Loading subjects...

Schools Parents Learning Science

GCSE Computer Science · OCR

Performance

Completion

Proficiency

Course

1. Computer Systems

1.1 Systems Architecture

1.1.1 Architecture of the CPU 1.1.2 CPU Performance 1.1.3 Embedded Systems

1.2 Memory and Storage

1.2.1 Primary Storage (Memory)1.2.2 Secondary Storage 1.2.3 Units 1.2.4 Numbers 1.2.5 Characters 1.2.6 Images 1.2.7 Sound 1.2.8 Compression

1.3 Computer Networks, Connections and Protocols

1.3.1 Computer Networks 1.3.2 Network Types 1.3.3 Network Hardware 1.3.4 The Internet as a Collection of Networks 1.3.5 Network Topologies 1.3.6 Wired and Wireless Networks 1.3.7 Network Protocols 1.3.8 Protocol Layers

1.4 Network Security

1.4.1 Threats To Computer Systems and Networks 1.4.2 Identifying and Preventing Vulnerabilities

1.5 Systems Software

1.5.1 Operating Systems 1.5.2 Utility Software

1.6 Ethical, Legal, Cultural and Environmental Impacts of Digital Technology

1.6.1 Impacts of Digital Technology on Wider Society 1.6.2 Legislation Relevant to Computer Science 1.6.3 Software Licences

2. Computational Thinking, Algorithms and Programming

2.1.1 Computational Thinking 2.1.2 Designing, Creating and Refining Algorithms 2.1.3 Searching Algorithms 2.1.4 Sorting Algorithms

2.2 Programming Fundamentals

2.2.1 Programming Fundamentals 2.2.2 Programming Constructs 2.2.3 Data Types 2.2.4 String Manipulation 2.2.5 File Handling 2.2.6 SQL (Structured Query Language)2.2.7 Arrays 2.2.8 Subprograms 2.2.9 Random Number Generation

2.3 Producing Robust Programs

2.3.1 Defensive Design 2.3.2 Testing

2.4 Boolean Logic

2.4.1 Boolean Logic

2.5 Programming Languages and Integrated Development Environments

2.5.1 Languages 2.5.2 The Integrated Development Environment (IDE)

GCSE Computer Science · OCR

Performance

Completion

Proficiency

Course

1. Computer Systems

1.1 Systems Architecture

1.1.1 Architecture of the CPU 1.1.2 CPU Performance 1.1.3 Embedded Systems

1.2 Memory and Storage

1.2.1 Primary Storage (Memory)1.2.2 Secondary Storage 1.2.3 Units 1.2.4 Numbers 1.2.5 Characters 1.2.6 Images 1.2.7 Sound 1.2.8 Compression

1.3 Computer Networks, Connections and Protocols

1.3.1 Computer Networks 1.3.2 Network Types 1.3.3 Network Hardware 1.3.4 The Internet as a Collection of Networks 1.3.5 Network Topologies 1.3.6 Wired and Wireless Networks 1.3.7 Network Protocols 1.3.8 Protocol Layers

1.4 Network Security

1.4.1 Threats To Computer Systems and Networks 1.4.2 Identifying and Preventing Vulnerabilities

1.5 Systems Software

1.5.1 Operating Systems 1.5.2 Utility Software

1.6 Ethical, Legal, Cultural and Environmental Impacts of Digital Technology

1.6.1 Impacts of Digital Technology on Wider Society 1.6.2 Legislation Relevant to Computer Science 1.6.3 Software Licences

2. Computational Thinking, Algorithms and Programming

2.1.1 Computational Thinking 2.1.2 Designing, Creating and Refining Algorithms 2.1.3 Searching Algorithms 2.1.4 Sorting Algorithms

2.2 Programming Fundamentals

2.2.1 Programming Fundamentals 2.2.2 Programming Constructs 2.2.3 Data Types 2.2.4 String Manipulation 2.2.5 File Handling 2.2.6 SQL (Structured Query Language)2.2.7 Arrays 2.2.8 Subprograms 2.2.9 Random Number Generation

2.3 Producing Robust Programs

2.3.1 Defensive Design 2.3.2 Testing

2.4 Boolean Logic

2.4.1 Boolean Logic

2.5 Programming Languages and Integrated Development Environments

2.5.1 Languages 2.5.2 The Integrated Development Environment (IDE)

Subjects2.1 Algorithms2.1.2 Designing, Creating and Refining Algorithms

2.1.2 Designing, Creating and Refining Algorithms

In this lesson, you will learn how algorithms are designed, represented, tested, and refined. You will identify the inputs, processes, and outputs of an algorithm, represent algorithms using pseudocode, flowcharts, and Python, and learn how trace tables can be used to test algorithms and identify common errors.

SummaryRevision

Topic 1

Algorithms

Topic 2

Identifying Inputs, Processes, and Outputs for a Problem

Topic 3

Structure Diagrams

Topic 4

Creating, Interpreting, Correcting, Completing, and Refining Algorithms

Topic 5

Identifying Common Errors

Topic 6

Trace Tables

Ready to finish?

Log in to save this lesson and earn rewards.

Built on over 50 years of learning and cognitive neuroscience.

The Exchange, 3 Centenary Square, Birmingham, B1 2DR

© 2026 Knowness

Product

Subjects Schools Parents Research

Company

About Team Partners Help Centre

Legal

GCSE

GCSE Computer Science

University Taster

Accounting - University Taster Archaeology - University Taster Architecture - University Taster Chemistry - University Taster Economics - University Taster Geography - University Taster Medicine - University Taster Philosophy - University Taster

Schools Parents Learning Science