AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 20 · 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 does this job need: counting the words in an essay? (a) a simple rule is enough (b) needs AI (learning)
2. 2.Which of these is good for training a model? (a) very few examples (b) many varied examples (c) labels added at random (d) blurry, unclear photos
3. 3.⏩ In machine learning, which comes first: labelled fruit photos or the trained program? (a) labelled fruit photos (b) the trained program
4. 4.✨ Generative or not: predicting rain? (a) sorts or predicts (b) makes something new
5. 5.🧐 Fact or myth: “AI can be wrong”? (a) a myth (b) a fact
6. 6.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) one single photo (d) a song about dogs
7. 7.✨ Generative or not: reading number plates? (a) makes something new (b) sorts or predicts
8. 8.Which of these is a fact about AI? (a) AI knows everything (b) long answers are true (c) AI can be wrong (d) AI is never wrong
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
10. 10.📱 What is the AI doing here: a shop guessing how many umbrellas will sell? (a) generating (b) recognising (c) predicting (d) recommending
11. 11.True or false: showing the time on a clock only needs a simple fixed rule. (a) False (b) True
12. 12.Which of these is training data? (a) typing a new spoken word (b) what training builds (c) old emails marked spam (d) naming a new leaf
13. 13.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
14. 14.📚 An AI chatbot names a book that does not exist. This is called… (a) a backup (b) a summary (c) a hallucination (d) a password
15. 15.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
16. 16.📱 What is the AI doing here: an AI tool making a brand-new tune? (a) predicting (b) generating (c) recognising (d) recommending
17. 17.🛠️ Does this reduce bias or add to it: add varied examples? (a) adds to bias (b) reduces bias
18. 18.🧮 Which of these is NOT AI? (a) voice typing (b) face unlock (c) a spam filter (d) a basic calculator
19. 19.📺 A video app suggests what to watch next. What is the AI doing? (a) recommending (b) cooking (c) printing (d) charging
20. 20.📅 An AI gives a date for a history event. How can you check? (a) ask it to repeat (b) guess (c) look in your textbook (d) pick a lucky number
21. 21.🤖 AI or a normal program: which one “does exactly as coded”? (a) a normal program (b) AI
22. 22.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) very few examples (d) photos in many lights
23. 23.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a fair model (c) bias from data (d) a broken screen
24. 24.🔍 Which is the odd one out? (a) very few examples (b) many varied examples (c) copies of one photo (d) labels added at random
25. 25.Which of these is the model? (a) old emails marked spam (b) tomorrow’s rain guess (c) naming a new fruit photo (d) what training builds
26. 26.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
27. 27.✨ Generative or not: spotting a sick leaf? (a) makes something new (b) sorts or predicts
28. 28.True or false: “fix wrong labels” adds to bias. (a) True (b) False
29. 29.True or false: a music app suggesting a song you may like is AI recognising something. (a) True (b) False
30. 30.True or false: “the learned patterns” is a prediction. (a) False (b) True
31. 31.True or false: “past weather records” is training data. (a) False (b) True
32. 32.True or false: “does exactly as coded” describes how AI works. (a) False (b) True
33. 33.🛠️ Does this reduce bias or add to it: ask different people? (a) adds to bias (b) reduces bias
34. 34.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) ask different people (d) add more of the same
35. 35.📱 What is the AI doing here: a music app suggesting a song you may like? (a) recognising (b) recommending (c) generating (d) predicting
36. 36.🔍 Which is the odd one out? (a) AI is never wrong (b) long answers are true (c) AI learns from data (d) AI has real feelings
37. 37.Which of these is bad for training a model? (a) correct labels (b) blurry, unclear photos (c) clear, sharp examples (d) new data for testing
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.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
40. 40.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True

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