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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 466 · 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.🎨 This prompt asks a generative AI for: a logo idea for the eco club. What kind of output is that? (a) music or sound (b) an image (c) text
  2. 2.✨ Generative or not: sorting photos by face? (a) sorts or predicts (b) makes something new
  3. 3.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  4. 4.🎨 An image generator makes a picture from… (a) your password (b) a text description (c) a phone number (d) the weather
  5. 5.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the textbook (b) trust the AI (c) share it online (d) stop studying
  6. 6.True or false: telling a cat photo from a dog photo needs AI that learns from examples. (a) False (b) True
  7. 7.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) only one kind of example (d) photos in many lights
  8. 8.🔦 Is a torch with an on/off switch AI? (a) no (b) only if it is bright (c) yes
  9. 9.Which of these describes how a normal program works? (a) handles unseen examples (b) spots patterns in data (c) improves with more data (d) does exactly as coded
  10. 10.True or false: “it answered quickly” is NOT a real way to check an AI answer. (a) False (b) True
  11. 11.🔍 Which is the odd one out? (a) a fan regulator (b) a microwave timer (c) a printed timetable (d) an image generator
  12. 12.📅 An AI gives a date for a history event. How can you check? (a) guess (b) pick a lucky number (c) ask it to repeat (d) look in your textbook
  13. 13.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  14. 14.True or false: “handles unseen examples” describes how AI works. (a) True (b) False
  15. 15.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
  16. 16.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
  17. 17.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  18. 18.Which of these is training data? (a) the trained program (b) 500 labelled leaf photos (c) what training builds (d) typing a new spoken word
  19. 19.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
  20. 20.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
  21. 21.True or false: “wrong labels” is good for training a model. (a) False (b) True
  22. 22.💬 What do we call the request you type to a generative AI? (a) a password (b) a battery (c) a prompt (d) a label
  23. 23.Which of these is a myth about AI? (a) AI is never wrong (b) AI answers need checking (c) AI can mix up numbers (d) AI learns from data
  24. 24.Which of these describes how AI works? (a) uses rules people wrote (b) never learns from data (c) makes a best guess (d) same steps every time
  25. 25.True or false: “AI can mix up numbers” is a myth about AI. (a) False (b) True
  26. 26.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) prediction, data, model (d) data, model, prediction
  27. 27.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  28. 28.🔍 Which is the odd one out? (a) a microwave timer (b) a torch (c) an AI chatbot (d) a doorbell
  29. 29.Which of these describes how a normal program works? (a) gives a likely answer (b) never learns from data (c) learns from examples (d) improves with more data
  30. 30.True or false: a music app suggesting a song you may like is AI recommending something. (a) False (b) True
  31. 31.🎨 This prompt asks a generative AI for: a cheerful tune for Sports Day. What kind of output is that? (a) an image (b) text (c) music or sound
  32. 32.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) its colour (d) the weather
  33. 33.🔍 Which is the odd one out? (a) wrong labels (b) clear, sharp examples (c) new data for testing (d) examples of every type
  34. 34.True or false: “copy old unfair choices” adds to bias. (a) True (b) False
  35. 35.🔍 Which is the odd one out? (a) examples of every type (b) correct labels (c) photos in many lights (d) testing on training data
  36. 36.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  37. 37.🔍 Which is the odd one out? (a) predicting rain (b) drafting a letter (c) composing a new tune (d) writing quiz questions
  38. 38.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) a list of rules only (d) many labelled photos
  39. 39.Which of these uses AI? (a) a map predicting traffic (b) a microwave timer (c) a doorbell (d) a digital watch
  40. 40.🏠 AI or not AI: a doorbell? (a) uses AI (b) not AI

Answer key

  1. an image
  2. sorts or predicts
  3. the learned patterns
  4. a text description
  5. trust the textbook
  6. True
  7. only one kind of example
  8. no
  9. does exactly as coded
  10. True
  11. an image generator
  12. look in your textbook
  13. balanced data
  14. True
  15. good for training
  16. False
  17. True
  18. 500 labelled leaf photos
  19. not spam
  20. False
  21. False
  22. a prompt
  23. AI is never wrong
  24. makes a best guess
  25. False
  26. data, model, prediction
  27. balanced data
  28. an AI chatbot
  29. never learns from data
  30. True
  31. music or sound
  32. its training data
  33. wrong labels
  34. True
  35. testing on training data
  36. training data
  37. predicting rain
  38. many labelled photos
  39. a map predicting traffic
  40. not AI

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