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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 551 · 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.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  2. 2.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) music or sound (b) an image (c) text
  3. 3.🔍 Which is the odd one out? (a) checking labels twice (b) very few examples (c) only one kind of example (d) testing on training data
  4. 4.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
  5. 5.🧪 Why test a model on NEW examples? (a) to see if it works (b) to make it slower (c) to delete its data (d) to change its name
  6. 6.🔍 Which is the odd one out? (a) AI learns from data (b) AI can make up facts (c) AI knows everything (d) AI answers need checking
  7. 7.🛠️ Which does this job need: ringing the school bell at 9 am? (a) a simple rule is enough (b) needs AI (learning)
  8. 8.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  9. 9.Which of these helps reduce bias? (a) use one group only (b) copy old unfair choices (c) test on many groups (d) add more of the same
  10. 10.True or false: “the learned patterns” is a prediction. (a) False (b) True
  11. 11.🎨 This prompt asks a generative AI for: five quiz questions on fractions. What kind of output is that? (a) music or sound (b) text (c) an image
  12. 12.Which of these is the model? (a) past weather records (b) the learned patterns (c) naming a new leaf (d) 500 labelled leaf photos
  13. 13.🏠 AI or not AI: a kitchen weighing scale? (a) uses AI (b) not AI
  14. 14.✨ Generative or not: spotting spam? (a) sorts or predicts (b) makes something new
  15. 15.Which of these describes how AI works? (a) follows fixed rules (b) handles unseen examples (c) uses rules people wrote (d) does exactly as coded
  16. 16.Which of these adds to bias? (a) balance the data (b) ask different people (c) ignore complaints (d) fix wrong labels
  17. 17.Which of these uses AI? (a) a fan regulator (b) a microwave timer (c) face unlock on a phone (d) a printed timetable
  18. 18.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  19. 19.🔍 Which is the odd one out? (a) very few examples (b) clear, sharp examples (c) checking labels twice (d) examples of every type
  20. 20.Which of these uses AI? (a) an app translating signs (b) a microwave timer (c) a light switch (d) a calculator
  21. 21.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  22. 22.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
  23. 23.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  24. 24.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  25. 25.True or false: “a picture of a castle made of mangoes” asks for text. (a) False (b) True
  26. 26.🔍 Which is the odd one out? (a) many varied examples (b) testing on training data (c) blurry, unclear photos (d) wrong labels
  27. 27.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) training data (c) a prediction
  28. 28.True or false: “a picture of a castle made of mangoes” asks for music or sound. (a) False (b) True
  29. 29.🤖 Who builds and trains AI systems? (a) nobody at all (b) the weather (c) the Moon (d) people
  30. 30.True or false: “makes a best guess” describes how AI works. (a) True (b) False
  31. 31.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
  32. 32.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
  33. 33.Which of these is good for training a model? (a) very few examples (b) clear, sharp examples (c) labels added at random (d) testing on training data
  34. 34.🧐 Fact or myth: “AI learns from data”? (a) a fact (b) a myth
  35. 35.✨ Generative or not: writing a new poem? (a) sorts or predicts (b) makes something new
  36. 36.🏠 AI or not AI: an AI chatbot? (a) uses AI (b) not AI
  37. 37.True or false: “recorded spoken words” is training data. (a) True (b) False
  38. 38.🏷️ 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
  39. 39.🔍 Which is the odd one out? (a) a torch (b) a fan regulator (c) a microwave timer (d) a voice assistant
  40. 40.🛠️ Which does this job need: suggesting the next word as you type? (a) a simple rule is enough (b) needs AI (learning)

Answer key

  1. one-sided data
  2. text
  3. checking labels twice
  4. False
  5. to see if it works
  6. AI knows everything
  7. a simple rule is enough
  8. True
  9. test on many groups
  10. False
  11. text
  12. the learned patterns
  13. not AI
  14. sorts or predicts
  15. handles unseen examples
  16. ignore complaints
  17. face unlock on a phone
  18. False
  19. very few examples
  20. an app translating signs
  21. one-sided data
  22. the model
  23. reduces bias
  24. a prediction
  25. False
  26. many varied examples
  27. training data
  28. False
  29. people
  30. True
  31. bad for training
  32. True
  33. clear, sharp examples
  34. a fact
  35. makes something new
  36. uses AI
  37. True
  38. not spam
  39. a voice assistant
  40. needs AI (learning)

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