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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 370 · 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 does this job need: suggesting the next word as you type? (a) needs AI (learning) (b) a simple rule is enough
  2. 2.Which of these uses AI? (a) a torch (b) face unlock on a phone (c) a printed timetable (d) a digital watch
  3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
  4. 4.✅ Is this a real check of an AI answer: it answered quickly? (a) a real check (b) not a real check
  5. 5.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) checking labels twice (d) testing on training data
  6. 6.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to see if it works (d) to make it slower
  7. 7.True or false: “try the sum on paper” is NOT a real way to check an AI answer. (a) False (b) True
  8. 8.True or false: “typing a new spoken word” is training data. (a) True (b) False
  9. 9.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a list of rules only (d) a song about dogs
  10. 10.🎨 This prompt asks a generative AI for: a story about a brave ant. What kind of output is that? (a) music or sound (b) an image (c) text
  11. 11.True or false: “never learns from data” describes how a normal program works. (a) True (b) False
  12. 12.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
  13. 13.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  14. 14.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  15. 15.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
  16. 16.True or false: “very few examples” is good for training a model. (a) False (b) True
  17. 17.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
  18. 18.Which of these is bad for training a model? (a) checking labels twice (b) examples of every type (c) clear, sharp examples (d) very few examples
  19. 19.📅 An AI gives a date for a history event. How can you check? (a) look in your textbook (b) ask it to repeat (c) guess (d) pick a lucky number
  20. 20.🔍 Which is the odd one out? (a) writing quiz questions (b) suggesting a video (c) writing a new poem (d) composing a new tune
  21. 21.🔍 Which is the odd one out? (a) making up a story (b) creating a cartoon (c) inventing a recipe (d) spotting a sick leaf
  22. 22.Which of these adds to bias? (a) test on many groups (b) check who is missing (c) add varied examples (d) add more of the same
  23. 23.True or false: “follows fixed rules” describes how AI works. (a) True (b) False
  24. 24.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) predicting (b) recommending (c) generating (d) recognising
  25. 25.🎨 This prompt asks a generative AI for: five quiz questions on fractions. What kind of output is that? (a) text (b) music or sound (c) an image
  26. 26.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) skip testing (d) check who is missing
  27. 27.🔍 Which is the odd one out? (a) unlocking with a face (b) writing quiz questions (c) sorting photos by face (d) spotting spam
  28. 28.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
  29. 29.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) very few examples (d) clear, sharp examples
  30. 30.🛠️ Which does this job need: finding 10% of a price? (a) needs AI (learning) (b) a simple rule is enough
  31. 31.Which of these is training data? (a) naming a new fruit photo (b) what training builds (c) old emails marked spam (d) flagging a new email
  32. 32.True or false: showing the time on a clock needs AI that learns from examples. (a) False (b) True
  33. 33.True or false: “find a trusted source” is NOT a real way to check an AI answer. (a) False (b) True
  34. 34.True or false: “a cartoon of a dancing elephant” asks for an image. (a) False (b) True
  35. 35.✍️ How does an AI chatbot write its replies? (a) copies one website (b) uses magic (c) predicts likely words (d) asks a person
  36. 36.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing a new poem (b) making up a story (c) spotting spam (d) writing quiz questions
  37. 37.True or false: a shop guessing how many umbrellas will sell is AI recommending something. (a) True (b) False
  38. 38.🤖 What makes an AI system different from a normal program? (a) it learns from examples (b) it is always right (c) it uses electricity (d) it has a screen
  39. 39.🤖 What does AI stand for? (a) actual information (b) artificial intelligence (c) automatic internet (d) app installer
  40. 40.🔍 Which is the odd one out? (a) a microwave timer (b) a stopwatch (c) a kitchen weighing scale (d) a map predicting traffic

Answer key

  1. needs AI (learning)
  2. face unlock on a phone
  3. spam
  4. not a real check
  5. testing on training data
  6. to see if it works
  7. False
  8. False
  9. many labelled photos
  10. text
  11. True
  12. good for training
  13. False
  14. reduces bias
  15. good for training
  16. False
  17. good for training
  18. very few examples
  19. look in your textbook
  20. suggesting a video
  21. spotting a sick leaf
  22. add more of the same
  23. False
  24. generating
  25. text
  26. skip testing
  27. writing quiz questions
  28. a normal program
  29. very few examples
  30. a simple rule is enough
  31. old emails marked spam
  32. False
  33. False
  34. True
  35. predicts likely words
  36. spotting spam
  37. False
  38. it learns from examples
  39. artificial intelligence
  40. a map predicting traffic

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