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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 809 · 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.🤖 What makes an AI system different from a normal program? (a) it has a screen (b) it learns from examples (c) it uses electricity (d) it is always right
  2. 2.Which of these is a myth about AI? (a) AI copies data patterns (b) AI knows everything (c) AI can make up facts (d) AI can be wrong
  3. 3.Which of these is generative AI (it makes something new)? (a) writing quiz questions (b) predicting rain (c) spotting spam (d) suggesting a video
  4. 4.🔍 Which is the odd one out? (a) check who is missing (b) test on one group only (c) test on many groups (d) add varied examples
  5. 5.🔍 Which is the odd one out? (a) making up a story (b) inventing a recipe (c) suggesting a video (d) drawing a new picture
  6. 6.✨ What does generative AI do? (a) makes new content (b) charges batteries (c) only adds numbers (d) only stores files
  7. 7.💬 What do we call the request you type to a generative AI? (a) a label (b) a password (c) a prompt (d) a battery
  8. 8.🛠️ Does this reduce bias or add to it: add more of the same? (a) adds to bias (b) reduces bias
  9. 9.✨ Generative or not: writing a new poem? (a) makes something new (b) sorts or predicts
  10. 10.Which of these is good for training a model? (a) correct labels (b) copies of one photo (c) blurry, unclear photos (d) testing on training data
  11. 11.Which of these is training data? (a) past weather records (b) typing a new spoken word (c) tomorrow’s rain guess (d) what training builds
  12. 12.Which of these describes how AI works? (a) never learns from data (b) follows fixed rules (c) uses rules people wrote (d) improves with more data
  13. 13.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
  14. 14.📱 What is the AI doing here: turning your spoken words into typed text? (a) recommending (b) generating (c) recognising (d) predicting
  15. 15.True or false: “follows fixed rules” describes how AI works. (a) True (b) False
  16. 16.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
  17. 17.🛠️ Which does this job need: sorting names in A to Z order? (a) needs AI (learning) (b) a simple rule is enough
  18. 18.🧪 Why test a model on NEW examples? (a) to delete its data (b) to change its name (c) to see if it works (d) to make it slower
  19. 19.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  20. 20.True or false: “learns from examples” describes how a normal program works. (a) False (b) True
  21. 21.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) check it on paper (b) never do maths (c) copy it straight away (d) ask it to hurry
  22. 22.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  23. 23.✨ Is everything a generative AI makes true? (a) only on Mondays (b) yes, always (c) no, it can be wrong
  24. 24.True or false: “a soft lullaby melody” asks for an image. (a) False (b) True
  25. 25.🔍 Which is the odd one out? (a) test on one group only (b) ignore complaints (c) add varied examples (d) skip testing
  26. 26.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  27. 27.True or false: telling a cat photo from a dog photo only needs a simple fixed rule. (a) True (b) False
  28. 28.🏠 AI or not AI: an AI chatbot? (a) uses AI (b) not AI
  29. 29.🔍 Which is the odd one out? (a) writing quiz questions (b) unlocking with a face (c) drawing a new picture (d) writing a new poem
  30. 30.⏩ In machine learning, which comes first: typing a new spoken word or old emails marked spam? (a) typing a new spoken word (b) old emails marked spam
  31. 31.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) charge faster (d) print pages
  32. 32.Which of these is AI that sorts, spots or predicts (not generative)? (a) drawing a new picture (b) making up a story (c) creating a cartoon (d) suggesting a video
  33. 33.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) one single photo (d) a list of rules only
  34. 34.Which of these is not AI? (a) an AI chatbot (b) a map predicting traffic (c) a digital watch (d) a spam filter
  35. 35.🧮 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
  36. 36.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
  37. 37.🔁 What is the right order? (a) model, prediction, data (b) data, prediction, model (c) prediction, data, model (d) data, model, prediction
  38. 38.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) new data for testing (d) very few examples
  39. 39.🏠 AI or not AI: a doorbell? (a) uses AI (b) not AI
  40. 40.True or false: “the trained program” is the model. (a) False (b) True

Answer key

  1. it learns from examples
  2. AI knows everything
  3. writing quiz questions
  4. test on one group only
  5. suggesting a video
  6. makes new content
  7. a prompt
  8. adds to bias
  9. makes something new
  10. correct labels
  11. past weather records
  12. improves with more data
  13. True
  14. recognising
  15. False
  16. bias from data
  17. a simple rule is enough
  18. to see if it works
  19. balanced data
  20. False
  21. check it on paper
  22. the model
  23. no, it can be wrong
  24. False
  25. add varied examples
  26. False
  27. False
  28. uses AI
  29. unlocking with a face
  30. old emails marked spam
  31. learn from data
  32. suggesting a video
  33. many labelled photos
  34. a digital watch
  35. no, it follows rules
  36. AI
  37. data, model, prediction
  38. very few examples
  39. not AI
  40. True

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