AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 600 · 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.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
2. 2.📅 An AI gives a date for a history event. How can you check? (a) ask it to repeat (b) pick a lucky number (c) look in your textbook (d) guess
3. 3.Which of these is good for training a model? (a) testing on training data (b) photos in many lights (c) wrong labels (d) very few examples
4. 4.True or false: “it uses big words” is NOT a real way to check an AI answer. (a) True (b) False
5. 5.True or false: “a picture of a castle made of mangoes” asks for an image. (a) True (b) False
6. 6.True or false: “add varied examples” helps reduce bias. (a) True (b) False
7. 7.✨ Generative or not: composing a new tune? (a) makes something new (b) sorts or predicts
8. 8.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI copies data patterns (c) AI learns from data (d) AI always checks facts
9. 9.🔍 Which is the odd one out? (a) a digital watch (b) an image generator (c) photos grouped by face (d) voice typing
10. 10.🤖 What makes an AI system different from a normal program? (a) it learns from examples (b) it has a screen (c) it uses electricity (d) it is always right
11. 11.✨ Generative or not: inventing a recipe? (a) sorts or predicts (b) makes something new
12. 12.Which of these is a prediction? (a) typing a new spoken word (b) past weather records (c) the trained program (d) old emails marked spam
13. 13.Which of these is not AI? (a) a map predicting traffic (b) photos grouped by face (c) video suggestions (d) a digital watch
14. 14.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will be perfect (d) it will turn yellow
15. 15.🧮 Which of these is NOT AI? (a) a basic calculator (b) a spam filter (c) face unlock (d) voice typing
16. 16.🧐 Fact or myth: “AI can be wrong”? (a) a myth (b) a fact
17. 17.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) testing on training data (d) many varied examples
18. 18.🎨 This prompt asks a generative AI for: a story about a brave ant. What kind of output is that? (a) music or sound (b) an image (c) text
19. 19.Which of these is AI that sorts, spots or predicts (not generative)? (a) composing a new tune (b) turning speech to text (c) creating a cartoon (d) writing quiz questions
20. 20.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
21. 21.Which of these helps reduce bias? (a) skip testing (b) use one group only (c) balance the data (d) add more of the same
22. 22.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
23. 23.Which of these is good for training a model? (a) labels added at random (b) copies of one photo (c) very few examples (d) checking labels twice
24. 24.Which of these helps reduce bias? (a) test on many groups (b) copy old unfair choices (c) skip testing (d) ignore complaints
25. 25.✨ Generative or not: making up a story? (a) sorts or predicts (b) makes something new
26. 26.🏷️ 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
27. 27.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
28. 28.Which of these is a prediction? (a) naming a new fruit photo (b) labelled fruit photos (c) past weather records (d) recorded spoken words
29. 29.📦 What happens during training? (a) it learns patterns (b) it charges up (c) it prints labels (d) it takes photos
30. 30.True or false: a weather app guessing tomorrow’s rain is AI recommending something. (a) True (b) False
31. 31.🏷️ 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
32. 32.True or false: translating a sentence into Hindi only needs a simple fixed rule. (a) True (b) False
33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
34. 34.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
35. 35.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
36. 36.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
37. 37.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
38. 38.True or false: “a cheerful tune for Sports Day” asks for an image. (a) True (b) False
39. 39.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
40. 40.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI

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