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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 462 · 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: ringing the school bell at 9 am only needs a simple fixed rule. (a) False (b) True
  2. 2.🛠️ Which does this job need: recognising a bird from its song? (a) needs AI (learning) (b) a simple rule is enough
  3. 3.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  4. 4.✍️ How does an AI chatbot write its replies? (a) predicts likely words (b) asks a person (c) copies one website (d) uses magic
  5. 5.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  6. 6.🏷️ 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
  7. 7.🔍 Which is the odd one out? (a) testing on training data (b) clear, sharp examples (c) copies of one photo (d) labels added at random
  8. 8.🔍 Which is the odd one out? (a) inventing a recipe (b) making up a story (c) spotting a sick leaf (d) writing a new poem
  9. 9.✨ Generative or not: writing quiz questions? (a) sorts or predicts (b) makes something new
  10. 10.True or false: “follows fixed rules” describes how a normal program works. (a) True (b) False
  11. 11.True or false: “add more of the same” adds to bias. (a) False (b) True
  12. 12.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) generating (b) predicting (c) recommending (d) recognising
  13. 13.✅ Is this a real check of an AI answer: asking the same AI again? (a) not a real check (b) a real check
  14. 14.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
  15. 15.Which of these is good for training a model? (a) copies of one photo (b) examples of every type (c) only one kind of example (d) labels added at random
  16. 16.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
  17. 17.⚖️ Where does bias in an AI system usually come from? (a) its screen size (b) its training data (c) the weather (d) its colour
  18. 18.True or false: a keyboard guessing your next word is AI recommending something. (a) False (b) True
  19. 19.⏩ In machine learning, which comes first: naming a new fruit photo or 500 labelled leaf photos? (a) naming a new fruit photo (b) 500 labelled leaf photos
  20. 20.Which of these is bad for training a model? (a) checking labels twice (b) labels added at random (c) clear, sharp examples (d) correct labels
  21. 21.🔁 What is the right order? (a) data, prediction, model (b) data, model, prediction (c) prediction, data, model (d) model, prediction, data
  22. 22.✨ Generative or not: creating a cartoon? (a) sorts or predicts (b) makes something new
  23. 23.True or false: reading messy handwriting only needs a simple fixed rule. (a) False (b) True
  24. 24.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  25. 25.✨ Generative or not: predicting rain? (a) makes something new (b) sorts or predicts
  26. 26.True or false: “wrong labels” is bad for training a model. (a) False (b) True
  27. 27.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  28. 28.🧮 Which of these is NOT AI? (a) face unlock (b) a spam filter (c) a basic calculator (d) voice typing
  29. 29.Which of these is training data? (a) flagging a new email (b) past weather records (c) the trained program (d) the learned patterns
  30. 30.True or false: reading messy handwriting needs AI that learns from examples. (a) False (b) True
  31. 31.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
  32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
  33. 33.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
  34. 34.🔍 Which is the odd one out? (a) AI has real feelings (b) AI is never wrong (c) AI knows everything (d) AI can mix up numbers
  35. 35.🏠 AI or not AI: a voice assistant? (a) uses AI (b) not AI
  36. 36.True or false: “does exactly as coded” describes how a normal program works. (a) True (b) False
  37. 37.True or false: a map app guessing how long a trip will take is AI predicting something. (a) True (b) False
  38. 38.True or false: recognising a friend’s face in photos only needs a simple fixed rule. (a) True (b) False
  39. 39.🛠️ Which does this job need: converting metres into centimetres? (a) needs AI (learning) (b) a simple rule is enough
  40. 40.Which of these is a myth about AI? (a) AI answers need checking (b) AI can be wrong (c) confident means correct (d) AI learns from data

Answer key

  1. True
  2. needs AI (learning)
  3. the model
  4. predicts likely words
  5. a prediction
  6. not spam
  7. clear, sharp examples
  8. spotting a sick leaf
  9. makes something new
  10. True
  11. True
  12. generating
  13. not a real check
  14. spam
  15. examples of every type
  16. False
  17. its training data
  18. False
  19. 500 labelled leaf photos
  20. labels added at random
  21. data, model, prediction
  22. makes something new
  23. False
  24. True
  25. sorts or predicts
  26. True
  27. the learned patterns
  28. a basic calculator
  29. past weather records
  30. True
  31. True
  32. spam
  33. False
  34. AI can mix up numbers
  35. uses AI
  36. True
  37. True
  38. False
  39. a simple rule is enough
  40. confident means correct

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