numbers, text, pictures or even music.  It goes on from there to cover aspects of computer architecture, showing exactly how data is accessed from main memory using assembly language instructions and the fetch-execute cycle.

As well as covering programming the course aims to promote good programming practices such as avoiding global variables, sensible variable naming, structured programming, good re-use of code through procedures and functions, and proper commenting of code.  It also covers higher level concepts such as the social and legal impact of computers, and how to go about breaking down a big problem into individual programmable steps.

W hat sort of work is involved?

The A level Computer science course consists of work towards two exam papers, both worth 40% of the whole, plus non-exam assessment worth 20% which will typically be done over a period of about 3 months.

The first exam is a programming test, which some exam boards, such as the AQA ,  like to do using an on-screen exam.  This will test your ability to solve problems as much as it will test your technical knowledge of the programming language you have learned.

The second exam tests theory and is a written exam.  Questions are designed to test your knowledge of computer systems, how they are formed, the social and legal parts of computing, communication, networking and databases.

For the non-exam assessment you  pick your own project which must have a significant programming element.  You will create a program to solve a problem, such as writing a computer game, making a mobile phone application or doing an investigation into machine learning.  There is no restriction on programming language used in the project, so you could use Swift, Objective C, C++ or any other language you wanted to do your project.  However,  drag-and-drop languages, such as Scratch, are not allowed. When writing coursework you won’t just be expected to produce working code, but will be expected to write good, well structured working code.

What background do I need?

To do A level Computer science it is not essential to have done computer science at GCSE, though it is advisable to have done some practice of programming in your own time.  The course has a significant programming element and those who have no previous experience of programming often find it very challenging.

You ought to have at least a B-grade in mathematics.  There are several topics that require the ability to reason logically and apply mathematical and logical processes to solutions.  It is likely that if you find mathematics enjoyable and interesting then you will also like computer science.

Where can it lead?

A level Computer science is naturally a strong subject to take if you wish to go on to do computer science at degree level, and although most computing-based degree courses don't require Computer science A level there are a number of software engineering courses which do.  There are also other degree courses such as information technology and information systems which will be served well by a Computer science A level.

After university, there are numerous interesting fields of study and professions that you can go in to.  Computer science will lead on to robotics, artificial intelligence, machine learning, cloud computing, big data processing, networking, ethical hacking, computer game development, home automation or even teaching.  So much of the world uses computers nowadays that having a good understanding of how computers work and how to program them will set you up for success in many strands of life.

Numbers of computers are also increasing in many developing countries too, meaning that your skills in computer science will be very portable.  The most popular programming languages in the world are based on the English language using statements such as for, while, if, else, repeat , so studying computer science in an English speaking college will give you a good foundation if you wish to travel and find a job working with computers in another country.

One year course?

Due to the coursework element, A level Computer science is very difficult to do in one year.  To succeed you would need to already have a firm grasp of programming such that you could begin the year doing coursework and getting it out of the way, leaving you enough time to cover the theory before taking exams in June.

There is an AS-level available which covers most of the topics but not in as much detail as the A-level.  Like the A level, there are two exams, one of which is programming and the other theory but they are each worth 50% of your overall grade.

As previously mentioned, A level Computer science consists of two exam papers, each 2 1/2 hours long and each worth 40%. The remaining 20% comes from your coursework.

The coursework assesses your ability to take on a significant problem and produce a solution to it.  Despite the large programming element, you will actually be marked on the documentation you produce.  This will typically consist of an analysis, designing the solution, annotated code showing your finished solution, tests demonstrating that your solution works and an evaluation.

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CIE A Level Computer Science

Unit 1 – information representation, 1.1 data representation.

• Binary & Denary Number Systems
• Hexadecimal Number Systems
• Binary and Decimal Prefixes
• One’s Compliment and Two’s Compliment
• Binary Addition and Subtraction
• Binary Coded Decimal
• ASCII, Extended ASCII and Unicode
• Binary Addition

1.2 Multimedia – Graphics, Sound

• Bitmap Images
• Vector Images
• Bitmaps vs Vectors
• Encoding & Compressing Video
• Encoding Sound

1.3 Compression

• The need for compression
• Lossy vs Lossless Compression
• Compression algorithms

Unit 2 – Communication

2.1 networks including the internet.

• Purpose of networking of devices
• Client-Server vs Peer to Peer
• Thin and Thick Clients
• Network Topologies
• Cloud Computing
• Wired and Wireless Networks
• Network Hardware
• Network routing and collisions(CSMA/CD)
• Bit Streaming
• WWW and the Internet
• Internet Hardware
• IPv4 & IPv6 Addresses
• Subnets & Network Masks
• Public vs Private IP Addresses
• Static Vs Dynamic IP, DHCP
• URLs, DNS and Serving Web Pages
• Client Side & Server Side Scripting

Unit 2 Past Paper Questions

Unit 3 – Hardware

3.1 computers and their components.

• Input Devices
• Laser Printer
• Primary Storage
• Secondary Storage Devices
• Embedded Systems
• Virtual and Augmented Reality
• RAM and ROM
• SRAM vs DRAM
• ROM,PROM,EPROM,EEPROM
• Open & Closed Loop Systems

CIE Teacher Support Materials Input/Output Devices

3.2 Logic Gates and Logic Circuits

• Logic Gates
• Logic Circuits
• Truth Tables

Unit 4 – Processor Fundamentals

4.1 central processing unit (cpu) architecture.

• VON Neumann Architecture
• Motherboard Ports
• Fetch  – Execute Cycle
• Register Transfer Notation
• ALU,CU,IAS, System Clock
• CPU Performance Factors

4.2 Assembly Language

• Assembly Language Vs Machine Code & The assembly process
• Grouping Instruction Sets
• Modes of addressing
• Dynamic Link Libraries

4.3 Bit manipulation

• Binary Shifts
• Bit Manipulation & Bitwise Operations

Unit 5 – System Software

5.1 operating systems.

• Purpose of an Operating System
• Operating System User Interface Types
• Management tasks
• Utility Software
• Program Libraries

5.2 Language Translators

• Assembler Software
• Interpreters

Unit 6 – Security, privacy and data integrity

6.1 data security.

• Security, Privacy and Integrity
• Data and System Security
• Computer & Network Threats
• Security / Threat reduction measures
• Backing Up Data

6.2 Data Integrity

• Methods of data validation
• Methods of data verification

Unit 6 Past Paper Questions

Unit 7 – Ethics and Ownership

7.1 ethics and ownership.

• Copyright legislation
• Software Licences
• Ethical implications of artificial intelligence
• IEEE Code of Ethics Rules
• IEEE/ACM Software Engineering Guiding Principles

CIE Ethics Teacher Materials

Unit 8 – Databases

8.1 database concepts.

• Introduction to Relational Databases
• Entity relationship diagrams
• Referential Integrity
• Normalisation process  – First, Second, Third Normal Form

8.2 Database Management System (DBMS)

• Features of a database management system & Query Processor
• DBMS Software Tools
• Backup Procedures
• Online,Offline, Onsite,Offsite Backups

8.3 Data Definition Language (DDL) and Data Manipulation Language (DML)

• Role of Data Definition Language
• Role of Data Manipulation Language
• SQL Language
• SQL DDL Queries
• SQL DML Queries

Helpful Resources

• Databases Past Paper Questions
• SQL Practice Games
• SQLite3 Cheat Sheet

Unit  9 – Algorithm Design and Problem-Solving

9.1 computational thinking skills.

• Input, process, Output
• Abstraction
• Decomposition
• Abstraction & Decomposition
• Step-wise refinement

9.2 Algorithms

• Identifier names and tables
• Logic statements

Unit 10 – Data Types and structures

10.1 data types and records.

• Selection of data types
• User Defined Types (Record, Enumerator, Set)

10.2 Arrays

• 1 Dimensional Arrays
• 2 Dimensional Arrays

Search Algorithms

• Linear Search
• Binary Search

Sorting Algorithms

• Bubble Sort
• Insertion Sort
• Lower and Upper Bounds
• Reading/Writing Text Files
• Reading/Writing CSV Files

10.4 Introduction to Abstract Data Types (ADT)

• Introduction to abstract data types
• Linked List

Unit 11 – Programming

11.1 programming basics.

• Basic input, processing & output
• Conditionals
• Dictionaries
• Subroutines

CIE Pseudocode

• Introduction, Input, Output, Variables
• If & Case Statements
• File Handling
• Functions & Procedures

Abstract Data Types

(Also create a cheat sheet and add it here)

11.2 Constructs

• Programming Constructs

11.3 Structured Programming

• Functions Exercises
• Input Parameters
• Efficient code

Unit 12 – Software Development

12.1 program development life cycle.

• Development life cycles
• Waterfall model
• Rapid Application Development

12.2 Program Design

• Structure Charts
• State Transition Diagrams

13. Program Testing & Maintenance

• Integrated Development Environments
• Syntax, Runtime & Logical Errors
• Methods of Testing
• Choosing Test Data
• Program Maintenance

Unit 13 – Data Representation (A – level)

13.1 user defined types.

• Classes, Objects & Instances

13.2 File Organisation & Access

• File organisation and access
• Hash Tables & Hashing Functions

13.3 Floating-point numbers, representation and manipulation

Unit 14  – Communication & Internet Technologies

14.1 protocols.

