AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 773 · 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 learns from data” is a myth about AI. (a) True (b) False
2. 2.🔍 Which is the odd one out? (a) a microwave timer (b) voice typing (c) a light switch (d) a stopwatch
3. 3.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
4. 4.Which of these uses AI? (a) photos grouped by face (b) a printed timetable (c) a torch (d) a kitchen weighing scale
5. 5.📱 What is the AI doing here: a book app suggesting a story like your last one? (a) recommending (b) predicting (c) recognising (d) generating
6. 6.🔍 Which is the odd one out? (a) add varied examples (b) add more of the same (c) test on many groups (d) balance the data
7. 7.Which of these is a fact about AI? (a) AI always checks facts (b) AI knows everything (c) AI is never wrong (d) AI answers need checking
8. 8.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) test on many groups (d) test on one group only
9. 9.🧪 Why test a model on NEW examples? (a) to make it slower (b) to delete its data (c) to change its name (d) to see if it works
10. 10.🔍 Which is the odd one out? (a) composing a new tune (b) spotting spam (c) writing a new poem (d) creating a cartoon
11. 11.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) many labelled photos (c) one single photo (d) a song about dogs
12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
13. 13.Which of these is a myth about AI? (a) AI is never wrong (b) AI learns from data (c) AI copies data patterns (d) AI can be wrong
14. 14.✨ What does generative AI do? (a) charges batteries (b) makes new content (c) only adds numbers (d) only stores files
15. 15.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) charge faster (d) print pages
16. 16.Which of these is good for training a model? (a) labels added at random (b) correct labels (c) testing on training data (d) very few examples
17. 17.📦 What happens during training? (a) it charges up (b) it prints labels (c) it learns patterns (d) it takes photos
18. 18.Which of these is AI that sorts, spots or predicts (not generative)? (a) drawing a new picture (b) drafting a letter (c) composing a new tune (d) suggesting a video
19. 19.Which of these describes how AI works? (a) uses rules people wrote (b) follows fixed rules (c) spots patterns in data (d) does exactly as coded
20. 20.🧐 Fact or myth: “AI copies data patterns”? (a) a fact (b) a myth
21. 21.Which of these is AI that sorts, spots or predicts (not generative)? (a) making up a story (b) writing quiz questions (c) turning speech to text (d) writing a new poem
22. 22.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a prediction (d) a password
23. 23.🔍 Which is the odd one out? (a) many varied examples (b) very few examples (c) correct labels (d) examples of every type
24. 24.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
25. 25.Which of these describes how AI works? (a) one set rule per case (b) learns from examples (c) never learns from data (d) same steps every time
26. 26.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) checking labels twice (d) blurry, unclear photos
27. 27.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will shut down (c) it will be perfect (d) it will turn yellow
28. 28.True or false: “makes a best guess” describes how AI works. (a) False (b) True
29. 29.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
30. 30.True or false: “AI can make up facts” is a myth about AI. (a) True (b) False
31. 31.True or false: “a drum beat for a dance” asks for music or sound. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) video suggestions (b) a digital watch (c) voice typing (d) face unlock on a phone
33. 33.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
34. 34.🔍 Which is the odd one out? (a) testing on training data (b) only one kind of example (c) wrong labels (d) clear, sharp examples
35. 35.📱 What is the AI doing here: turning your spoken words into typed text? (a) predicting (b) recommending (c) generating (d) recognising
36. 36.True or false: “one set rule per case” describes how a normal program works. (a) False (b) True
37. 37.Which of these is training data? (a) the trained program (b) flagging a new email (c) 500 labelled leaf photos (d) tomorrow’s rain guess
38. 38.📺 A video app suggests what to watch next. What is the AI doing? (a) charging (b) printing (c) recommending (d) cooking
39. 39.🎨 This prompt asks a generative AI for: five quiz questions on fractions. What kind of output is that? (a) music or sound (b) text (c) an image
40. 40.True or false: “add more of the same” helps reduce bias. (a) False (b) True

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