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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 964 · 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: “follows fixed rules” describes how AI works. (a) True (b) False
  2. 2.Which of these describes how AI works? (a) does exactly as coded (b) uses rules people wrote (c) gives a likely answer (d) never learns from data
  3. 3.True or false: “it has a neat layout” is NOT a real way to check an AI answer. (a) True (b) False
  4. 4.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  5. 5.🤖 What makes an AI system different from a normal program? (a) it learns from examples (b) it uses electricity (c) it is always right (d) it has a screen
  6. 6.Which of these is generative AI (it makes something new)? (a) suggesting a video (b) drafting a letter (c) predicting rain (d) turning speech to text
  7. 7.🤖 AI or a normal program: which one “learns from examples”? (a) a normal program (b) AI
  8. 8.Which of these is a prediction? (a) recorded spoken words (b) naming a new leaf (c) 500 labelled leaf photos (d) old emails marked spam
  9. 9.True or false: “AI copies data patterns” is a fact about AI. (a) True (b) False
  10. 10.True or false: recognising a friend’s face in photos only needs a simple fixed rule. (a) True (b) False
  11. 11.True or false: “naming a new leaf” is the model. (a) False (b) True
  12. 12.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) clear, sharp examples (d) only one kind of example
  13. 13.True or false: “see if the book exists” is a real way to check an AI answer. (a) False (b) True
  14. 14.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) wrong labels (d) photos in many lights
  15. 15.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
  16. 16.✨ Is everything a generative AI makes true? (a) yes, always (b) only on Mondays (c) no, it can be wrong
  17. 17.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) clear, sharp examples (d) blurry, unclear photos
  18. 18.Which of these is the model? (a) old emails marked spam (b) naming a new fruit photo (c) flagging a new email (d) the learned patterns
  19. 19.🏠 AI or not AI: a printed timetable? (a) not AI (b) uses AI
  20. 20.True or false: “add more of the same” adds to bias. (a) False (b) True
  21. 21.🧮 Which of these is NOT AI? (a) face unlock (b) voice typing (c) a basic calculator (d) a spam filter
  22. 22.True or false: “improves with more data” describes how a normal program works. (a) False (b) True
  23. 23.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  24. 24.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  25. 25.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
  26. 26.Which of these helps reduce bias? (a) ignore complaints (b) use one group only (c) skip testing (d) check who is missing
  27. 27.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
  28. 28.⏩ In machine learning, which comes first: old emails marked spam or typing a new spoken word? (a) old emails marked spam (b) typing a new spoken word
  29. 29.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  30. 30.🔍 Which is the odd one out? (a) a printed timetable (b) a torch (c) a digital watch (d) an image generator
  31. 31.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
  32. 32.True or false: “check who is missing” adds to bias. (a) False (b) True
  33. 33.Which of these is the model? (a) what training builds (b) old emails marked spam (c) labelled fruit photos (d) recorded spoken words
  34. 34.🎨 This prompt asks a generative AI for: rain sound effects for a play. What kind of output is that? (a) an image (b) text (c) music or sound
  35. 35.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
  36. 36.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
  37. 37.Which of these is bad for training a model? (a) copies of one photo (b) checking labels twice (c) examples of every type (d) correct labels
  38. 38.🔍 Which is the odd one out? (a) confident means correct (b) AI is never wrong (c) long answers are true (d) AI copies data patterns
  39. 39.True or false: “the trained program” is the model. (a) True (b) False
  40. 40.🤖 AI or a normal program: which one “same steps every time”? (a) AI (b) a normal program

Answer key

  1. False
  2. gives a likely answer
  3. True
  4. False
  5. it learns from examples
  6. drafting a letter
  7. AI
  8. naming a new leaf
  9. True
  10. False
  11. False
  12. clear, sharp examples
  13. True
  14. wrong labels
  15. bad for training
  16. no, it can be wrong
  17. blurry, unclear photos
  18. the learned patterns
  19. not AI
  20. True
  21. a basic calculator
  22. False
  23. a prediction
  24. adds to bias
  25. good for training
  26. check who is missing
  27. True
  28. old emails marked spam
  29. a prediction
  30. an image generator
  31. one-sided data
  32. False
  33. what training builds
  34. music or sound
  35. True
  36. makes something new
  37. copies of one photo
  38. AI copies data patterns
  39. True
  40. a normal program

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