AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 96 · 40 questions

AI tip (Name the idea, then answer): Learning from examples → AI; fixed rules → a normal program. Order: training data → model → prediction; good data is many, varied and correctly labelled. Generative AI makes new things and can hallucinate; one-sided data causes bias.

1. 1.True or false: “add more of the same” helps reduce bias. (a) True (b) False
2. 2.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
3. 3.🔍 Which is the odd one out? (a) AI answers need checking (b) AI has real feelings (c) AI is never wrong (d) AI always checks facts
4. 4.Which of these is generative AI (it makes something new)? (a) suggesting a video (b) drafting a letter (c) spotting a sick leaf (d) predicting rain
5. 5.💬 What do we call the request you type to a generative AI? (a) a prompt (b) a battery (c) a password (d) a label
6. 6.Which of these is a prediction? (a) the trained program (b) labelled fruit photos (c) what training builds (d) tomorrow’s rain guess
7. 7.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
8. 8.🤖 AI or a normal program: which one “learns from examples”? (a) a normal program (b) AI
9. 9.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
10. 10.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
11. 11.🏷️ What is a “label” in machine learning? (a) the price (b) the right answer tag (c) a sticker on a laptop (d) the font size
12. 12.True or false: “five quiz questions on fractions” asks for text. (a) True (b) False
13. 13.True or false: “a logo idea for the eco club” asks for text. (a) False (b) True
14. 14.🧐 Fact or myth: “AI has real feelings”? (a) a fact (b) a myth
15. 15.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) a list of rules only (d) many labelled photos
16. 16.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
17. 17.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it will be perfect (d) it may get it wrong
18. 18.🛠️ Which does this job need: ringing the school bell at 9 am? (a) needs AI (learning) (b) a simple rule is enough
19. 19.🛠️ Which does this job need: reading messy handwriting? (a) needs AI (learning) (b) a simple rule is enough
20. 20.Which of these is AI that sorts, spots or predicts (not generative)? (a) spotting spam (b) composing a new tune (c) inventing a recipe (d) drafting a letter
21. 21.True or false: turning your spoken words into typed text is AI predicting something. (a) False (b) True
22. 22.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) generating (b) predicting (c) recognising (d) recommending
23. 23.True or false: “see if the book exists” is NOT a real way to check an AI answer. (a) True (b) False
24. 24.🛠️ What helps make an AI system fairer? (a) one group only (b) fewer tests (c) ignoring mistakes (d) more varied data
25. 25.True or false: “AI copies data patterns” is a fact about AI. (a) False (b) True
26. 26.🔍 Which is the odd one out? (a) AI has real feelings (b) confident means correct (c) long answers are true (d) AI can make up facts
27. 27.📱 What is the AI doing here: turning your spoken words into typed text? (a) predicting (b) recommending (c) generating (d) recognising
28. 28.✅ Is this a real check of an AI answer: it uses big words? (a) not a real check (b) a real check
29. 29.🤖 What makes an AI system different from a normal program? (a) it has a screen (b) it learns from examples (c) it is always right (d) it uses electricity
30. 30.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
31. 31.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
32. 32.True or false: “flagging a new email” is a prediction. (a) False (b) True
33. 33.Which of these is a prediction? (a) past weather records (b) old emails marked spam (c) labelled fruit photos (d) naming a new fruit photo
34. 34.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
35. 35.🔦 Is a torch with an on/off switch AI? (a) yes (b) no (c) only if it is bright
36. 36.Which of these is the model? (a) naming a new fruit photo (b) recorded spoken words (c) what training builds (d) typing a new spoken word
37. 37.True or false: “one set rule per case” describes how AI works. (a) True (b) False
38. 38.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a label error (c) a password (d) training data
39. 39.Which of these is bad for training a model? (a) correct labels (b) wrong labels (c) clear, sharp examples (d) new data for testing
40. 40.🎨 This prompt asks a generative AI for: a thank-you note to the bus driver. What kind of output is that? (a) music or sound (b) text (c) an image

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