• The need for protocols
• Protocol stack
• TCP/IP Protocol Suite
• HTTP,FTP,POP3,IMAP,SMTP,BitTorrent

14.2 Circuit switching, packet switching

• Circuit Switching
• Packet Switching
• Function of a router

Unit 15 – Hardware & Virtual Machines

15.1 processors, parallel processing and virtual machines.

• RISC & CISC Computers
• Interrupt Handling in RISC & CISC
• Pipelining & Registers
• SISD,SIMD,MISD,MIMD
• Massively Parallel Computers
• Virtual Machines

15.2 Boolean Algebra and Logic Circuits

• Half Adders & Full Adders
• Flip Flop Circuits
• Karnaugh Maps
• Boolean Algebra Simplification Examples

Unit 16 – System Software

16.1 purposes of an operating system (os).

Process Management

16.2 Translation Software

• Compilers and compilation stages
• Syntax Diagrams
• Backus-Naur Form
• Reverse Polish Notation

Unit 17 – Security

17.1 encryption, encryption protocols and digital certificates.

• Symmetric Encryption
• Asymmetric Encryption
• Digital Certificates
• Transport Layer Security & Digital Certificates (SSL/TLS)
• Quantum Cryptography

Unit 18 – Artificial Intelligence

18.1 artificial intelligence.

• Artificial Intelligence, Machine Learning and Deep Learning
• Classification, Regression, Clustering & Reinforcement  &
• Dijkstra’s Algorithm
• A* Algorithm
• Deep Learning & Neural Networks
• Supervised, Unsupervised Learning & Reinforcement Learning
• Back Propagation

Artificial Intelligence Exam Questions

Unit 19 – Computational thinking and problem solving

19.1 algorithms.

Big O Notation with searching and sorting algorithms

• Binary Tree

19.2 Recursion

• Maze Solving Recursive Algorithm

Unit 20 – Further Programming

20.1 programming paradigms.

• Low Level Programming
• Imperative (Procedural) Programming
• Object Orientated Programming
• Declarative Programming

20.2 File Processing and Exception Handling

June 2021-2023 9618 Syllabus

Folder Structure

Pseudocode Guide

AS & A Level Exam Components

Paper 1 -Theory Fundamentals

• Sections 1 to 8
• 90 minute exam (25% of A level)

Paper 2 – Problem-solving and  Programming

• Sections  9 to 12
• 120 minute exam (25% of A level)
• Includes writing algorithms in code *, Pseudocode & Flowcharts

Paper 3 – Advanced Theory

• Sections 13 to 20
• 90 minute exam (25% of A level)

Paper 4 – Practical

• Sections 19 to 20
• 150 minute exam (25% of A level)
• Answered on computer
• Students will submit program code* and evidence of testing
• No email or internet access

* Permitted Programming languages – Java, VB.net or Python.  No other languages are allowed.

Exam Practice

Past papers, mark schemes & specimen papers.

Past Papers & Mark Schemes

Specimen Papers 2021+

Printable revision resources

Paper 4 Practice Tasks

Paper 4 Programming Skills CheckList

Year 11 Transition work

Course Book

Course book for 9618 specification.

Hodder Education: Cambridge International AS & A Level Computer Science Course Book.

This is the book we will be using from 2020 onward, as it is tailored towards the specific requirements of the course and offers a full structured approach to the CIE A level Computer Science 9618 course content.

The Hodder Education CIE Computer Science book for the new 2021 -2023 Specification. Available on paper and Kindle.

A-level Computer Science

Computer Science has rational thinking at its core; combining human and computer intelligence to provide intelligent solutions to problems. Choosing to study International A-level Computer Science can open doors to various career opportunities in data science, web development, product management and software development, or prepare you for higher education at university .

In this engaging online computer science course, you’ll study communication and Internet technologies, software development, artificial intelligence, data representation and much more. As you study, you’ll develop key skills such as abstraction, decomposition and algorithmic thinking.

What you will learn

Unit 1 - information representation.

• Binary Number System
• Binary Coded Decimal
• Hexadecimal 
• Bits, Bytes and Binary
• Representing Images
• Analogue and Digital Sound
• Data Compression

Unit 2 - Communication and Internet Technologies

• Data Transmission
• Wireless Networking, CSMA and SSID
• Structure of the Internet
• Packet Switching and Routers
• IP Addresses 
• Network Topology
• Client-Server and Peer-to-Peer
• Client Server Model

Unit 3 - Hardware

• Computers and their components
• Logic gates
• Creating logic circuits
• Interpreting the results of a truth table

Unit 4 - Processor Fundamentals

• Central Processing Unit
• The Fetch-Decode-Execute Cycle
• The Processor
• Assembly Language
• Machine Code
• Bit Manipulation

Unit 5 - System Software

• Operating systems (OS)
• Processor scheduling
• Programming language classification
• Language translators
• Machine code

Unit 6 - Security, Privacy and Data Integrity

• Data security
• Cyber security
• MALWARE – malicious software
• Data integrity

Unit 7 - Ethics and Ownership

• Ethics and ownership
• The rise of artificial intelligence
• The Computer Misuse Act 1990
• Data Protection Act (1998)
• Copyright, Designs and Patents Act (1998)
• Introduction to software licences

Unit 8 - Databases

• Flat file databases
• Relational database model
• Database normalisation
• Database Management Systems (DBMS)
• Data Definition Language (DDL) and Data Manipulation Language (DML)
• Common data types
• Linking tables

Unit 9 - Fundamental Problem Solving - Algorithm Design and Problem Solving

• Abstraction and decomposition
• Solving logic problems
• Software development

Unit 10 - Fundamental Problem Solving - Data Types and Structures

• Data Types and Records
• Searching and sorting algorithms
• Files and Exception Handling
• Abstract Data Types (ADT)

Unit 11 - Fundamental Problem Solving - Programming

• Complex Boolean Expressions
• The CASE Statement
• Subroutines

Unit 12 - Fundamental Problem Solving - Software Development

• Program Development Life Cycle
• The Waterfall Model
• Iterative and Rapid Application Development
• Program Design
• Program Testing and Maintenance
• Error Types

Unit 13 - Advanced Theory - Data Representation

• User Defined Data Types
• File Organisation and Access
• Floating-Point Numbers, Representation and Manipulation
• Precision and Normalisation

Unit 14 - Advanced Theory - Communication and Internet Technologies

• the TCP/IP Model
• Circuit Switching 
• Packet Switching

Unit 15 - Advanced Theory - Hardware and Virtual Machines

• Processors, Parallel Processing and Virtual Machines
• Comparing RISC and CISC
• Virtual Machines
• Boolean Algebra and Logic Gates
• De Morgan’s Laws
• Karnaugh Maps

Unit 16 - Advanced Theory - System Software

• Purposes of an Operating System
• Processor Scheduling
• IO Device Management
• Translation Software
• Backus-Naur Form
• Syntax Diagram

Unit 17 - Advanced Theory - Security

• Encryption Protocols and Digital Certificates
• Types of Encryption
• Encryption Protocol
• The Electronic Communications Act (2000)
• Digital Certificates
• Digital Signatures

Unit 18 - Advanced Theory - Artificial Intelligence

• Machine Learning
• Deep Learning
• Reinforcement Learning
• Dijkstra’s Algorithm
• A* Algorithm

Unit 19 - Computational Thinking and Problem Solving

• Abstract Data Types
• Linked Lists
• Binary Tree
• Big O Notation

Unit 20 - Further Programming

• Programming Paradigms
• Imperative (High Level) Programming
• Files Processing and Exception Handling
• Inputs and Outputs
• Exception Handling

Awarding Body

Cambridge Assessment International Education (CAIE) is the world’s largest provider of  A-level courses  and  GCSE courses , qualifications and exams, delivering assessments to over 8 million learners in over 170 countries.

Recognised through UCAS

This course carries UCAS points . This means that it can be used to gain direct access to University courses and other Higher Education, through the UCAS system .

Course Outcome

After completing the course, you will be awarded the qualification: A-level Computer Science, issued by  CAIE  (Cambridge Assessment International Education. This syllabus ( 9618 ) has been selected specifically because it is best suited to distance learning. Your certificate will be identical to that issued in any other school, college or university.

How is this course assessed or examined?

You will be expected to complete three standard A-level Computer Science written exams and one practical exam:

Written exams:

• Paper 1:  1 hour 30 minutes, 25% of A-level, 75 marks.
• Paper 2:  1 hour 30 minutes, 25% of A-level, 75 marks.
• Paper 3:  2 hours 30 minutes, 25% of A-level, 75 marks.

Practical exam:

•  2 hours 30 minutes, 25% of A-level, 75 marks.

As part of the practical exam, you will submit complete program code and evidence of testing and will be required to use either Java, VB.NET or Python programming languages.

Entry requirements

In order to study this course, you will need to have achieved a  maths GCSE  or the equivalent. If you wish to study computer science at a degree level, then you’ll need to combine this qualification with  A-level maths , as this is a requirement at many universities. It is a difficulty level three: the equivalent difficulty of an A-level or BTEC, usually suitable for most learners of all ages.

