AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 483 · 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: “confident means correct” is a fact about AI. (a) True (b) False
2. 2.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
4. 4.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) copy old unfair choices (d) balance the data
5. 5.Which of these is the model? (a) naming a new fruit photo (b) past weather records (c) tomorrow’s rain guess (d) the trained program
6. 6.True or false: a map app guessing how long a trip will take is AI predicting something. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) check who is missing (b) use one group only (c) ignore complaints (d) add more of the same
8. 8.🧮 Is a basic calculator an AI system? (a) yes, it can think (b) yes, it is smart (c) no, it follows rules (d) only at night
9. 9.🏠 AI or not AI: a spam filter? (a) uses AI (b) not AI
10. 10.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
11. 11.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
12. 12.🏠 AI or not AI: a printed timetable? (a) not AI (b) uses AI
13. 13.⏩ In machine learning, which comes first: tomorrow’s rain guess or labelled fruit photos? (a) tomorrow’s rain guess (b) labelled fruit photos
14. 14.✨ Generative or not: spotting a sick leaf? (a) makes something new (b) sorts or predicts
15. 15.Which of these is good for training a model? (a) correct labels (b) only one kind of example (c) copies of one photo (d) very few examples
16. 16.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
17. 17.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
18. 18.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
19. 19.True or false: an AI chatbot writing a story about a lost kite is AI recommending something. (a) False (b) True
20. 20.🤖 Who builds and trains AI systems? (a) the weather (b) nobody at all (c) people (d) the Moon
21. 21.Which of these is a prediction? (a) typing a new spoken word (b) old emails marked spam (c) 500 labelled leaf photos (d) what training builds
22. 22.Which of these is bad for training a model? (a) wrong labels (b) many varied examples (c) clear, sharp examples (d) checking labels twice
23. 23.🛠️ Which does this job need: telling a cat photo from a dog photo? (a) a simple rule is enough (b) needs AI (learning)
24. 24.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) copy old unfair choices (d) add varied examples
25. 25.Which of these is AI that sorts, spots or predicts (not generative)? (a) spotting spam (b) writing quiz questions (c) drafting a letter (d) writing a new poem
26. 26.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to change its name (d) to see if it works
27. 27.Which of these is a myth about AI? (a) AI learns from data (b) long answers are true (c) AI can be wrong (d) AI answers need checking
28. 28.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
29. 29.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
30. 30.Which of these is AI that sorts, spots or predicts (not generative)? (a) creating a cartoon (b) composing a new tune (c) making up a story (d) sorting photos by face
31. 31.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
32. 32.🏠 AI or not AI: a map predicting traffic? (a) uses AI (b) not AI
33. 33.Which of these helps reduce bias? (a) skip testing (b) balance the data (c) copy old unfair choices (d) add more of the same
34. 34.🏠 AI or not AI: a digital watch? (a) not AI (b) uses AI
35. 35.True or false: suggesting the next word as you type only needs a simple fixed rule. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) test on many groups (b) fix wrong labels (c) check who is missing (d) copy old unfair choices
37. 37.✅ Is this a real check of an AI answer: ask your teacher? (a) a real check (b) not a real check
38. 38.True or false: “asking the same AI again” is NOT a real way to check an AI answer. (a) False (b) True
39. 39.🎨 This prompt asks a generative AI for: a cartoon of a dancing elephant. What kind of output is that? (a) text (b) an image (c) music or sound
40. 40.Which of these uses AI? (a) a fan regulator (b) a microwave timer (c) a printed timetable (d) a spam filter

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