AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 556 · 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.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
2. 2.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
3. 3.✅ Is this a real check of an AI answer: try the sum on paper? (a) not a real check (b) a real check
4. 4.True or false: “match it to the textbook” is NOT a real way to check an AI answer. (a) True (b) False
5. 5.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) new data for testing (d) photos in many lights
6. 6.True or false: “spots patterns in data” describes how a normal program works. (a) True (b) False
7. 7.🤖 AI or a normal program: which one “uses rules people wrote”? (a) a normal program (b) AI
8. 8.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) change colour (d) better at its task
9. 9.True or false: a shop guessing how many umbrellas will sell is AI predicting something. (a) False (b) True
10. 10.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) copy old unfair choices (d) check who is missing
11. 11.Which of these is AI that sorts, spots or predicts (not generative)? (a) composing a new tune (b) writing quiz questions (c) creating a cartoon (d) spotting spam
12. 12.✅ Is this a real check of an AI answer: find a trusted source? (a) not a real check (b) a real check
13. 13.Which of these is good for training a model? (a) very few examples (b) only one kind of example (c) labels added at random (d) new data for testing
14. 14.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
15. 15.🛠️ Which does this job need: recognising a bird from its song? (a) a simple rule is enough (b) needs AI (learning)
16. 16.🧮 Which of these is NOT AI? (a) face unlock (b) voice typing (c) a basic calculator (d) a spam filter
17. 17.✅ Is this a real check of an AI answer: ask your teacher? (a) not a real check (b) a real check
18. 18.True or false: an AI tool making a brand-new tune is AI predicting something. (a) True (b) False
19. 19.Which of these is bad for training a model? (a) checking labels twice (b) photos in many lights (c) very few examples (d) clear, sharp examples
20. 20.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
21. 21.🏠 AI or not AI: video suggestions? (a) uses AI (b) not AI
22. 22.🤖 Who builds and trains AI systems? (a) nobody at all (b) the Moon (c) people (d) the weather
23. 23.✅ Is this a real check of an AI answer: it sounds very sure? (a) not a real check (b) a real check
24. 24.✍️ How does an AI chatbot write its replies? (a) predicts likely words (b) asks a person (c) uses magic (d) copies one website
25. 25.Which of these is generative AI (it makes something new)? (a) predicting rain (b) spotting spam (c) creating a cartoon (d) suggesting a video
26. 26.Which of these describes how AI works? (a) never learns from data (b) one set rule per case (c) handles unseen examples (d) follows fixed rules
27. 27.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) ignoring mistakes (d) one group only
28. 28.Which of these uses AI? (a) a microwave timer (b) an image generator (c) a torch (d) a digital watch
29. 29.Which of these is training data? (a) naming a new fruit photo (b) flagging a new email (c) past weather records (d) the learned patterns
30. 30.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
31. 31.📱 What is the AI doing here: an online shop showing “you may also like”? (a) predicting (b) generating (c) recognising (d) recommending
32. 32.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) a list of rules only (d) one single photo
33. 33.True or false: finding 10% of a price needs AI that learns from examples. (a) True (b) False
34. 34.True or false: “AI copies data patterns” is a fact about AI. (a) True (b) False
35. 35.True or false: “naming a new leaf” is the model. (a) True (b) False
36. 36.✨ Is everything a generative AI makes true? (a) yes, always (b) only on Mondays (c) no, it can be wrong
37. 37.True or false: “AI can make up facts” is a fact about AI. (a) True (b) False
38. 38.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
39. 39.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the right answer tag (d) the font size
40. 40.True or false: “AI can mix up numbers” is a myth about AI. (a) False (b) True

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