Past Papers

You can access past papers for this course . They are free to access and cover a range of exam boards.

Find out more about the exams here .

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Cambridge International AS & A Level Computer Science

Topic outline.

• Please rotate your device.

• Syllabus content - what you need to know about

There are four components that you will need to take:

• Paper 1 (Theory Fundamentals)

Paper 2 (Fundamental Problem-solving and Programming Skills)

• Paper 3 (Advanced theory)
• Paper 4 (Practical)

Key concepts

Key concepts are essential ideas that help you to develop a deep understanding of your subject and make links between different aspects of the course. The key concepts for Cambridge International AS & A Level Computer Science are:

• Computational thinking

Computational thinking is a set of fundamental skills that help produce a solution to a problem. Skills such as abstraction, decomposition and algorithmic thinking are used to study a problem and design a solution that can be implemented. This may involve using a range of technologies and programming languages.

• Programming paradigms

A programming paradigm is a way of thinking about or approaching problems. There are many different programming styles that can be used, which are suited to unique functions, tools and specific situations. An understanding of programming paradigms is essential to ensure they are used appropriately, when designing and building programs.

• C ommunication

Communication is a core requirement of computer systems. It includes the ability to transfer data from one device or component to another and an understanding of the rules and methods that are used in this data transfer. Communication could range from the internal transfer of data within a computer system, to the transfer of a video across the internet.

• Comput er architecture and hardware 

Computer architecture is the design of the internal operation of a computer system. It includes the rules that dictate how components and data are organised, how data are communicated between components, to allow hardware to function. There is a range of architectures, with different components and rules, that are appropriate for different scenarios.

All computers comprise of a combination of hardware components, ranging from internal components, such as the Central Processing Unit (CPU) and main memory, to peripherals. To produce effective and efficient programs to run on hardware, it is important to understand how the components work independently and together to produce a system that can be used. Hardware needs software to be able to perform a task. Software allows hardware to become functional. This enables the user to communicate with the hardware to perform tasks.

• Data representation and structures  

Computers use binary and understanding how a binary number can be interpreted in many different ways is important. Programming requires an understanding of how data can be organised for efficient access and/or transfer. 

These key concepts help you to gain:

• a greater depth as well as breadth of subject knowledge 

• confidence, especially in applying your knowledge and skills in new situations

• the vocabulary to discuss the subject conceptually and show how different aspects link together

• a level of mastery of their subject to help them enter higher education. 

Make sure you always check the latest syllabus, which is available at  www.cambridgeinternational.org .

• How you will be assessed
• Please rotate your device
• What skills will be assessed?
• The examiners take account of the following skills areas (assessment objectives) in the examinations: AO1: Knowledge with understanding Demonstrate knowledge and understanding of the principles and concepts of computer science including abstraction, logic, algorithms and data representation. AO2: Application Apply knowledge and understanding of the principles and concepts of computer science, including to analyse problems in computational terms. AO3: Design, program and evaluation Design, program and evaluate computer systems to solve problems, making reasoned judgements about these.
• Command words
• The flipcards below include command words used in the assessment for this syllabus. The use of the command word will relate to the subject context.
• Example candidate response
• All information and advice in this section is specific to the example question and response being demonstrated. It should give you an idea of how your responses might be viewed by an examiner but it is not a list of what to do in all questions. In your own examination, you will need to pay careful attention to what each question is asking you to do.

Example candidate response and examiner comments

• (a) Application layer Transport (layer) Internet (layer) Network (access layer) [See examiner comment] (b) (i) Peer – to – peer. (ii) File sharing. (iii) BitTorrent client software is made available, this is used to load the torrent descriptor for the required file by computers joining it swarm. A server, called tracker, keeps records of all the computers joining the swarm and allows them to connect to each other by sharing their IP addresses. The torrent is split into small pieces that can be downloaded or uploaded by each computer in the swarm. Once a computer has downloaded a piece of the torrent file it can upload that piece to other computers in the swarm and become a seed. (c) Protocol 1 SMTP Example Sending email messages Protocol POP3 Example retirement of email messages [See examiner comment] [Total mark awarded]
• Explore the advice below to help you revise and prepare for the examinations.  It is divided into general advice for all papers and more specific advice for each of the papers.
• Find out when the examinations are and plan your revision so you have enough time for each topic. A revision timetable will help you
• Find out how long each paper is and how many questions you have to answer
• Know the meaning of the command words used in questions and how to apply them to the information given. Highlight the command words in past papers and check what they mean. There is a list on page 11 of this guide
• Make revision notes; try different styles of notes. See the Learner Guide: Planning, Reflection and Revision  which as ideas about note-taking. Discover what works best for you
• Work for short periods then have a break. Revise small sections of the syllabus at a time
• Build your confidence by practising questions on each of the topics
• Make sure you practice lots of past examination questions so that you are familiar with the format of the examination papers. You could time yourself when doing a paper so that you know how quickly you need to work in the real examination
• Look at mark schemes to help you understand how the marks are awarded for each question
• Make sure you are familar with the technical terminology that you need for this syllabus. Your teacher will be able to advise you on what is expected.
• Read the instructions carefully and answer all the questions
• Check the number of marks for each question or part question. This helps you to judge how long you should be spending on the response. You don't want to spend too long on some questions and then run out of time at the end
• Do not leave out questions or parts of questions. Remember, no answer means no mark
• If a question has several parts, then the parts with more marks will need more time and more developed answers
• You do not have to answer the questions in the order they are printed in the answer booklet. You may be able to do a later question more easily then come back to an earlier one for another try
• Identify the command words – you could underline or highlight them
• Identify the technical terms and perhaps underline them too
• Try to put the question into your own words to understand what it is really asking.
• Read all parts of a question before starting your answer. Think carefully about what is needed for each part. You will not need to repeat material
• Use your knowledge and understanding
• Do not write everything you know about a topic. Only use the information you need to answer the question.
• Make sure that you have answered everything that a question asks. Sometimes one part requires two things, e.g. 'Calculate...' and 'Show your working.'. It is easy to concentrate on the first request and forget about the second one
• Always show your working. Marks are usually awarded for using correct steps in the method even if you make a mistake somewhere
• Don't cross out any working in a calculation until you have replaced it by trying again. Even if you know it's not correct you may still be able to get method marks. If you have made more than two attempts, make sure you cross out all except the one you want marked
• Make sure all your numbers are clear, for example make sure your '1' doesn't look like a '7'
• If you need to change a word or a number, it is better to cross out your work and rewrite it. Don't try to write over the top of your previous work as it will be difficult to read and you may not get the marks
• Don't write any pseudocode answers in two columns in the examination. It is difficult for the examiners to read and follow your working.
• Always use the logic gate symbols from the syllabus when drawing logic circuits
• Always use the opcodes given on the syllabus or shown on the examination paper when writing assembly language instructions
• Try and use capital letters when writing assembly language opcodes, SQL, or pseudocode commands so they can be clearly recognised as commands by the examiner
• Where possible use SQL and pseudocode commands that are given in the syllabus, any other commands should be identified and explained.
• Try and use capital letters when writing pseudocode commands so they can be clearly recognised as commands by the examiner
• Where possible use pseudocode commands that are given in the syllabus, any other commands should be identified and explained
• Annotate pseudocode with comments
• Fully label diagrams.
• Remember you will need to write and test programs in the examination

Visual Basic

• Be able to use your chosen programming language in console mode
• Get plenty of practice at debugging and testing programs using your chosen programming language
• Where possible use the same programming language for all your answers.

• Paper 1 - Theory Fundamentals
• 1.1 Data Representation 1.2 Multimedia 1.3 Compression 1.4 Communication 1.5 Hardware 1.6 Processor Fundamentals 1.7 System Software 1.8 Security, privacy and data integrity 1.9 Ethics and ownership 1.10 Databases TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT
• Paper 2 - Fundamental Problem-solving and Programming Skills
• 2.1 Computational thinking skills 2.2 Algorithm Design 2.3 Data types and structures 2.4 Programming 2.5 Software Development TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT
• Paper 3 - Advanced Theory
• 3.1 Data Representation 3.2 Communication and internet technologies 3.3 Hardware 3.4 System Software 3.5 Security 3.6 Artificial Intelligence (AI) 3.7 Algorithms TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT
• Paper 4 - Practical
• 4.1 Programming
• Useful websites
• The websites listed below are reliable useful resources to help you study for your Cambridge International AS and A Level Computer Science.

www.w3schools.com/

www.jetbrains.com/idea/documentation/

www.jetbrains.com/idea/download/#section=windows -

https://visualstudio.microsoft.com/vs/express/

www.python.org/downloads/

Prolog 

www.swi-prolog.org/

British Computer Society Glossary

www.bcs.org/category/5656

A Level Computer Science AQA – Revision Content

Browse Study Rocket's A Level Computer Science AQA free revision notes.

A Level Computer Science AQA – Topics

Programmes & Qualifications

Cambridge international as & a level computer science (9618).

• Published resources

Cambridge International AS & A Level Computer Science: Student's Book

Endorsed by Cambridge Resources align to the syllabus they support, and have been through a detailed quality assurance process.

