Australia · Years 5 to 12 and adults · AI with judgement

Learn to think, not just use AI tools

An AI chatbot will write a paragraph, a program or a maths solution in seconds, and most of the time the result looks convincing. The skill that matters now is not getting an answer; it is knowing whether the answer is right, and knowing what you would have done without it. Australian schools are already teaching students to write prompts. This page sets out what the curriculum actually asks for, what the AI companies themselves say about age, and a piece of mathematics that answers a question every student should ask: if I cannot check every answer, how many do I need to check before I trust the rest?

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In short

Learning to think with AI means understanding how a tool produces its answer, checking that answer, and being able to solve the problem without it. The Australian Curriculum already includes writing prompts and refining output "to improve its correctness". Because no one can check every answer, students also need to know how many to spot-check: if 4 of 40 AI answers are wrong, checking 17 at random gives at least a 90% chance of catching one.

Where to start

Three courses that put understanding first

Matched to age and to the AI tools each age may use. The free first lesson confirms the right one.

AI Literacy for Kids (Ages 8 to 14) course thumbnail

LTAU / 01

How AI works, for children

Ages 8 to 14. What AI learns from, where it goes wrong, and how to check it, without needing an adult-only chatbot.

Open the syllabus →
AI Tools Course for Teens (13+) course thumbnail

LTAU / 02

AI tools with judgement, for teens

Ages 13 and up. Prompting, checking and citing, using tools whose terms allow teenagers.

Open the syllabus →
AI and Machine Learning for Teens course thumbnail

LTAU / 03

Building the models yourself

Teens ready for Python. Train small models and see exactly where their answers come from.

Open the syllabus →

The curriculum

What Australian classrooms already ask of students

Prompting is not a fringe skill in Australia. The Australian Curriculum v9 names it in Digital Technologies for Years 7 and 8, alongside the expectation that students improve the correctness of what a model produces.

AI in the Australian Curriculum v9, Digital Technologies 7 to 10, as published
WhereCodeThe curriculum's words
Years 7 and 8, elaborationAC9TDI8P11"using effective prompts with generative AI models to create output that is better suited to the problem being solved"
Years 7 and 8, elaborationAC9TDI8P11"using a progressive series of prompts with generative models to refine output to improve its correctness"
Years 9 and 10, elaborationAC9TDI10P11"locating relevant content by using Boolean operators or artificial intelligence search features of search engines"
Years 7 and 8, band descriptionNone"Students check their solutions meet the specifications by testing and debugging their algorithms"

The word that matters

Look closely at the second line. The curriculum does not stop at writing a prompt; it expects students to refine the output "to improve its correctness". That assumes the student can tell when the output is wrong.

Telling right from wrong is a thinking skill, and it depends on understanding the subject well enough to notice a mistake.

Testing is the same habit

The band description for Years 7 and 8 asks students to check their own solutions "by testing and debugging". Checking an AI's answer is the same discipline applied to someone else's work.

A student who tests their own code habitually is already halfway to checking an AI properly.

Source, read 7 October 2026: ACARA, Australian Curriculum v9, Digital Technologies content, Years 7 to 10 (Word file). Elaborations are examples of how a content description may be taught, not compulsory content.

Age rules

Which AI tools a student is allowed to use

Thinking well about AI starts with using the right tool for your age. The companies and the education system each set their own lines, and they are not all the same.

Age lines we read at source
Who says itWhat they say
Anthropic, consumer terms for Claude"You must be at least 18 years old or the minimum age required to consent to use the Services in your location, whichever is higher."
Digital Technologies Hub, AI implementation module for teachersStrategies "for integrating GenAI with students (age 13+)"
Our coursesChildren under 13 learn how AI works through activities that need no adult-only accounts

Why we teach AI to children without chatbots

AI tools set their own minimum ages, and Claude's is 18. We follow each tool's current terms, which shapes how we teach younger students.

Children aged 8 to 12 learn how a model learns from examples, train small classifiers in child-safe tools, and practise checking outputs, without signing up to any adult service.

