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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 840 · 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: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  2. 2.🎨 This prompt asks a generative AI for: a story about a brave ant. What kind of output is that? (a) an image (b) music or sound (c) text
  3. 3.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
  4. 4.🔍 Which is the odd one out? (a) AI copies data patterns (b) AI is never wrong (c) AI can be wrong (d) AI learns from data
  5. 5.True or false: recognising a bird from its song only needs a simple fixed rule. (a) True (b) False
  6. 6.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to see if it works (d) to delete its data
  7. 7.Which of these is the model? (a) flagging a new email (b) recorded spoken words (c) the learned patterns (d) past weather records
  8. 8.Which of these describes how a normal program works? (a) gives a likely answer (b) makes a best guess (c) does exactly as coded (d) handles unseen examples
  9. 9.Which of these describes how a normal program works? (a) gives a likely answer (b) spots patterns in data (c) follows fixed rules (d) improves with more data
  10. 10.Which of these is a prediction? (a) the learned patterns (b) naming a new fruit photo (c) old emails marked spam (d) what training builds
  11. 11.🛠️ Which does this job need: suggesting the next word as you type? (a) a simple rule is enough (b) needs AI (learning)
  12. 12.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  13. 13.🏠 AI or not AI: an image generator? (a) not AI (b) uses AI
  14. 14.💬 What do we call the request you type to a generative AI? (a) a label (b) a battery (c) a prompt (d) a password
  15. 15.🤖 What makes an AI system different from a normal program? (a) it is always right (b) it learns from examples (c) it has a screen (d) it uses electricity
  16. 16.Which of these is a fact about AI? (a) AI is never wrong (b) AI has real feelings (c) confident means correct (d) AI answers need checking
  17. 17.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  18. 18.True or false: “find a trusted source” is a real way to check an AI answer. (a) True (b) False
  19. 19.🎨 This prompt asks a generative AI for: a soft lullaby melody. What kind of output is that? (a) text (b) an image (c) music or sound
  20. 20.📺 A video app suggests what to watch next. What is the AI doing? (a) printing (b) charging (c) cooking (d) recommending
  21. 21.🏠 AI or not AI: a microwave timer? (a) uses AI (b) not AI
  22. 22.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) its colour (d) the weather
  23. 23.True or false: “a logo idea for the eco club” asks for an image. (a) True (b) False
  24. 24.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
  25. 25.Which of these is training data? (a) what training builds (b) the trained program (c) typing a new spoken word (d) labelled fruit photos
  26. 26.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) sleeping (b) predicting (c) drawing (d) singing
  27. 27.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  28. 28.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  29. 29.True or false: “AI can make up facts” is a myth about AI. (a) True (b) False
  30. 30.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) check who is missing (d) skip testing
  31. 31.True or false: “photos in many lights” is good for training a model. (a) True (b) False
  32. 32.True or false: “AI learns from data” is a myth about AI. (a) True (b) False
  33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
  34. 34.Which of these is training data? (a) naming a new leaf (b) 500 labelled leaf photos (c) flagging a new email (d) the trained program
  35. 35.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  36. 36.🌍 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 AI (d) trust the textbook
  37. 37.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
  38. 38.🧐 Fact or myth: “AI always checks facts”? (a) a myth (b) a fact
  39. 39.True or false: “a summary of chapter 3” asks for an image. (a) False (b) True
  40. 40.🔍 Which is the odd one out? (a) copies of one photo (b) correct labels (c) only one kind of example (d) blurry, unclear photos

Answer key

  1. True
  2. text
  3. makes something new
  4. AI is never wrong
  5. False
  6. to see if it works
  7. the learned patterns
  8. does exactly as coded
  9. follows fixed rules
  10. naming a new fruit photo
  11. needs AI (learning)
  12. reduces bias
  13. uses AI
  14. a prompt
  15. it learns from examples
  16. AI answers need checking
  17. a prediction
  18. True
  19. music or sound
  20. recommending
  21. not AI
  22. its training data
  23. True
  24. False
  25. labelled fruit photos
  26. predicting
  27. balanced data
  28. training data
  29. False
  30. skip testing
  31. True
  32. False
  33. not spam
  34. 500 labelled leaf photos
  35. False
  36. trust the textbook
  37. adds to bias
  38. a myth
  39. False
  40. correct labels

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