AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 581 · 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: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
2. 2.🛠️ Which does this job need: telling a cat photo from a dog photo? (a) needs AI (learning) (b) a simple rule is enough
3. 3.🔍 Which is the odd one out? (a) confident means correct (b) AI learns from data (c) AI can make up facts (d) AI answers need checking
4. 4.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
5. 5.🔍 Which is the odd one out? (a) long answers are true (b) AI has real feelings (c) AI always checks facts (d) AI copies data patterns
6. 6.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
7. 7.True or false: converting metres into centimetres needs AI that learns from examples. (a) True (b) False
8. 8.✅ Is this a real check of an AI answer: it has a neat layout? (a) a real check (b) not a real check
9. 9.📅 An AI gives a date for a history event. How can you check? (a) ask it to repeat (b) guess (c) pick a lucky number (d) look in your textbook
10. 10.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
11. 11.✨ Generative or not: drafting a letter? (a) sorts or predicts (b) makes something new
12. 12.Which of these uses AI? (a) a calculator (b) an app translating signs (c) a digital watch (d) a light switch
13. 13.True or false: “AI copies data patterns” is a myth about AI. (a) False (b) True
14. 14.Which of these is a fact about AI? (a) AI can make up facts (b) long answers are true (c) AI has real feelings (d) AI always checks facts
15. 15.🧐 Fact or myth: “AI can mix up numbers”? (a) a myth (b) a fact
16. 16.🧐 Fact or myth: “AI is never wrong”? (a) a fact (b) a myth
17. 17.📺 A video app suggests what to watch next. What is the AI doing? (a) cooking (b) printing (c) charging (d) recommending
18. 18.Which of these is bad for training a model? (a) new data for testing (b) wrong labels (c) clear, sharp examples (d) checking labels twice
19. 19.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
20. 20.True or false: “makes a best guess” describes how a normal program works. (a) True (b) False
21. 21.🛠️ Which does this job need: recognising a bird from its song? (a) a simple rule is enough (b) needs AI (learning)
22. 22.True or false: “AI has real feelings” is a myth about AI. (a) True (b) False
23. 23.🧐 Fact or myth: “AI answers need checking”? (a) a myth (b) a fact
24. 24.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a strong battery (c) bias from data (d) a fair model
25. 25.Which of these describes how AI works? (a) gives a likely answer (b) follows fixed rules (c) same steps every time (d) never learns from data
26. 26.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
27. 27.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) a song about dogs (d) many labelled photos
28. 28.🛠️ Which does this job need: suggesting the next word as you type? (a) needs AI (learning) (b) a simple rule is enough
29. 29.✨ Generative or not: creating a cartoon? (a) sorts or predicts (b) makes something new
30. 30.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
31. 31.⏩ In machine learning, which comes first: naming a new fruit photo or the trained program? (a) naming a new fruit photo (b) the trained program
32. 32.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
33. 33.Which of these helps reduce bias? (a) test on many groups (b) skip testing (c) copy old unfair choices (d) add more of the same
34. 34.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
35. 35.Which of these adds to bias? (a) check who is missing (b) test on one group only (c) ask different people (d) fix wrong labels
36. 36.True or false: suggesting the next word as you type needs AI that learns from examples. (a) True (b) False
37. 37.Which of these adds to bias? (a) balance the data (b) check who is missing (c) fix wrong labels (d) add more of the same
38. 38.🤖 Does an AI system think and feel like a person? (a) only on weekends (b) no, it finds patterns (c) yes, it gets sad (d) yes, just like us
39. 39.True or false: reading messy handwriting needs AI that learns from examples. (a) False (b) True
40. 40.Which of these is generative AI (it makes something new)? (a) inventing a recipe (b) turning speech to text (c) reading number plates (d) predicting rain

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