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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 656 · 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.✅ Is this a real check of an AI answer: it answered quickly? (a) not a real check (b) a real check
  2. 2.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
  3. 3.🏠 AI or not AI: voice typing? (a) not AI (b) uses AI
  4. 4.Which of these uses AI? (a) a kitchen weighing scale (b) a torch (c) a microwave timer (d) face unlock on a phone
  5. 5.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
  6. 6.Which of these describes how AI works? (a) uses rules people wrote (b) gives a likely answer (c) one set rule per case (d) follows fixed rules
  7. 7.🏠 AI or not AI: a stopwatch? (a) uses AI (b) not AI
  8. 8.True or false: “learns from examples” describes how AI works. (a) True (b) False
  9. 9.🧐 Fact or myth: “AI can be wrong”? (a) a fact (b) a myth
  10. 10.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a label error (c) a prediction (d) a password
  11. 11.True or false: “redo the maths yourself” is a real way to check an AI answer. (a) False (b) True
  12. 12.Which of these describes how a normal program works? (a) learns from examples (b) handles unseen examples (c) never learns from data (d) gives a likely answer
  13. 13.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
  14. 14.🔍 Which is the odd one out? (a) AI can make up facts (b) AI has real feelings (c) AI knows everything (d) AI is never wrong
  15. 15.✨ Generative or not: spotting a sick leaf? (a) sorts or predicts (b) makes something new
  16. 16.True or false: “one set rule per case” describes how AI works. (a) True (b) False
  17. 17.📚 An AI chatbot names a book that does not exist. This is called… (a) a password (b) a backup (c) a summary (d) a hallucination
  18. 18.Which of these helps reduce bias? (a) test on one group only (b) use one group only (c) ask different people (d) copy old unfair choices
  19. 19.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
  20. 20.🤖 AI or a normal program: which one “does exactly as coded”? (a) AI (b) a normal program
  21. 21.🏠 AI or not AI: a map predicting traffic? (a) uses AI (b) not AI
  22. 22.🤖 AI or a normal program: which one “improves with more data”? (a) a normal program (b) AI
  23. 23.🔍 Which is the odd one out? (a) face unlock on a phone (b) a kitchen weighing scale (c) voice typing (d) a map predicting traffic
  24. 24.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
  25. 25.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  26. 26.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
  27. 27.🤖 AI or a normal program: which one “follows fixed rules”? (a) AI (b) a normal program
  28. 28.True or false: “new data for testing” is good for training a model. (a) True (b) False
  29. 29.Which of these is AI that sorts, spots or predicts (not generative)? (a) inventing a recipe (b) making up a story (c) spotting spam (d) creating a cartoon
  30. 30.Which of these is a myth about AI? (a) AI can be wrong (b) AI learns from data (c) AI answers need checking (d) AI has real feelings
  31. 31.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  32. 32.True or false: “correct labels” is bad for training a model. (a) True (b) False
  33. 33.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  34. 34.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
  35. 35.Which of these uses AI? (a) a spam filter (b) a torch (c) a kitchen weighing scale (d) a light switch
  36. 36.True or false: “flagging a new email” is training data. (a) True (b) False
  37. 37.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  38. 38.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
  39. 39.Which of these describes how a normal program works? (a) same steps every time (b) improves with more data (c) spots patterns in data (d) makes a best guess
  40. 40.True or false: recognising a friend’s face in photos only needs a simple fixed rule. (a) True (b) False

Answer key

  1. not a real check
  2. True
  3. uses AI
  4. face unlock on a phone
  5. good for training
  6. gives a likely answer
  7. not AI
  8. True
  9. a fact
  10. a prediction
  11. True
  12. never learns from data
  13. AI
  14. AI can make up facts
  15. sorts or predicts
  16. False
  17. a hallucination
  18. ask different people
  19. a normal program
  20. a normal program
  21. uses AI
  22. AI
  23. a kitchen weighing scale
  24. bad for training
  25. balanced data
  26. a prediction
  27. a normal program
  28. True
  29. spotting spam
  30. AI has real feelings
  31. a prediction
  32. False
  33. what training builds
  34. bad for training
  35. a spam filter
  36. False
  37. adds to bias
  38. True
  39. same steps every time
  40. False

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