AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 400 · 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.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
2. 2.Which of these is not AI? (a) voice typing (b) a voice assistant (c) a doorbell (d) a map predicting traffic
3. 3.True or false: “the learned patterns” is training data. (a) False (b) True
4. 4.Which of these is a myth about AI? (a) AI knows everything (b) AI copies data patterns (c) AI can make up facts (d) AI answers need checking
5. 5.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
6. 6.Which of these is not AI? (a) a printed timetable (b) face unlock on a phone (c) video suggestions (d) a map predicting traffic
7. 7.🌍 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
8. 8.True or false: ringing the school bell at 9 am needs AI that learns from examples. (a) True (b) False
9. 9.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
10. 10.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
11. 11.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
12. 12.🔍 Which is the odd one out? (a) new data for testing (b) correct labels (c) many varied examples (d) blurry, unclear photos
13. 13.🎨 This prompt asks a generative AI for: a soft lullaby melody. What kind of output is that? (a) an image (b) text (c) music or sound
14. 14.🔍 Which is the odd one out? (a) photos in many lights (b) checking labels twice (c) copies of one photo (d) many varied examples
15. 15.Which of these helps reduce bias? (a) add varied examples (b) skip testing (c) add more of the same (d) copy old unfair choices
16. 16.True or false: showing the time on a clock only needs a simple fixed rule. (a) True (b) False
17. 17.Which of these is AI that sorts, spots or predicts (not generative)? (a) making up a story (b) drawing a new picture (c) spotting spam (d) inventing a recipe
18. 18.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
19. 19.🛠️ Which does this job need: recognising a bird from its song? (a) needs AI (learning) (b) a simple rule is enough
20. 20.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
21. 21.🛠️ Which does this job need: turning spoken words into typed text? (a) a simple rule is enough (b) needs AI (learning)
22. 22.True or false: a video app suggesting what to watch next is AI predicting something. (a) False (b) True
23. 23.🤖 Who builds and trains AI systems? (a) people (b) the weather (c) the Moon (d) nobody at all
24. 24.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
25. 25.📚 An AI chatbot names a book that does not exist. This is called… (a) a password (b) a backup (c) a summary (d) a hallucination
26. 26.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
27. 27.True or false: “learns from examples” describes how AI works. (a) True (b) False
28. 28.Which of these is the model? (a) recorded spoken words (b) what training builds (c) naming a new leaf (d) past weather records
29. 29.🏷️ 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
30. 30.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) a broken screen (c) a strong battery (d) bias from data
31. 31.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) new data for testing (d) very few examples
32. 32.✨ Generative or not: making up a story? (a) makes something new (b) sorts or predicts
33. 33.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
34. 34.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
35. 35.True or false: a book app suggesting a story like your last one is AI recommending something. (a) True (b) False
36. 36.🧐 Fact or myth: “AI learns from data”? (a) a myth (b) a fact
37. 37.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) predicting (b) drawing (c) singing (d) sleeping
38. 38.🛠️ Which does this job need: suggesting the next word as you type? (a) a simple rule is enough (b) needs AI (learning)
39. 39.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) one single photo (d) a list of rules only
40. 40.🔍 Which is the odd one out? (a) only one kind of example (b) examples of every type (c) copies of one photo (d) wrong labels

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