Lesson 1 | 60 minutes
Decomposing problems
Learning intention Break a familiar task into jobs, identify what each job produces, and explain one dependency.
Curriculum focus K1 · P1
Lesson 2 | 60 minutes
Exact instructions
Learning intention Write a sandwich algorithm, test it literally and retest an improved instruction.
Curriculum focus K1 · P1
Lesson 3 | 60 minutes
Pattern recognition abstraction and algorithms
Learning intention Identify a reusable pattern, explain which details matter, and use both ideas to write clearer instructions.
Curriculum focus K1 · P1
Lesson 4 | 60 minutes
Bubble sort
Learning intention Trace bubble sort by comparing neighbours and swapping out-of-order pairs.
Curriculum focus K1 · P1
Lesson 5 | 60 minutes
Selection sort
Learning intention Trace selection sort by finding the smallest remaining value and placing it at the sorted boundary.
Curriculum focus K1 · P1
Lesson 6 | 60 minutes
Quicksort and evaluating sorting algorithms
Learning intention Partition around a pivot, finish a small sort, and use measured evidence to compare sorting methods.
Curriculum focus K1 · P1
Lesson 8 | 60 minutes
Binary conversion
Learning intention Convert unsigned numbers between binary and decimal and check by converting back.
Curriculum focus K2 · P2
Lesson 7 | 60 minutes
Binary place value
Learning intention Explain how binary place values double and use labelled bits to represent small unsigned numbers.
Curriculum focus K2 · P2
Lesson 9 | 60 minutes
Encoding text
Learning intention Use a shared character code to represent text and explain why ASCII cannot represent every name.
Curriculum focus K2 · P2
Lesson 10 | 60 minutes
Representing images
Learning intention Reconstruct a monochrome raster image and predict the effect of changing a decimal RGB channel.
Curriculum focus K2 · P2
Lesson 11 | 60 minutes
How AI learns and makes predictions
Learning intention Investigate Quick, Draw! and a small classifier. Explain how training data and input conditions affect predictions.
Curriculum focus K1 · K2 · P1 · Responsible practice
Lesson 12 | 60 minutes
AI assisted and source based research
Learning intention Compare AI-assisted and source-based research on how technology has changed communication, work or learning.
Curriculum focus K1 · P1 · Responsible practice
Unit plan Year 9 • Digital Technologies and Computer Science • 12 weeks
Rationale and local context
How can a new student find a school destination from a tiny digital sign? The class begins by breaking down problems and testing instructions. Students then learn how bits can represent a number, a character or a pixel, before sending a sign that another student can reconstruct and interpret.
Given design brief
Design a 4 × 4 wayfinding icon and a short text label for a visitor. Send a partner the label bytes, the pixel data and all decoding instructions. The reader must reconstruct all 16 pixels and identify the intended meaning without hints. Keep the reader’s first attempt and use it to improve the sign.
Links to prior and future learning
Entry points to check
Year 8 experience with instructions, simple maps, whole-number place value and grid coordinates. Check rather than assume prior access to coding.
Year 10: trace longer algorithms, evaluate their behaviour on varied inputs and introduce hexadecimal notation as a further way to write RGB channel values.
Delivery and resources
Each week has one 60-minute core lesson and one 60-minute application lesson for a two-period timetable. In a one-period course teach the core lesson each week. Weeks 1–11 introduce the specified concepts; week 12 brings them together. No programming account is required.
Prepare number cards, paper sandwich pieces, square grids, mini-whiteboards, place-value cards, coloured pencils and a projector. Use an RGB slider or colour picker showing decimal values. Paper grids and labelled channel cards work offline.
The unit has a useful progression:
Lesson 1-5: Decomposition → Abstraction → Pattern Recognition → Algorithms → Evaluation
Lessons 6-11: Binary → Numbers → Text → Images
That means the first five lessons establish how computer scientists approach problems, while the final six establish how computers represent information.
For the data-representation section, make this one idea recur constantly:
So the same binary pattern might represent a number, a character, a pixel value, or something else depending on the agreed representation. That gives the binary lessons a purpose rather than binary conversion being just an isolated mathematical exercise.
For the explicit curriculum knowledge, I would put the boxed terms on the board and deliberately use them in student explanations: Decomposition, Abstraction, Pattern Recognition, Algorithms, Evaluation, Binary Representation, Character Encoding, and Image Representation.
TECHQUITY / YEAR 9 COMPUTER SCIENCE
Knowledge and practices
The statements below unpack the supplied Year 9 content for this unit. These are teacher planning statements rather than verbatim curriculum wording.
TECHQUITY / YEAR 9 COMPUTER SCIENCE
Knowledge and practices
The statements below unpack the supplied Year 9 content for this unit. These are teacher planning statements rather than verbatim curriculum wording.
Subject knowledge
A bit string has no single inherent meaning. For example, 01000001 can mean 65, the ASCII character A, or eight monochrome pixels under an agreed key. Decimal RGB describes amounts of emitted light. A colour key maps a short pixel code to an RGB triple; storing palette indexes is different from storing three full channels for every pixel.
TECHQUITY / YEAR 9 COMPUTER SCIENCE
Science of learning in the sequence
Start from memory before revealing the answer. Return to an older idea as well as the previous lesson: week 8 reuses binary conversion; week 10 revisits decoding conventions; week 12 asks for all three interpretations of one byte. Use a worked example, complete a second together, then ask for an independent response. Use errors to choose the next example
TECHQUITY / YEAR 9 COMPUTER SCIENCE
Connections and access
Mathematics contributes place value and grid coordinates; English contributes precise procedural writing. Local place names give encoding a real consequence. Ask a knowledgeable speaker or use the school’s established spelling before publishing a label. Offer tactile tokens, large grids, oral explanations and written colour-channel labels. Rotate encoder and decoder roles so each learner practises both.
Use DMI where a design decision depends on the intended user. A correctly encoded sign can still be hard to recognise. That difference gives students a reason to test and revise it.
TECHQUITY / YEAR 9 COMPUTER SCIENCE
Using the evidence
Record separately whether each student can explain the knowledge and demonstrate the practice independently, with a prompt, or not yet. A correct group product alone is insufficient. Reteach the first failed step, then check a fresh example.
Teacher reflection
Which errors persisted after a week? Which support could be removed? Did students explain both technical correctness and user understanding? Record one example and one change for the next class.
Teacher references: Tāhūrangi, Technology Years 0–10 (2026); Australian Education Research Organisation, Spacing and retrieval practice and Explicit instruction practice guides. Visual styling follows the Techquity Hub’s purple, Righteous headings and Arial body type.
Individual transfer check