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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 473 · 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: “use one group only” helps reduce bias. (a) False (b) True
  2. 2.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  3. 3.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing a new poem (b) inventing a recipe (c) unlocking with a face (d) composing a new tune
  4. 4.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) copy it straight away (b) check it on paper (c) never do maths (d) ask it to hurry
  5. 5.✅ Is this a real check of an AI answer: try the sum on paper? (a) not a real check (b) a real check
  6. 6.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
  7. 7.✨ Generative or not: spotting a sick leaf? (a) makes something new (b) sorts or predicts
  8. 8.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  9. 9.Which of these is generative AI (it makes something new)? (a) spotting spam (b) predicting rain (c) reading number plates (d) composing a new tune
  10. 10.📱 What is the AI doing here: an online shop showing “you may also like”? (a) recognising (b) generating (c) predicting (d) recommending
  11. 11.True or false: “fix wrong labels” adds to bias. (a) False (b) True
  12. 12.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  13. 13.🔁 What is the right order? (a) data, prediction, model (b) data, model, prediction (c) prediction, data, model (d) model, prediction, data
  14. 14.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
  15. 15.True or false: “asking the same AI again” is NOT a real way to check an AI answer. (a) True (b) False
  16. 16.🏠 AI or not AI: a doorbell? (a) not AI (b) uses AI
  17. 17.True or false: “the trained program” is a prediction. (a) True (b) False
  18. 18.🤖 Who builds and trains AI systems? (a) the weather (b) the Moon (c) people (d) nobody at all
  19. 19.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  20. 20.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) testing on training data (d) blurry, unclear photos
  21. 21.Which of these describes how a normal program works? (a) never learns from data (b) makes a best guess (c) spots patterns in data (d) improves with more data
  22. 22.Which of these describes how a normal program works? (a) gives a likely answer (b) same steps every time (c) handles unseen examples (d) spots patterns in data
  23. 23.🏠 AI or not AI: an image generator? (a) not AI (b) uses AI
  24. 24.🧮 Is a basic calculator an AI system? (a) no, it follows rules (b) only at night (c) yes, it is smart (d) yes, it can think
  25. 25.🔍 Which is the odd one out? (a) long answers are true (b) AI has real feelings (c) AI answers need checking (d) confident means correct
  26. 26.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
  27. 27.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
  28. 28.True or false: “very few examples” is bad for training a model. (a) True (b) False
  29. 29.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) its colour (d) the weather
  30. 30.True or false: turning your spoken words into typed text is AI predicting something. (a) False (b) True
  31. 31.True or false: “add varied examples” adds to bias. (a) True (b) False
  32. 32.🏠 AI or not AI: a printed timetable? (a) not AI (b) uses AI
  33. 33.True or false: “naming a new fruit photo” is training data. (a) True (b) False
  34. 34.True or false: ringing the school bell at 9 am needs AI that learns from examples. (a) True (b) False
  35. 35.True or false: “add more of the same” adds to bias. (a) True (b) False
  36. 36.🔍 Which is the odd one out? (a) an app translating signs (b) a digital watch (c) a kitchen weighing scale (d) a doorbell
  37. 37.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) recognising (b) recommending (c) predicting (d) generating
  38. 38.True or false: ringing the school bell at 9 am only needs a simple fixed rule. (a) True (b) False
  39. 39.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) sleeping (c) drawing (d) predicting
  40. 40.True or false: “one set rule per case” describes how a normal program works. (a) False (b) True

Answer key

  1. False
  2. balanced data
  3. unlocking with a face
  4. check it on paper
  5. a real check
  6. True
  7. sorts or predicts
  8. the learned patterns
  9. composing a new tune
  10. recommending
  11. False
  12. one-sided data
  13. data, model, prediction
  14. not spam
  15. True
  16. not AI
  17. False
  18. people
  19. the trained program
  20. examples of every type
  21. never learns from data
  22. same steps every time
  23. uses AI
  24. no, it follows rules
  25. AI answers need checking
  26. spam
  27. reduces bias
  28. True
  29. its training data
  30. False
  31. False
  32. not AI
  33. False
  34. False
  35. True
  36. an app translating signs
  37. generating
  38. True
  39. predicting
  40. True

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