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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 250 · 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.🤖 What makes an AI system different from a normal program? (a) it is always right (b) it has a screen (c) it uses electricity (d) it learns from examples
  2. 2.True or false: “labels added at random” is good for training a model. (a) True (b) False
  3. 3.True or false: “AI has real feelings” is a myth about AI. (a) False (b) True
  4. 4.True or false: “it is long and detailed” is NOT a real way to check an AI answer. (a) True (b) False
  5. 5.True or false: “examples of every type” is good for training a model. (a) False (b) True
  6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
  7. 7.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  8. 8.🔍 Which is the odd one out? (a) test on one group only (b) balance the data (c) test on many groups (d) add varied examples
  9. 9.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  10. 10.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  11. 11.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) a password (d) training data
  12. 12.True or false: “ask different people” helps reduce bias. (a) False (b) True
  13. 13.✨ Generative or not: suggesting a video? (a) makes something new (b) sorts or predicts
  14. 14.🛠️ Which does this job need: switching on a street light at 6 pm? (a) needs AI (learning) (b) a simple rule is enough
  15. 15.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
  16. 16.✨ Generative or not: sorting photos by face? (a) makes something new (b) sorts or predicts
  17. 17.True or false: “test on one group only” helps reduce bias. (a) True (b) False
  18. 18.🎨 This prompt asks a generative AI for: a drum beat for a dance. What kind of output is that? (a) music or sound (b) text (c) an image
  19. 19.🤖 AI or a normal program: which one “handles unseen examples”? (a) AI (b) a normal program
  20. 20.🔍 Which is the odd one out? (a) sorting photos by face (b) drawing a new picture (c) writing quiz questions (d) creating a cartoon
  21. 21.Which of these is a fact about AI? (a) AI has real feelings (b) AI is never wrong (c) confident means correct (d) AI copies data patterns
  22. 22.🔍 Which is the odd one out? (a) photos grouped by face (b) a fan regulator (c) a spam filter (d) a map predicting traffic
  23. 23.Which of these is a prediction? (a) old emails marked spam (b) flagging a new email (c) labelled fruit photos (d) past weather records
  24. 24.📚 Usually, more good examples make a model… (a) forget everything (b) slower to switch on (c) change colour (d) better at its task
  25. 25.✨ Generative or not: predicting rain? (a) sorts or predicts (b) makes something new
  26. 26.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  27. 27.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  28. 28.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
  29. 29.✨ Generative or not: writing a new poem? (a) sorts or predicts (b) makes something new
  30. 30.Which of these is the model? (a) typing a new spoken word (b) the trained program (c) tomorrow’s rain guess (d) past weather records
  31. 31.✅ Is this a real check of an AI answer: it uses big words? (a) not a real check (b) a real check
  32. 32.True or false: a car camera reading a speed sign is AI recognising something. (a) True (b) False
  33. 33.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
  34. 34.True or false: “naming a new leaf” is a prediction. (a) True (b) False
  35. 35.🔍 Which is the odd one out? (a) new data for testing (b) examples of every type (c) testing on training data (d) clear, sharp examples
  36. 36.True or false: “check who is missing” helps reduce bias. (a) True (b) False
  37. 37.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  38. 38.True or false: “AI can mix up numbers” is a fact about AI. (a) False (b) True
  39. 39.✨ Is everything a generative AI makes true? (a) only on Mondays (b) no, it can be wrong (c) yes, always
  40. 40.True or false: “new data for testing” is good for training a model. (a) True (b) False

Answer key

  1. it learns from examples
  2. False
  3. True
  4. True
  5. True
  6. spam
  7. past weather records
  8. test on one group only
  9. one-sided data
  10. False
  11. a prediction
  12. True
  13. sorts or predicts
  14. a simple rule is enough
  15. good for training
  16. sorts or predicts
  17. False
  18. music or sound
  19. AI
  20. sorting photos by face
  21. AI copies data patterns
  22. a fan regulator
  23. flagging a new email
  24. better at its task
  25. sorts or predicts
  26. training data
  27. the model
  28. True
  29. makes something new
  30. the trained program
  31. not a real check
  32. True
  33. True
  34. True
  35. testing on training data
  36. True
  37. training data
  38. True
  39. no, it can be wrong
  40. True

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