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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 679 · 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.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) False (b) True
  2. 2.True or false: an online shop showing “you may also like” is AI generating something new. (a) False (b) True
  3. 3.Which of these uses AI? (a) a kitchen weighing scale (b) a microwave timer (c) a fan regulator (d) an image generator
  4. 4.✅ Is this a real check of an AI answer: see if the book exists? (a) a real check (b) not a real check
  5. 5.True or false: “it sounds very sure” is a real way to check an AI answer. (a) True (b) False
  6. 6.🔍 Which is the odd one out? (a) spotting a sick leaf (b) predicting rain (c) spotting spam (d) inventing a recipe
  7. 7.🔍 Which is the odd one out? (a) suggesting a video (b) drafting a letter (c) unlocking with a face (d) reading number plates
  8. 8.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
  9. 9.True or false: “try the sum on paper” is a real way to check an AI answer. (a) False (b) True
  10. 10.🔍 Which is the odd one out? (a) examples of every type (b) testing on training data (c) copies of one photo (d) wrong labels
  11. 11.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
  12. 12.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the AI (b) trust the textbook (c) share it online (d) stop studying
  13. 13.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) recommending (b) generating (c) predicting (d) recognising
  14. 14.True or false: “never learns from data” describes how AI works. (a) False (b) True
  15. 15.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
  16. 16.Which of these is generative AI (it makes something new)? (a) spotting a sick leaf (b) unlocking with a face (c) reading number plates (d) inventing a recipe
  17. 17.True or false: “learns from examples” describes how AI works. (a) False (b) True
  18. 18.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
  19. 19.True or false: “asking the same AI again” is a real way to check an AI answer. (a) False (b) True
  20. 20.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
  21. 21.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) sleeping (c) drawing (d) predicting
  22. 22.🔍 Which is the odd one out? (a) skip testing (b) copy old unfair choices (c) test on one group only (d) test on many groups
  23. 23.True or false: photos of people of many ages and skin tones is balanced data (fairer for everyone). (a) True (b) False
  24. 24.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) a sticker on a laptop (d) the font size
  25. 25.🎨 This prompt asks a generative AI for: a story about a brave ant. What kind of output is that? (a) music or sound (b) text (c) an image
  26. 26.✨ Is everything a generative AI makes true? (a) only on Mondays (b) no, it can be wrong (c) yes, always
  27. 27.🤖 Who builds and trains AI systems? (a) people (b) the weather (c) the Moon (d) nobody at all
  28. 28.Which of these describes how AI works? (a) gives a likely answer (b) never learns from data (c) same steps every time (d) follows fixed rules
  29. 29.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing quiz questions (b) writing a new poem (c) predicting rain (d) drafting a letter
  30. 30.🤖 What does AI stand for? (a) actual information (b) app installer (c) automatic internet (d) artificial intelligence
  31. 31.True or false: “see if the book exists” is NOT a real way to check an AI answer. (a) True (b) False
  32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
  33. 33.True or false: turning spoken words into typed text needs AI that learns from examples. (a) True (b) False
  34. 34.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
  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.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) the model (c) training data
  37. 37.⏩ In machine learning, which comes first: the learned patterns or typing a new spoken word? (a) the learned patterns (b) typing a new spoken word
  38. 38.🧠 Machine learning is a way for computers to… (a) learn from data (b) charge faster (c) clean screens (d) print pages
  39. 39.Which of these is bad for training a model? (a) examples of every type (b) only one kind of example (c) new data for testing (d) many varied examples
  40. 40.Which of these is a fact about AI? (a) AI always checks facts (b) AI has real feelings (c) AI is never wrong (d) AI answers need checking

Answer key

  1. False
  2. False
  3. an image generator
  4. a real check
  5. False
  6. inventing a recipe
  7. drafting a letter
  8. old emails marked spam
  9. True
  10. examples of every type
  11. True
  12. trust the textbook
  13. predicting
  14. False
  15. False
  16. inventing a recipe
  17. True
  18. good for training
  19. False
  20. makes something new
  21. predicting
  22. test on many groups
  23. True
  24. the right answer tag
  25. text
  26. no, it can be wrong
  27. people
  28. gives a likely answer
  29. predicting rain
  30. artificial intelligence
  31. False
  32. spam
  33. True
  34. False
  35. no, it follows rules
  36. a prediction
  37. the learned patterns
  38. learn from data
  39. only one kind of example
  40. AI answers need checking

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