WA DATA SCIENCE INNOVATION HUB

AI LIFT-OFF

Your role 🚀
Student
Click through activities, complete tasks,
and track your progress session by session.
Your role 📋
Teacher
Full curriculum codes, WHY IT MATCHES rationale, learning outcomes and assessment guidance visible.
AI LIFT-OFF

Curriculum Alignment

A 60-minute incursion introducing Years 7–10 students to artificial intelligence through conceptual grounding and hands-on experimentation — from system-prompted robots to classifier training and generative-AI coding.

Digital Technologies Alignment

Addresses core WA Digital Technologies strands — Data Representation, Privacy & Security, Digital Implementation, and Investigating & Defining — while embedding ethical, social, and legal thinking throughout. Complexity scales by year group.

WA7DIGAD1 · WA7DIGPS1 · WA7DIGDI1 · WA7DIGDI2 · WA7DIGDI3 · WA7DIGDTID3 · WA7DIGDTEV1

Introduced to AI through observation and guided inquiry — building foundational skills across data acquisition and visualisation, digital footprint and data permanence, and basic algorithms and programs with control structures. Activities bring data collection, accuracy, and ethical ownership of training data to life.

WA8DIGDR1 · WA8DIGAD2 · WA8DIGPS1 · WA8DIGPS2 · WA8DIGDI1 · WA8DIGDI2 · WA8DIGDI3 · WA8DIGDTID3 · WA8DIGDTEV1

Engages with how digital systems represent image and audio data in binary, analyses and validates data for accuracy and authenticity, and explores ethical data ownership and cybersecurity risks posed by hidden AI behaviours. Incorporated into designing and tracing algorithms with nested control structures, and evaluating the resulting solutions.

WA9DIGDR1 · WA9DIGDR2 · WA9DIGAD1 · WA9DIGPS1 · WA9DIGDI3 · WA9DIGDI5 · WA9DIGDTID3

Explores privacy in the context of real AI data practices, acquires and validates data from live AI systems, examines data manipulation and compression, and designs and implements modular programs using functions. Students critically evaluate the social and ethical constraints shaping AI technology choices.

WA10DIGDR1 · WA10DIGAD1 · WA10DIGAD2 · WA10DIGPS1 · WA10DIGPS2 · WA10DIGDI3 · WA10DIGDI4 · WA10DIGDI5 · WA10DIGDTID3 · WA10DIGDTDE1 · WA10DIGDTPI1

Analyses and visualises AI output data to identify trends, explores privacy and security issues around AI systems, represents and generates structured content including HTML, and designs, implements and tests modular programs with logical operators. Completes a shortened "investigate, design, and produce" cycle with social, ethical, and legal considerations at its core.

M1Intro to AI

From "what is AI?" to training your own classifier — the foundations.

WA7DIGAD1 · WA7DIGPS1 · WA7DIGDTID3 · WA7DIGDTEV1
M2Generative AI & Prompting

How LLMs learn, and crafting effective prompts and system instructions.

WA7DIGDR1 · WA7DIGAD1 · WA7DIGPS1 · WA7DIGDTPM1 · WA7DIGDTID3 · WA7DIGDTDE1 · WA7DIGDTEV1
M3AI Ethics & Case Studies

What can go wrong with AI — and how to think responsibly about it.

WA7DIGPS1 · WA7DIGPS2 · WA7DIGDTID2 · WA7DIGDTEV1
M4Programming with AI

Apply prompting skills to build and configure AI-powered programs.

WA7DIGPS1 · WA7DIGDI1 · WA7DIGDI2 · WA7DIGDI3 · WA7DIGDTID3 · WA7DIGDTDE1 · WA7DIGDTEV1
M5–6Design Thinking, Testing & Hackathon Project

Structured design framework culminating in a hackathon-built Gen-AI tool.

