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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 105 · 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.🔦 Is a torch with an on/off switch AI? (a) only if it is bright (b) yes (c) no
  2. 2.True or false: “same steps every time” describes how AI works. (a) False (b) True
  3. 3.True or false: “gives a likely answer” describes how AI works. (a) False (b) True
  4. 4.🧐 Fact or myth: “AI copies data patterns”? (a) a fact (b) a myth
  5. 5.True or false: “test on one group only” helps reduce bias. (a) False (b) True
  6. 6.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it learns patterns (d) it charges up
  7. 7.Which of these is AI that sorts, spots or predicts (not generative)? (a) inventing a recipe (b) composing a new tune (c) making up a story (d) unlocking with a face
  8. 8.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) labels added at random (d) clear, sharp examples
  9. 9.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
  10. 10.Which of these is the model? (a) typing a new spoken word (b) old emails marked spam (c) flagging a new email (d) the learned patterns
  11. 11.True or false: “AI learns from data” is a myth about AI. (a) True (b) False
  12. 12.🏠 AI or not AI: voice typing? (a) not AI (b) uses AI
  13. 13.🔍 Which is the odd one out? (a) add more of the same (b) copy old unfair choices (c) use one group only (d) ask different people
  14. 14.📱 What is the AI doing here: a music app suggesting a song you may like? (a) recognising (b) recommending (c) predicting (d) generating
  15. 15.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) children speak too fast (d) the phone was new
  16. 16.Which of these is the model? (a) labelled fruit photos (b) tomorrow’s rain guess (c) the trained program (d) naming a new leaf
  17. 17.🔍 Which is the odd one out? (a) very few examples (b) blurry, unclear photos (c) labels added at random (d) correct labels
  18. 18.True or false: “very few examples” is good for training a model. (a) True (b) False
  19. 19.🔍 Which is the odd one out? (a) AI answers need checking (b) AI is never wrong (c) AI can mix up numbers (d) AI copies data patterns
  20. 20.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  21. 21.True or false: an AI chatbot writing a story about a lost kite is AI generating something new. (a) False (b) True
  22. 22.🧐 Fact or myth: “AI has real feelings”? (a) a fact (b) a myth
  23. 23.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  24. 24.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  25. 25.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  26. 26.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  27. 27.📅 An AI gives a date for a history event. How can you check? (a) guess (b) ask it to repeat (c) pick a lucky number (d) look in your textbook
  28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
  29. 29.🏠 AI or not AI: a torch? (a) uses AI (b) not AI
  30. 30.Which of these describes how a normal program works? (a) improves with more data (b) one set rule per case (c) learns from examples (d) handles unseen examples
  31. 31.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) test on one group only (d) check who is missing
  32. 32.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) skip testing (d) balance the data
  33. 33.True or false: “correct labels” is good for training a model. (a) False (b) True
  34. 34.True or false: “examples of every type” is bad for training a model. (a) True (b) False
  35. 35.Which of these is training data? (a) what training builds (b) 500 labelled leaf photos (c) typing a new spoken word (d) naming a new fruit photo
  36. 36.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) a song about dogs (d) many labelled photos
  37. 37.Which of these is a prediction? (a) recorded spoken words (b) labelled fruit photos (c) naming a new leaf (d) 500 labelled leaf photos
  38. 38.True or false: “AI can be wrong” is a fact about AI. (a) True (b) False
  39. 39.True or false: “find a trusted source” is a real way to check an AI answer. (a) False (b) True
  40. 40.Which of these describes how a normal program works? (a) makes a best guess (b) same steps every time (c) learns from examples (d) spots patterns in data

Answer key

  1. no
  2. False
  3. True
  4. a fact
  5. False
  6. it learns patterns
  7. unlocking with a face
  8. labels added at random
  9. AI
  10. the learned patterns
  11. False
  12. uses AI
  13. ask different people
  14. recommending
  15. few child voices in data
  16. the trained program
  17. correct labels
  18. False
  19. AI is never wrong
  20. True
  21. True
  22. a myth
  23. one-sided data
  24. training data
  25. training data
  26. a prediction
  27. look in your textbook
  28. not spam
  29. not AI
  30. one set rule per case
  31. check who is missing
  32. skip testing
  33. True
  34. False
  35. 500 labelled leaf photos
  36. many labelled photos
  37. naming a new leaf
  38. True
  39. True
  40. same steps every time

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