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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 963 · 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.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) ask different people (d) fix wrong labels
  2. 2.🧐 Fact or myth: “AI can mix up numbers”? (a) a myth (b) a fact
  3. 3.True or false: “does exactly as coded” describes how AI works. (a) True (b) False
  4. 4.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) checking labels twice (d) blurry, unclear photos
  5. 5.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) training data (c) the model
  6. 6.🔍 Which is the odd one out? (a) ignore complaints (b) balance the data (c) add more of the same (d) skip testing
  7. 7.True or false: “follows fixed rules” describes how a normal program works. (a) False (b) True
  8. 8.🔍 Which is the odd one out? (a) a light switch (b) voice typing (c) a doorbell (d) a stopwatch
  9. 9.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) labels added at random (d) clear, sharp examples
  10. 10.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
  11. 11.📱 What is the AI doing here: a camera app naming the flower you point at? (a) generating (b) recognising (c) predicting (d) recommending
  12. 12.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
  13. 13.Which of these is a prediction? (a) the learned patterns (b) old emails marked spam (c) past weather records (d) typing a new spoken word
  14. 14.🧐 Fact or myth: “AI is never wrong”? (a) a myth (b) a fact
  15. 15.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
  16. 16.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  17. 17.🔍 Which is the odd one out? (a) copies of one photo (b) very few examples (c) only one kind of example (d) examples of every type
  18. 18.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  19. 19.🛠️ Which does this job need: translating a sentence into Hindi? (a) a simple rule is enough (b) needs AI (learning)
  20. 20.✅ Is this a real check of an AI answer: see if the book exists? (a) a real check (b) not a real check
  21. 21.🏠 AI or not AI: a spam filter? (a) not AI (b) uses AI
  22. 22.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
  23. 23.Which of these is a prediction? (a) 500 labelled leaf photos (b) naming a new fruit photo (c) recorded spoken words (d) the trained program
  24. 24.True or false: “follows fixed rules” describes how AI works. (a) False (b) True
  25. 25.Which of these is a fact about AI? (a) AI has real feelings (b) AI can be wrong (c) long answers are true (d) AI knows everything
  26. 26.🧮 Which of these is NOT AI? (a) a spam filter (b) a basic calculator (c) face unlock (d) voice typing
  27. 27.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  28. 28.📱 What is the AI doing here: a car camera reading a speed sign? (a) generating (b) recognising (c) predicting (d) recommending
  29. 29.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) a list of rules only (d) one single photo
  30. 30.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  31. 31.💬 What do we call the request you type to a generative AI? (a) a battery (b) a label (c) a password (d) a prompt
  32. 32.🤖 Who builds and trains AI systems? (a) nobody at all (b) people (c) the Moon (d) the weather
  33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
  34. 34.True or false: “improves with more data” describes how AI works. (a) False (b) True
  35. 35.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
  36. 36.True or false: “makes a best guess” describes how AI works. (a) False (b) True
  37. 37.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
  38. 38.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  39. 39.🔦 Is a torch with an on/off switch AI? (a) yes (b) no (c) only if it is bright
  40. 40.True or false: “a poster of a rainforest” asks for text. (a) False (b) True

Answer key

  1. test on one group only
  2. a fact
  3. False
  4. blurry, unclear photos
  5. a prediction
  6. balance the data
  7. True
  8. voice typing
  9. clear, sharp examples
  10. good for training
  11. recognising
  12. good for training
  13. typing a new spoken word
  14. a myth
  15. bad for training
  16. past weather records
  17. examples of every type
  18. True
  19. needs AI (learning)
  20. a real check
  21. uses AI
  22. AI
  23. naming a new fruit photo
  24. False
  25. AI can be wrong
  26. a basic calculator
  27. True
  28. recognising
  29. many labelled photos
  30. training data
  31. a prompt
  32. people
  33. spam
  34. True
  35. a normal program
  36. True
  37. True
  38. adds to bias
  39. no
  40. False

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