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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 628 · 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.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
  2. 2.🔍 Which is the odd one out? (a) only one kind of example (b) checking labels twice (c) clear, sharp examples (d) many varied examples
  3. 3.True or false: “AI answers need checking” is a fact about AI. (a) True (b) False
  4. 4.🛠️ Which does this job need: turning spoken words into typed text? (a) needs AI (learning) (b) a simple rule is enough
  5. 5.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  6. 6.True or false: “handles unseen examples” describes how AI works. (a) True (b) False
  7. 7.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  8. 8.True or false: “past weather records” is the model. (a) True (b) False
  9. 9.True or false: “a soft lullaby melody” asks for an image. (a) False (b) True
  10. 10.🧐 Fact or myth: “AI answers need checking”? (a) a fact (b) a myth
  11. 11.🔍 Which is the odd one out? (a) video suggestions (b) a digital watch (c) a light switch (d) a kitchen weighing scale
  12. 12.True or false: “AI knows everything” is a myth about AI. (a) True (b) False
  13. 13.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) children speak too fast (d) few child voices in data
  14. 14.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it charges up (d) it learns patterns
  15. 15.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) learn from data (d) clean screens
  16. 16.True or false: “see if the book exists” is NOT a real way to check an AI answer. (a) True (b) False
  17. 17.True or false: “use one group only” helps reduce bias. (a) True (b) False
  18. 18.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  19. 19.✨ Is everything a generative AI makes true? (a) no, it can be wrong (b) yes, always (c) only on Mondays
  20. 20.🏠 AI or not AI: a digital watch? (a) uses AI (b) not AI
  21. 21.True or false: “it uses big words” is a real way to check an AI answer. (a) False (b) True
  22. 22.🏠 AI or not AI: photos grouped by face? (a) uses AI (b) not AI
  23. 23.⏩ In machine learning, which comes first: past weather records or typing a new spoken word? (a) past weather records (b) typing a new spoken word
  24. 24.True or false: “makes a best guess” describes how a normal program works. (a) False (b) True
  25. 25.🔍 Which is the odd one out? (a) AI always checks facts (b) AI can be wrong (c) AI can mix up numbers (d) AI copies data patterns
  26. 26.🔍 Which is the odd one out? (a) new data for testing (b) testing on training data (c) checking labels twice (d) photos in many lights
  27. 27.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  28. 28.🤖 AI or a normal program: which one “improves with more data”? (a) a normal program (b) AI
  29. 29.Which of these is generative AI (it makes something new)? (a) predicting rain (b) turning speech to text (c) drawing a new picture (d) sorting photos by face
  30. 30.🔍 Which is the odd one out? (a) add more of the same (b) add varied examples (c) check who is missing (d) balance the data
  31. 31.True or false: “it has a neat layout” is a real way to check an AI answer. (a) False (b) True
  32. 32.🔍 Which is the odd one out? (a) spotting a sick leaf (b) composing a new tune (c) inventing a recipe (d) drafting a letter
  33. 33.True or false: “testing on training data” is bad for training a model. (a) False (b) True
  34. 34.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  35. 35.Which of these helps reduce bias? (a) skip testing (b) copy old unfair choices (c) test on one group only (d) balance the data
  36. 36.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
  37. 37.Which of these is good for training a model? (a) labels added at random (b) wrong labels (c) very few examples (d) examples of every type
  38. 38.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
  39. 39.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) blurry, unclear photos (d) correct labels
  40. 40.Which of these is training data? (a) tomorrow’s rain guess (b) typing a new spoken word (c) what training builds (d) recorded spoken words

Answer key

  1. bad for training
  2. only one kind of example
  3. True
  4. needs AI (learning)
  5. what training builds
  6. True
  7. what training builds
  8. False
  9. False
  10. a fact
  11. video suggestions
  12. True
  13. few child voices in data
  14. it learns patterns
  15. learn from data
  16. False
  17. False
  18. adds to bias
  19. no, it can be wrong
  20. not AI
  21. False
  22. uses AI
  23. past weather records
  24. False
  25. AI always checks facts
  26. testing on training data
  27. the learned patterns
  28. AI
  29. drawing a new picture
  30. add more of the same
  31. False
  32. spotting a sick leaf
  33. True
  34. the model
  35. balance the data
  36. False
  37. examples of every type
  38. False
  39. blurry, unclear photos
  40. recorded spoken words

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