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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 224 · 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.🧐 Fact or myth: “AI always checks facts”? (a) a myth (b) a fact
  2. 2.🧮 Is a basic calculator an AI system? (a) no, it follows rules (b) yes, it can think (c) only at night (d) yes, it is smart
  3. 3.Which of these describes how AI works? (a) same steps every time (b) does exactly as coded (c) handles unseen examples (d) never learns from data
  4. 4.Which of these is a myth about AI? (a) AI answers need checking (b) AI knows everything (c) AI can mix up numbers (d) AI can be wrong
  5. 5.🔍 Which is the odd one out? (a) skip testing (b) test on many groups (c) balance the data (d) ask different people
  6. 6.🧐 Fact or myth: “AI knows everything”? (a) a myth (b) a fact
  7. 7.🛠️ Which does this job need: turning spoken words into typed text? (a) a simple rule is enough (b) needs AI (learning)
  8. 8.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
  9. 9.Which of these is not AI? (a) face unlock on a phone (b) a light switch (c) a voice assistant (d) an AI chatbot
  10. 10.🔍 Which is the odd one out? (a) face unlock on a phone (b) an app translating signs (c) a calculator (d) a voice assistant
  11. 11.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
  12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
  13. 13.Which of these describes how a normal program works? (a) learns from examples (b) improves with more data (c) one set rule per case (d) gives a likely answer
  14. 14.🏠 AI or not AI: a stopwatch? (a) not AI (b) uses AI
  15. 15.🏠 AI or not AI: a spam filter? (a) not AI (b) uses AI
  16. 16.Which of these is generative AI (it makes something new)? (a) unlocking with a face (b) sorting photos by face (c) turning speech to text (d) inventing a recipe
  17. 17.Which of these is generative AI (it makes something new)? (a) sorting photos by face (b) drafting a letter (c) spotting spam (d) spotting a sick leaf
  18. 18.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  19. 19.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  20. 20.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
  21. 21.🔍 Which is the odd one out? (a) check who is missing (b) test on one group only (c) copy old unfair choices (d) ignore complaints
  22. 22.🔍 Which is the odd one out? (a) making up a story (b) writing a new poem (c) drawing a new picture (d) spotting spam
  23. 23.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  24. 24.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) not spam (b) spam
  25. 25.True or false: reading messy handwriting needs AI that learns from examples. (a) True (b) False
  26. 26.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
  27. 27.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) photos in many lights (d) labels added at random
  28. 28.Which of these is AI that sorts, spots or predicts (not generative)? (a) creating a cartoon (b) unlocking with a face (c) drawing a new picture (d) inventing a recipe
  29. 29.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, if it is long (b) no, check it anyway (c) yes, always
  30. 30.🎨 This prompt asks a generative AI for: a cheerful tune for Sports Day. What kind of output is that? (a) an image (b) music or sound (c) text
  31. 31.True or false: “labelled fruit photos” is training data. (a) False (b) True
  32. 32.Which of these is generative AI (it makes something new)? (a) unlocking with a face (b) drawing a new picture (c) sorting photos by face (d) spotting a sick leaf
  33. 33.🛠️ Which does this job need: switching on a street light at 6 pm? (a) a simple rule is enough (b) needs AI (learning)
  34. 34.True or false: a shop guessing how many umbrellas will sell is AI recognising something. (a) False (b) True
  35. 35.Which of these helps reduce bias? (a) test on one group only (b) check who is missing (c) add more of the same (d) use one group only
  36. 36.🔍 Which is the odd one out? (a) checking labels twice (b) very few examples (c) many varied examples (d) photos in many lights
  37. 37.True or false: “AI always checks facts” is a fact about AI. (a) False (b) True
  38. 38.🔍 Which is the odd one out? (a) spotting a sick leaf (b) composing a new tune (c) unlocking with a face (d) sorting photos by face
  39. 39.✅ Is this a real check of an AI answer: match it to the textbook? (a) not a real check (b) a real check
  40. 40.True or false: “test on many groups” helps reduce bias. (a) True (b) False

Answer key

  1. a myth
  2. no, it follows rules
  3. handles unseen examples
  4. AI knows everything
  5. skip testing
  6. a myth
  7. needs AI (learning)
  8. a normal program
  9. a light switch
  10. a calculator
  11. makes something new
  12. not spam
  13. one set rule per case
  14. not AI
  15. uses AI
  16. inventing a recipe
  17. drafting a letter
  18. one-sided data
  19. a prediction
  20. good for training
  21. check who is missing
  22. spotting spam
  23. a prediction
  24. not spam
  25. True
  26. False
  27. labels added at random
  28. unlocking with a face
  29. no, check it anyway
  30. music or sound
  31. True
  32. drawing a new picture
  33. a simple rule is enough
  34. False
  35. check who is missing
  36. very few examples
  37. False
  38. composing a new tune
  39. a real check
  40. True

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