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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 129 · 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 is the AI doing here: a music app suggesting a song you may like? (a) predicting (b) recommending (c) recognising (d) generating
  2. 2.Which of these describes how a normal program works? (a) learns from examples (b) gives a likely answer (c) makes a best guess (d) uses rules people wrote
  3. 3.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the textbook (b) share it online (c) stop studying (d) trust the AI
  4. 4.🔍 Which is the odd one out? (a) a spam filter (b) face unlock on a phone (c) a voice assistant (d) a calculator
  5. 5.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
  6. 6.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  7. 7.🔍 Which is the odd one out? (a) only one kind of example (b) testing on training data (c) photos in many lights (d) labels added at random
  8. 8.🔍 Which is the odd one out? (a) reading number plates (b) creating a cartoon (c) drawing a new picture (d) writing a new poem
  9. 9.🏠 AI or not AI: a voice assistant? (a) not AI (b) uses AI
  10. 10.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) more varied data (d) fewer tests
  11. 11.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) generating (b) predicting (c) recognising (d) recommending
  12. 12.📱 What is the AI doing here: an online shop showing “you may also like”? (a) recognising (b) recommending (c) generating (d) predicting
  13. 13.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will be perfect (d) it will shut down
  14. 14.True or false: “the trained program” is a prediction. (a) True (b) False
  15. 15.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) the right answer tag (d) a sticker on a laptop
  16. 16.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
  17. 17.True or false: “AI always checks facts” is a fact about AI. (a) True (b) False
  18. 18.True or false: sorting names in A to Z order needs AI that learns from examples. (a) True (b) False
  19. 19.True or false: “AI knows everything” is a fact about AI. (a) False (b) True
  20. 20.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
  21. 21.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  22. 22.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI copies data patterns (c) AI has real feelings (d) AI answers need checking
  23. 23.🔍 Which is the odd one out? (a) a torch (b) a light switch (c) a digital watch (d) an image generator
  24. 24.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) training data (d) a password
  25. 25.True or false: “typing a new spoken word” is the model. (a) True (b) False
  26. 26.True or false: “it sounds very sure” is NOT a real way to check an AI answer. (a) True (b) False
  27. 27.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  28. 28.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) False (b) True
  29. 29.✨ What does generative AI do? (a) charges batteries (b) makes new content (c) only stores files (d) only adds numbers
  30. 30.🔍 Which is the odd one out? (a) very few examples (b) correct labels (c) examples of every type (d) many varied examples
  31. 31.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  32. 32.True or false: “naming a new fruit photo” is the model. (a) False (b) True
  33. 33.🧐 Fact or myth: “AI always checks facts”? (a) a myth (b) a fact
  34. 34.True or false: “fix wrong labels” helps reduce bias. (a) False (b) True
  35. 35.💬 What do we call the request you type to a generative AI? (a) a battery (b) a prompt (c) a password (d) a label
  36. 36.True or false: “examples of every type” is good for training a model. (a) False (b) True
  37. 37.True or false: “labelled fruit photos” is the model. (a) True (b) False
  38. 38.Which of these adds to bias? (a) balance the data (b) fix wrong labels (c) test on many groups (d) use one group only
  39. 39.🔍 Which is the odd one out? (a) AI learns from data (b) AI can mix up numbers (c) AI answers need checking (d) AI is never wrong
  40. 40.True or false: “long answers are true” is a myth about AI. (a) False (b) True

Answer key

  1. recommending
  2. uses rules people wrote
  3. trust the textbook
  4. a calculator
  5. False
  6. a prediction
  7. photos in many lights
  8. reading number plates
  9. uses AI
  10. more varied data
  11. predicting
  12. recommending
  13. it may get it wrong
  14. False
  15. the right answer tag
  16. False
  17. False
  18. False
  19. False
  20. old emails marked spam
  21. balanced data
  22. AI has real feelings
  23. an image generator
  24. a prediction
  25. False
  26. True
  27. False
  28. True
  29. makes new content
  30. very few examples
  31. balanced data
  32. False
  33. a myth
  34. True
  35. a prompt
  36. True
  37. False
  38. use one group only
  39. AI is never wrong
  40. True

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