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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 655 · 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.🔍 Which is the odd one out? (a) confident means correct (b) AI knows everything (c) AI has real feelings (d) AI can be wrong
  2. 2.True or false: “check who is missing” adds to bias. (a) False (b) True
  3. 3.Which of these describes how a normal program works? (a) learns from examples (b) one set rule per case (c) makes a best guess (d) handles unseen examples
  4. 4.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
  5. 5.🔍 Which is the odd one out? (a) AI learns from data (b) confident means correct (c) AI copies data patterns (d) AI answers need checking
  6. 6.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
  7. 7.⏩ In machine learning, which comes first: naming a new fruit photo or what training builds? (a) naming a new fruit photo (b) what training builds
  8. 8.🔍 Which is the odd one out? (a) spotting spam (b) turning speech to text (c) creating a cartoon (d) unlocking with a face
  9. 9.📱 What is the AI doing here: a video app suggesting what to watch next? (a) predicting (b) generating (c) recommending (d) recognising
  10. 10.🔍 Which is the odd one out? (a) add more of the same (b) skip testing (c) copy old unfair choices (d) balance the data
  11. 11.Which of these adds to bias? (a) balance the data (b) check who is missing (c) use one group only (d) test on many groups
  12. 12.Which of these is the model? (a) what training builds (b) flagging a new email (c) labelled fruit photos (d) 500 labelled leaf photos
  13. 13.True or false: counting the words in an essay only needs a simple fixed rule. (a) True (b) False
  14. 14.🔍 Which is the odd one out? (a) photos in many lights (b) very few examples (c) examples of every type (d) checking labels twice
  15. 15.✅ Is this a real check of an AI answer: asking the same AI again? (a) a real check (b) not a real check
  16. 16.True or false: “old emails marked spam” is the model. (a) False (b) True
  17. 17.Which of these is a fact about AI? (a) AI is never wrong (b) AI has real feelings (c) AI knows everything (d) AI learns from data
  18. 18.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  19. 19.🧐 Fact or myth: “AI copies data patterns”? (a) a myth (b) a fact
  20. 20.True or false: an AI tool making a brand-new tune is AI predicting something. (a) True (b) False
  21. 21.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
  22. 22.🧐 Fact or myth: “AI can mix up numbers”? (a) a fact (b) a myth
  23. 23.True or false: a keyboard guessing your next word is AI recognising something. (a) False (b) True
  24. 24.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) share it online (b) stop studying (c) trust the textbook (d) trust the AI
  25. 25.True or false: “a drawing of a cat on the Moon” asks for music or sound. (a) False (b) True
  26. 26.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  27. 27.🤖 AI or a normal program: which one “uses rules people wrote”? (a) AI (b) a normal program
  28. 28.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) drawing (b) sleeping (c) predicting (d) singing
  29. 29.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
  30. 30.Which of these is AI that sorts, spots or predicts (not generative)? (a) drafting a letter (b) creating a cartoon (c) composing a new tune (d) sorting photos by face
  31. 31.True or false: “match it to the textbook” is a real way to check an AI answer. (a) True (b) False
  32. 32.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
  33. 33.Which of these adds to bias? (a) balance the data (b) check who is missing (c) ask different people (d) ignore complaints
  34. 34.🛠️ Which does this job need: switching on a street light at 6 pm? (a) needs AI (learning) (b) a simple rule is enough
  35. 35.✅ Is this a real check of an AI answer: it sounds very sure? (a) a real check (b) not a real check
  36. 36.True or false: “gives a likely answer” describes how AI works. (a) False (b) True
  37. 37.True or false: “a poster of a rainforest” asks for an image. (a) False (b) True
  38. 38.True or false: “very few examples” is good for training a model. (a) False (b) True
  39. 39.🏷️ 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
  40. 40.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True

Answer key

  1. AI can be wrong
  2. False
  3. one set rule per case
  4. False
  5. confident means correct
  6. one-sided data
  7. what training builds
  8. creating a cartoon
  9. recommending
  10. balance the data
  11. use one group only
  12. what training builds
  13. True
  14. very few examples
  15. not a real check
  16. False
  17. AI learns from data
  18. training data
  19. a fact
  20. False
  21. bad for training
  22. a fact
  23. False
  24. trust the textbook
  25. False
  26. the learned patterns
  27. a normal program
  28. predicting
  29. adds to bias
  30. sorting photos by face
  31. True
  32. AI
  33. ignore complaints
  34. a simple rule is enough
  35. not a real check
  36. True
  37. True
  38. False
  39. not spam
  40. False

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