AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 902 · 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.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a label error (c) a password (d) a prediction
2. 2.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
3. 3.✍️ How does an AI chatbot write its replies? (a) asks a person (b) copies one website (c) uses magic (d) predicts likely words
4. 4.Which of these describes how AI works? (a) follows fixed rules (b) learns from examples (c) uses rules people wrote (d) same steps every time
5. 5.True or false: “new data for testing” is bad for training a model. (a) False (b) True
6. 6.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
7. 7.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
8. 8.🎨 This prompt asks a generative AI for: a story about a brave ant. What kind of output is that? (a) text (b) an image (c) music or sound
9. 9.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) test on one group only (d) use one group only
10. 10.✅ Is this a real check of an AI answer: redo the maths yourself? (a) not a real check (b) a real check
11. 11.Which of these is training data? (a) naming a new leaf (b) the learned patterns (c) flagging a new email (d) past weather records
12. 12.⏩ In machine learning, which comes first: naming a new fruit photo or 500 labelled leaf photos? (a) naming a new fruit photo (b) 500 labelled leaf photos
13. 13.Which of these is a myth about AI? (a) long answers are true (b) AI can mix up numbers (c) AI can make up facts (d) AI answers need checking
14. 14.🎨 This prompt asks a generative AI for: a soft lullaby melody. What kind of output is that? (a) an image (b) music or sound (c) text
15. 15.Which of these is the model? (a) what training builds (b) labelled fruit photos (c) recorded spoken words (d) flagging a new email
16. 16.🔍 Which is the odd one out? (a) new data for testing (b) copies of one photo (c) many varied examples (d) checking labels twice
17. 17.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) False (b) True
18. 18.Which of these is a myth about AI? (a) AI can be wrong (b) AI knows everything (c) AI learns from data (d) AI can make up facts
19. 19.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
20. 20.True or false: recognising a bird from its song only needs a simple fixed rule. (a) True (b) False
21. 21.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
22. 22.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) very few examples (d) correct labels
24. 24.True or false: “does exactly as coded” describes how a normal program works. (a) True (b) False
25. 25.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI is never wrong (c) AI can be wrong (d) AI can make up facts
26. 26.⏩ In machine learning, which comes first: naming a new fruit photo or what training builds? (a) naming a new fruit photo (b) what training builds
27. 27.🔍 Which is the odd one out? (a) spotting spam (b) predicting rain (c) spotting a sick leaf (d) making up a story
28. 28.🏠 AI or not AI: photos grouped by face? (a) uses AI (b) not AI
29. 29.🔍 Which is the odd one out? (a) checking labels twice (b) blurry, unclear photos (c) wrong labels (d) only one kind of example
30. 30.True or false: “a story about a brave ant” asks for music or sound. (a) True (b) False
31. 31.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
32. 32.📅 An AI gives a date for a history event. How can you check? (a) look in your textbook (b) ask it to repeat (c) guess (d) pick a lucky number
33. 33.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
34. 34.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
35. 35.🤖 AI or a normal program: which one “makes a best guess”? (a) AI (b) a normal program
36. 36.✅ Is this a real check of an AI answer: ask your teacher? (a) a real check (b) not a real check
37. 37.True or false: finding 10% of a price only needs a simple fixed rule. (a) True (b) False
38. 38.True or false: “AI can be wrong” is a fact about AI. (a) True (b) False
39. 39.True or false: “a soft lullaby melody” asks for text. (a) False (b) True
40. 40.True or false: “check who is missing” helps reduce bias. (a) False (b) True

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