Session 1 — What is AI?
Duration: 60 min · Format: live online · Ages: 8–11
Session goal: by the end, students can explain what AI is, point to AI they use every day, and describe how a computer learns from examples.
Before class — prep (5 min)
- Open Quick, Draw! in a tab — you'll demo it and screen-share.
- Have the two diagrams below ready to share on screen (AI around us and how a machine learns).
- Ask students to have paper and a pencil ready.
Agenda
| Time | Segment |
|---|---|
| 0:00 | Hook — everyday mysteries (5 min) |
| 0:05 | Teach — what "AI" means (12 min) |
| 0:17 | Teach — how a computer learns (13 min) |
| 0:30 | Activity — Quick, Draw! + pattern game (20 min) |
| 0:50 | Check for understanding (7 min) |
| 0:57 | Wrap-up + homework (3 min) |
0:00 · Hook (5 min)
Ask the class and take a few answers (chat or unmute):
- "How does a phone know it's your face and unlocks just for you?"
- "How does a game enemy chase you around the screen?"
- "How does a video app always know what you'll like next?"
Let them guess, then reveal: the secret behind all of these is one thing — AI. Tell them that today they'll find out what that really means.
0:05 · Teach — What does "AI" mean? (12 min)
Explain, writing the key words on your shared screen:
- AI = Artificial Intelligence.
- Artificial = made by people (not natural).
- Intelligence = being smart — learning, deciding, solving problems.
- So AI = a computer that can do smart things — a little like a brain we build.
⚠ Watch for the #1 misconception: students assume AI is alive or thinks/feels like a person. Correct it right away — a computer is not alive and has no feelings; it just gets very good at spotting patterns and following examples.
Share this diagram and point out where students already meet AI:
Left to right: voice assistants · video suggestions · face unlock · smart game characters · map directions · language translation.
Ask: "Which of these did you use today? Can anyone name one that isn't in the picture?" (Take 2–3 answers.)
0:17 · Teach — How does a computer learn? (13 min)
Explain: computers can learn from examples — this is called Machine Learning. Use the "teach a robot to recognise a cat" story and share the diagram:
Walk through the three steps out loud:
- Show examples — we give it lots of pictures, each labelled ("this is a cat", "this is a dog").
- It finds patterns — it notices cats have pointy ears and whiskers and slowly learns.
- It makes a guess — show a brand-new picture and it predicts: "Cat!"
Key point to land: the more good examples it sees, the better it guesses.
Ask the class: "If I only showed it 2 cats, would it be good or bad at guessing? Why?" (Answer: bad — too few examples to find a reliable pattern.)
0:30 · Activity (20 min)
Activity 1 — Quick, Draw! (≈10 min). Open Quick, Draw!. Demo one drawing yourself, then have students play on their own devices (or take turns if you're sharing one screen).
- Point out: it learned from millions of drawings other kids made.
- Ask as they play: "When did it guess right? When did it get confused? Why?"
Activity 2 — Be the AI (≈10 min, no computer). Pair students (or run it as a whole class). One person secretly picks a rule (e.g. "things that are round") and shows 5 examples; the partner spots the pattern and predicts the next one.
Debrief: "That's exactly what an AI does — find the pattern from examples, then make a guess."
0:50 · Check for understanding (7 min)
Ask these aloud or drop them in the chat. Answer key (for you):
- What does AI stand for? → Artificial Intelligence — "made by people" + "being smart".
- How does a computer learn to recognise a cat? → From lots of labelled examples; it finds patterns (Machine Learning).
- True or False: an AI thinks exactly like a human brain. → False — it doesn't feel or think like us; it's just good at spotting patterns from examples.
0:57 · Wrap-up + homework (3 min)
- Ask one student to finish the sentence: "AI is…"
- Homework — Pattern Detective: find 3 things at home or school that use AI. For one of them, guess what examples it might have learned from. Bring the list to Session 2.
Teaching notes
- Correct this misconception: "AI is alive / thinks like us." Reframe as pattern-spotting from examples.
- Fast finishers (extension): introduce model (the "brain" it builds), training (the teaching part), and label (the correct answer on each example). Ask them to name 3 real problems an AI could help solve.
- Low-tech fallback: if devices are limited, screen-share Quick, Draw! yourself and run Activity 2 (the pattern game) as a whole class.
Vocabulary
| Term | Meaning |
|---|---|
| AI (Artificial Intelligence) | A computer that does smart things |
| Machine Learning | Teaching a computer using examples |
| Pattern | A thing that repeats, like a rule |
| Example / Data | The pictures or facts we show the computer |
| Prediction | The answer the computer gives |
Resources
- Quick, Draw! — draw and watch AI guess (main demo).
- Teachable Machine — students will train their own model in Session 3.
- Machine Learning for Kids — friendly projects for extension.
- AI Experiments by Google — short demos of what AI can do.
Next session
Session 2 — Patterns Everywhere: students become pattern-spotters and teach the computer to sort things into groups.