AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 214 · 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 is the odd one out? (a) spotting a sick leaf (b) suggesting a video (c) predicting rain (d) drafting a letter
2. 2.Which of these is the model? (a) typing a new spoken word (b) old emails marked spam (c) what training builds (d) tomorrow’s rain guess
3. 3.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing a new poem (b) spotting spam (c) writing quiz questions (d) drafting a letter
4. 4.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
5. 5.Which of these is training data? (a) naming a new fruit photo (b) what training builds (c) 500 labelled leaf photos (d) the learned patterns
6. 6.🔍 Which is the odd one out? (a) suggesting a video (b) unlocking with a face (c) sorting photos by face (d) writing quiz questions
7. 7.Which of these is good for training a model? (a) clear, sharp examples (b) labels added at random (c) blurry, unclear photos (d) copies of one photo
8. 8.True or false: “the learned patterns” is training data. (a) True (b) False
9. 9.Which of these is a fact about AI? (a) long answers are true (b) AI can be wrong (c) AI knows everything (d) confident means correct
10. 10.🔍 Which is the odd one out? (a) only one kind of example (b) labels added at random (c) new data for testing (d) very few examples
11. 11.🧐 Fact or myth: “AI has real feelings”? (a) a fact (b) a myth
12. 12.Which of these is bad for training a model? (a) photos in many lights (b) new data for testing (c) very few examples (d) correct labels
13. 13.True or false: “check who is missing” helps reduce bias. (a) True (b) False
14. 14.True or false: “AI knows everything” is a fact about AI. (a) False (b) True
15. 15.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
16. 16.🔍 Which is the odd one out? (a) spotting a sick leaf (b) spotting spam (c) composing a new tune (d) reading number plates
17. 17.📺 A video app suggests what to watch next. What is the AI doing? (a) cooking (b) printing (c) recommending (d) charging
18. 18.🔍 Which is the odd one out? (a) a map predicting traffic (b) photos grouped by face (c) voice typing (d) a stopwatch
19. 19.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the AI (b) share it online (c) trust the textbook (d) stop studying
20. 20.🤖 Who builds and trains AI systems? (a) the weather (b) the Moon (c) nobody at all (d) people
21. 21.True or false: “examples of every type” is good for training a model. (a) False (b) True
22. 22.🧐 Fact or myth: “AI can make up facts”? (a) a myth (b) a fact
23. 23.Which of these is generative AI (it makes something new)? (a) sorting photos by face (b) suggesting a video (c) writing quiz questions (d) spotting spam
24. 24.⏩ In machine learning, which comes first: old emails marked spam or flagging a new email? (a) old emails marked spam (b) flagging a new email
25. 25.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing quiz questions (b) inventing a recipe (c) predicting rain (d) composing a new tune
26. 26.Which of these is a prediction? (a) tomorrow’s rain guess (b) past weather records (c) the trained program (d) 500 labelled leaf photos
27. 27.🏷️ 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
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
29. 29.True or false: “spots patterns in data” describes how AI works. (a) False (b) True
30. 30.Which of these is generative AI (it makes something new)? (a) turning speech to text (b) reading number plates (c) predicting rain (d) drafting a letter
31. 31.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
32. 32.Which of these is a prediction? (a) typing a new spoken word (b) recorded spoken words (c) what training builds (d) 500 labelled leaf photos
33. 33.True or false: “it answered quickly” is NOT a real way to check an AI answer. (a) True (b) False
34. 34.Which of these is bad for training a model? (a) new data for testing (b) wrong labels (c) correct labels (d) examples of every type
35. 35.🎨 An image generator makes a picture from… (a) the weather (b) your password (c) a phone number (d) a text description
36. 36.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
37. 37.📚 Usually, more good examples make a model… (a) better at its task (b) slower to switch on (c) change colour (d) forget everything
38. 38.🔍 Which is the odd one out? (a) long answers are true (b) AI learns from data (c) AI always checks facts (d) AI knows everything
39. 39.💬 What do we call the request you type to a generative AI? (a) a battery (b) a prompt (c) a label (d) a password
40. 40.Which of these is a prediction? (a) recorded spoken words (b) naming a new leaf (c) 500 labelled leaf photos (d) what training builds

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