WA7DIGDR1 · WA7DIGAD1 · WA7DIGPS1 · WA7DIGPS2 · WA7DIGDI1 · WA7DIGDI2 · WA7DIGDI3 · WA7DIGDTPM1 · WA7DIGDTID1 · WA7DIGDTID2 · WA7DIGDTID3 · WA7DIGDTDE1 · WA7DIGDTPI1 · WA7DIGDTEV1
M1Intro to AI

From "what is AI?" to training your own classifier — the foundations.

WA8DIGDR1 · WA8DIGAD2 · WA8DIGPS1 · WA8DIGPS2
M2Generative AI & Prompting

How LLMs learn, and crafting effective prompts and system instructions.

WA8DIGDS2 · WA8DIGDR1 · WA8DIGAD2 · WA8DIGPS1 · WA8DIGPS2 · WA8DIGDTID1 · WA8DIGDTID3 · WA8DIGDTDE1
M3AI Ethics & Case Studies

What can go wrong with AI — and how to think responsibly about it.

WA8DIGAD2 · WA8DIGPS1 · WA8DIGPS2 · WA8DIGDTEV1
M4Programming with AI

Apply prompting skills to build and configure AI-powered programs.

WA8DIGAD2 · WA8DIGPS1 · WA8DIGPS2 · WA8DIGDI1 · WA8DIGDI2 · WA8DIGDI3 · WA8DIGDI4 · WA8DIGDTID3
M5–6Design Thinking, Testing & Hackathon Project

Structured design framework culminating in a hackathon-built Gen-AI tool.

WA8DIGDS2 · WA8DIGDR1 · WA8DIGAD2 · WA8DIGPS1 · WA8DIGPS2 · WA8DIGDI1 · WA8DIGDI2 · WA8DIGDI3 · WA8DIGDI4 · WA8DIGDTPM1 · WA8DIGDTID1 · WA8DIGDTID2 · WA8DIGDTID3 · WA8DIGDTDE1 · WA8DIGDTPI1 · WA8DIGDTEV1
M1Intro to AI

From "what is AI?" to training your own classifier — the foundations.

WA9DIGDR1 · WA9DIGDR2 · WA9DIGAD1 · WA9DIGPS1 · WA9DIGDTID3
M2Generative AI & Prompting

How LLMs learn, and crafting effective prompts and system instructions.

WA9DIGDR1 · WA9DIGAD1 · WA9DIGPS1 · WA9DIGDTID3 · WA9DIGDTDE1 · WA9DIGDTEV1
M3AI Ethics & Case Studies

What can go wrong with AI — and how to think responsibly about it.

WA9DIGAD1 · WA9DIGPS1 · WA9DIGDTPM1 · WA9DIGDTID3 · WA9DIGDTEV1
M4Programming with AI

Apply prompting skills to build and configure AI-powered programs.

WA9DIGAD1 · WA9DIGPS1 · WA9DIGDI3 · WA9DIGDI5 · WA9DIGDTID3
M5–6Design Thinking, Testing & Hackathon Project

Structured design framework culminating in a hackathon-built Gen-AI tool.

WA9DIGDR1 · WA9DIGDR2 · WA9DIGAD1 · WA9DIGPS1 · WA9DIGDI1 · WA9DIGDI2 · WA9DIGDI3 · WA9DIGDI4 · WA9DIGDI5 · WA9DIGDTPM1 · WA9DIGDTID1 · WA9DIGDTID2 · WA9DIGDTID3 · WA9DIGDTDE1 · WA9DIGDTPI1 · WA9DIGDTEV1
M1Intro to AI

From "what is AI?" to training your own classifier — the foundations.

WA10DIGAD1 · WA10DIGPS1 · WA10DIGDI4 · WA10DIGDTID3
M2Generative AI & Prompting

How LLMs learn, and crafting effective prompts and system instructions.

