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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 882 · 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.🎨 An image generator makes a picture from… (a) a text description (b) a phone number (c) your password (d) the weather
  2. 2.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) print pages (d) charge faster
  3. 3.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  4. 4.True or false: “naming a new leaf” is training data. (a) True (b) False
  5. 5.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) better at its task (d) slower to switch on
  6. 6.🔁 What is the right order? (a) prediction, data, model (b) data, model, prediction (c) model, prediction, data (d) data, prediction, model
  7. 7.🏠 AI or not AI: a doorbell? (a) uses AI (b) not AI
  8. 8.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
  9. 9.✨ Generative or not: unlocking with a face? (a) makes something new (b) sorts or predicts
  10. 10.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
  11. 11.Which of these is good for training a model? (a) only one kind of example (b) labels added at random (c) many varied examples (d) blurry, unclear photos
  12. 12.Which of these describes how AI works? (a) one set rule per case (b) same steps every time (c) never learns from data (d) improves with more data
  13. 13.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
  14. 14.🔍 Which is the odd one out? (a) inventing a recipe (b) drawing a new picture (c) writing a new poem (d) spotting spam
  15. 15.True or false: “follows fixed rules” describes how AI works. (a) False (b) True
  16. 16.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  17. 17.🔍 Which is the odd one out? (a) AI can be wrong (b) AI copies data patterns (c) AI has real feelings (d) AI learns from data
  18. 18.🧐 Fact or myth: “AI has real feelings”? (a) a myth (b) a fact
  19. 19.🛠️ Which does this job need: adding up the marks on a report card? (a) needs AI (learning) (b) a simple rule is enough
  20. 20.🏷️ 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
  21. 21.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
  22. 22.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
  23. 23.True or false: “labels added at random” is bad for training a model. (a) False (b) True
  24. 24.💬 What do we call the request you type to a generative AI? (a) a password (b) a battery (c) a label (d) a prompt
  25. 25.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  26. 26.🏠 AI or not AI: face unlock on a phone? (a) not AI (b) uses AI
  27. 27.True or false: “a summary of chapter 3” asks for text. (a) True (b) False
  28. 28.🤖 AI or a normal program: which one “improves with more data”? (a) a normal program (b) AI
  29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
  30. 30.🔍 Which is the odd one out? (a) writing a new poem (b) unlocking with a face (c) writing quiz questions (d) making up a story
  31. 31.🧮 Is a basic calculator an AI system? (a) yes, it can think (b) yes, it is smart (c) only at night (d) no, it follows rules
  32. 32.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  33. 33.Which of these is not AI? (a) a map predicting traffic (b) an AI chatbot (c) face unlock on a phone (d) a microwave timer
  34. 34.True or false: converting metres into centimetres needs AI that learns from examples. (a) False (b) True
  35. 35.🧐 Fact or myth: “AI can make up facts”? (a) a fact (b) a myth
  36. 36.True or false: “a drawing of a cat on the Moon” asks for text. (a) True (b) False
  37. 37.🤖 Who builds and trains AI systems? (a) nobody at all (b) the weather (c) the Moon (d) people
  38. 38.✨ What does generative AI do? (a) makes new content (b) only stores files (c) charges batteries (d) only adds numbers
  39. 39.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
  40. 40.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias

Answer key

  1. a text description
  2. learn from data
  3. the trained program
  4. False
  5. better at its task
  6. data, model, prediction
  7. not AI
  8. a normal program
  9. sorts or predicts
  10. good for training
  11. many varied examples
  12. improves with more data
  13. good for training
  14. spotting spam
  15. False
  16. training data
  17. AI has real feelings
  18. a myth
  19. a simple rule is enough
  20. spam
  21. training data
  22. one-sided data
  23. True
  24. a prompt
  25. the learned patterns
  26. uses AI
  27. True
  28. AI
  29. not spam
  30. unlocking with a face
  31. no, it follows rules
  32. balanced data
  33. a microwave timer
  34. False
  35. a fact
  36. False
  37. people
  38. makes new content
  39. True
  40. reduces bias

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