AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 227 · 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: “flagging a new email” is training data. (a) True (b) False
2. 2.🛠️ Which does this job need: switching on a street light at 6 pm? (a) a simple rule is enough (b) needs AI (learning)
3. 3.🧐 Fact or myth: “AI learns from data”? (a) a fact (b) a myth
4. 4.True or false: “what training builds” is the model. (a) True (b) False
5. 5.🛠️ Which does this job need: recognising a friend’s face in photos? (a) needs AI (learning) (b) a simple rule is enough
6. 6.🔍 Which is the odd one out? (a) turning speech to text (b) making up a story (c) sorting photos by face (d) spotting a sick leaf
7. 7.🔍 Which is the odd one out? (a) very few examples (b) only one kind of example (c) correct labels (d) copies of one photo
8. 8.✨ Generative or not: composing a new tune? (a) makes something new (b) sorts or predicts
9. 9.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
10. 10.True or false: “does exactly as coded” describes how AI works. (a) False (b) True
11. 11.✨ What does generative AI do? (a) makes new content (b) only adds numbers (c) charges batteries (d) only stores files
12. 12.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
13. 13.Which of these describes how AI works? (a) does exactly as coded (b) same steps every time (c) one set rule per case (d) gives a likely answer
14. 14.🤖 What does AI stand for? (a) app installer (b) artificial intelligence (c) automatic internet (d) actual information
15. 15.🛠️ Which does this job need: turning spoken words into typed text? (a) a simple rule is enough (b) needs AI (learning)
16. 16.🔍 Which is the odd one out? (a) AI can be wrong (b) AI answers need checking (c) AI can mix up numbers (d) confident means correct
17. 17.True or false: “learns from examples” describes how AI works. (a) True (b) False
18. 18.💬 What do we call the request you type to a generative AI? (a) a password (b) a label (c) a battery (d) a prompt
19. 19.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
20. 20.Which of these is AI that sorts, spots or predicts (not generative)? (a) making up a story (b) drafting a letter (c) writing a new poem (d) suggesting a video
21. 21.True or false: “AI can mix up numbers” is a myth about AI. (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) AI can make up facts (b) AI is never wrong (c) AI answers need checking (d) AI copies data patterns
23. 23.✨ Generative or not: spotting a sick leaf? (a) makes something new (b) sorts or predicts
24. 24.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) ask different people (d) test on one group only
25. 25.Which of these is bad for training a model? (a) wrong labels (b) examples of every type (c) checking labels twice (d) correct labels
26. 26.🤖 Does an AI system think and feel like a person? (a) yes, just like us (b) yes, it gets sad (c) only on weekends (d) no, it finds patterns
27. 27.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI learns from data (c) long answers are true (d) AI copies data patterns
28. 28.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its colour (c) the weather (d) its screen size
29. 29.Which of these is good for training a model? (a) checking labels twice (b) wrong labels (c) testing on training data (d) very few examples
30. 30.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
31. 31.✨ Generative or not: predicting rain? (a) makes something new (b) sorts or predicts
32. 32.Which of these is good for training a model? (a) copies of one photo (b) very few examples (c) photos in many lights (d) labels added at random
33. 33.True or false: “one set rule per case” describes how a normal program works. (a) False (b) True
34. 34.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
35. 35.Which of these adds to bias? (a) check who is missing (b) test on many groups (c) test on one group only (d) add varied examples
36. 36.✅ Is this a real check of an AI answer: it answered quickly? (a) a real check (b) not a real check
37. 37.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
38. 38.✅ Is this a real check of an AI answer: redo the maths yourself? (a) not a real check (b) a real check
39. 39.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
40. 40.🔍 Which is the odd one out? (a) add varied examples (b) test on one group only (c) fix wrong labels (d) balance the data

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