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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 719 · 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.🔍 Which is the odd one out? (a) writing a new poem (b) drawing a new picture (c) creating a cartoon (d) predicting rain
  2. 2.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  3. 3.🔍 Which is the odd one out? (a) face unlock on a phone (b) video suggestions (c) a calculator (d) photos grouped by face
  4. 4.🛠️ Which does this job need: recognising a bird from its song? (a) needs AI (learning) (b) a simple rule is enough
  5. 5.✅ Is this a real check of an AI answer: try the sum on paper? (a) a real check (b) not a real check
  6. 6.Which of these describes how AI works? (a) one set rule per case (b) same steps every time (c) follows fixed rules (d) gives a likely answer
  7. 7.🧮 Is a basic calculator an AI system? (a) only at night (b) yes, it can think (c) yes, it is smart (d) no, it follows rules
  8. 8.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to make it slower (d) to delete its data
  9. 9.🧐 Fact or myth: “AI has real feelings”? (a) a myth (b) a fact
  10. 10.🔍 Which is the odd one out? (a) confident means correct (b) AI is never wrong (c) AI has real feelings (d) AI learns from data
  11. 11.✨ Generative or not: drafting a letter? (a) makes something new (b) sorts or predicts
  12. 12.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  13. 13.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  14. 14.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
  15. 15.🧐 Fact or myth: “AI answers need checking”? (a) a myth (b) a fact
  16. 16.True or false: a leaf app trained only on summer leaves is balanced data (fairer for everyone). (a) True (b) False
  17. 17.True or false: “never learns from data” describes how a normal program works. (a) False (b) True
  18. 18.Which of these is good for training a model? (a) labels added at random (b) only one kind of example (c) testing on training data (d) examples of every type
  19. 19.Which of these is not AI? (a) face unlock on a phone (b) a calculator (c) voice typing (d) an image generator
  20. 20.🏠 AI or not AI: a spam filter? (a) not AI (b) uses AI
  21. 21.Which of these is not AI? (a) face unlock on a phone (b) a printed timetable (c) a voice assistant (d) photos grouped by face
  22. 22.True or false: “makes a best guess” describes how AI works. (a) False (b) True
  23. 23.True or false: translating a sentence into Hindi needs AI that learns from examples. (a) True (b) False
  24. 24.🎨 This prompt asks a generative AI for: a summary of chapter 3. What kind of output is that? (a) an image (b) text (c) music or sound
  25. 25.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
  26. 26.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) True (b) False
  27. 27.Which of these is bad for training a model? (a) checking labels twice (b) very few examples (c) examples of every type (d) many varied examples
  28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
  29. 29.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
  30. 30.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
  31. 31.Which of these is a myth about AI? (a) AI answers need checking (b) AI learns from data (c) AI knows everything (d) AI can be wrong
  32. 32.🔍 Which is the odd one out? (a) face unlock on a phone (b) voice typing (c) photos grouped by face (d) a torch
  33. 33.✨ Generative or not: making up a story? (a) makes something new (b) sorts or predicts
  34. 34.🛠️ Which does this job need: reading messy handwriting? (a) a simple rule is enough (b) needs AI (learning)
  35. 35.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  36. 36.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
  38. 38.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  39. 39.⏩ In machine learning, which comes first: the trained program or typing a new spoken word? (a) the trained program (b) typing a new spoken word
  40. 40.True or false: “AI can be wrong” is a fact about AI. (a) False (b) True

Answer key

  1. predicting rain
  2. True
  3. a calculator
  4. needs AI (learning)
  5. a real check
  6. gives a likely answer
  7. no, it follows rules
  8. to see if it works
  9. a myth
  10. AI learns from data
  11. makes something new
  12. past weather records
  13. a prediction
  14. False
  15. a fact
  16. False
  17. True
  18. examples of every type
  19. a calculator
  20. uses AI
  21. a printed timetable
  22. True
  23. True
  24. text
  25. makes something new
  26. True
  27. very few examples
  28. spam
  29. bad for training
  30. True
  31. AI knows everything
  32. a torch
  33. makes something new
  34. needs AI (learning)
  35. False
  36. a prediction
  37. spam
  38. balanced data
  39. the trained program
  40. True

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