AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 39 · 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: “handles unseen examples” describes how AI works. (a) False (b) True
2. 2.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
3. 3.🔦 Is a torch with an on/off switch AI? (a) no (b) only if it is bright (c) yes
4. 4.True or false: “match it to the textbook” is a real way to check an AI answer. (a) False (b) True
5. 5.Which of these describes how a normal program works? (a) learns from examples (b) improves with more data (c) same steps every time (d) spots patterns in data
6. 6.True or false: suggesting the next word as you type only needs a simple fixed rule. (a) True (b) False
7. 7.Which of these is generative AI (it makes something new)? (a) writing quiz questions (b) spotting spam (c) spotting a sick leaf (d) predicting rain
8. 8.True or false: “same steps every time” describes how a normal program works. (a) False (b) True
9. 9.🤖 AI or a normal program: which one “one set rule per case”? (a) AI (b) a normal program
10. 10.Which of these is AI that sorts, spots or predicts (not generative)? (a) drafting a letter (b) making up a story (c) writing quiz questions (d) predicting rain
11. 11.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) a list of rules only (d) many labelled photos
12. 12.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
13. 13.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI answers need checking (c) confident means correct (d) AI copies data patterns
14. 14.True or false: “same steps every time” describes how AI works. (a) True (b) False
15. 15.True or false: “makes a best guess” describes how a normal program works. (a) False (b) True
16. 16.💬 What do we call the request you type to a generative AI? (a) a label (b) a battery (c) a password (d) a prompt
17. 17.🛠️ Which does this job need: spotting spam emails by their patterns? (a) needs AI (learning) (b) a simple rule is enough
18. 18.🎨 This prompt asks a generative AI for: a thank-you note to the bus driver. What kind of output is that? (a) music or sound (b) text (c) an image
19. 19.🔁 What is the right order? (a) prediction, data, model (b) data, model, prediction (c) data, prediction, model (d) model, prediction, data
20. 20.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) wrong labels (d) correct labels
21. 21.True or false: an AI chatbot writing a story about a lost kite is AI recommending something. (a) False (b) True
22. 22.🤖 AI or a normal program: which one “follows fixed rules”? (a) AI (b) a normal program
23. 23.Which of these describes how a normal program works? (a) spots patterns in data (b) does exactly as coded (c) gives a likely answer (d) makes a best guess
24. 24.⏩ In machine learning, which comes first: what training builds or 500 labelled leaf photos? (a) what training builds (b) 500 labelled leaf photos
25. 25.🧐 Fact or myth: “AI knows everything”? (a) a fact (b) a myth
26. 26.True or false: “naming a new leaf” is training data. (a) False (b) True
27. 27.Which of these is not AI? (a) a voice assistant (b) a printed timetable (c) video suggestions (d) voice typing
28. 28.Which of these is the model? (a) old emails marked spam (b) the learned patterns (c) recorded spoken words (d) naming a new leaf
29. 29.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
30. 30.🛠️ Which does this job need: turning spoken words into typed text? (a) needs AI (learning) (b) a simple rule is enough
31. 31.Which of these is not AI? (a) face unlock on a phone (b) video suggestions (c) a light switch (d) a map predicting traffic
32. 32.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
33. 33.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
34. 34.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a label error (c) training data (d) a password
35. 35.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
36. 36.🧐 Fact or myth: “AI is never wrong”? (a) a fact (b) a myth
37. 37.🔍 Which is the odd one out? (a) testing on training data (b) new data for testing (c) only one kind of example (d) copies of one photo
38. 38.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
39. 39.✨ What does generative AI do? (a) charges batteries (b) only adds numbers (c) only stores files (d) makes new content
40. 40.True or false: “balance the data” helps reduce bias. (a) True (b) False

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