Computer Science for Cambridge International AS & A Level

Stay up to date

Sign up for updates about changes to the syllabuses you teach

• Syllabus overview
• Past papers, examiner reports and specimen papers

Systems architecture in A Level computer science

CP505 Live remote training course

During this course you'll explore the structure of the internal components of a computer system. In addition you'll explore the von Neumann architecture and fetch-execute cycle.

• Live remote training 25 April 15:30—25 April 2024
• Live remote training 8 May 13:00—8 May 2024
• Live remote training 16 May 08:00—16 May 2024
• Live remote training 28 May 16:00—28 May 2024
• Live remote training 5 June 09:30—5 June 2024
• Live remote training 10 June 14:00—10 June 2024
• Live remote training 20 June 15:30—20 June 2024
• Live remote training 1 July 14:00—1 July 2024
• Live remote training 11 July 09:30—11 July 2024
• Live remote training 23 July 13:00—23 July 2024

Unlock the inner workings of computer systems during this course. Delve into the purpose and function of key system components, gaining insight into how they impact overall performance and functionality. Master the fundamentals of Von Neumann architecture and the fetch-decode-execute cycle. You’ll evaluate the factors influencing CPU performance through the use of a real-world scenario.

Discover the intriguing distinctions between Von Neumann and Harvard processor architectures, and explore the pivotal role of GPUs as co-processors. Investigate the applications of both RISC and CISC processor designs, and examine their key differences. Through the exploration of a variety of online resources, engagement in professional discussions with educators alongside practical experience of exam questions, emerge from this course best equipped to support student success within the topic of systems architecture.

Who is it for?

This course is aimed at teachers delivering A Level computer science. It is advised you have some basic knowledge of systems architecture from GCSE computer science specifications.

During this course you’ll access the Isaac Computer Science platform , it is advised you sign up for a free, teachers account ahead of the course.

Topics covered

Key system components – during this session, you will discover the vital system components that power your computer's performance. You will explore models of the Von Neumann architecture and investigate the fetch-decode-execute cycle. You’ll analyse and evaluate the factors affecting CPU performance using a real-world scenario.

Processor architectures – during this session, you will explore a variety of processor architectures. You will uncover the distinctions between Von Neumann and Harvard designs, unveiling the core of computing innovation. You will dive into the fascinating world of GPUs and their pivotal role as co-processors, before investigating the differences between RISC and CISC architectures.

How long is this course?

This course will last approximately 2.5 hours, these sessions maybe split across multiple days.

How will you learn?

Scheduled live, interactive online sessions led by an experienced practitioner. Flexible Professional Development Leader-supported, participant-led tasks, involving deep exploration of the subject content.

By the end of this intensive CPD pathway you will be able to:

• Demonstrate understanding of computer system components and their impact on performance and functionality
• Explore Von Neumann architecture and evaluate the factors affecting CPU performance
• Effectively differentiate between processor architectures, including Von Neumann vs. Harvard and RISC vs. CISC

This course is part of Teach secondary computing

Teach secondary computing

Our nationally recognised qualification will give you confidence to take your computing teaching to the next level and to apply those skills in the classroom.

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Adapted teaching and effective learning interventions in secondary computing

Develop an evidence-informed approach to education recovery over a sustained period, securing the computing education of young people following a period of great disruption.

Adapting the Teach Computing Curriculum for mixed-year classes - short course

Explore progression within Teach Computing Curriculum and how to use this to adapt it for your own mixed-age setting.

AI in primary computing

Explore how Artificial Intelligence (AI) may be linked to aspects of the primary computing curriculum, supporting creativity, digital literacy, and the use of information technology.

Computer Science A Level

Computer Science is an exciting, modern subject relevant to many disciplines and careers.

Almost every aspect of modern life involves computing; from cloud and internet use, through mobile devices and home appliances, to complex programs that help businesses and public services run smoothly. Vast networked systems of computers control global communication, trade, finance and transportation. Experience of Computer Science is relevant to all.

A good computer scientist wants to learn more about how computers work, to learn the language of code (C#) and to find ways to solve puzzles using logical thinking and mathematics. Our course offers a blend of practical coding and development experience with theory and discussion of how computers work and their impact on society. Computer Science is a creative subject that combines invention and excitement, that can look at the natural world through a digital prism.

Entry requirements

A minimum of 4 subjects at grade 5 or above at GCSE with a grade 5 in GCSE English Language and a grade 6 in Maths. GCSE Computer Science is not a prerequisite but is an advantage.

What will I study?

You will gain an understanding of different levels and types of programming languages and scripting. Strategies for problem-solving are studied, together with information management techniques. You will gain an understanding of computer hardware and software functionality as well as a detailed appreciation of how computer architectures operate. The course addresses all stages of the life cycle of computer software.

Units studied include:

Computer Systems

• Characteristics of processors, input, output and storage devices
• Software types and software development
• Networks and exchanging data (web, encryption and security)
• Data types, data structures and algorithms
• Legal, moral, cultural and ethical issues

Algorithms and Programming

• Elements of computational thinking (designing and coding in C#)
• Problem solving and programming (coding in C# and using LMC)
• Algorithms to solve problems and standard algorithms (e.g. sorting, traversal)

Method of delivery

You will be taught in well-equipped computer rooms for every session. Individual computers are available both in session and during study times to enable you to use online learning and resources effectively. Our A Level Computing team all bring experience from industry as well as years of teaching experience. Each member has experience of examination marking and/or external verification.

How will I be assessed?

OCR Computer Science A Level: Two x 150 minute exams plus 20% coursework (NEA).

Programming Project: The NEA (Non-Exam Assessment) coursework is a student-led experience of problem analysis, system design, software development and testing and evaluating. Your project will be of your own choice, assessed internally and moderated by an external examiner.

In the past students have produced exciting games, simulations, web applications and robot programs. Students will need to do autonomous research to develop more complex projects.

Good course combinations

This course combines well with most other A Levels and is particularly complemented by Maths, and sciences or Engineering. Other successful students have a strong background in creative or humanities subjects such as Design Technology and Media.

Your next steps

Computer Science is an extremely useful A Level, leading into a wide variety of computer-based disciplines, plus technologically rich subjects such as engineering or science. Computer Science skills and an understanding of technology are relevant to a wide range of careers and courses.

Students can progress into industry or apprenticeships to gain experience and qualifications as a Software Engineer, Software Developer, and a host of related roles. There is a significant shortage in Computer Science skills so your knowledge will be in demand! Students typically go on to study degree courses in:

• Computer Science
• Artificial Intelligence
• Computer Games Programming
• Cybersecurity
• Business Computing
• Engineering
• Mathematics
• Aeronautics

Computer Science is an area I have had interest in for a long time. The College course has been so worthwhile and interesting. The programming project in this course helps us to be prepared for the real world of work and the tutors here are really knowledgeable.

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A Level Computer Science

What Board do we do?  AQA, AS/A Level code: AS (7516) A Level (7517)

The new AS and A Levels in Computer Science are now "standalone" qualifications. Marks gained at AS Level do not contribute to the final grade at A Level.

What is Computer Science? Computer Science is a discipline which requires thinking both in abstract and in concrete terms. On a higher level, computer science is concerned with problem-solving: modelling and analysing problems, designing solutions, and implementing them. Problem-solving requires precision, creativity, and careful reasoning.

In AS and A Level Computer Science, students learn the principles of computation and algorithms, computer programming, machine data representation, computer systems (hardware and software), computer organisation and architecture, communications and networking, databases and the consequences of using computing. The syllabus is taught in Python.

Which subjects combine well with Computer Science?  Computer Science has strong connections to many other disciplines. Mathematics , Further Mathematics ,  Physics , and Economics combine well with Computer Science. 

Students who wish to study for a Computer Science degree should combine it with A Level Mathematics as this is a prerequisite at many universities.

What can Computer Science lead to?  A good grade in Computer Science at A Level is valued by universities and employers since it requires the development of analytical thinking and problem solving skills. This course also lays an appropriate foundation for further study of Computer Science, Engineering, Physics or related subjects in higher education. Many problems in the sciences, engineering, health care, business and other areas can be solved effectively with computers, but finding a solution requires both computer science expertise and knowledge of the particular application domain. Thus, computer scientists often become proficient in other subjects. 

AS Level AS Paper 1 on-screen exam: 50% of the marks

Students answer a series of short questions and write/adapt/extend programs in an electronic answer document. This paper tests a student's programming ability, and theoretical knowledge of data structures, systematic problem solving, and the theory of computation.

AS Paper 2 written exam: 50% of the marks

This paper tests the fundamentals of data representation, computer systems (hardware and software), computer architecture and organisation, communications and networking, and the consequences of using computing.

A Level A Level Paper 1 on-screen exam: 40% of the marks

Students answer a series of short questions and write/adapt/extend programs in an electronic answer document. This paper is in Python. This paper tests a student's programming ability, and theoretical knowledge of data structures, systematic problem solving, and the theory of computation.

A Level Paper 2 written exam: 40% of the marks

This paper tests the fundamentals of data representation, computer systems (hardware and software), computer architecture and organisation, communications and networking, the consequences of using computing, databases and big data, and functional programming.

Non exam assessment: 20% of the marks

This coursework unit assesses students’ ability to use the knowledge and skills gained through the course to solve or investigate a practical problem.

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Online A Level Computer Science

Description.

