← Part 1 test: what AI is lesson New set →

AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 846 · 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 does this job need: sorting names in A to Z order? (a) needs AI (learning) (b) a simple rule is enough
  2. 2.Which of these is a fact about AI? (a) AI knows everything (b) AI has real feelings (c) confident means correct (d) AI can make up facts
  3. 3.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) a song about dogs (d) many labelled photos
  4. 4.🔍 Which is the odd one out? (a) ignore complaints (b) add more of the same (c) balance the data (d) skip testing
  5. 5.🏠 AI or not AI: a voice assistant? (a) not AI (b) uses AI
  6. 6.Which of these describes how a normal program works? (a) learns from examples (b) gives a likely answer (c) uses rules people wrote (d) spots patterns in data
  7. 7.True or false: a book app suggesting a story like your last one is AI recommending something. (a) False (b) True
  8. 8.True or false: “see if the book exists” is NOT a real way to check an AI answer. (a) True (b) False
  9. 9.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the price (d) the font size
  10. 10.True or false: “follows fixed rules” describes how a normal program works. (a) False (b) True
  11. 11.🔍 Which is the odd one out? (a) many varied examples (b) checking labels twice (c) examples of every type (d) copies of one photo
  12. 12.🤖 AI or a normal program: which one “learns from examples”? (a) AI (b) a normal program
  13. 13.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) data, model, prediction (d) model, prediction, data
  14. 14.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
  15. 15.🛠️ What helps make an AI system fairer? (a) one group only (b) ignoring mistakes (c) fewer tests (d) more varied data
  16. 16.True or false: neat and messy writing from many people is balanced data (fairer for everyone). (a) False (b) True
  17. 17.Which of these is bad for training a model? (a) very few examples (b) clear, sharp examples (c) new data for testing (d) many varied examples
  18. 18.🧐 Fact or myth: “AI can make up facts”? (a) a fact (b) a myth
  19. 19.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
  20. 20.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will be perfect (d) it will turn yellow
  21. 21.True or false: “write a poem about the monsoon” asks for music or sound. (a) True (b) False
  22. 22.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  23. 23.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  24. 24.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  25. 25.True or false: “the trained program” is training data. (a) False (b) True
  26. 26.Which of these adds to bias? (a) fix wrong labels (b) add varied examples (c) use one group only (d) test on many groups
  27. 27.True or false: a map app guessing how long a trip will take is AI predicting something. (a) True (b) False
  28. 28.🔍 Which is the odd one out? (a) drafting a letter (b) inventing a recipe (c) spotting spam (d) writing quiz questions
  29. 29.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  30. 30.True or false: “ignore complaints” adds to bias. (a) False (b) True
  31. 31.True or false: “a summary of chapter 3” asks for text. (a) True (b) False
  32. 32.True or false: “only one kind of example” is good for training a model. (a) True (b) False
  33. 33.Which of these describes how AI works? (a) follows fixed rules (b) same steps every time (c) one set rule per case (d) handles unseen examples
  34. 34.Which of these describes how a normal program works? (a) gives a likely answer (b) handles unseen examples (c) follows fixed rules (d) improves with more data
  35. 35.⚖️ One-sided or balanced data: leaves from every season of the year? (a) one-sided data (b) balanced data
  36. 36.🏠 AI or not AI: an app translating signs? (a) uses AI (b) not AI
  37. 37.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) an image (b) text (c) music or sound
  38. 38.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  39. 39.Which of these is the model? (a) 500 labelled leaf photos (b) naming a new fruit photo (c) past weather records (d) what training builds
  40. 40.True or false: a phone unlocking when it sees your face is AI recognising something. (a) False (b) True

Answer key

  1. a simple rule is enough
  2. AI can make up facts
  3. many labelled photos
  4. balance the data
  5. uses AI
  6. uses rules people wrote
  7. True
  8. False
  9. the right answer tag
  10. True
  11. copies of one photo
  12. AI
  13. data, model, prediction
  14. True
  15. more varied data
  16. True
  17. very few examples
  18. a fact
  19. balanced data
  20. it may get it wrong
  21. False
  22. training data
  23. past weather records
  24. reduces bias
  25. False
  26. use one group only
  27. True
  28. spotting spam
  29. False
  30. True
  31. True
  32. False
  33. handles unseen examples
  34. follows fixed rules
  35. balanced data
  36. uses AI
  37. text
  38. True
  39. what training builds
  40. True

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students