Free teacher modules

The Digital Technologies Hub offers teachers nine modules on AI "designed to build understanding of AI concepts such as Generative AI, machine learning and bias, responsible AI, programming and ethics", with no log-in required.

If your school uses them, our lessons will feel familiar; if it does not, they are a useful read for parents too.

Sources, read 7 October 2026: Anthropic consumer terms and Digital Technologies Hub, Explore AI in education. Terms change; always check the current terms of any tool before a child signs up.

Spot-checking

How many AI answers do you need to check?

Suppose an AI has produced 40 answers for you: worked solutions, translations, or lines of code. Checking all 40 defeats the purpose of using it. Checking two feels too few. Factories face the same question with batches of parts, and the answer has a name: acceptance sampling.

Chance of catching at least one wrong answer, checking n of 40 at random (our calculation)
Wrong answers in the batchCheck 3Check 5Check 10Check 20
1 of 407.5%12.5%25.0%50.0%
2 of 4014.6%23.7%44.2%75.6%
4 of 4027.7%42.7%70.0%94.7%
8 of 4049.8%69.4%92.4%99.8%

What the table says

If 4 of the 40 answers are wrong and you check 5, you have only a 42.7% chance of spotting even one mistake. More often than not, a quick glance passes a batch that contains four errors.

To reach a 90% chance of catching at least one mistake in that batch, you need to check 17 answers. With 8 wrong, 10 checks are enough; with 2 wrong, you need 27.

The mathematics

The chance of missing every wrong answer is the number of ways to choose your checks from the correct answers, divided by the number of ways to choose them from all 40. One minus that is the chance of catching at least one.

In Python it is a single line using math.comb: 1 - comb(40 - k, n) / comb(40, n). Students in Years 9 and 10 can derive it; younger students can simulate it by drawing cards.

The thinking lesson

A few spot-checks catch a tool that is often wrong, but they rarely catch one that is occasionally wrong. The rarer the mistakes, the more you have to understand the subject yourself, because sampling alone will not save you.

Thinking habits

Five habits that keep the thinking yours

These are the habits we build in every course that touches AI, at every age.

Predict first

Before asking an AI, write down what you expect the answer to look like. A prediction turns a surprising answer into a question rather than an acceptance.

Ask why

For any answer you keep, be able to explain why it is right in your own words. If you cannot, you have borrowed it, not learned it.

Check at random

When you cannot check everything, check a random sample, not the first few. Errors are not polite enough to sit at the top of a list.

Solve one by hand

Every so often, solve a problem without the tool. It keeps the skill alive and gives you a benchmark for the tool's answers.

Know the limits

Learn what kinds of question a tool handles badly, such as exact arithmetic, recent events or sources it cannot see.

Own the result

Whatever you submit or ship is yours. Schools and employers judge the work, not the tool that helped.

For assessed school work, each state's rules decide what AI use is allowed, and the work must be the student's own. We teach the understanding and the checking; we never write a student's assessed work. For a deeper look at reading and owning code, see our page on understanding the code rather than copying it.

Stages

From AI user to AI thinker

A progression we see in students who learn to work with AI well.

Four stages of thinking with AI
StageWhat the student can do
1. UseGet a useful answer from a tool appropriate for their age
2. DoubtNotice when an answer looks wrong, and say why
3. CheckTest answers systematically, including by random sampling
4. BuildWrite programs, and train small models, that do the checking

For younger students

The first two stages come through activities and games, without adult-only accounts.

Children learn that a computer can be confidently wrong, which is the most useful lesson of all.

For teenagers and adults

Stages three and four involve real code: test harnesses, sampling programs and small models whose every decision can be inspected.

By then the AI is a tool the student directs, not an oracle they obey.

The catalogue

Nine courses about understanding AI, not just using it

Grouped by age. The free first lesson places each student.

I

Children

Ages 8 to 12

LTAU / CHD / 01

What AI is and is not

Activities that show how machines learn.

Open the syllabus

LTAU / CHD / 02

Python projects with AI inside

Small, checkable AI programs.

Open the syllabus

LTAU / CHD / 03

Thinking before computing

Logic that makes checking possible.

