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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 345 · 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.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
  2. 2.🤖 What makes an AI system different from a normal program? (a) it uses electricity (b) it has a screen (c) it learns from examples (d) it is always right
  3. 3.🔍 Which is the odd one out? (a) a light switch (b) photos grouped by face (c) a microwave timer (d) a digital watch
  4. 4.🔍 Which is the odd one out? (a) test on one group only (b) skip testing (c) balance the data (d) copy old unfair choices
  5. 5.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  6. 6.🔦 Is a torch with an on/off switch AI? (a) yes (b) no (c) only if it is bright
  7. 7.True or false: “what training builds” is the model. (a) False (b) True
  8. 8.🔍 Which is the odd one out? (a) new data for testing (b) labels added at random (c) photos in many lights (d) checking labels twice
  9. 9.🛠️ Which does this job need: counting the words in an essay? (a) needs AI (learning) (b) a simple rule is enough
  10. 10.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  11. 11.🤖 AI or a normal program: which one “improves with more data”? (a) AI (b) a normal program
  12. 12.True or false: translating a sentence into Hindi only needs a simple fixed rule. (a) False (b) True
  13. 13.True or false: “ask your teacher” is NOT a real way to check an AI answer. (a) True (b) False
  14. 14.True or false: “does exactly as coded” describes how a normal program works. (a) True (b) False
  15. 15.✅ Is this a real check of an AI answer: find a trusted source? (a) not a real check (b) a real check
  16. 16.🧐 Fact or myth: “AI is never wrong”? (a) a fact (b) a myth
  17. 17.✨ Generative or not: reading number plates? (a) makes something new (b) sorts or predicts
  18. 18.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
  19. 19.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  20. 20.True or false: “AI learns from data” is a fact about AI. (a) False (b) True
  21. 21.🔍 Which is the odd one out? (a) copy old unfair choices (b) test on many groups (c) balance the data (d) ask different people
  22. 22.🧐 Fact or myth: “AI always checks facts”? (a) a fact (b) a myth
  23. 23.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
  24. 24.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  25. 25.Which of these is a myth about AI? (a) AI copies data patterns (b) AI can be wrong (c) AI answers need checking (d) long answers are true
  26. 26.🔍 Which is the odd one out? (a) add more of the same (b) fix wrong labels (c) check who is missing (d) balance the data
  27. 27.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
  28. 28.⏩ In machine learning, which comes first: the learned patterns or naming a new fruit photo? (a) the learned patterns (b) naming a new fruit photo
  29. 29.🛠️ Which does this job need: telling a cat photo from a dog photo? (a) needs AI (learning) (b) a simple rule is enough
  30. 30.Which of these is training data? (a) the learned patterns (b) what training builds (c) past weather records (d) the trained program
  31. 31.📺 A video app suggests what to watch next. What is the AI doing? (a) recommending (b) printing (c) cooking (d) charging
  32. 32.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  33. 33.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) a prediction (c) training data
  34. 34.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
  35. 35.True or false: “what training builds” is training data. (a) True (b) False
  36. 36.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  37. 37.True or false: “skip testing” adds to bias. (a) True (b) False
  38. 38.Which of these is generative AI (it makes something new)? (a) suggesting a video (b) unlocking with a face (c) reading number plates (d) creating a cartoon
  39. 39.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
  40. 40.True or false: “five quiz questions on fractions” asks for text. (a) True (b) False

Answer key

  1. data, model, prediction
  2. it learns from examples
  3. photos grouped by face
  4. balance the data
  5. one-sided data
  6. no
  7. True
  8. labels added at random
  9. a simple rule is enough
  10. reduces bias
  11. AI
  12. False
  13. False
  14. True
  15. a real check
  16. a myth
  17. sorts or predicts
  18. spam
  19. reduces bias
  20. True
  21. copy old unfair choices
  22. a myth
  23. False
  24. training data
  25. long answers are true
  26. add more of the same
  27. adds to bias
  28. the learned patterns
  29. needs AI (learning)
  30. past weather records
  31. recommending
  32. a prediction
  33. the model
  34. bad for training
  35. False
  36. False
  37. True
  38. creating a cartoon
  39. True
  40. True

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