AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 886 · 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.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
2. 2.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
3. 3.Which of these is good for training a model? (a) many varied examples (b) very few examples (c) blurry, unclear photos (d) only one kind of example
4. 4.🔍 Which is the odd one out? (a) a doorbell (b) a kitchen weighing scale (c) a torch (d) an AI chatbot
5. 5.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
6. 6.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
7. 7.True or false: “skip testing” helps reduce bias. (a) True (b) False
8. 8.🤖 AI or a normal program: which one “learns from examples”? (a) AI (b) a normal program
9. 9.True or false: “uses rules people wrote” describes how AI works. (a) True (b) False
10. 10.🏠 AI or not AI: a calculator? (a) uses AI (b) not AI
11. 11.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
12. 12.📺 A video app suggests what to watch next. What is the AI doing? (a) cooking (b) recommending (c) printing (d) charging
13. 13.🛠️ Which does this job need: translating a sentence into Hindi? (a) needs AI (learning) (b) a simple rule is enough
14. 14.🏠 AI or not AI: a doorbell? (a) not AI (b) uses AI
15. 15.🧐 Fact or myth: “AI always checks facts”? (a) a fact (b) a myth
16. 16.Which of these is not AI? (a) photos grouped by face (b) a digital watch (c) voice typing (d) a map predicting traffic
17. 17.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) slower to switch on (d) change colour
18. 18.True or false: an AI chatbot writing a story about a lost kite is AI generating something new. (a) True (b) False
19. 19.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
20. 20.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
21. 21.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a prediction (c) a password (d) a label error
22. 22.True or false: “learns from examples” describes how a normal program works. (a) True (b) False
23. 23.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) many labelled photos (d) one single photo
24. 24.Which of these is not AI? (a) a kitchen weighing scale (b) video suggestions (c) a spam filter (d) a map predicting traffic
25. 25.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it may get it wrong (d) it will be perfect
26. 26.✨ Generative or not: predicting rain? (a) makes something new (b) sorts or predicts
27. 27.🏠 AI or not AI: a digital watch? (a) not AI (b) uses AI
28. 28.Which of these describes how a normal program works? (a) gives a likely answer (b) learns from examples (c) handles unseen examples (d) never learns from data
29. 29.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) skip testing (d) check who is missing
30. 30.Which of these is a fact about AI? (a) AI always checks facts (b) AI can be wrong (c) long answers are true (d) AI has real feelings
31. 31.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
32. 32.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
33. 33.Which of these helps reduce bias? (a) skip testing (b) ask different people (c) ignore complaints (d) use one group only
34. 34.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
35. 35.Which of these helps reduce bias? (a) check who is missing (b) copy old unfair choices (c) use one group only (d) add more of the same
36. 36.📱 What is the AI doing here: a book app suggesting a story like your last one? (a) recommending (b) recognising (c) generating (d) predicting
37. 37.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
38. 38.True or false: “rain sound effects for a play” asks for an image. (a) True (b) False
39. 39.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its training data (d) its colour
40. 40.🎨 This prompt asks a generative AI for: a poster of a rainforest. What kind of output is that? (a) text (b) music or sound (c) an image

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