AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 49 · 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.🎨 This prompt asks a generative AI for: rain sound effects for a play. What kind of output is that? (a) music or sound (b) an image (c) text
2. 2.🎨 This prompt asks a generative AI for: a poster of a rainforest. What kind of output is that? (a) an image (b) text (c) music or sound
3. 3.🧮 Which of these is NOT AI? (a) a spam filter (b) voice typing (c) a basic calculator (d) face unlock
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
5. 5.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
6. 6.True or false: telling a cat photo from a dog photo only needs a simple fixed rule. (a) True (b) False
7. 7.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
8. 8.Which of these is a myth about AI? (a) AI has real feelings (b) AI answers need checking (c) AI can make up facts (d) AI learns from data
9. 9.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) forget everything (d) slower to switch on
10. 10.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
11. 11.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) testing on training data (d) wrong labels
12. 12.⏩ In machine learning, which comes first: what training builds or labelled fruit photos? (a) what training builds (b) labelled fruit photos
13. 13.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
14. 14.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) a list of rules only (d) one single photo
15. 15.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its training data (d) its colour
16. 16.🔍 Which is the odd one out? (a) AI copies data patterns (b) AI has real feelings (c) AI answers need checking (d) AI learns from data
17. 17.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) drawing (b) predicting (c) singing (d) sleeping
18. 18.⏩ 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
19. 19.True or false: finding 10% of a price only needs a simple fixed rule. (a) True (b) False
20. 20.✨ Generative or not: composing a new tune? (a) sorts or predicts (b) makes something new
21. 21.True or false: “the trained program” is the model. (a) True (b) False
22. 22.🏠 AI or not AI: a stopwatch? (a) uses AI (b) not AI
23. 23.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
24. 24.Which of these describes how a normal program works? (a) spots patterns in data (b) makes a best guess (c) improves with more data (d) follows fixed rules
25. 25.True or false: “photos in many lights” is good for training a model. (a) True (b) False
26. 26.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
27. 27.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) children speak too fast (d) few child voices in data
28. 28.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
29. 29.🛠️ Which does this job need: switching on a street light at 6 pm? (a) needs AI (learning) (b) a simple rule is enough
30. 30.⏩ In machine learning, which comes first: past weather records or what training builds? (a) past weather records (b) what training builds
31. 31.True or false: a camera app naming the flower you point at is AI predicting something. (a) False (b) True
32. 32.True or false: “improves with more data” describes how AI works. (a) False (b) True
33. 33.Which of these adds to bias? (a) ask different people (b) balance the data (c) skip testing (d) check who is missing
34. 34.Which of these is bad for training a model? (a) clear, sharp examples (b) new data for testing (c) examples of every type (d) blurry, unclear photos
35. 35.🛠️ Which does this job need: sorting names in A to Z order? (a) a simple rule is enough (b) needs AI (learning)
36. 36.🤖 What makes an AI system different from a normal program? (a) it uses electricity (b) it has a screen (c) it is always right (d) it learns from examples
37. 37.📱 What is the AI doing here: a shop guessing how many umbrellas will sell? (a) recognising (b) generating (c) predicting (d) recommending
38. 38.🔍 Which is the odd one out? (a) drawing a new picture (b) turning speech to text (c) creating a cartoon (d) writing a new poem
39. 39.Which of these is a prediction? (a) 500 labelled leaf photos (b) what training builds (c) old emails marked spam (d) naming a new fruit photo
40. 40.True or false: “fix wrong labels” adds to bias. (a) True (b) False

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