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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 749 · 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.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  2. 2.Which of these is not AI? (a) a voice assistant (b) an image generator (c) a spam filter (d) a printed timetable
  3. 3.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) the model (c) a prediction
  4. 4.Which of these describes how a normal program works? (a) uses rules people wrote (b) spots patterns in data (c) gives a likely answer (d) learns from examples
  5. 5.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) fix wrong labels (d) add more of the same
  6. 6.✨ Generative or not: spotting a sick leaf? (a) makes something new (b) sorts or predicts
  7. 7.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
  8. 8.🔍 Which is the odd one out? (a) clear, sharp examples (b) blurry, unclear photos (c) examples of every type (d) checking labels twice
  9. 9.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) only one kind of example (d) many varied examples
  10. 10.Which of these is training data? (a) 500 labelled leaf photos (b) typing a new spoken word (c) naming a new fruit photo (d) what training builds
  11. 11.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) data, model, prediction (d) prediction, data, model
  12. 12.True or false: “balance the data” adds to bias. (a) True (b) False
  13. 13.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing quiz questions (b) composing a new tune (c) sorting photos by face (d) writing a new poem
  14. 14.✅ Is this a real check of an AI answer: try the sum on paper? (a) a real check (b) not a real check
  15. 15.✨ Generative or not: drafting a letter? (a) sorts or predicts (b) makes something new
  16. 16.🧐 Fact or myth: “AI copies data patterns”? (a) a myth (b) a fact
  17. 17.🎨 This prompt asks a generative AI for: five quiz questions on fractions. What kind of output is that? (a) an image (b) music or sound (c) text
  18. 18.🤖 What does AI stand for? (a) actual information (b) automatic internet (c) artificial intelligence (d) app installer
  19. 19.✅ Is this a real check of an AI answer: asking the same AI again? (a) not a real check (b) a real check
  20. 20.🔍 Which is the odd one out? (a) sorting photos by face (b) inventing a recipe (c) spotting a sick leaf (d) reading number plates
  21. 21.Which of these is training data? (a) the learned patterns (b) old emails marked spam (c) flagging a new email (d) what training builds
  22. 22.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  23. 23.True or false: “only one kind of example” is good for training a model. (a) False (b) True
  24. 24.Which of these adds to bias? (a) test on one group only (b) check who is missing (c) test on many groups (d) ask different people
  25. 25.True or false: “a story about a brave ant” asks for music or sound. (a) True (b) False
  26. 26.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
  27. 27.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) False (b) True
  28. 28.True or false: a car camera reading a speed sign is AI recognising something. (a) False (b) True
  29. 29.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
  30. 30.✨ Generative or not: spotting spam? (a) sorts or predicts (b) makes something new
  31. 31.True or false: “a summary of chapter 3” asks for text. (a) True (b) False
  32. 32.True or false: “AI answers need checking” is a myth about AI. (a) False (b) True
  33. 33.🔍 Which is the odd one out? (a) a light switch (b) a digital watch (c) a map predicting traffic (d) a kitchen weighing scale
  34. 34.True or false: an AI chatbot writing a poem about rain is AI recognising something. (a) False (b) True
  35. 35.True or false: “it sounds very sure” is NOT a real way to check an AI answer. (a) True (b) False
  36. 36.True or false: “write a poem about the monsoon” asks for text. (a) False (b) True
  37. 37.True or false: “never learns from data” describes how a normal program works. (a) False (b) True
  38. 38.Which of these is a prediction? (a) naming a new leaf (b) old emails marked spam (c) the trained program (d) what training builds
  39. 39.🧐 Fact or myth: “AI learns from data”? (a) a fact (b) a myth
  40. 40.True or false: “recorded spoken words” is training data. (a) False (b) True

Answer key

  1. reduces bias
  2. a printed timetable
  3. training data
  4. uses rules people wrote
  5. add more of the same
  6. sorts or predicts
  7. makes something new
  8. blurry, unclear photos
  9. many varied examples
  10. 500 labelled leaf photos
  11. data, model, prediction
  12. False
  13. sorting photos by face
  14. a real check
  15. makes something new
  16. a fact
  17. text
  18. artificial intelligence
  19. not a real check
  20. inventing a recipe
  21. old emails marked spam
  22. True
  23. False
  24. test on one group only
  25. False
  26. False
  27. False
  28. True
  29. good for training
  30. sorts or predicts
  31. True
  32. False
  33. a map predicting traffic
  34. False
  35. True
  36. True
  37. True
  38. naming a new leaf
  39. a fact
  40. True

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