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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 784 · 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: turning spoken words into typed text only needs a simple fixed rule. (a) True (b) False
  2. 2.Which of these is good for training a model? (a) copies of one photo (b) clear, sharp examples (c) testing on training data (d) labels added at random
  3. 3.True or false: “AI can make up facts” is a fact about AI. (a) False (b) True
  4. 4.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  5. 5.🎨 This prompt asks a generative AI for: a poster of a rainforest. What kind of output is that? (a) music or sound (b) an image (c) text
  6. 6.🤖 AI or a normal program: which one “learns from examples”? (a) AI (b) a normal program
  7. 7.🤖 AI or a normal program: which one “one set rule per case”? (a) AI (b) a normal program
  8. 8.📱 What is the AI doing here: an online shop showing “you may also like”? (a) predicting (b) recognising (c) generating (d) recommending
  9. 9.True or false: recognising a bird from its song needs AI that learns from examples. (a) True (b) False
  10. 10.✅ Is this a real check of an AI answer: asking the same AI again? (a) not a real check (b) a real check
  11. 11.✅ Is this a real check of an AI answer: match it to the textbook? (a) a real check (b) not a real check
  12. 12.📱 What is the AI doing here: an AI tool making a brand-new tune? (a) recognising (b) generating (c) recommending (d) predicting
  13. 13.True or false: “labelled fruit photos” is training data. (a) False (b) True
  14. 14.🤖 AI or a normal program: which one “improves with more data”? (a) AI (b) a normal program
  15. 15.Which of these is a prediction? (a) past weather records (b) tomorrow’s rain guess (c) 500 labelled leaf photos (d) the learned patterns
  16. 16.🔍 Which is the odd one out? (a) AI learns from data (b) AI can be wrong (c) AI is never wrong (d) AI can mix up numbers
  17. 17.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
  18. 18.Which of these is generative AI (it makes something new)? (a) predicting rain (b) sorting photos by face (c) unlocking with a face (d) drafting a letter
  19. 19.🏠 AI or not AI: a kitchen weighing scale? (a) uses AI (b) not AI
  20. 20.🤖 What does AI stand for? (a) app installer (b) artificial intelligence (c) actual information (d) automatic internet
  21. 21.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
  22. 22.💬 What do we call the request you type to a generative AI? (a) a label (b) a battery (c) a password (d) a prompt
  23. 23.🤖 Who builds and trains AI systems? (a) the Moon (b) nobody at all (c) people (d) the weather
  24. 24.Which of these is not AI? (a) an image generator (b) a map predicting traffic (c) a spam filter (d) a stopwatch
  25. 25.True or false: a video app suggesting what to watch next is AI recommending something. (a) False (b) True
  26. 26.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
  27. 27.Which of these is generative AI (it makes something new)? (a) suggesting a video (b) spotting spam (c) predicting rain (d) writing a new poem
  28. 28.🎨 This prompt asks a generative AI for: a summary of chapter 3. What kind of output is that? (a) text (b) an image (c) music or sound
  29. 29.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) a prediction (c) training data
  30. 30.True or false: “naming a new leaf” is the model. (a) True (b) False
  31. 31.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
  32. 32.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
  34. 34.Which of these is good for training a model? (a) wrong labels (b) many varied examples (c) blurry, unclear photos (d) only one kind of example
  35. 35.Which of these is a fact about AI? (a) AI copies data patterns (b) AI is never wrong (c) long answers are true (d) AI always checks facts
  36. 36.True or false: “add more of the same” adds to bias. (a) True (b) False
  37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
  38. 38.🛠️ Which does this job need: showing the time on a clock? (a) needs AI (learning) (b) a simple rule is enough
  39. 39.🛠️ Which does this job need: finding 10% of a price? (a) needs AI (learning) (b) a simple rule is enough
  40. 40.True or false: “same steps every time” describes how AI works. (a) False (b) True

Answer key

  1. False
  2. clear, sharp examples
  3. True
  4. what training builds
  5. an image
  6. AI
  7. a normal program
  8. recommending
  9. True
  10. not a real check
  11. a real check
  12. generating
  13. True
  14. AI
  15. tomorrow’s rain guess
  16. AI is never wrong
  17. not spam
  18. drafting a letter
  19. not AI
  20. artificial intelligence
  21. True
  22. a prompt
  23. people
  24. a stopwatch
  25. True
  26. bad for training
  27. writing a new poem
  28. text
  29. a prediction
  30. False
  31. bad for training
  32. past weather records
  33. not spam
  34. many varied examples
  35. AI copies data patterns
  36. True
  37. spam
  38. a simple rule is enough
  39. a simple rule is enough
  40. False

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