Our online Computer Science A Level course is meticulously designed to equip students with a comprehensive understanding of computational thinking, problem-solving, and the development of computer-based solutions. This cutting-edge A Level computer science online curriculum dives deep into algorithms, programming languages, and the ethical implications that arise in the realm of current and emerging computing technologies.

Additionally, the course provides a robust foundation in Information representation, communication and Internet technologies, hardware, software development, and relational database modelling. If you’re looking to gain an edge in the ever-evolving tech industry or pursue further studies in Computer Science, this course offers you a ticket to a bright future.

Homework, Assessment and Reporting

Students enrolled in our A Level computer science course online are expected to complete at least one piece of homework per subject each week. To maximise success, it’s imperative to revise class notes and solidify one’s understanding after each lesson. The rule of thumb is to dedicate an hour of independent study for every hour of in-class instruction.

Assessment is a structured process with Level 5 internal assessments occurring in June and Level 6 internal mock assessments scheduled for November and March. Following these assessments, comprehensive reports are issued. These reports include grades for both attainment and effort, along with valuable written feedback from Success Coaches and the Head Teacher, at the end of the Autumn and Summer terms for Level 5 and after the mock assessments for Level 6.

Parental Engagement

Parents are highly encouraged to actively participate in their child’s educational journey. Our unique family Teams account enables parents to maintain an ongoing dialogue with teachers throughout the academic year. This provides a more detailed tracking of student progress, far exceeding what a typical annual parent consultation evening could offer.

Embark on an intellectually stimulating journey with our A Level Computer Science online course and prepare for a future where technology is omnipresent.

Click here to see this year’s Assessment and Reporting schedule

Students will gain knowledge and understanding of Computer Studies by studying the key topics – see ‘Key Topics’ section below. Students gain technical skills, as well as being able to effectively test and evaluate computing solutions. Studying A Level Computer Science will help students appreciate computing technologies, how they can be used and the potential risks.

1. Theory Fundamentals

1.1 Information representation

1.1.1 Number representation

1.1.2 Images

1.1.3 Sound

1.1.4 Video

1.1.5 Compression techniques

1.2 Communication and Internet technologies

1.2.1 Networks

1.2.2 IP addressing

1.2.3 Client- and server-side scripting

1.3 Hardware

1.3.1 Input, output and storage devices

1.3.2 Main memory

1.3.3 Logic gates and logic circuits

1.4 Processor fundamentals

1.4.1 CPU architecture

1.4.2 The fetch-execute cycle

1.4.3 The processor’s instruction set

1.4.4 Assembly language

1.5 System software

1.5.1 Operating system

1.5.2 Utility programs

1.5.3 Library programs

1.5.4 Language translators

1.6 Security, privacy and data integrity

1.6.1 Data security

1.6.2 Data integrity

1.7 Ethics and ownership

1.7.1 Ethics

1.7.2 Ownership

1.8 Database and data modelling

1.8.1 Database Management Systems (DBMS)

1.8.2 Relational database modelling

1.8.3 Data Definition Language (DDL) and Data Manipulation Language (DML)

2. Fundamental Problem-Solving and Programming

2.1 Algorithm design and problem-solving

2.1.1 Algorithms

2.1.2 Structure chart

2.1.3 Corrective maintenance

2.1.4 Adaptive maintenance

2.2 Data representation

2.2.1 Data types

2.2.2 Arrays

2.2.3 Files

2.3 Programming

2.3.1 Programming basics

2.3.2 Transferable skills

2.3.3 Selection

2.3.4 Iteration

2.3.5 Built-in functions

2.3.6 Structured programming

2.4 Software development

2.4.1 Programming

2.4.2 Program testing

2.4.3 Testing strategies

3. Advanced Theory

3.1 Data representation

3.1.1 User-defined data types

3.1.2 File organisation and access

3.1.3 Real numbers and normalised floating-point representation

3.2 Communication and Internet technologies

3.2.1 Protocols

3.2.2 Circuit switching, packet switching and routers

3.2.3 Local Area Networks (LAN)

3.3 Hardware

3.3.1 Logic gates and circuit design

3.3.2 Boolean algebra

3.3.3 Karnaugh Maps

3.3.4 Flip-flops

3.3.5 RISC processors

3.3.6 Parallel processing

3.4 System software

3.4.1 Purposes of an operating system (OS)

3.4.2 Virtual machine

3.4.3 Translation software

3.5 Security

3.5.1 Asymmetric keys and encryption methods

3.5.2 Digital signatures and digital certificates

3.5.3 Encryption protocols

3.5.4 Malware

3.6 Monitoring and control systems

3.6.1 Overview of monitoring and control systems

3.6.2 Bit manipulation to monitor and control device

Computer, broadband internet connection

It is the parents’ responsibility to arrange their child’s examinations; our teachers will provide all the support required. Most students will sit their examination papers at a school or college who accept private candidates. Some students sit their examinations at private examination centres.

If you are intending to study A Level Computer Science, we recommend that you spend some time in the summer holidays preparing.

Work through the Java Script tutorials on W3 Schools: JavaScript Tutorial

What skills will students develop in the A Level Computer Science online course?

The A Level Computer Science online course is designed to help students enhance their computational thinking and problem-solving skills. They will learn how to develop solutions using algorithms and various programming languages. Students will also understand the ethical considerations that accompany current and emerging technologies.

What topics are covered in the Computer Science A Level course?

The course dives into various subjects such as information representation, communication and Internet technologies, hardware, software development, and relational database modelling. It aims to provide a comprehensive understanding of these areas, helping students gain both knowledge and practical skills.

What is the assessment structure for the online Computer Science A Level?

Students in the sixth form are required to complete a minimum of one piece of homework per subject weekly. Internal assessments occur in June, November, and March. Reports are then issued twice a year and comprise grades for both attainment and effort, accompanied by written feedback from the educators.

How is progress monitored in the Computer Science A Level online course?

Parents can engage in continuous dialogue with teachers through their family Teams account, which allows for more thorough tracking of a student’s progress throughout the year compared to a single annual consultation evening.

What equipment is needed for the Computer Science A Level online course?

The teachers.

Computer Science at Cambridge Home School Online is taught by Mr Evans and Mr Descombe. Click on the names below to find out more about our Computer Science teachers.

How to apply

Our school is nearly always full, with very few school places!

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AS and A-level Computer Science

• Specification
• Planning resources
• Teaching resources
• Assessment resources
• Introduction
• Specification at a glance
• 3.1 Fundamentals of programming
• 3.2 Fundamentals of data structures
• 3.3 Systematic approach to problem solving
• 3.4 Theory of computation
• 3.5 Fundamentals of data representation
• 3.6 Fundamentals of computer systems
• 3.7 Fundamentals of computer organisation and architecture
• 3.8 Consequences of uses of computing
• 3.9 Fundamentals of communication and networking
• 4.1 Fundamentals of programming
• 4.2 Fundamentals of data structures
• 4.3 Fundamentals of algorithms
• 4.4 Theory of computation
• 4.5 Fundamentals of data representation
• 4.6 Fundamentals of computer systems
• 4.7 Fundamentals of computer organisation and architecture
• 4.8 Consequences of uses of computing
• 4.9 Fundamentals of communication and networking
• 4.10 Fundamentals of databases
• 4.11 Big Data
• 4.12 Fundamentals of functional programming
• 4.13 Systematic approach to problem solving

4.14 Non-exam assessment - the computing practical project

• Scheme of assessment
• Non-exam assessment administration
• General administration

Purpose of the project

The project allows students to develop their practical skills in the context of solving a realistic problem or carrying out an investigation. The project is intended to be as much a learning experience as a method of assessment; students have the opportunity to work independently on a problem of interest over an extended period, during which they can extend their programming skills and deepen their understanding of computer science.

The most important skill that should be assessed through the project is a student's ability to create a programmed solution to a problem or investigation. This is recognised by allocating 42 of the 75 available marks to the technical solution and a lower proportion of marks for supporting documentation to reflect the expectation that reporting of the problem, its analysis, the design of a solution or plan of an investigation and testing and evaluation will be concise.

Types of problem/investigation

Students are encouraged to choose a problem to solve or investigate that will interest them and that relates to a field that they have some knowledge of. There are no restrictions on the types of problem/investigation that can be submitted or the development tools (for example programming language) that can be used. The two key questions to ask when selecting a problem/investigation are:

• Does the student have existing knowledge of the field, or are they in a position to find out about it?
• Is a solution to the problem/investigation likely to give the student the opportunity to demonstrate the necessary degree of technical skill to achieve a mark that reflects their potential?

Some examples of the types of problem to solve or investigate are:

• a simulation for example, of a business or scientific nature, or an investigation of a well-known problem such as the game of life
• a solution to a data processing problem for an organisation, such as membership systems
• the solution of an optimisation problem, such as production of a rota, shortest-path problems or  route finding
• a computer game
• an application of artificial intelligence
• a control system, operated using a device such as an Arduino board
• a website with dynamic content, driven by a database back-end
• an app for a mobile phone or tablet
• an investigation into an area of computing, such as rendering a three-dimensional world on screen
• investigating an area of data science using, for example, Twitter feed data or online public data sets
• investigating machine learning algorithms.

