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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 530 · 40 questions
TalentJR

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.

NameDateTime takenScore ___ / 40
  1. 1.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) True (b) False
  2. 2.True or false: “handles unseen examples” describes how a normal program works. (a) True (b) False
  3. 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) few child voices in data (d) it was a rainy day
  4. 4.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  5. 5.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) add varied examples (d) use one group only
  6. 6.True or false: “makes a best guess” describes how AI works. (a) True (b) False
  7. 7.True or false: “spots patterns in data” describes how AI works. (a) False (b) True
  8. 8.🔍 Which is the odd one out? (a) only one kind of example (b) clear, sharp examples (c) correct labels (d) examples of every type
  9. 9.Which of these describes how a normal program works? (a) learns from examples (b) does exactly as coded (c) gives a likely answer (d) spots patterns in data
  10. 10.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will turn yellow (c) it may get it wrong (d) it will shut down
  11. 11.🛠️ Which does this job need: recognising a bird from its song? (a) needs AI (learning) (b) a simple rule is enough
  12. 12.🔍 Which is the odd one out? (a) AI has real feelings (b) AI knows everything (c) AI always checks facts (d) AI copies data patterns
  13. 13.Which of these is not AI? (a) an app translating signs (b) a digital watch (c) face unlock on a phone (d) voice typing
  14. 14.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) more varied data (d) ignoring mistakes
  15. 15.🔍 Which is the odd one out? (a) AI can mix up numbers (b) AI is never wrong (c) AI can make up facts (d) AI answers need checking
  16. 16.🤖 Who builds and trains AI systems? (a) the Moon (b) people (c) the weather (d) nobody at all
  17. 17.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) fix wrong labels (d) use one group only
  18. 18.Which of these is good for training a model? (a) labels added at random (b) correct labels (c) only one kind of example (d) blurry, unclear photos
  19. 19.🏠 AI or not AI: a digital watch? (a) uses AI (b) not AI
  20. 20.✅ Is this a real check of an AI answer: see if the book exists? (a) a real check (b) not a real check
  21. 21.True or false: “one set rule per case” describes how AI works. (a) False (b) True
  22. 22.Which of these is the model? (a) 500 labelled leaf photos (b) recorded spoken words (c) naming a new fruit photo (d) the learned patterns
  23. 23.True or false: “testing on training data” is good for training a model. (a) True (b) False
  24. 24.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  25. 25.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  26. 26.True or false: “recorded spoken words” is training data. (a) True (b) False
  27. 27.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  28. 28.True or false: “AI learns from data” is a myth about AI. (a) False (b) True
  29. 29.📱 What is the AI doing here: a map app guessing how long a trip will take? (a) recognising (b) generating (c) recommending (d) predicting
  30. 30.🔍 Which is the odd one out? (a) examples of every type (b) many varied examples (c) wrong labels (d) new data for testing
  31. 31.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  32. 32.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) clear, sharp examples (d) blurry, unclear photos
  33. 33.🧐 Fact or myth: “AI copies data patterns”? (a) a myth (b) a fact
  34. 34.True or false: “old emails marked spam” is the model. (a) True (b) False
  35. 35.True or false: “spots patterns in data” describes how a normal program works. (a) False (b) True
  36. 36.True or false: spotting spam emails by their patterns needs AI that learns from examples. (a) True (b) False
  37. 37.True or false: “balance the data” helps reduce bias. (a) True (b) False
  38. 38.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
  39. 39.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  40. 40.Which of these is AI that sorts, spots or predicts (not generative)? (a) inventing a recipe (b) writing quiz questions (c) drawing a new picture (d) predicting rain

Answer key

  1. True
  2. False
  3. few child voices in data
  4. adds to bias
  5. add varied examples
  6. True
  7. True
  8. only one kind of example
  9. does exactly as coded
  10. it may get it wrong
  11. needs AI (learning)
  12. AI copies data patterns
  13. a digital watch
  14. more varied data
  15. AI is never wrong
  16. people
  17. fix wrong labels
  18. correct labels
  19. not AI
  20. a real check
  21. False
  22. the learned patterns
  23. False
  24. a prediction
  25. the model
  26. True
  27. reduces bias
  28. False
  29. predicting
  30. wrong labels
  31. a prediction
  32. blurry, unclear photos
  33. a fact
  34. False
  35. False
  36. True
  37. True
  38. reduces bias
  39. False
  40. predicting rain

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