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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 32 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
  2. 2.Which of these describes how a normal program works? (a) learns from examples (b) does exactly as coded (c) spots patterns in data (d) makes a best guess
  3. 3.True or false: “AI can be wrong” is a myth about AI. (a) True (b) False
  4. 4.Which of these adds to bias? (a) check who is missing (b) fix wrong labels (c) test on one group only (d) test on many groups
  5. 5.🤖 AI or a normal program: which one “follows fixed rules”? (a) AI (b) a normal program
  6. 6.Which of these is bad for training a model? (a) examples of every type (b) clear, sharp examples (c) new data for testing (d) only one kind of example
  7. 7.🔍 Which is the odd one out? (a) AI copies data patterns (b) confident means correct (c) AI can make up facts (d) AI can mix up numbers
  8. 8.✨ Generative or not: writing a new poem? (a) sorts or predicts (b) makes something new
  9. 9.🧐 Fact or myth: “AI can make up facts”? (a) a myth (b) a fact
  10. 10.True or false: “the learned patterns” is a prediction. (a) True (b) False
  11. 11.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  12. 12.🏠 AI or not AI: a map predicting traffic? (a) not AI (b) uses AI
  13. 13.True or false: “examples of every type” is bad for training a model. (a) True (b) False
  14. 14.Which of these is a myth about AI? (a) AI can make up facts (b) AI has real feelings (c) AI answers need checking (d) AI can be wrong
  15. 15.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
  16. 16.🧐 Fact or myth: “AI learns from data”? (a) a myth (b) a fact
  17. 17.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) drawing (b) predicting (c) singing (d) sleeping
  18. 18.True or false: ringing the school bell at 9 am needs AI that learns from examples. (a) True (b) False
  19. 19.Which of these describes how AI works? (a) follows fixed rules (b) learns from examples (c) does exactly as coded (d) uses rules people wrote
  20. 20.True or false: “add more of the same” adds to bias. (a) False (b) True
  21. 21.🤖 Who builds and trains AI systems? (a) people (b) nobody at all (c) the weather (d) the Moon
  22. 22.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) True (b) False
  23. 23.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
  24. 24.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  25. 25.True or false: “many varied examples” is bad for training a model. (a) False (b) True
  26. 26.True or false: “add varied examples” helps reduce bias. (a) False (b) True
  27. 27.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) text (b) an image (c) music or sound
  28. 28.💬 What do we call the request you type to a generative AI? (a) a password (b) a battery (c) a prompt (d) a label
  29. 29.📚 Usually, more good examples make a model… (a) forget everything (b) better at its task (c) slower to switch on (d) change colour
  30. 30.🛠️ Which does this job need: recognising a friend’s face in photos? (a) needs AI (learning) (b) a simple rule is enough
  31. 31.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) predicting (b) recommending (c) generating (d) recognising
  32. 32.🤖 What makes an AI system different from a normal program? (a) it has a screen (b) it uses electricity (c) it learns from examples (d) it is always right
  33. 33.True or false: “improves with more data” describes how a normal program works. (a) True (b) False
  34. 34.Which of these is a fact about AI? (a) AI can make up facts (b) confident means correct (c) AI always checks facts (d) AI is never wrong
  35. 35.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a prediction (d) a password
  36. 36.True or false: “check who is missing” adds to bias. (a) True (b) False
  37. 37.Which of these is bad for training a model? (a) many varied examples (b) photos in many lights (c) checking labels twice (d) wrong labels
  38. 38.True or false: sorting names in A to Z order only needs a simple fixed rule. (a) True (b) False
  39. 39.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) examples of every type (d) copies of one photo
  40. 40.🧐 Fact or myth: “AI always checks facts”? (a) a myth (b) a fact

Answer key

  1. spam
  2. does exactly as coded
  3. False
  4. test on one group only
  5. a normal program
  6. only one kind of example
  7. confident means correct
  8. makes something new
  9. a fact
  10. False
  11. False
  12. uses AI
  13. False
  14. AI has real feelings
  15. makes something new
  16. a fact
  17. predicting
  18. False
  19. learns from examples
  20. True
  21. people
  22. True
  23. bad for training
  24. one-sided data
  25. False
  26. True
  27. text
  28. a prompt
  29. better at its task
  30. needs AI (learning)
  31. predicting
  32. it learns from examples
  33. False
  34. AI can make up facts
  35. a prediction
  36. False
  37. wrong labels
  38. True
  39. copies of one photo
  40. a myth

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