There is an expectation that within a centre, the problems chosen by students to solve or investigate will be sufficiently different to avoid the work of one student informing the work of another because they are working on the same problem or investigation. Teachers will be required to record on the Candidate Record Form for each student that they have followed this guideline. If in any doubt on whether problems chosen by students have the potential to raise this issue, please contact your AQA adviser.

Table 1 and Table 2 show the technical skills and coding styles required for an A-level standard project. If a problem/investigation is selected that is not of A-level standard then the marks available in each section will be restricted.

Project documentation structure

The project is assessed in five sections. The table below lists the maximum available mark for each section of the project:

For marking purposes, the project documentation should be presented in the order indicated in the table above. The table does not imply that students are expected to follow a traditional systems life cycle approach when working on their projects, whereby a preceding stage must be completed before the next can be tackled. It is recognised that this approach is unsuited to the vast majority of project work, and that project development is likely to be an iterative process, with earlier parts of the project being revisited as a result of discoveries made in later parts. Students should be encouraged to start prototyping and writing code early on in the project process. A recommended strategy is to tackle the critical path early in the project development process. The critical path is the part of the project that everything else depends on for a working system or a complete investigation result to be achieved.

Using a level of response mark scheme

Level of response mark schemes are broken down into a number of levels, each of which has a descriptor. The descriptor for the level shows the average performance for the level. There are a range of marks in each level. The descriptor for the level represents a typical mid-mark performance in that level.

Before applying the mark scheme to a student’s project, read it through and annotate it to show the qualities that are being looked for. You can then apply the mark scheme.

Step 1 Determine a level

Start at the lowest level of the mark scheme and use it as a ladder to see whether the performance in that section of the project meets the descriptor for that level. The descriptor for the level indicates the different qualities that might be seen in the student’s work for that level. If it meets the lowest level then go to the next one and decide if it meets this level, and so on, until you have a match between the level descriptor and the work. With practice and familiarity you will find you will be able to quickly skip through the lower levels of the mark scheme.

When assigning a level you should look at the overall quality of the work rather than any small or specific parts where the student has not performed quite as the level descriptor. If the work covers different aspects of different levels of the mark scheme you should use a best fit approach for defining the level and then use the variability of the response to help decide the mark within the level. ie if the response is predominantly level 3 with a small amount of level 4 material it would be placed in level 3 but be awarded a mark near the top of the level because of the level 4 content.

Step 2 Determine a mark

Once you have assigned a level you need to decide on the mark. The exemplar materials used for standardisation will help. This work will have been awarded a mark by AQA. You can compare your student’s work with the exemplar to determine if it is the same standard, better or worse. You can then use this to allocate a mark for the work based on AQA's mark on the exemplar.

You may well need to read back through the work as you apply the mark scheme to clarify points and assure yourself that the level and the mark are appropriate.

Work which contains nothing of relevance to the project area being assessed must be awarded no marks for that area.

Marking criteria

Analysis (9 marks), documented design (12 marks), technical solution (42 marks), completeness of solution (15 marks), techniques used (27 marks).

Select the band, 1, 2 or 3 with level of demand description that best matches the techniques and skill that the student’s program attempts to cover. The emphasis is on what the student has actually achieved that demonstrates proficiency at this level rather than what the student has set out to use and do but failed to demonstrate, eg because of poor execution. Check the proficiency demonstrated in the program. If the student fails to demonstrate proficiency at the initial level of choice, drop down a level to see if what the student has done demonstrates proficiency at this level for the lower demand until a match is obtained. Table 1 is indicative of the standard required and is not to be treated as just a list of things for students to select from and to be automatically credited for including in their work.

As indicated above, having selected the appropriate level for techniques used and proficiency in their use, the exact mark to award should be determined based upon:

• the extent to which the criteria for the mark band have been achieved
• the quality of the coding style that the student has demonstrated (see Table 2 for exemplification of what is expected)
• the effectiveness of the solution.

Example technical skills

Table 1: example technical skills.

Note that the contents of Table 1 are examples, selected to illustrate the level of demand of the technical skills that would be expected to be demonstrated in each group. The use of alternative algorithms and data models is encouraged. If a project cannot easily be marked against Table 1 (for example, a project with a considerable hardware component) then please consult your AQA non-exam assessment Adviser or provide a full explanation of how you have arrived at the mark for this section when submitting work for moderation.

Table 2: Coding styles

The descriptions in Table 2 are cumulative, ie for a program to be classified as excellent it would be expected to exhibit the characteristics listed as excellent, good and basic not just those listed as excellent.

Testing (8 marks)

Evidence for the testing section may be produced after the system has been fully coded or during the coding process. It is expected that tests will either be planned in a test plan or that the tests will be fully explained alongside the evidence for them. Only carefully selected representative samples are required.

Evaluation (4 marks)

Project tasks that are not of a-level standard.

If the task (problem or investigation) selected for a project is not of A-level standard, mark the project against the criteria given, but adjust, the mark awarded downwards by two marking levels (two marks in the case of evaluation) in each section for all but the technical solution. You should have already taken the standard into account for this, by directly applying the criteria. For example, if a student had produced a 'fully or nearly fully articulated design of a real problem describing how solution is to be structured/is structured'. This would, for an A-level standard project, achieve a mark in Level Four for Documented Design (10-12 marks). If the problem selected was too simple to be of A-level standard but the same criteria had been fulfilled, shift the mark awarded down by two levels, into Level Two, an award of 4-6 marks. If a downward shift by two levels is not possible, then a mark in the lowest level should be awarded.

Guide to non-exam assessment documentation

Students are expected to:

• produce a clear statement that describes the problem area and specific problem that is being solved/investigated
• outline how they researched the problem
• state for whom the problem is being solved/investigated
• provide background in sufficient detail for a third party to understand the problem being solved/investigated
• produce a numbered list of measurable, "appropriate" specific objectives, covering all required functionality of the solution or areas of investigation (Appropriate means that the specific objectives are single purpose and at a level of detail that is without ambiguity.)
• report any modelling of the problem that will inform the Design stage, for example a graph/network model of Facebook connections or an E-R model.

A fully scoped analysis is one that has:

• researched the problem thoroughly
• has clearly defined the problem being solved/investigated
• omitted nothing that is relevant to subsequent stages
• statements of objectives which clearly and unambiguously identify the scope of the project
• modelled the problem for the Design stage where this is possible and necessary.

Students are expected to articulate their design in a manner appropriate to the task and with sufficient clarity for a third party to understand how the key aspects of the solution/investigation are structured and on what the design will rely, eg use of numerical and scientific package libraries, data visualisation package library, particular relational database and/or web design framework. The emphasis is on communicating the design; therefore it is acceptable to provide a description of the design in a combination of diagrams and prose as appropriate, as well as a description of algorithms, SQL, data structures, database relations as appropriate, and using relevant technical description languages, such as pseudo-code. Where design of a user interface is relevant, screen shots of actual screens are acceptable.

Technical solution

Students should provide program listing(s) that demostrate their technical skill. The program listing(s) should be appropriately annotated and self-documenting (an approach that uses meaningful identifiers, with well structured code that minimises instances where program comments are necessary).

Students should present their work in a way that will enable a third party to discern the quality and purpose of the coding. This could take the form of:

• an overview guide which amongst other things includes the names of entities such as executables, data filenames/urls, database names, pathnames so that a third party can, if they so desire, run the solution/investigation
• explanations of particularly difficult-to-understand code sections; a careful division of the presentation of the code listing into appropriately labelled sections to make navigation as easy as possible for a third party reading the code listing.

Students must provide and present in a structured way for example in tabular form, clear evidence of testing. This should take the form of carefully selected and representative samples, which demonstrate the robustness of the complete, or nearly complete, solution/thoroughness of investigation and which demonstrate that the requirements of the solution/investigation have been achieved. The emphasis should be on producing a representative sample in a balanced way and not on recording every possible test and test outcome. Students should explain the tests carried out alongside the evidence for them. This could take the form of:

• an introduction and overview
• the test performed
• its purpose if not self-evident
• the test data
• the expected test outcome
• the actual outcome with a sample of the evidence, for example screen shots of before and after the test, etc, sampled in order to limit volume.

Students should consider and assess how well the outcome meets its requirements. Students should obtain independent feedback on how well the outcome meets its requirements and discuss this feedback. Some of this feedback could be generated during prototyping. If so, this feedback, and how/why it was taken account must be presented and referenced so it can be found easily.

Students should also consider and discuss how the outcome could be improved more realistically if the problem/investigation were to be revisited.

Assessment objective breakdown for non-exam assessment

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Computer Science, BA (Hons) and MEng

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Computer Science at Cambridge

Computer Science at Cambridge brings together disciplines including mathematics, engineering, the natural sciences, psychology and linguistics.

Study modern computer science, along with the underlying theory and foundations in economics, law and business.  

Here at Cambridge, we pioneered computer science and we continue to lead its development today.

Our links to Computing go back to the 1930s when Alan Turing developed the theoretical foundations for computation. We’ve been at the forefront of Computer Science research ever since.

This is a broad and deep course that covers all aspects of modern computer science.