WA10DIGDR1 · WA10DIGAD1 · WA10DIGPS1 · WA10DIGDI1 · WA10DIGDTID2 · WA10DIGDTID3 · WA10DIGDTDE1 · WA10DIGDTPI1
M3AI Ethics & Case Studies

What can go wrong with AI — and how to think responsibly about it.

WA10DIGPS1 · WA10DIGPS2 · WA10DIGDI1 · WA10DIGDTPM1 · WA10DIGDTID3 · WA10DIGDTEV1
M4Programming with AI

Apply prompting skills to build and configure AI-powered programs.

WA10DIGDR1 · WA10DIGAD1 · WA10DIGAD2 · WA10DIGPS1 · WA10DIGPS2 · WA10DIGDI3 · WA10DIGDI5 · WA10DIGDTID3 · WA10DIGDTDE1 · WA10DIGDTPI1
M5–6Design Thinking, Testing & Hackathon Project

Structured design framework culminating in a hackathon-built Gen-AI tool.

WA10DIGDR1 · WA10DIGAD1 · WA10DIGAD2 · WA10DIGPS1 · WA10DIGPS2 · WA10DIGDI1 · WA10DIGDI2 · WA10DIGDI3 · WA10DIGDI4 · WA10DIGDI5 · WA10DIGDTPM1 · WA10DIGDTID1 · WA10DIGDTID2 · WA10DIGDTID3 · WA10DIGDTDE1 · WA10DIGDTPI1 · WA10DIGDTEV1

General Capabilities

WA Curriculum General Capabilities
Digital Literacy
From users to critical analysts to creators — operating AI tools, evaluating outputs, and building AI-powered solutions safely.
Literacy
Interpret technical content, produce purpose-driven texts, and use nuanced descriptive language for Gen-AI prompting.
Ethical Understanding
Every activity raises questions about data ownership, transparency, hidden AI behaviours, and responsible design.
Personal & Social
Collaborative activities build discussion, decision-making, empathy, and resilience.
Numeracy
Probability, classifier performance data, and logical/computational reasoning in programming.
Critical & Creative Thinking
Generate → test → evaluate cycles. Students analyse AI as a designed artefact and creatively solve problems.

AI Curriculum Connection

Australian Curriculum · AI Connection
  • Understanding AI systems. Conceptual grounding in AI, ML, and GenAI, reinforced by live interaction with real AI systems.
  • Curriculum-mapped content. AI learning is mapped directly to curriculum outcomes instead of bolted on.
  • Educator-supported tools. Model Builder, Block Console with AI extensions, and well-documented open-source libraries.
  • Critical evaluation of impact. Ethical reflection is central — students leave with frameworks to critically evaluate any AI system they encounter.
AI LIFT-OFF

Safety & Privacy

How the platform keeps students safe while they learn with AI

6Content Filter Layers
100%Interactions Logged
0Emails Collected
11Flag Categories
AI Lift-Off is designed for school classrooms from the ground up. Every AI interaction passes through multiple safety layers, all conversations are logged for teacher review, and the platform deliberately minimises the personal data it collects.

Multi-Layer Content Guardrails

Every student prompt passes through six layers of safety checks before an AI response is generated — and the response itself is checked again before it reaches the student.

1
Input Validation
Prompts are limited to 100 words. Empty or malformed requests are rejected immediately.
2
Keyword & Pattern Blocking
A fast, regex-based filter catches explicit profanity, drug references, violence, self-harm language, weapons instructions, phishing templates, and jailbreak phrases.
3
Obfuscation Detection
Text is normalised to defeat common evasion tricks: Unicode look-alikes, diacritics, leetspeak, and inserted special characters are stripped before checking.
4
AI-Powered Input Guardrail
A dedicated AI model reviews the full prompt in context, covering 57+ specific safety rules. It can block the request or rewrite it to remove problematic elements.
5
Educational System Prompt
Every conversation begins with a mandatory safety preamble that instructs the AI to keep responses appropriate for a school classroom and refuse harmful content.
6
Response Guardrail
After the AI generates its response, a second AI guardrail reviews the output for violent, sexual, self-harm, or otherwise inappropriate content.
What happens when content is blocked? The student sees a brief, neutral message. No explanation of why it was blocked is given, to prevent circumvention. The blocked prompt is logged and flagged for teacher review.

