Skip to the page
KS3 Computing · Architect

Year 9

Bigger programs with lists and strings, cybersecurity, how pictures and sound become numbers, compression, and the logic gates that do it all in hardware.

Units, term by term

One unit each half term. Open a lesson to study it, try it and check yourself.

Autumn 1

Python II: lists and strings

Lists and indexing, append and remove, iterating, slicing and string methods, functions with parameters and return values, and validation.

What you will know by the end
  • Lists start at 0; the last item is at len(list) - 1.
  • append, remove, len, in: what each does and returns.
  • A slice s[a:b] takes from a up to but not including b.
  • A function takes parameters and returns a value; print shows, return hands back.
  • Validate input with normal, boundary and erroneous test data.
Syllabus and key words
  • Topic 14: Programming further
    • Read and change lists (including 2D lists) using indexes that start at 0.
    • Slice strings with s[a:b] and predict the result, every time.
    • Write procedures and functions with parameters and return values, and explain local vs global scope.
    • Make programs robust: validation, authentication, try/except and file handling.
    • Plan tests with normal, boundary and erroneous data.
  • Topic 13: Programming basics
    • Read a Scratch script and write the same thing in Python.
    • Use variables, the four data types and casting, and spot the input() bug.
    • Work out DIV (//) and MOD (%) by hand, and use MOD to test for even numbers.
    • Trace if / elif / else, for with range() and while loops line by line.
    • Tell syntax, runtime and logic errors apart, and fix each kind.
List
One name holding many values in order. Also called an array.
Index
An item's position in a list, counting from 0.
Subroutine
A named block of code you can call when needed.
Function
A subroutine that returns a value.
Parameter
A placeholder in a subroutine for a value passed in.
Validation
Checking input is reasonable before using it.
Boundary data
Test data at the very edge of what's allowed.
Variable
A named place in memory that holds a value.
Assignment
Storing a value in a variable. = in Python, ← in pseudocode.
Casting
Changing a value from one data type to another, like int("13").
Concatenation
Joining strings together: "7" + "7" = "77".
Selection
Choosing a path with if / else.
Iteration
Repeating steps: a loop.
Boolean
A value that is only True or False.
Infinite loop
A loop whose condition never becomes false.
  1. Lists: creating and indexingPractical
  2. append, remove, len and inPractical
  3. Iterating with forPractical
  4. Slicing and string methodsPractical
  5. Functions with parameters and return valuesPractical

End-of-unit challenge: A quiz program that stores questions in lists and uses at least two functions.

Homework: Study page 14 to the quiz.

Extra challenge: A function that turns a name into initials.

Arcade: this unit
Autumn 2

Cybersecurity

Social engineering and phishing, malware, brute force and a password checker, defences and a Caesar cipher, the Computer Misuse Act and data protection.

What you will know by the end
  • Most attacks start with a person: phishing, pretexting, shoulder surfing.
  • Virus, worm, trojan, ransomware, spyware: how each spreads and what it does.
  • Brute force tries every password; length defeats it. Lock-outs defeat it faster.
  • Defences in layers: strong passwords, 2FA, updates, firewall, backups, training.
  • Encryption scrambles with a key; hashing is one-way. The Computer Misuse Act and the Data Protection Act.
Syllabus and key words
  • Topic 17: Cybersecurity
    • Use the CIA triad to say what an attack damages.
    • Tell the kinds of malware and social engineering apart, and name the defence for each.
    • Work out why a long password beats a short messy one, with the maths.
    • Encrypt and decrypt with Caesar, break it with frequency analysis, and explain why modern encryption is different.
    • Know the law in the UK and in Spain, and what makes ethical hacking legal.
  • Topic 19: Digital life, law and ethics
    • Explain a digital footprint, keep accounts private, and know the steps when something online feels wrong.
    • Spot the red flags in a phishing message, and check whether information online is trustworthy.
    • Name the three UK laws (Computer Misuse Act, Data Protection Act, Copyright Act), what each one covers, and the Spanish equivalents.
    • Choose and read a Creative Commons licence.
    • Argue both sides of an ethical question: AI, surveillance, the digital divide, the environment and wellbeing.
Malware
Malicious software: viruses, worms, trojans, ransomware, spyware.
Phishing
Fake messages that trick people into giving details.
Brute force
Trying every possible password until one works.
Encryption
Scrambling data so only someone with the key can read it.
Firewall
Checks network traffic and blocks what isn't allowed.
Digital footprint
The trail of everything you do online.
Computer Misuse Act
UK law (1990) that makes hacking and spreading malware crimes.
Data Protection Act
UK law (2018), with UK GDPR, controlling how personal data is used.
Copyright
Automatic legal protection for original creative work.
Open source
Software whose code anyone can see, change and share.
Ethics
AI that is biased because its training data was. Cameras that keep us safe and also watch us. The digital divide: who is left out when everything moves online. Screen time and sleep. Practise arguing both sides.
  1. Social engineering and phishingTheory
  2. Malware: viruses, worms, trojans, ransomwareTheory
  3. Brute force: a Python password-strength checkerPractical
  4. Defences, and a Caesar cipher in PythonPractical
  5. The Computer Misuse Act and data protectionTheory