We have 3 and 4 year course options:

• the 3-year course is a BA honours degree
• the 4-year course includes a Masters, leading to a BA and Master of Engineering (MEng) degree

Whichever option you choose, you will develop practical skills in:

• programming, in various languages such as OCaml, Java, C/C++ and Prolog
• hardware systems, such as chip design

Teaching and facilities

We are the oldest Computer Science department in the world – our Computer Lab has been at the forefront of research in Computer Science ever since its inception, in 1970.

We offer a learning environment that is creative, stimulating, modern and entrepreneurial. You will be taught by pioneers and leading researchers in this fast-moving field.

You'll also take part in group projects which will be presented to external companies. Find out more about how Computer Science at Cambridge can support your future career.

The Department of Computer Science and Technology is packed with the latest technology. Our facilities include:

• advanced lecture theatres
• dedicated practical rooms

Our West Cambridge site, home of the Computer Laboratory, offers:

• a fantastic environment for both study and relaxation
• a large library stocked with the latest Computer Science publications
• big and comfortable lecture theatres
• a great café

At Cambridge, you'll also have access to the impressive Cambridge University Library, one of the world’s oldest university libraries.

Course costs

When you go to university, you’ll need to consider two main costs – your tuition fees and your living costs (sometimes referred to as maintenance costs).

Your living costs will include costs related to your studies that are not covered by your tuition fees. There are some general study costs that will apply for all students – you can find details of these costs here .

Other additional costs for Computer Science are detailed below. If you have any queries about resources/materials, please contact the Department.

• Laptop specification: £800 for a modern entry-level laptop is sufficient, but we recommend at least half the main drive is dedicated to a bootable Linux system, such as Ubuntu.
• University approved scientific calculator: please see the Department website for details.

You don't have to buy your own copies of textbooks, but it's strongly recommended. The number of textbooks you need depends on the course options you’ve chosen. The costs below are an estimate of how much you can expect to spend each year if you do purchase your own copies.

• Year 1: Estimated cost of core texts £150.
• Years 2, 3 and 4: Estimated cost of core texts £150 to £250 per year.

Your future career

There are more than 1,000 specialist computing and advanced technology companies and commercial laboratories in the Cambridge area, known as ‘Silicon Fen'.

A number of local firms and start-ups support our teaching and employ our graduates, in areas from chip design to mathematical modelling and AI.

As a graduate, you’ll have knowledge and skills that embody principles which will outlast today’s technology. This makes you highly sought after by industry and commerce alike.

Many of our graduates go on to work as:

• programmers
• software development professionals

Other graduates decide to pursue:

• further study
• careers in teaching and research

Many have also founded companies, or gained employment in:

• the games industry
• communications

Teaching is provided through lectures, practical classes and small-group supervisions.

In your first year you will typically have 20 hours of teaching each week, including up to 12 lectures and practical classes.

In your first and second year you will be assessed through 3-hour examinations, taken in the final term of each year.

In your third year you will be assessed through coursework and 3-hour examinations.

Practical work is undertaken and assessed in all years of the degree programme.

You won't usually be able to resit any of your exams.

Year 1 (Part IA)

You take 4 papers, including 3 compulsory Computer Science papers, covering topics such as:

• foundations of computer science, taught in OCaml
• Java and object-oriented programming
• operating systems
• digital electronics
• interaction design
• machine learning

You will also take a Mathematics paper, from the first year of the Natural Sciences course.

Year 2 (Part IB)

You take 4 papers, spanning core topics:

• theory – including logic and proof, computation theory
• systems – including computer architecture, computer networking
• programming – including compiler construction, programming in C/C++
• human aspects – including Human Interaction design, Artificial Intelligence

You also undertake a group project, which reflects current industrial practice.

Year 3 (Part II)

You choose from a large selection of topics which allows you to concentrate on an area of interest to you, such as:

• computer architecture
• applications (including bioinformatics and natural language processing)

New topics inspired by current research interests include computer architecture, data science and robotics.

You will also work on a substantial project that demonstrates your computer science skills, and write a 10,000 to 12,000 word dissertation on it.

Projects are often connected with current Cambridge research, and many utilise cutting-edge technology.

Year 4 (Part III, optional Masters)

The fourth year is designed for students considering a career in academic or industrial research.

• explore issues at the very forefront of computer science
• undertake a substantial research project

Progression to fourth year depends on how well you do in your third year exams.

If you successfully complete the fourth year, you’ll get the MEng qualification, as well as the BA degree which you get at the end of the third year.

• For further information about this course and the papers you can take see the Faculty of Computer Science and Technology website .

Changing course

It’s really important to think carefully about which course you want to study before you apply. 

In rare cases, it may be possible to change course once you’ve joined the University. You will usually have to get agreement from your College and the relevant departments. It’s not guaranteed that your course change will be approved.

You might also have to:

• take part in an interview
• complete an admissions test
• produce some written work
• achieve a particular grade in your current studies
• do some catch-up work
• start your new course from the beginning 

For more information visit the Faculty website .

You can also apply to change to:

• Management Studies at the Judge Business School

You can't apply to this course until you're at Cambridge. You would usually apply when you have completed 1 year or more of your original Cambridge course.

You should contact your College’s Admissions Office if you’re thinking of changing your course. They will be able to give you advice and explain how changing courses works.

Minimum offer level

A level: A*A*A IB: 41-42 points, with 776 at Higher Level Other qualifications : Check which other qualifications we accept .

Subject requirements

To apply to any of our Colleges for Computer Science, you will need A levels/IB Higher Levels (or the equivalent) in: 

• Mathematics 
• Further Mathematics to AS or A level if your school offers it. Please see the further guidance below. 

If you’re studying IB, we ask for Analysis and Approaches for this course. If this isn’t an option at your school, please contact the College you wish to apply to for advice. 

If you’re applying to Churchill, Downing or Lucy Cavendish, you will also need a third science subject at A level/IB Higher Level. If you apply to Christ's College you must have Further Mathematics A level.

Colleges will require A*/7 in Mathematics or Further Mathematics. Colleges may also require an A*/7 in specific subjects as part of your offer. If you apply to Churchill College they require an A*/7 in Chemistry, Computer Science or Physics as well as Mathematics or Further Mathematics. 

These subject requirements are provisional for 2025 entry. Please check back in April 2024 for confirmed details.

Further Mathematics A level and additional maths 

If your school offers Further Mathematics to AS or A level, you should take it.  

Additional mathematics is helpful and all candidates are strongly encouraged to take up opportunities to develop their skills, such as by participating in olympiads or accessing the online resources in the Advanced Mathematics Support Programme .

What Computer Science students have studied

Most Computer Science students (who had studied A levels and started at Cambridge in 2017-19) achieved at least A*A*A* (81% of entrants).

All of these students studied Mathematics and most also took:

• Further Mathematics (96%)
• Physics (85%)
• Computing (59%)

The majority of students who studied IB achieved at least 43 points overall.

Check our advice on choosing your high school subjects . You should also check if there are any required subjects for your course when you apply.

Admission assessment

All applicants for Computer Science for 2025 entry are required to take the Test of Mathematics for University Admission (TMUA) at an authorised assessment centre. You must register in advance for this test.

Please see the admissions test page for more information.

Check the TMUA page for further details and example papers.

Submitted work

You won't usually be asked to submit examples of written work. You may be asked to do some reading prior to your interview, but if this is required the College will provide full details in your interview invitation.

Offers above the minimum requirement

The minimum offer level and subject requirements outline the minimum you'll usually need to achieve to get an offer from Cambridge.

In some cases, you'll get a higher or more challenging offer. Colleges set higher offer requirements for a range of reasons. If you'd like to find out more about why we do this,  check the information about offers above the minimum requirement  on the entry requirements page.

Some Colleges usually make offers above the minimum offer level. Find out more on our qualifications page .

All undergraduate admissions decisions are the responsibility of the Cambridge Colleges. Please contact the relevant  College admissions office  if you have any queries.

Discover your department or faculty

• Visit the Department of Computer Science and Technology website - The Department of Computer Science and Technology website has more information about this course, facilities, people and research.

Explore our Colleges

• Find out how Colleges work - A College is where you’ll live, eat and socialise. It’s also where you’ll have teaching in a small group, known as supervisions.
• How to choose a Cambridge College that's right for you - If you think you know which course you’d like to study, it’s time to choose a College.

Visit us on open day

• Book an open day - Get a feel for the city and the University.
• Find an event - We offer a range of events where you can find out more about Cambridge, Colleges, and your course. Many of our events have hybrid options so you can join us virtually.

Find out how to apply

• Find out how to apply and how our admissions processes work - Our admissions process is slightly different to other universities. We’ve put together a handy guide to tell you everything you need to know about applying to study at Cambridge.
• Improve your application - Supercurricular activities are a great way to engage with your chosen subject outside of school or college.

Discover Uni data

Contextual information.

Discover Uni allows you to compare information about individual courses at different higher education institutions.  This can be a useful method of considering your options and what course may suit you best.

However, please note that superficially similar courses often have very different structures and objectives, and that the teaching, support and learning environment that best suits you can only be determined by identifying your own interests, needs, expectations and goals, and comparing them with detailed institution- and course-specific information.

We recommend that you look thoroughly at the course and University information contained on these webpages and consider coming to visit us on an Open Day , rather than relying solely on statistical comparison.