Image Safety

  • Requests for identity documents (passports, licences, IDs, credit cards) are blocked.
  • Requests depicting minors are automatically rewritten to enforce a cartoon illustration style.
  • Requests for school photos or student portraits are blocked.
  • When students upload photos, faces are automatically detected and blurred on-device before storage.
  • All generated images are stored and visible to teachers in the dashboard.

Rate Limiting & Abuse Prevention

  • Request limit: 50 AI requests per minute per student.
  • Block cooldown: 3 content blocks within 5 minutes triggers a 5-minute restriction.
  • Instant session revocation: Teachers can log out all students with a single click.

Full Logging & Teacher Transparency

All AI interactions — text and image — are logged with full details. Teachers can review these at any time.

  • Text logs: Original prompt, system prompt, AI response, model used, and guardrail actions.
  • Image logs: The prompt, any rewritten version, and the generated image itself.
  • Timing and metadata: When it occurred, how long it took, which tool was used.

Teacher Dashboard

  • Text log viewer — Browse and search all student text interactions.
  • Image log viewer — See all AI-generated images with their prompts.
  • Flag review panel — See all flagged interactions with reason and category.
  • Student questions — See any help requests submitted by students.

Automatic Flagging System

When a guardrail blocks a request or detects a concern, a flag is automatically created for the teacher.

Profanity Sexual Content Violence Self-Harm Drugs Bullying Personal Information Identity Fraud Jailbreak Attempt Inappropriate Output NSFW Image

Teacher Controls

  • Create and manage student accounts — Add students, reset passwords, or remove accounts.
  • Assign modules and tools — Choose which AI activities are available.
  • Create classes — Organise students and control module access per class.
  • Review all AI usage — Browse text logs, image logs, and flagged content.
  • Instant logout — Immediately revoke all student sessions in one click.

Minimal Student Data Collection

AI Lift-Off is designed around the principle of data minimisation. Student accounts require only the bare minimum to function.

Username✓Set by teacher; can be a pseudonym
Password✓Stored securely hashed (bcrypt)
Display name✓Optional; first name or nickname
Email address—Not collected
Phone number—Not collected
Date of birth—Not collected
Home address—Not collected
Guardian info—Not collected
Tip for teachers: Since usernames are set by you, you can use anonymous identifiers (e.g. "student01", "table3-blue") making the platform effectively anonymous.

Personal Information Detection

If a student accidentally shares personal information in a prompt, the platform automatically detects and flags it:

  • Email addresses and phone numbers
  • Home or street addresses and postcodes
  • Passwords, PINs, or passcodes shared in conversation
  • Government ID numbers (TFN, Medicare, driver's licence, Centrelink, SSN)
  • Credit or debit card numbers
  • Dates of birth and full names (when shared with context)

Authentication & School Isolation

  • No anonymous access: Every student must log in with a username and password.
  • School-level isolation: Every database query is scoped to the school.
  • Secure tokens: JWT sessions expire after 8 hours.
  • Password security: Stored using bcrypt hashing — cannot be read by anyone.
  • Soft-delete: Removed records are marked inactive, preserving the audit trail.

Summary

6-layer content guardrails AI input & output guardrails Obfuscation detection Automatic face blurring Minor protection ID generation blocked PII detection & flagging Full interaction logging 11 flag categories Teacher dashboard Rate limiting No email collection School data isolation Bcrypt password hashing Instant session revocation
No system is perfect. While AI Lift-Off implements extensive safeguards, no content filtering system is 100% effective. That's why transparency and teacher oversight are central — every interaction is logged and flags are raised automatically. We recommend using the platform as a supervised classroom tool.