End-of-unit challenge: An incident-response scenario: identify the attack, its impact and three defences.

Homework: Study page 17 to the quiz; study page 19 steps on the laws.

Extra challenge: Turn on two-factor authentication on one account and write how it works.

Arcade: this unit
Spring 1

Data Science and AI

Asking questions and collecting data, cleaning, analysing in a spreadsheet or Python, charts and correlation versus causation, and how machine learning learns and where bias comes from.

What you will know by the end
  • The data cycle: question, collect, clean, analyse, present.
  • Cleaning: missing values, typos, outliers; decide and record what you did.
  • Mean, median, mode, range; which one the question needs.
  • Correlation is not causation: ice cream and sunburn.
  • Machine learning finds patterns in examples; biased examples give biased answers.
Syllabus and key words
  • Topic 18: Data, spreadsheets and AI
    • Tell data from information, and read any cell reference like B3 or range like B2:B6.
    • Write formulas with SUM, AVERAGE, MAX, MIN, COUNT, IF and COUNTIF, in English and Spanish Excel.
    • Use $ to lock a reference, pick the right chart, and work out mean, median, mode and range by hand.
    • Explain tables, records, fields and primary keys, and read an SQL query.
    • Explain how machine learning learns from training data, and why bad data makes a biased model.
Formula
A spreadsheet calculation. Always starts with =.
Function
A subroutine that returns a value.
Record / field
One row in a database table: everything stored about one thing.
Primary key
A field whose value is unique for every record.
SQL
Structured Query Language: asks databases questions.
Machine learning
The computer finds rules itself from labelled examples.
  1. Asking questions and collecting dataTheory
  2. Cleaning: missing values and outliersPractical
  3. Analysing in a spreadsheet or PythonPractical
  4. Visualising; correlation vs causationTheory
  5. How machine learning learns, and where bias comes fromUnplugged

End-of-unit challenge: Investigate a dataset and present one finding with a chart and a caveat.

Homework: Study page 18 to the quiz; 'SQL result' practice.

Extra challenge: Find a chart in the news and say what it hides.

Arcade: this unit
Spring 2

Representations: going audio-visual

Pixels and colour depth, resolution and file size, sampling and bit depth, lossy versus lossless compression, choosing file formats.