Open the syllabus
II

Teenagers

Ages 13 to 18

LTAU / TEN / 01

Prompting, checking, citing

AI tools used with judgement.

Open the syllabus

LTAU / TEN / 02

Models you train yourself

From data to a working model.

Open the syllabus

LTAU / TEN / 03

Data before conclusions

Python for real datasets.

Open the syllabus
III

Adults

18 and over

LTAU / ADL / 01

AI tools for work

Productive, checked, accountable.

Open the syllabus

LTAU / ADL / 02

How LLM systems are built

Retrieval, agents and evaluation.

Open the syllabus

LTAU / ADL / 03

Automation you can audit

Scripts with applied AI.

Open the syllabus

How lessons run

Lessons where the student explains every answer

Whether or not an AI tool is involved, the student does the thinking, out loud, with a teacher listening.

After school

Weekday afternoons in your state.

Evenings

For senior students and adults.

Weekends

Saturday and Sunday options.

Predict, then run

Students say what they expect before any code or tool runs.

Explain it back

An answer counts only once the student can explain it.

Age-appropriate tools

We follow each tool's terms on minimum age.

Groups

Fifteen to twenty students, or one to one.

Their own work

Teachers question and guide; they do not do the work.

Real checks

Students write tests and samplers, not just opinions.

Student work

Student projects that think for themselves

Work our students built and can explain line by line. Many more are collected on the student labs page.

NutriLife AI nutrition coach project screenshot

AI and ML

NutriLife

An AI nutrition coach that reads what you eat and works you toward a target.

by Bhavya · Open it

Misti AI chatbot for maths and coding screenshot

AI and ML

Misti

A chatbot that answers mathematics and programming questions, built and deployed by a student.

by Harshit · Open it

GuardianX AI internet safety assistant screenshot

AI and ML

GuardianX

An assistant that helps a young person recognise unsafe situations online.

by Vivaan · Open it

SkyCast weather forecast application screenshot

Web app

SkyCast

A weather forecasting site with live conditions for any location.

by Krish

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Questions from parents and students

Common questions about thinking with AI

What does learn to think, not just use AI tools mean?

It means understanding how an AI tool reaches its answer, checking that answer properly, and keeping the ability to solve the problem without the tool, so the student directs the AI rather than depending on it.

What is acceptance sampling?

Acceptance sampling is a way of deciding whether to trust a batch of items by checking a random sample of them. Applied to AI, it tells you how many answers to check: with 4 wrong in 40, checking 17 at random gives at least a 90% chance of catching one.

Does the Australian Curriculum teach students to use AI?

Yes. The Australian Curriculum v9 includes elaborations in Digital Technologies for Years 7 and 8 about using effective prompts with generative AI and refining output to improve its correctness.

How old do you have to be to use AI chatbots?

It depends on the tool. Anthropic's consumer terms for Claude require users to be at least 18. Other tools set their own minimum ages, so always check the current terms before a child signs up.

Can children under 13 learn about AI with you?

Yes. Children aged 8 to 12 learn how AI works through activities and child-safe tools that need no adult-only accounts.

Will you help my child use AI for school assignments?

We teach understanding and checking. We never write a student's assessed work, and each state's rules decide what AI use is allowed in assessments.

Why not just trust AI tools since they are usually right?

Because "usually" hides the problem. If a tool is wrong only occasionally, a few spot-checks rarely catch it, so the student must understand the subject well enough to notice errors.

Does my child need to know coding first?

No. Younger students start with activities and Scratch; programming in Python comes later, when they write programs that test AI answers.

Are lessons live?

Yes. Every lesson is live over video with a teacher, in small groups or one to one, at times set for your state.

How much do the courses cost?

The first lesson is free. After that, fees are monthly with no joining fee and no term commitment, as shown in the fees section on this page.

Elsewhere on this site

Related pages

More on reading code, AI for children and building AI rather than prompting it.

Coding classes in Australia

Our main page for Australian families.

Understand the code, do not copy-paste

Owning what you submit.

Learn to train AI

Building models rather than prompting them.

AI courses for kids

AI for primary-age children.

AI classes for teens

AI for secondary students.

HSC Software Engineering

For NSW senior students.

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