AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 88 · 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: “AI always checks facts” is a myth about AI. (a) True (b) False
2. 2.✨ Generative or not: writing quiz questions? (a) makes something new (b) sorts or predicts
3. 3.🏠 AI or not AI: an app translating signs? (a) uses AI (b) not AI
4. 4.Which of these helps reduce bias? (a) use one group only (b) skip testing (c) test on one group only (d) add varied examples
5. 5.True or false: “the learned patterns” is the model. (a) False (b) True
6. 6.📦 What happens during training? (a) it takes photos (b) it prints labels (c) it learns patterns (d) it charges up
7. 7.🧐 Fact or myth: “AI answers need checking”? (a) a fact (b) a myth
8. 8.🔍 Which is the odd one out? (a) a printed timetable (b) a calculator (c) a light switch (d) a spam filter
9. 9.True or false: “rain sound effects for a play” asks for music or sound. (a) True (b) False
10. 10.Which of these describes how AI works? (a) learns from examples (b) does exactly as coded (c) never learns from data (d) same steps every time
11. 11.🛠️ Which does this job need: converting metres into centimetres? (a) a simple rule is enough (b) needs AI (learning)
12. 12.📱 What is the AI doing here: a map app guessing how long a trip will take? (a) generating (b) predicting (c) recognising (d) recommending
13. 13.🔍 Which is the odd one out? (a) AI knows everything (b) AI has real feelings (c) confident means correct (d) AI can be wrong
14. 14.Which of these is a myth about AI? (a) AI can make up facts (b) AI answers need checking (c) long answers are true (d) AI can mix up numbers
15. 15.⏩ In machine learning, which comes first: tomorrow’s rain guess or old emails marked spam? (a) tomorrow’s rain guess (b) old emails marked spam
16. 16.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) training data (c) a prediction
17. 17.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) not spam (b) spam
18. 18.🎨 This prompt asks a generative AI for: a drum beat for a dance. What kind of output is that? (a) music or sound (b) text (c) an image
19. 19.🔍 Which is the odd one out? (a) making up a story (b) composing a new tune (c) drawing a new picture (d) suggesting a video
20. 20.Which of these describes how AI works? (a) follows fixed rules (b) never learns from data (c) does exactly as coded (d) makes a best guess
21. 21.Which of these is AI that sorts, spots or predicts (not generative)? (a) drawing a new picture (b) writing a new poem (c) creating a cartoon (d) reading number plates
22. 22.🏷️ 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
23. 23.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
24. 24.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
25. 25.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
26. 26.True or false: “labels added at random” is bad for training a model. (a) False (b) True
27. 27.📱 What is the AI doing here: an online shop showing “you may also like”? (a) generating (b) recommending (c) predicting (d) recognising
28. 28.Which of these is the model? (a) the learned patterns (b) tomorrow’s rain guess (c) flagging a new email (d) recorded spoken words
29. 29.💬 What do we call the request you type to a generative AI? (a) a battery (b) a password (c) a prompt (d) a label
30. 30.🖼️ 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
31. 31.Which of these is generative AI (it makes something new)? (a) spotting spam (b) spotting a sick leaf (c) unlocking with a face (d) composing a new tune
32. 32.Which of these is a prediction? (a) what training builds (b) past weather records (c) labelled fruit photos (d) naming a new leaf
33. 33.True or false: “examples of every type” is bad for training a model. (a) True (b) False
34. 34.True or false: spotting spam emails by their patterns needs AI that learns from examples. (a) True (b) False
35. 35.🛠️ Which does this job need: finding 10% of a price? (a) needs AI (learning) (b) a simple rule is enough
36. 36.🤖 AI or a normal program: which one “same steps every time”? (a) a normal program (b) AI
37. 37.Which of these is generative AI (it makes something new)? (a) predicting rain (b) turning speech to text (c) writing quiz questions (d) spotting spam
38. 38.True or false: “labelled fruit photos” is training data. (a) False (b) True
39. 39.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
40. 40.✅ Is this a real check of an AI answer: see if the book exists? (a) not a real check (b) a real check

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