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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 965 · 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.⏩ In machine learning, which comes first: tomorrow’s rain guess or labelled fruit photos? (a) tomorrow’s rain guess (b) labelled fruit photos
  2. 2.True or false: “redo the maths yourself” is NOT a real way to check an AI answer. (a) True (b) False
  3. 3.Which of these is training data? (a) what training builds (b) naming a new leaf (c) past weather records (d) flagging a new email
  4. 4.True or false: sorting names in A to Z order needs AI that learns from examples. (a) True (b) False
  5. 5.✅ Is this a real check of an AI answer: match it to the textbook? (a) a real check (b) not a real check
  6. 6.True or false: “does exactly as coded” describes how AI works. (a) False (b) True
  7. 7.🤖 What makes an AI system different from a normal program? (a) it uses electricity (b) it learns from examples (c) it has a screen (d) it is always right
  8. 8.🧮 Which of these is NOT AI? (a) a basic calculator (b) face unlock (c) a spam filter (d) voice typing
  9. 9.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
  10. 10.🧐 Fact or myth: “AI copies data patterns”? (a) a myth (b) a fact
  11. 11.Which of these describes how AI works? (a) does exactly as coded (b) uses rules people wrote (c) spots patterns in data (d) one set rule per case
  12. 12.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) False (b) True
  13. 13.True or false: “it is long and detailed” is NOT a real way to check an AI answer. (a) False (b) True
  14. 14.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) False (b) True
  15. 15.True or false: “AI always checks facts” is a fact about AI. (a) False (b) True
  16. 16.True or false: “ignore complaints” adds to bias. (a) False (b) True
  17. 17.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) only one kind of example (d) clear, sharp examples
  18. 18.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  19. 19.True or false: “uses rules people wrote” describes how AI works. (a) False (b) True
  20. 20.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  21. 21.📅 An AI gives a date for a history event. How can you check? (a) guess (b) ask it to repeat (c) pick a lucky number (d) look in your textbook
  22. 22.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  23. 23.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
  24. 24.Which of these describes how a normal program works? (a) improves with more data (b) spots patterns in data (c) uses rules people wrote (d) gives a likely answer
  25. 25.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) forget everything (d) better at its task
  26. 26.True or false: “AI knows everything” is a fact about AI. (a) True (b) False
  27. 27.🤖 AI or a normal program: which one “learns from examples”? (a) AI (b) a normal program
  28. 28.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
  29. 29.🔍 Which is the odd one out? (a) a printed timetable (b) a kitchen weighing scale (c) an AI chatbot (d) a stopwatch
  30. 30.Which of these is good for training a model? (a) new data for testing (b) labels added at random (c) copies of one photo (d) blurry, unclear photos
  31. 31.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) a prediction (c) training data
  32. 32.🏠 AI or not AI: a stopwatch? (a) uses AI (b) not AI
  33. 33.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  34. 34.True or false: “examples of every type” is good for training a model. (a) False (b) True
  35. 35.🔍 Which is the odd one out? (a) fix wrong labels (b) ignore complaints (c) check who is missing (d) balance the data
  36. 36.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
  37. 37.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
  38. 38.True or false: “labelled fruit photos” is training data. (a) False (b) True
  39. 39.🛠️ Which does this job need: switching on a street light at 6 pm? (a) a simple rule is enough (b) needs AI (learning)
  40. 40.🔍 Which is the odd one out? (a) examples of every type (b) blurry, unclear photos (c) copies of one photo (d) labels added at random

Answer key

  1. labelled fruit photos
  2. False
  3. past weather records
  4. False
  5. a real check
  6. False
  7. it learns from examples
  8. a basic calculator
  9. False
  10. a fact
  11. spots patterns in data
  12. True
  13. True
  14. False
  15. False
  16. True
  17. only one kind of example
  18. the model
  19. False
  20. one-sided data
  21. look in your textbook
  22. training data
  23. good for training
  24. uses rules people wrote
  25. better at its task
  26. False
  27. AI
  28. needs AI (learning)
  29. an AI chatbot
  30. new data for testing
  31. a prediction
  32. not AI
  33. one-sided data
  34. True
  35. ignore complaints
  36. reduces bias
  37. a normal program
  38. True
  39. a simple rule is enough
  40. examples of every type

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