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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 160 · 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.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, always (b) no, check it anyway (c) yes, if it is long
  2. 2.🔍 Which is the odd one out? (a) fix wrong labels (b) ask different people (c) ignore complaints (d) balance the data
  3. 3.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
  4. 4.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  5. 5.Which of these is the model? (a) labelled fruit photos (b) 500 labelled leaf photos (c) the learned patterns (d) recorded spoken words
  6. 6.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  7. 7.Which of these describes how AI works? (a) uses rules people wrote (b) follows fixed rules (c) makes a best guess (d) same steps every time
  8. 8.🏠 AI or not AI: a fan regulator? (a) not AI (b) uses AI
  9. 9.🔍 Which is the odd one out? (a) blurry, unclear photos (b) copies of one photo (c) testing on training data (d) clear, sharp examples
  10. 10.True or false: “it sounds very sure” is a real way to check an AI answer. (a) False (b) True
  11. 11.Which of these is generative AI (it makes something new)? (a) unlocking with a face (b) writing a new poem (c) predicting rain (d) turning speech to text
  12. 12.Which of these is training data? (a) recorded spoken words (b) tomorrow’s rain guess (c) typing a new spoken word (d) what training builds
  13. 13.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
  14. 14.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to see if it works (d) to delete its data
  15. 15.Which of these describes how AI works? (a) gives a likely answer (b) does exactly as coded (c) one set rule per case (d) follows fixed rules
  16. 16.🗣️ 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
  17. 17.🧐 Fact or myth: “AI can mix up numbers”? (a) a myth (b) a fact
  18. 18.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
  19. 19.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  20. 20.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
  21. 21.True or false: “the learned patterns” is the model. (a) False (b) True
  22. 22.True or false: “does exactly as coded” describes how AI works. (a) False (b) True
  23. 23.True or false: “handles unseen examples” describes how a normal program works. (a) True (b) False
  24. 24.🏠 AI or not AI: an image generator? (a) not AI (b) uses AI
  25. 25.🧮 Is a basic calculator an AI system? (a) yes, it is smart (b) yes, it can think (c) no, it follows rules (d) only at night
  26. 26.True or false: “AI can make up facts” is a myth about AI. (a) True (b) False
  27. 27.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  28. 28.🎨 This prompt asks a generative AI for: a picture of a castle made of mangoes. What kind of output is that? (a) an image (b) music or sound (c) text
  29. 29.🧐 Fact or myth: “AI learns from data”? (a) a myth (b) a fact
  30. 30.🤖 AI or a normal program: which one “one set rule per case”? (a) a normal program (b) AI
  31. 31.True or false: converting metres into centimetres only needs a simple fixed rule. (a) True (b) False
  32. 32.Which of these describes how a normal program works? (a) spots patterns in data (b) never learns from data (c) learns from examples (d) makes a best guess
  33. 33.True or false: “does exactly as coded” describes how a normal program works. (a) True (b) False
  34. 34.True or false: recognising a friend’s face in photos needs AI that learns from examples. (a) False (b) True
  35. 35.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) only one kind of example (d) examples of every type
  36. 36.True or false: “AI copies data patterns” is a myth about AI. (a) False (b) True
  37. 37.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
  38. 38.🔍 Which is the odd one out? (a) creating a cartoon (b) sorting photos by face (c) composing a new tune (d) making up a story
  39. 39.Which of these is a prediction? (a) 500 labelled leaf photos (b) the trained program (c) past weather records (d) flagging a new email
  40. 40.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI can make up facts (c) AI always checks facts (d) AI copies data patterns

Answer key

  1. no, check it anyway
  2. ignore complaints
  3. good for training
  4. a prediction
  5. the learned patterns
  6. a prediction
  7. makes a best guess
  8. not AI
  9. clear, sharp examples
  10. False
  11. writing a new poem
  12. recorded spoken words
  13. False
  14. to see if it works
  15. gives a likely answer
  16. few child voices in data
  17. a fact
  18. False
  19. balanced data
  20. True
  21. True
  22. False
  23. False
  24. uses AI
  25. no, it follows rules
  26. False
  27. reduces bias
  28. an image
  29. a fact
  30. a normal program
  31. True
  32. never learns from data
  33. True
  34. True
  35. examples of every type
  36. False
  37. False
  38. sorting photos by face
  39. flagging a new email
  40. AI always checks facts

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