Generative AI concepts
Generative AI concepts cover tokens, context windows and why a model eventually forgets the start of a long conversation.
AI for Kids · Class 8 · Module 1 of 9
AI Literacy and Models
Different models are good at different things. Knowing which is which is a real skill.
8 sessionsSessions 1–8
4 weeksTypical pace
IntermediateLevel
Class 8Artificial Intelligence
The big idea
Students move from using one tool to comparing several — testing the same task across models, recording where each performs well, and observing hallucination as a measurable behaviour rather than a rumour.
Why it matters
Model literacy prevents both blind trust and blanket dismissal. Both are common, and both are wrong.
Unpacked
What you will actually learn
Three core ideas, each taught with worked examples and then practised until it feels obvious.
Model capabilities
Model capabilities differ by design — some reason better, some write better, some see images, some search the web.
Hallucinations
Hallucinations are systematic, not random. They cluster around obscure facts, recent events, numbers and citations.
Did you know?
A context window is the model’s working memory. Exceed it and the earliest parts of the conversation genuinely fall out of view.
Common mix-up
“The newest model is best at everything.” Benchmarks vary by task. The right question is always “best for what?”
Session by session
Your 8-session journey
Sessions 1–8 of the 72-session year, at two one-hour sessions per week.
- 1
Warm-up and big picture
Where this module fits, what you will build, and a hands-on starter that gets everyone curious about generative ai concepts.
- 2
Generative AI concepts
Guided teaching on generative ai concepts, worked through together with the teacher.
- 3
Generative AI concepts — practice lab
Independent practice, small challenges and one deliberate mistake to diagnose.
- 4
Model capabilities
Guided teaching on model capabilities, building directly on the previous two sessions.
- 5
Model capabilities — practice lab
Applied tasks that combine generative ai concepts and model capabilities in one piece of work.
- 6
Hallucinations
Hallucinations introduced and practised, completing the toolkit needed for the project.
- 7
Project build
Guided build session for the module project: Model comparison experiment.
- 8
Test, present and reflect
Finish, test against the checklist, present the work and explain the decisions behind it.
Project lab
Model comparison experiment
Every module ends with something the student built themselves and can demonstrate. This is the piece that goes into their portfolio and gets explained out loud at the end of session 8.
Try this at home
Run one identical, difficult task across three models and score them on accuracy, usefulness and honesty about uncertainty.
It is finished when
- It works from start to finish without breaking
- You can explain every part of it in your own words
- You tested it and improved at least one thing afterwards
- Someone else used or understood it without your help
By the end of this module
Students finishing Module 1 can:
- Explain and use generative ai concepts without prompting
- Explain and use model capabilities without prompting
- Explain and use hallucinations without prompting
- Build and finish model comparison experiment
- Test your own work and correct what you find
- Talk an adult through what you made and why
Word bank
The vocabulary introduced here, in plain language:
- token
- A chunk of text a model processes at a time.
- context window
- How much text a model can consider at once.
- benchmark
- A standard test used to compare models.
Module challenge
Think you have got this?
0 XPLevel 1 · Curious Beginner
6 quick questions drawn from this module — vocabulary, the project you build, and a myth-or-fact round. Every wrong answer explains itself, so a mistake still teaches you something.
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