What you will know by the end
  • An image is a grid of pixels; colour depth is bits per pixel; 2ⁿ colours.
  • File size = width × height × colour depth, then divide by 8 for bytes.
  • Sound: sample rate × bit depth × seconds × channels. Nyquist: sample at twice the highest frequency.
  • Lossless (RLE, PNG, ZIP) keeps everything; lossy (JPEG, MP3) throws away what we notice least.
  • Choose the format for the job: PNG for graphics, JPEG for photos, WAV to edit, MP3 to share.
Syllabus and key words
  • Topic 5: Representing images
    • Explain how a bitmap image is a grid of pixels, stored row by row as binary.
    • Use colour depth: work out how many colours d bits give, and how many bits n colours need.
    • Read RGB and hex colour codes like #FF8000.
    • Calculate an image's file size by hand, in bits, bytes, KB and MB, and explain the quality–size trade-off.
  • Topic 6: Representing sound
    • Explain how a microphone, an ADC and a DAC turn sound into numbers and back again.
    • Describe sample rate and bit depth, and how each changes quality and file size.
    • Use the Nyquist rule to explain why CDs use 44,100 samples a second.
    • Calculate a sound file's size by hand, for mono and stereo.
  • Topic 7: Compression
    • Explain why we compress, and the difference between lossless and lossy.
    • Encode and decode with run-length encoding (RLE).
    • Build a Huffman tree, read the codes off it, and count the bits saved compared with ASCII.
    • Work out a compression ratio and the percentage saved, and choose lossy or lossless for a job.
Pixel
The smallest single-colour dot of an image.
Bitmap
An image stored as a grid of pixels.
Resolution
Number of pixels: width × height.
Colour depth
Bits per pixel. Sets how many colours are possible.
Metadata
Data about data, like an image's width and height.
Vector
An image stored as shapes and instructions.
Analogue
Smooth and continuous, with any value possible.
Digital
Made of separate, countable steps.
ADC / DAC
Analogue-to-digital converter: turns a smooth signal into numbers.
Sample rate
Sound samples taken per second, in hertz.
Bit depth
Bits per sound sample. Sets how precisely each is measured.
Lossless
A reversible way of writing the same data in fewer bits. Every bit comes back exactly. ZIP, PNG, FLAC. Needed for text, code and spreadsheets.
Lossy
Throw away detail that people barely notice. The original cannot be recovered. JPEG, MP3, MP4. Fine for photos, music and video.
RLE
Run-length encoding: store how many and what, for repeats.
Huffman coding
Lossless compression giving common characters short codes.
Compression ratio
Original size ÷ compressed size. A ratio of 4 means a quarter of the size. Percentage saved = (1 − compressed ÷ original) × 100.
  1. Pixels and colour depthTheory
  2. Resolution and file-size calculationTheory
  3. Sampling, sample rate and bit depthPractical
  4. Lossy vs lossless compressionUnplugged
  5. Choosing file formatsPractical

End-of-unit challenge: File-size calculations plus a justified format choice for three scenarios.

Homework: Study pages 5, 6 and 7 to each quiz.

Extra challenge: Find the resolution and size of a photo on your phone; calculate the uncompressed size.

Arcade: this unit
Summer 1

Physical Computing

Inputs, processing and outputs on a real board: display and lights, buttons and sensors, messages between devices, and designing a device for a user.

