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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 696 · 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.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  2. 2.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
  3. 3.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
  4. 4.Which of these is AI that sorts, spots or predicts (not generative)? (a) unlocking with a face (b) composing a new tune (c) writing a new poem (d) creating a cartoon
  5. 5.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
  6. 6.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) sleeping (b) predicting (c) drawing (d) singing
  7. 7.🤔 An AI answer sounds very confident. Does that mean it is right? (a) no, check it anyway (b) yes, always (c) yes, if it is long
  8. 8.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
  9. 9.📦 What happens during training? (a) it charges up (b) it prints labels (c) it takes photos (d) it learns patterns
  10. 10.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  11. 11.🤖 Does an AI system think and feel like a person? (a) yes, it gets sad (b) no, it finds patterns (c) yes, just like us (d) only on weekends
  12. 12.✅ Is this a real check of an AI answer: find a trusted source? (a) a real check (b) not a real check
  13. 13.Which of these describes how a normal program works? (a) uses rules people wrote (b) improves with more data (c) learns from examples (d) spots patterns in data
  14. 14.🛠️ Which does this job need: turning spoken words into typed text? (a) needs AI (learning) (b) a simple rule is enough
  15. 15.✨ Generative or not: predicting rain? (a) sorts or predicts (b) makes something new
  16. 16.⏩ In machine learning, which comes first: tomorrow’s rain guess or old emails marked spam? (a) tomorrow’s rain guess (b) old emails marked spam
  17. 17.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
  18. 18.True or false: “recorded spoken words” is the model. (a) True (b) False
  19. 19.✨ Generative or not: reading number plates? (a) makes something new (b) sorts or predicts
  20. 20.🔍 Which is the odd one out? (a) testing on training data (b) copies of one photo (c) many varied examples (d) only one kind of example
  21. 21.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
  22. 22.🔍 Which is the odd one out? (a) a digital watch (b) a map predicting traffic (c) face unlock on a phone (d) voice typing
  23. 23.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  24. 24.⏩ In machine learning, which comes first: past weather records or what training builds? (a) past weather records (b) what training builds
  25. 25.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) correct labels (d) blurry, unclear photos
  26. 26.Which of these uses AI? (a) a digital watch (b) a map predicting traffic (c) a torch (d) a light switch
  27. 27.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  28. 28.🔍 Which is the odd one out? (a) ignore complaints (b) fix wrong labels (c) test on one group only (d) skip testing
  29. 29.True or false: “skip testing” helps reduce bias. (a) False (b) True
  30. 30.Which of these is good for training a model? (a) only one kind of example (b) correct labels (c) wrong labels (d) labels added at random
  31. 31.True or false: “very few examples” is bad for training a model. (a) False (b) True
  32. 32.🤖 AI or a normal program: which one “handles unseen examples”? (a) AI (b) a normal program
  33. 33.🤖 AI or a normal program: which one “gives a likely answer”? (a) AI (b) a normal program
  34. 34.✨ Is everything a generative AI makes true? (a) only on Mondays (b) yes, always (c) no, it can be wrong
  35. 35.🔍 Which is the odd one out? (a) very few examples (b) copies of one photo (c) clear, sharp examples (d) labels added at random
  36. 36.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
  37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) not spam (b) spam
  38. 38.🤖 AI or a normal program: which one “does exactly as coded”? (a) AI (b) a normal program
  39. 39.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  40. 40.🤖 AI or a normal program: which one “same steps every time”? (a) AI (b) a normal program

Answer key

  1. a prediction
  2. AI
  3. good for training
  4. unlocking with a face
  5. False
  6. predicting
  7. no, check it anyway
  8. False
  9. it learns patterns
  10. adds to bias
  11. no, it finds patterns
  12. a real check
  13. uses rules people wrote
  14. needs AI (learning)
  15. sorts or predicts
  16. old emails marked spam
  17. good for training
  18. False
  19. sorts or predicts
  20. many varied examples
  21. False
  22. a digital watch
  23. reduces bias
  24. past weather records
  25. correct labels
  26. a map predicting traffic
  27. True
  28. fix wrong labels
  29. False
  30. correct labels
  31. True
  32. AI
  33. AI
  34. no, it can be wrong
  35. clear, sharp examples
  36. True
  37. not spam
  38. a normal program
  39. the model
  40. a normal program

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