AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 371 · 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.⏩ In machine learning, which comes first: labelled fruit photos or the learned patterns? (a) labelled fruit photos (b) the learned patterns
2. 2.True or false: “the trained program” is training data. (a) True (b) False
3. 3.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its colour (c) the weather (d) its training data
4. 4.🔍 Which is the odd one out? (a) add varied examples (b) test on one group only (c) skip testing (d) copy old unfair choices
5. 5.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
6. 6.Which of these is training data? (a) old emails marked spam (b) the learned patterns (c) naming a new fruit photo (d) tomorrow’s rain guess
7. 7.True or false: “match it to the textbook” is NOT a real way to check an AI answer. (a) True (b) False
8. 8.🔍 Which is the odd one out? (a) AI learns from data (b) confident means correct (c) AI has real feelings (d) AI always checks facts
9. 9.🔍 Which is the odd one out? (a) drafting a letter (b) creating a cartoon (c) composing a new tune (d) sorting photos by face
10. 10.🤖 AI or a normal program: which one “gives a likely answer”? (a) AI (b) a normal program
11. 11.True or false: “add more of the same” helps reduce bias. (a) True (b) False
12. 12.Which of these is a myth about AI? (a) AI can be wrong (b) AI has real feelings (c) AI learns from data (d) AI can make up facts
13. 13.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) blurry, unclear photos (d) examples of every type
14. 14.Which of these describes how a normal program works? (a) handles unseen examples (b) spots patterns in data (c) follows fixed rules (d) gives a likely answer
15. 15.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
16. 16.Which of these is AI that sorts, spots or predicts (not generative)? (a) predicting rain (b) drafting a letter (c) drawing a new picture (d) writing a new poem
17. 17.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
18. 18.🔍 Which is the odd one out? (a) skip testing (b) add varied examples (c) check who is missing (d) fix wrong labels
19. 19.✨ Generative or not: composing a new tune? (a) sorts or predicts (b) makes something new
20. 20.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
21. 21.🤖 AI or a normal program: which one “does exactly as coded”? (a) AI (b) a normal program
22. 22.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to delete its data (d) to make it slower
23. 23.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a list of rules only (d) a song about dogs
24. 24.Which of these adds to bias? (a) test on many groups (b) ask different people (c) copy old unfair choices (d) balance the data
25. 25.🔍 Which is the odd one out? (a) long answers are true (b) AI has real feelings (c) AI can make up facts (d) AI always checks facts
26. 26.True or false: spotting spam emails by their patterns needs AI that learns from examples. (a) False (b) True
27. 27.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
28. 28.True or false: “very few examples” is good for training a model. (a) True (b) False
29. 29.🎨 This prompt asks a generative AI for: a picture of a castle made of mangoes. What kind of output is that? (a) text (b) an image (c) music or sound
30. 30.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) prediction, data, model (d) data, prediction, model
31. 31.True or false: adding up the marks on a report card needs AI that learns from examples. (a) False (b) True
32. 32.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
33. 33.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) False (b) True
34. 34.🤖 What makes an AI system different from a normal program? (a) it is always right (b) it uses electricity (c) it learns from examples (d) it has a screen
35. 35.True or false: “a logo idea for the eco club” asks for text. (a) False (b) True
36. 36.True or false: “does exactly as coded” describes how AI works. (a) False (b) True
37. 37.📱 What is the AI doing here: turning your spoken words into typed text? (a) predicting (b) generating (c) recommending (d) recognising
38. 38.🏠 AI or not AI: face unlock on a phone? (a) not AI (b) uses AI
39. 39.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
40. 40.True or false: an AI tool making a brand-new tune is AI generating something new. (a) False (b) True

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