What you will know by the end
  • Input, process, output on a board: a sensor reads, the code decides, an actuator acts.
  • A loop that polls: while True, read, decide, act.
  • An LED needs a resistor; Ohm's law says which one.
  • An embedded system is a computer with one job.
  • Sensors give analogue readings; the ADC turns them into numbers.
Syllabus and key words
  • Topic 9: Logic gates
    • Know the rules for NOT, AND, OR and XOR, and draw their symbols.
    • Write a full truth table for any circuit, with no missing rows.
    • Turn a circuit into an expression, and an expression into a circuit, in AQA or OCR notation.
    • Explain how a half adder uses XOR and AND to add two bits.
    • Link gates to real chips, transistors and and / or / not in Python.
  • Topic 1: What a computer is
    • Sort any device into input, process, output or storage, and follow one real example through all four.
    • Explain why computers use electricity, and why they use only two states (0 and 1), not ten.
    • Describe a transistor as a switch, and show how two switches can make a decision.
    • Tell hardware from software, and embedded computers from general-purpose ones.
    • Explain the stored-program idea, place the big inventions on a timeline, and say why an LED needs a resistor.
  • Topic 13: Programming basics
    • Read a Scratch script and write the same thing in Python.
    • Use variables, the four data types and casting, and spot the input() bug.
    • Work out DIV (//) and MOD (%) by hand, and use MOD to test for even numbers.
    • Trace if / elif / else, for with range() and while loops line by line.
    • Tell syntax, runtime and logic errors apart, and fix each kind.
Boolean
A value that is only True or False.
Logic gate
A tiny circuit that takes bits in and gives one bit out by a fixed rule.
Truth table
Lists every input combination and its output.
Boolean expression
A rule written with AND, OR and NOT that gives True or False, like A AND NOT B.
Half adder
An XOR gate plus an AND gate: adds two bits.
Transistor
An electronic switch with no moving parts.
Input / output
Anything that gets information into the computer. Keyboard, mouse, touchscreen, microphone, camera, a temperature sensor.
Process
The computer follows instructions to change that information. Add two numbers. Move a character. Sort a list. The CPU does this.
Hardware
The physical parts of a computer.
Software
Programs: instructions that tell hardware what to do.
Embedded system
A small computer built into a device for one job.
Variable
A named place in memory that holds a value.
Assignment
Storing a value in a variable. = in Python, ← in pseudocode.
Casting
Changing a value from one data type to another, like int("13").
Concatenation
Joining strings together: "7" + "7" = "77".
Selection
Choosing a path with if / else.
Iteration
Repeating steps: a loop.
Infinite loop
A loop whose condition never becomes false.
  1. Lights and the first programPractical
  2. Inputs: buttons, light and temperaturePractical
  3. Signals between devicesPractical
  4. Designing a device for a userTheory
  5. Build, test and refineProject

End-of-unit challenge: A live demo plus a code walkthrough of inputs, processing and outputs.

Homework: Lab Tracker: mark the builds you have done; study page 9 to the quiz.

Extra challenge: Climb one rung of the twelve-project ladder at home in Tinkercad.

Arcade: this unit
Summer 2

Raid: Capstone

Brief and planning, two build sprints, testing against success criteria, evaluation and next steps, with a look ahead to Key Stage 4 options.

What you will know by the end
  • The development cycle: analysis, design, build, test, evaluate.
  • Success criteria are written before building and tested after.
  • Test data: normal, boundary, erroneous, and what each should do.
  • Evaluation says what works, what does not, and what you would do next, with evidence.
Syllabus and key words
  • Topic 14: Programming further
    • Read and change lists (including 2D lists) using indexes that start at 0.
    • Slice strings with s[a:b] and predict the result, every time.
    • Write procedures and functions with parameters and return values, and explain local vs global scope.
    • Make programs robust: validation, authentication, try/except and file handling.
    • Plan tests with normal, boundary and erroneous data.
  • Topic 11: Algorithms
    • Say what makes a set of instructions an algorithm: precise, ordered, finite.
    • Use decomposition, pattern recognition, abstraction and algorithmic thinking on a real problem.
    • Read and write the same algorithm as a flowchart, AQA and OCR pseudocode, and Scratch blocks.
    • Dry-run an algorithm with a trace table, count loop repeats, and spot the bug.
    • Compare two algorithms by counting their steps.
  • Topic 19: Digital life, law and ethics
    • Explain a digital footprint, keep accounts private, and know the steps when something online feels wrong.
    • Spot the red flags in a phishing message, and check whether information online is trustworthy.
    • Name the three UK laws (Computer Misuse Act, Data Protection Act, Copyright Act), what each one covers, and the Spanish equivalents.
    • Choose and read a Creative Commons licence.
    • Argue both sides of an ethical question: AI, surveillance, the digital divide, the environment and wellbeing.
List
One name holding many values in order. Also called an array.
Index
An item's position in a list, counting from 0.
Subroutine
A named block of code you can call when needed.
Function
A subroutine that returns a value.
Parameter
A placeholder in a subroutine for a value passed in.
Validation
Checking input is reasonable before using it.
Boundary data
Test data at the very edge of what's allowed.
Algorithm
Precise, ordered, finite steps to solve a problem.
Decomposition
Breaking a problem into smaller ones.
Abstraction
Ignoring detail that doesn't matter for the problem.
Sequence · selection · iteration
Steps one after another. First this, then this.
Pseudocode
Code-like writing for algorithms, without strict rules.
Trace table
Records variable values step by step to check logic.
Variable
A named place in memory that holds a value.
Digital footprint
The trail of everything you do online.
Phishing
Fake messages that trick people into giving details.
Computer Misuse Act
UK law (1990) that makes hacking and spreading malware crimes.
Data Protection Act
UK law (2018), with UK GDPR, controlling how personal data is used.
Copyright
Automatic legal protection for original creative work.
Open source
Software whose code anyone can see, change and share.
Ethics
AI that is biased because its training data was. Cameras that keep us safe and also watch us. The digital divide: who is left out when everything moves online. Screen time and sleep. Practise arguing both sides.
  1. Brief and planning: user needs, success criteria, task splitTheory
  2. Build sprint 1Project
  3. Build sprint 2Project
  4. Testing against success criteriaPractical
  5. Evaluation and next steps; Key Stage 4 optionsTheory

