Clever Compression Strategies

Overview

Year Level: Year 9
Duration: 50 minutes
Subject: Technology
Australian Curriculum Reference:
Digital Technologies – Years 9–10 (ACTDIP039, ACTDIP040)

• Investigate the role of hardware and software in managing, controlling and securing the movement of and access to data in networked digital systems.
• Analyse simple compression of data, and how content data are separated from presentation.

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Learning Intentions

By the end of this lesson, students will be able to:

• Understand the concept of data compression and why it’s used.
• Explore and apply simple data compression techniques such as Run-Length Encoding and Huffman coding.
• Compare the effectiveness of different compression methods.
• Recognise real-world uses of data compression in everyday technologies (e.g. streaming, image sharing, communication).

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Success Criteria

Students will demonstrate success by:

• Accurately explaining the purpose of data compression.
• Using simple algorithms or manual strategies to compress given data sets.
• Participating in group challenges that promote computational thinking.

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Resources Required

• Whiteboard and markers
• Student laptops/tablets
• Printed worksheets (including strings/images to be compressed)
• Digital compression simulation (teacher preloads on class devices or displays via projector)
• Pack of coloured sticky notes (in 4–5 different colours)
• Timer (for short bursts of team challenge work)

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Lesson Sequence

Introduction (0–10 minutes)

Hook (5 mins):
Project a high-resolution image on the board and ask:

“If you wanted to text this to a friend, what would you need to do?”

Prompt for answers such as file size, send time, mobile data usage.

Mini Discussion (5 mins):
Introduce the term data compression. Ask guiding questions:

• “Ever wondered how Snapchat loads so fast?”
• “Why do videos not take hours to send anymore?”

Explain that data compression reduces file size — but students will decode how today.

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Teacher Input & Modelling (10–15 minutes)

Key Concept 1: Run-Length Encoding (RLE) – (5 mins)
Use the whiteboard to demonstrate simple RLE:

String: AAAABBBCCDAA
Compressed: 4A3B2C1D2A

Use coloured sticky notes to represent repeating letters (e.g. 4 blue notes = 4 A’s). Visually rearrange them into “4A”.

Key Concept 2: Huffman Coding (5 mins)
Introduce with a visual analogy using frequency:

• Most used letter = shortest code
  Assign fake frequencies to A, B, C, D, E and demonstrate visually with students acting as nodes in a tree:
• Create a Huffman Tree: Each student represents a character and they merge, forming binary codes.

Use this kinaesthetic activity to illustrate how fewer bits are used for frequently used letters.

Think-Pair-Share (5 mins)
Pose the question:

“Where might this happen in real technology you use daily?”

• Encourage students to briefly discuss, then share some thoughts. Students often draw on music streaming, image sharing, messaging apps, or gaming experience.

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Group Challenge (20 minutes)

Activity: The Great Data Shrink!
Students split into teams of 4.

Each team receives:

• A worksheet with different strings and image pixel rows (expressed as characters).
• Instructions to run both RLE and Huffman coding manually.
• A short debrief worksheet to calculate compression ratio.

Differentiation Options

• Extension: Provide real binary streams and ask for size calculations in bits.
• Support: Offer scaffolding hints and worked examples on worksheets.

Teams must:

1. Compress the data manually.
2. Determine which method was more efficient for each case.
3. Justify which method they would use, and why.

Teacher monitors and assists with decoding Huffman part if needed.

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Consolidation & Reflection (5 minutes)

Back to full class. Ask:

• “Which data was harder to compress?”
• “What surprised you today about how this works?”

Display a pie chart showing how much data is compressed when Australians upload photos to social media daily (approximation only).

Optional AI Integration ("Wow" Moment):
Use a local AI chatbot or teacher’s AI assistant tool on the projector. Ask:

“Write a short code snippet that compresses a string using RLE.”
Demonstrate how AI can be used to automate tasks like compression — discuss pros and cons.

Emphasise AI as a thinking assistant rather than a replacement. Ask:

• “How might this impact future jobs in app development or media storage?”

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Assessment Opportunities

Formative Assessment:

• Participation in group activity
• Accuracy of compressed data submissions
• Partner discussion contributions
• Responses during class questioning

Summative (Optional Extension):

• Quiz or mini-project next lesson: Implementing RLE in Python OR researching an Australian company using compression in their products (e.g. Canva, Atlassian).

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Cross-Curriculum Priorities and Capabilities

• Critical and Creative Thinking: Students compare methods via trial and error.
• ICT Capability: Understanding how digital systems work under the hood.
• Numeracy: Applying patterns, ratios and efficiency concepts in real-world data handling.

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Teacher Reflection Notes (Post-lesson)

• Which technique did students find more intuitive?
• Did students engage with the concept of data as a physical, manipulatable item?
• How well did collaborative strategies work for exploring conceptual material?
• Success in demonstrating AI as a classroom tool – what questions or interest did it generate?

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Follow-on Ideas

• Coding challenge: Implement RLE in a block or text-based coding environment.
• Link with Media Arts: Explore how MP3 or JPEG compressions affect fidelity.
• Invite a local game or app developer to explain how compression impacts app performance.

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Thank you for using a forward-thinking digital technologies approach! This lesson balances theory, collaboration, critical thinking and AI curiosity while aligning precisely with the Australian Curriculum.