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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 805 · 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.🏠 AI or not AI: a light switch? (a) uses AI (b) not AI
  2. 2.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  3. 3.Which of these describes how a normal program works? (a) never learns from data (b) makes a best guess (c) improves with more data (d) learns from examples
  4. 4.True or false: an image generator drawing a robot from a sentence is AI predicting something. (a) True (b) False
  5. 5.🏷️ What is a “label” in machine learning? (a) the font size (b) a sticker on a laptop (c) the right answer tag (d) the price
  6. 6.🤖 AI or a normal program: which one “makes a best guess”? (a) AI (b) a normal program
  7. 7.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) charge faster (d) print pages
  8. 8.🔍 Which is the odd one out? (a) ignore complaints (b) check who is missing (c) fix wrong labels (d) test on many groups
  9. 9.📱 What is the AI doing here: turning your spoken words into typed text? (a) recommending (b) generating (c) recognising (d) predicting
  10. 10.⏩ In machine learning, which comes first: typing a new spoken word or 500 labelled leaf photos? (a) typing a new spoken word (b) 500 labelled leaf photos
  11. 11.Which of these describes how AI works? (a) improves with more data (b) same steps every time (c) uses rules people wrote (d) one set rule per case
  12. 12.Which of these is generative AI (it makes something new)? (a) spotting spam (b) suggesting a video (c) spotting a sick leaf (d) writing a new poem
  13. 13.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) recommending (b) predicting (c) generating (d) recognising
  14. 14.🤖 AI or a normal program: which one “same steps every time”? (a) AI (b) a normal program
  15. 15.True or false: “a cheerful tune for Sports Day” asks for music or sound. (a) True (b) False
  16. 16.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  17. 17.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
  18. 18.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
  19. 19.Which of these describes how AI works? (a) learns from examples (b) uses rules people wrote (c) does exactly as coded (d) never learns from data
  20. 20.🏠 AI or not AI: voice typing? (a) uses AI (b) not AI
  21. 21.Which of these is training data? (a) the learned patterns (b) what training builds (c) labelled fruit photos (d) tomorrow’s rain guess
  22. 22.Which of these is not AI? (a) an AI chatbot (b) face unlock on a phone (c) a map predicting traffic (d) a stopwatch
  23. 23.Which of these is good for training a model? (a) testing on training data (b) wrong labels (c) photos in many lights (d) only one kind of example
  24. 24.🏷️ 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
  25. 25.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  26. 26.True or false: “a summary of chapter 3” asks for an image. (a) True (b) False
  27. 27.True or false: “find a trusted source” is a real way to check an AI answer. (a) False (b) True
  28. 28.True or false: “naming a new leaf” is training data. (a) True (b) False
  29. 29.🧐 Fact or myth: “AI can mix up numbers”? (a) a myth (b) a fact
  30. 30.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
  31. 31.🔍 Which is the odd one out? (a) add varied examples (b) ignore complaints (c) copy old unfair choices (d) use one group only
  32. 32.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  33. 33.📱 What is the AI doing here: a map app guessing how long a trip will take? (a) predicting (b) generating (c) recommending (d) recognising
  34. 34.Which of these is a prediction? (a) 500 labelled leaf photos (b) naming a new leaf (c) what training builds (d) the learned patterns
  35. 35.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  36. 36.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
  37. 37.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  38. 38.🔍 Which is the odd one out? (a) spotting spam (b) spotting a sick leaf (c) drawing a new picture (d) unlocking with a face
  39. 39.🧐 Fact or myth: “AI is never wrong”? (a) a fact (b) a myth
  40. 40.True or false: “old emails marked spam” is a prediction. (a) True (b) False

Answer key

  1. not AI
  2. the learned patterns
  3. never learns from data
  4. False
  5. the right answer tag
  6. AI
  7. learn from data
  8. ignore complaints
  9. recognising
  10. 500 labelled leaf photos
  11. improves with more data
  12. writing a new poem
  13. generating
  14. a normal program
  15. True
  16. balanced data
  17. good for training
  18. needs AI (learning)
  19. learns from examples
  20. uses AI
  21. labelled fruit photos
  22. a stopwatch
  23. photos in many lights
  24. spam
  25. False
  26. False
  27. True
  28. False
  29. a fact
  30. bad for training
  31. add varied examples
  32. True
  33. predicting
  34. naming a new leaf
  35. the model
  36. True
  37. False
  38. drawing a new picture
  39. a myth
  40. False

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