United Kingdom · National Curriculum Attainment Targets
Year 9 Computing
A comprehensive exploration of advanced computer science principles designed to prepare students for GCSE Computing. This course bridges the gap between basic digital literacy and complex system design, focusing on algorithmic efficiency, cybersecurity, and physical computing.
Algorithmic Thinking and Logic
Mastering the design and analysis of algorithms using flowcharts and pseudocode with a focus on efficiency.
Comparing linear versus binary searches and bubble versus merge sorts to understand computational complexity.
Using AND, OR, and NOT gates to solve complex logical problems and design circuits.
Advanced Programming with Python
Moving beyond basic syntax to explore data structures, functions, and file handling in high-level languages.
Organizing and manipulating complex sets of data using advanced Python structures.
Breaking down large programs into reusable functions and procedures to improve readability and maintenance.
Learning how to read from and write to external files to save program state and data.
Computer Systems and Architecture
Investigating how hardware components work together and how data is represented at the machine level.
Analyzing the Fetch-Decode-Execute cycle and the role of registers, CPU, and memory.
Understanding how images, sound, and video are converted into binary and the impact of compression.
Exploring the layer between hardware and the user, including memory management and file systems.
Networks and Cybersecurity
Understanding how computers communicate globally and how to defend against digital threats.
Comparing Star, Mesh, and Bus networks and the rules that govern data transmission.
Identifying vulnerabilities like SQL injection and social engineering and implementing robust defenses.
Examining the shift from local storage to cloud computing and the technology behind virtual machines.
Data Science and Society
Using data to identify patterns and exploring the societal impact of big data and artificial intelligence.
Analyzing large datasets to draw conclusions and understanding how algorithms predict behavior.
Exploring machine learning, neural networks, and the ethical dilemmas of autonomous systems.
Assessing the carbon footprint of data centers and the lifecycle of hardware components.
Physical Computing Project
Applying programming and hardware knowledge to create a functioning prototype using microcontrollers.
Interfacing with the physical world using inputs like light sensors and outputs like motors.
Building, testing, and refining a solution to a specific real-world problem.