You may find the following notes helpful when considering information presented by Discover Uni.

• Discover Uni relies on superficially similar courses being coded in the same way. Whilst this works on one level, it may lead to some anomalies. For example, Music courses and Music Technology courses can have exactly the same code despite being very different programmes with quite distinct educational and career outcomes. Any course which combines several disciplines (as many courses at Cambridge do) tends to be compared nationally with courses in just one of those disciplines, and in such cases the Discover Uni comparison may not be an accurate or fair reflection of the reality of either. For example, you may find that when considering a degree which embraces a range of disciplines such as biology, physics, chemistry and geology (for instance, Natural Sciences at Cambridge), the comparison provided is with courses at other institutions that primarily focus on just one (or a smaller combination) of those subjects.You may therefore find that not all elements of the Cambridge degree are represented in the Discover Uni data.
• Some contextual data linked from other surveys, such as the National Student Survey (NSS) or the Destination of Leavers in Higher Education (DLHE), may not be available or may be aggregated across several courses or several years due to small sample sizes.  When using the data to inform your course choice, it is important to ensure you understand how it has been processed prior to its presentation. Discover Uni offers some explanatory information about how the contextual data is collated, and how it may be used, which you can view here: https://discoveruni.gov.uk/about-our-data/ .
• Discover Uni draws on national data to provide average salaries and employment/continuation data.  Whilst starting salaries can be a useful measure, they do not give any sense of career trajectory or take account of the voluntary/low paid work that many graduates undertake initially in order to gain valuable experience necessary/advantageous for later career progression. Discover Uni is currently piloting use of the Longitudinal Education Outcomes (LEO) data to demonstrate possible career progression; it is important to note that this is experimental and its use may be modified as it embeds.

The above list is not exhaustive and there may be other important factors that are relevant to the choices that you are making, but we hope that this will be a useful starting point to help you delve deeper than the face value of the Discover Uni data.

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PhD student receives fellowship from Apple Scholars program

Nataliya Nechyporenko, a computer science Ph.D. student, has received a PhD fellowship in AI and Machine Learning (AIML) through the Apple Scholars program . The program was created by Apple to recognize the contributions of emerging leaders in computer science and engineering at the graduate and postgraduate level. 

The fellowship provides Nechyporenko support for her research and academic travel for two years, internship opportunities and a two-year mentorship with an Apple researcher. 

Let's learn more about Nechyporenko's research aims and her perspective on the future of robotics research: 

What research do you hope to accomplish through this fellowship?

Think about how you might manually feel around an object to understand its shape, weight, and texture. Or if something is in your way, you'd just push it aside without overthinking it. If you drop something, you'll persistently keep trying to pick it up from different angles until you get it. As you're doing these everyday tasks, you're constantly building up an intuitive sense of your surroundings through trial-and-error. That's the kind of resourceful, flexible, multi-sensory approach I want robots to have when manipulating things – rather than just blindly following a fixed routine. 

The goal is for robotic arms to move and behave with that same kind of curious, improvisational, problem-solving spirit we take for granted as humans. As an Apple AIML scholar, I hope to gain insights into this problem with the help of a fresh network of mentors and collaborators.  

Is this an extension of work you are already doing in your lab? If so, how?

Driven to establish contact-rich planning as a dominant feature in robotics, I focused the first two years of my PhD on analyzing the methods used by state-of-the-art planners and solving the shortcomings leading to the lack of physical robot interaction. 

I have started to extend this work by integrating the empirical formulation of machine learning with model-based algorithmic approaches. I believe this is the path to making robots more adaptable to chaotic human environments. I will continue this work as an Apple scholar. 

What do you think of the current hype around AI and ML? What do you wish people understood about this research area?

The AI and machine learning hype trains have been barreling full steam ahead lately. But robotics? That's an entirely different beast that doesn't follow the overnight disruption narratives. It's a synergy of achievements in areas like materials, manufacturing, sensing, controls theory, and others aligning to reshape the physical world. 

The robotics future will reshape industries and labor concepts, but it will be catalyzed through the patient advancement of many disciplines.

How did you come to study at CU Boulder?

I spent a couple years in the trenches, getting my hands dirty actually building and deploying robots in industry. But after a while, I got this craving -- like there was so much more potential waiting to be unlocked if I could really dive into the deep scientific questions around robotics. That's why I decided to take the plunge back into academia.

What is one of your plans or hopes for the future, either professionally or personally?

I hope to be an expert, a leader, a thinker and a builder. Outside of research endeavors, I aim to be a leader and educator for the robotics and the AI community. Previously, I’ve led volunteering activities, mentored students, and co-organized events that foster discussions around AI. I hope to continue to do so in the future at a larger scale. 

• Alessandro Roncone
• Graduate Student Stories

Nataliya Nechyporenko

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Office of the Vice President for Research

Four clas faculty researchers secure prestigious early career awards.

Continuing  an upward trend of University of Iowa faculty securing prestigious early-career grants, four investigators from the Departments of Physics and Astronomy and Computer Science have been awarded notable grant awards to advance their careers.

DeRoo, Hoadley advance space instrumentation with Nancy Grace Roman Technology Fellowships in Astrophysics for Early Career Researchers

Casey DeRoo and Keri Hoadley , both assistant professors in the Department of Physics and Astronomy, each received a Nancy Grace Roman Technology Fellowship in Astrophysics for Early Career Researchers. The NASA fellowship provides each researcher with $500,000 over two years to support their research in space-based instrumentation. 

Hoadley’s research is two-pronged. She will design and ultimately prototype a mirror-based vacuum ultraviolet polarizer, which will allow researchers to access polarized light from space below 120-nanometer wavelength. Polarizing light at such a low wavelength is crucial to building optics for NASA’s future Habitable World Observatory (HWO), the agency’s next flagship astrophysics mission after the Nancy Grace Roman Space Telescope. 

“Our vacuum ultraviolet polarizer project is meant to help set up our lab to propose to NASA for one or more follow-up technology programs, including adapting this polarizer for use in vacuum systems, duplicating it and measuring its efficiency to measure additional flavors of polarized UV light, quantifying the polarization effects introduced by UV optical components that may be used on HWO, and building an astronomical instrument to measure the polarization of UV from around massive stars and throughout star-forming regions,” said Hoadley.

In addition, Hoadley and her team will build a facility to align, calibrate, and integrate small space telescopes before flight, using a vacuum chamber and wavelengths of light typically only accessible in space, which could help the university win future small satellite and suborbital missions from NASA. 

DeRoo will work to advance diffraction gratings made with electron beams that pattern structures on a nanometer scale.   Like a prism, diffraction gratings spread out and direct light coming from stars and galaxies, allowing researchers to deduce things like the temperature, density, or composition of an astronomical object.

The fellowship will allow DeRoo to upgrade the university’s Raith

 Voyager tool, a specialized fabrication tool hosted by OVPR’s Materials Analysis, Testing and Fabrication (MATFab) facility.

“These upgrades will let us perform algorithmic patterning, which uses computer code to quickly generate the patterns to be manufactured,” DeRoo said. “This is a major innovation that should enable us to make more complex grating shapes as well as make gratings more quickly.” DeRoo added that the enhancements mean his team may be able to make diffraction gratings that allow space instrument designs that are distinctly different from those launched to date.

“For faculty who develop space-based instruments, the Nancy Grace Roman Technology Fellowship is on par with the prestige of an NSF CAREER or Department of Energy Early Career award,” said Mary Hall Reno, professor and department chair. “Our track record with the program elevates our status as a destination university for astrophysics and space physics missions.”

Uppu pursues building blocks quantum computing with NSF CAREER Award

Ravitej Uppu, assistant professor in the Department of Physics and Astronomy, received a 5-year NSF CAREER award of $550,000 to conduct research aimed at amplifying the power of quantum computing and making its application more practical. 

Uppu and his team will explore the properties of light-matter interactions at the level of a single photon interacting with a single molecule, enabling them to generate efficient and high-quality multiphoton entangled states of light. Multiphoton entangled states, in which photons become inextricably linked, are necessary for photons to serve as practical quantum interconnects, transmitting information between quantum computing units, akin to classical cluster computers. 

“ In our pursuit of secure communication, exploiting quantum properties of light is the final frontier,” said Uppu. “However, unavoidable losses that occur in optical fiber links between users can easily nullify the secure link. Our research on multiphoton entangled states is a key building block for implementing ‘quantum repeaters’ that can overcome this challenge.”

Jiang tackles real-world data issues with NSF CAREER Award

Peng Jiang, assistant professor in the Department of Computer Science, received an NSF CAREER Award that will provide $548,944 over five years to develop tools to support the use of sampling-based algorithms. 

Sampling-based algorithms reduce computing costs by processing only a random selection of a dataset, which has made them increasingly popular, but the method still faces limited efficiency. Jiang will develop a suite of tools that simplify the implementation of sampling-based algorithms and improve their efficacy across wide range of computing and big data applications.

“ A simple example of a real-world application is subgraph matching,” Jiang said. “For example, one might be interested in finding a group of people with certain connections in a social network. The use of sampling-based algorithms can significantly accelerate this process.”

In addition to providing undergraduate students the opportunity to engage with this research, Jiang also plans for the project to enhance projects in computer science courses.