End-of-unit challenge: Annual Raid: a showcase for other classes or parents; an Architect certificate for everyone who completes it.

Extra challenge: Write the three projects up as a one-page portfolio for options evening.

Arcade: this unit

Topics, in teaching order

Year 9 hub: this year's formulas and Tinkercad builds.

Topic 14 · Year 9

Programming further

Real programs keep data in lists, take text apart as strings, split work into subroutines, and get tested on purpose.

Topic 17 · Year 9

Cybersecurity

Cybersecurity protects computers and data. Most attacks trick people or exploit weak systems, so defences cover both.

Topic 5 · Year 9

Representing images

A picture is a grid of tiny squares called pixels. Each pixel's colour is a binary number. More pixels and more colours = better picture, bigger file.

Topic 6 · Year 9

Representing sound

A computer measures the height of a sound wave thousands of times a second and saves each measurement as a binary number. This is sampling.

Topic 7 · Year 9

Compression

Compression stores the same information in fewer bits. Lossless gets every bit back. Lossy throws away detail you probably won't notice.

Topic 9 · Year 9

Logic gates

A logic gate is a tiny circuit that takes bits in and gives one bit out by a fixed rule. Millions of gates let a CPU decide and do maths.

Revise

Revise

Revise Year 9

A mixed quiz, key-word flashcards and endless practice for this year.

Projects and games

Years 7–9

PC Build Bench

Build a PC on screen part by part, fill a customer's order, then face the Boss Battle.

Years 7–9

Computing Quest Arcade

Games, puzzles and retrieval starters for all 18 KS3 Quest units: phishing spotter, packet puzzle, bot maze, logic gate lab and more.

Years 7–11

Tinkercad Maker Course

How electricity really works, 3D design, circuits that run real code, and a build checker.

Tinkercad · Intermediate · 25 minutes

Analogue to digital: the knob

Turn a knob and watch the Arduino turn a smooth voltage into numbers, just like sampling sound.

Tinkercad · Intermediate · 35 minutes

Logic gates

Two buttons go in, AND, OR and XOR come out. First with blocks, then in C++, then with real logic-gate chips and no code at all.

Tinkercad · Advanced · 30 minutes

Password lock

A lock that checks a password typed in the Serial Monitor, with validation checks and a lock-out after 3 wrong tries. Warm up the lights with blocks, then write the lock in C++.

Explainers and study pages

Years 8–11

Bit Maths Lab

All the binary maths, one small step at a time and colour-coded. Tap anything; nothing can break.

Years 8–11

Binary, Denary and Hex

Three ways of writing the same numbers. Place value column by column, with every conversion broken down.

Years 8–11

Code in Words

Python, Java, HTML, CSS and C++ explained line by line in plain words, with a step-through runner.

Years 7–9

The Skipped Resistor

Your LED lit up but Tinkercad put a star on it. Why too much current flows, and how to fix it.

Years 7–9

Every topic, step by step

All 19 KS3 topics as one long read: every why answered, every calculation shown line by line.