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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 126 · 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: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  2. 2.Which of these is a myth about AI? (a) AI copies data patterns (b) AI can mix up numbers (c) AI can make up facts (d) confident means correct
  3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
  4. 4.🏠 AI or not AI: a printed timetable? (a) not AI (b) uses AI
  5. 5.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) labels added at random (d) checking labels twice
  6. 6.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) clean screens (d) learn from data
  7. 7.Which of these is a fact about AI? (a) AI always checks facts (b) AI has real feelings (c) AI knows everything (d) AI answers need checking
  8. 8.🔍 Which is the odd one out? (a) copies of one photo (b) testing on training data (c) wrong labels (d) new data for testing
  9. 9.🤖 AI or a normal program: which one “does exactly as coded”? (a) a normal program (b) AI
  10. 10.Which of these adds to bias? (a) check who is missing (b) ask different people (c) test on many groups (d) ignore complaints
  11. 11.True or false: “it sounds very sure” is NOT a real way to check an AI answer. (a) False (b) True
  12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
  13. 13.🛠️ Which does this job need: telling a cat photo from a dog photo? (a) needs AI (learning) (b) a simple rule is enough
  14. 14.🤖 What makes an AI system different from a normal program? (a) it uses electricity (b) it has a screen (c) it is always right (d) it learns from examples
  15. 15.True or false: a camera app naming the flower you point at is AI recommending something. (a) True (b) False
  16. 16.Which of these is a fact about AI? (a) long answers are true (b) AI is never wrong (c) AI copies data patterns (d) AI always checks facts
  17. 17.✨ Generative or not: unlocking with a face? (a) sorts or predicts (b) makes something new
  18. 18.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) checking labels twice (d) wrong labels
  19. 19.🤖 AI or a normal program: which one “spots patterns in data”? (a) AI (b) a normal program
  20. 20.🎨 This prompt asks a generative AI for: a story about a brave ant. What kind of output is that? (a) an image (b) music or sound (c) text
  21. 21.Which of these is AI that sorts, spots or predicts (not generative)? (a) inventing a recipe (b) turning speech to text (c) making up a story (d) writing quiz questions
  22. 22.True or false: “long answers are true” is a fact about AI. (a) True (b) False
  23. 23.📱 What is the AI doing here: a video app suggesting what to watch next? (a) recognising (b) recommending (c) generating (d) predicting
  24. 24.Which of these describes how a normal program works? (a) gives a likely answer (b) same steps every time (c) learns from examples (d) spots patterns in data
  25. 25.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
  26. 26.🧐 Fact or myth: “AI is never wrong”? (a) a fact (b) a myth
  27. 27.Which of these is the model? (a) flagging a new email (b) the trained program (c) 500 labelled leaf photos (d) tomorrow’s rain guess
  28. 28.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
  29. 29.🔍 Which is the odd one out? (a) ignore complaints (b) ask different people (c) use one group only (d) add more of the same
  30. 30.🎨 This prompt asks a generative AI for: a cartoon of a dancing elephant. What kind of output is that? (a) an image (b) music or sound (c) text
  31. 31.🔍 Which is the odd one out? (a) labels added at random (b) copies of one photo (c) very few examples (d) correct labels
  32. 32.Which of these describes how AI works? (a) uses rules people wrote (b) one set rule per case (c) learns from examples (d) follows fixed rules
  33. 33.✨ What does generative AI do? (a) charges batteries (b) makes new content (c) only stores files (d) only adds numbers
  34. 34.⏩ In machine learning, which comes first: the trained program or naming a new fruit photo? (a) the trained program (b) naming a new fruit photo
  35. 35.🛠️ Which does this job need: ringing the school bell at 9 am? (a) needs AI (learning) (b) a simple rule is enough
  36. 36.True or false: recognising a bird from its song only needs a simple fixed rule. (a) False (b) True
  37. 37.Which of these is the model? (a) recorded spoken words (b) what training builds (c) typing a new spoken word (d) naming a new leaf
  38. 38.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  39. 39.📱 What is the AI doing here: an image generator drawing a robot from a sentence? (a) predicting (b) recommending (c) generating (d) recognising
  40. 40.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True

Answer key

  1. what training builds
  2. confident means correct
  3. spam
  4. not AI
  5. labels added at random
  6. learn from data
  7. AI answers need checking
  8. new data for testing
  9. a normal program
  10. ignore complaints
  11. True
  12. not spam
  13. needs AI (learning)
  14. it learns from examples
  15. False
  16. AI copies data patterns
  17. sorts or predicts
  18. wrong labels
  19. AI
  20. text
  21. turning speech to text
  22. False
  23. recommending
  24. same steps every time
  25. True
  26. a myth
  27. the trained program
  28. a prediction
  29. ask different people
  30. an image
  31. correct labels
  32. learns from examples
  33. makes new content
  34. the trained program
  35. a simple rule is enough
  36. False
  37. what training builds
  38. the learned patterns
  39. generating
  40. True

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