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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 517 · 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.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  2. 2.🛠️ Which does this job need: spotting spam emails by their patterns? (a) a simple rule is enough (b) needs AI (learning)
  3. 3.Which of these is a fact about AI? (a) AI is never wrong (b) AI knows everything (c) AI learns from data (d) AI has real feelings
  4. 4.🧐 Fact or myth: “AI can make up facts”? (a) a myth (b) a fact
  5. 5.🧐 Fact or myth: “AI has real feelings”? (a) a myth (b) a fact
  6. 6.Which of these is generative AI (it makes something new)? (a) making up a story (b) sorting photos by face (c) suggesting a video (d) reading number plates
  7. 7.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
  8. 8.🤖 Does an AI system think and feel like a person? (a) only on weekends (b) yes, just like us (c) yes, it gets sad (d) no, it finds patterns
  9. 9.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) check who is missing (d) add varied examples
  10. 10.✨ Generative or not: inventing a recipe? (a) makes something new (b) sorts or predicts
  11. 11.True or false: “the learned patterns” is a prediction. (a) True (b) False
  12. 12.🛠️ Which does this job need: translating a sentence into Hindi? (a) needs AI (learning) (b) a simple rule is enough
  13. 13.🧪 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
  14. 14.Which of these describes how AI works? (a) same steps every time (b) handles unseen examples (c) never learns from data (d) follows fixed rules
  15. 15.Which of these uses AI? (a) a torch (b) a printed timetable (c) a digital watch (d) a map predicting traffic
  16. 16.🔍 Which is the odd one out? (a) new data for testing (b) labels added at random (c) many varied examples (d) photos in many lights
  17. 17.Which of these adds to bias? (a) check who is missing (b) add varied examples (c) test on many groups (d) test on one group only
  18. 18.True or false: “naming a new fruit photo” is the model. (a) False (b) True
  19. 19.🔦 Is a torch with an on/off switch AI? (a) yes (b) only if it is bright (c) no
  20. 20.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
  21. 21.Which of these is a prediction? (a) what training builds (b) recorded spoken words (c) typing a new spoken word (d) 500 labelled leaf photos
  22. 22.🛠️ Which does this job need: adding up the marks on a report card? (a) needs AI (learning) (b) a simple rule is enough
  23. 23.🌍 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
  24. 24.🎨 This prompt asks a generative AI for: a picture of a castle made of mangoes. What kind of output is that? (a) text (b) music or sound (c) an image
  25. 25.🏠 AI or not AI: voice typing? (a) uses AI (b) not AI
  26. 26.True or false: “it uses big words” is NOT a real way to check an AI answer. (a) False (b) True
  27. 27.True or false: a keyboard guessing your next word is AI recommending something. (a) True (b) False
  28. 28.✨ Generative or not: drafting a letter? (a) sorts or predicts (b) makes something new
  29. 29.🏠 AI or not AI: a spam filter? (a) uses AI (b) not AI
  30. 30.Which of these is the model? (a) old emails marked spam (b) tomorrow’s rain guess (c) what training builds (d) typing a new spoken word
  31. 31.🔍 Which is the odd one out? (a) wrong labels (b) clear, sharp examples (c) blurry, unclear photos (d) only one kind of example
  32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
  33. 33.Which of these describes how AI works? (a) uses rules people wrote (b) makes a best guess (c) never learns from data (d) one set rule per case
  34. 34.Which of these is AI that sorts, spots or predicts (not generative)? (a) spotting a sick leaf (b) composing a new tune (c) writing quiz questions (d) writing a new poem
  35. 35.True or false: ringing the school bell at 9 am needs AI that learns from examples. (a) False (b) True
  36. 36.Which of these is training data? (a) 500 labelled leaf photos (b) tomorrow’s rain guess (c) naming a new fruit photo (d) typing a new spoken word
  37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
  38. 38.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
  39. 39.🤖 What does AI stand for? (a) actual information (b) automatic internet (c) app installer (d) artificial intelligence
  40. 40.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) the phone was new (d) few child voices in data

Answer key

  1. False
  2. needs AI (learning)
  3. AI learns from data
  4. a fact
  5. a myth
  6. making up a story
  7. good for training
  8. no, it finds patterns
  9. use one group only
  10. makes something new
  11. False
  12. needs AI (learning)
  13. to see if it works
  14. handles unseen examples
  15. a map predicting traffic
  16. labels added at random
  17. test on one group only
  18. False
  19. no
  20. True
  21. typing a new spoken word
  22. a simple rule is enough
  23. trust the textbook
  24. an image
  25. uses AI
  26. True
  27. False
  28. makes something new
  29. uses AI
  30. what training builds
  31. clear, sharp examples
  32. not spam
  33. makes a best guess
  34. spotting a sick leaf
  35. False
  36. 500 labelled leaf photos
  37. not spam
  38. spam
  39. artificial intelligence
  40. few child voices in data

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