AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 118 · 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.Which of these is a myth about AI? (a) AI answers need checking (b) AI learns from data (c) AI knows everything (d) AI can make up facts
2. 2.⏩ In machine learning, which comes first: what training builds or 500 labelled leaf photos? (a) what training builds (b) 500 labelled leaf photos
3. 3.🛠️ Which does this job need: counting the words in an essay? (a) needs AI (learning) (b) a simple rule is enough
4. 4.True or false: “a story about a brave ant” asks for an image. (a) True (b) False
5. 5.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
6. 6.Which of these is a prediction? (a) the learned patterns (b) what training builds (c) naming a new leaf (d) old emails marked spam
7. 7.True or false: “test on many groups” adds to bias. (a) True (b) False
8. 8.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) one single photo (d) a list of rules only
9. 9.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False
10. 10.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing quiz questions (b) unlocking with a face (c) creating a cartoon (d) making up a story
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
12. 12.🛠️ Which does this job need: recognising a bird from its song? (a) a simple rule is enough (b) needs AI (learning)
13. 13.✅ Is this a real check of an AI answer: it has a neat layout? (a) a real check (b) not a real check
14. 14.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
15. 15.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) recommending (b) recognising (c) predicting (d) generating
16. 16.🛠️ Which does this job need: translating a sentence into Hindi? (a) needs AI (learning) (b) a simple rule is enough
17. 17.📱 What is the AI doing here: an online shop showing “you may also like”? (a) recognising (b) recommending (c) predicting (d) generating
18. 18.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos
19. 19.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
20. 20.📦 What happens during training? (a) it learns patterns (b) it takes photos (c) it charges up (d) it prints labels
21. 21.True or false: “what training builds” is training data. (a) False (b) True
22. 22.Which of these is not AI? (a) video suggestions (b) voice typing (c) photos grouped by face (d) a light switch
23. 23.Which of these describes how a normal program works? (a) does exactly as coded (b) gives a likely answer (c) makes a best guess (d) spots patterns in data
24. 24.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a label error (c) training data (d) a prediction
25. 25.💬 What do we call the request you type to a generative AI? (a) a label (b) a battery (c) a prompt (d) a password
26. 26.🧮 Which of these is NOT AI? (a) voice typing (b) a basic calculator (c) a spam filter (d) face unlock
27. 27.True or false: “labels added at random” is bad for training a model. (a) False (b) True
28. 28.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
29. 29.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) ignore complaints (d) fix wrong labels
30. 30.Which of these is not AI? (a) face unlock on a phone (b) a torch (c) photos grouped by face (d) voice typing
31. 31.Which of these is a fact about AI? (a) AI has real feelings (b) AI always checks facts (c) AI knows everything (d) AI answers need checking
32. 32.True or false: ringing the school bell at 9 am needs AI that learns from examples. (a) False (b) True
33. 33.Which of these is a myth about AI? (a) AI answers need checking (b) AI can be wrong (c) AI can mix up numbers (d) AI has real feelings
34. 34.🔍 Which is the odd one out? (a) composing a new tune (b) writing a new poem (c) turning speech to text (d) making up a story
35. 35.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data
36. 36.🎨 An image generator makes a picture from… (a) your password (b) the weather (c) a text description (d) a phone number
37. 37.🧐 Fact or myth: “AI copies data patterns”? (a) a myth (b) a fact
38. 38.Which of these is the model? (a) the trained program (b) 500 labelled leaf photos (c) flagging a new email (d) labelled fruit photos
39. 39.🔍 Which is the odd one out? (a) unlocking with a face (b) composing a new tune (c) reading number plates (d) turning speech to text
40. 40.Which of these is AI that sorts, spots or predicts (not generative)? (a) sorting photos by face (b) creating a cartoon (c) writing quiz questions (d) making up a story

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