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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 895 · 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: “new data for testing” is bad for training a model. (a) False (b) True
  2. 2.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  3. 3.⏩ In machine learning, which comes first: labelled fruit photos or typing a new spoken word? (a) labelled fruit photos (b) typing a new spoken word
  4. 4.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) training data (c) the model
  5. 5.True or false: “balance the data” helps reduce bias. (a) False (b) True
  6. 6.True or false: “ignore complaints” adds to bias. (a) True (b) False
  7. 7.📱 What is the AI doing here: a shop guessing how many umbrellas will sell? (a) recognising (b) generating (c) recommending (d) predicting
  8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
  9. 9.🤖 What makes an AI system different from a normal program? (a) it is always right (b) it learns from examples (c) it has a screen (d) it uses electricity
  10. 10.True or false: “AI always checks facts” is a fact about AI. (a) False (b) True
  11. 11.🔍 Which is the odd one out? (a) AI answers need checking (b) AI can mix up numbers (c) AI learns from data (d) confident means correct
  12. 12.Which of these is not AI? (a) a voice assistant (b) an app translating signs (c) a map predicting traffic (d) a fan regulator
  13. 13.🤖 AI or a normal program: which one “does exactly as coded”? (a) AI (b) a normal program
  14. 14.🔍 Which is the odd one out? (a) photos grouped by face (b) voice typing (c) an AI chatbot (d) a kitchen weighing scale
  15. 15.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
  16. 16.Which of these describes how a normal program works? (a) gives a likely answer (b) learns from examples (c) one set rule per case (d) improves with more data
  17. 17.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  18. 18.🧮 Is a basic calculator an AI system? (a) only at night (b) no, it follows rules (c) yes, it can think (d) yes, it is smart
  19. 19.✨ Is everything a generative AI makes true? (a) yes, always (b) only on Mondays (c) no, it can be wrong
  20. 20.True or false: “the learned patterns” is the model. (a) True (b) False
  21. 21.🏠 AI or not AI: a microwave timer? (a) uses AI (b) not AI
  22. 22.Which of these is a fact about AI? (a) AI is never wrong (b) AI learns from data (c) long answers are true (d) confident means correct
  23. 23.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) balanced data (b) one-sided data
  24. 24.📱 What is the AI doing here: a keyboard guessing your next word? (a) recommending (b) generating (c) recognising (d) predicting
  25. 25.Which of these is a myth about AI? (a) AI is never wrong (b) AI can make up facts (c) AI answers need checking (d) AI can be wrong
  26. 26.True or false: stories with doctors of every gender is balanced data (fairer for everyone). (a) False (b) True
  27. 27.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) many labelled photos (c) one single photo (d) a song about dogs
  28. 28.True or false: “five quiz questions on fractions” asks for text. (a) False (b) True
  29. 29.🤖 AI or a normal program: which one “handles unseen examples”? (a) a normal program (b) AI
  30. 30.🔍 Which is the odd one out? (a) AI can make up facts (b) AI copies data patterns (c) AI can be wrong (d) AI has real feelings
  31. 31.True or false: “spots patterns in data” describes how a normal program works. (a) True (b) False
  32. 32.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
  33. 33.Which of these uses AI? (a) a doorbell (b) a microwave timer (c) a digital watch (d) voice typing
  34. 34.True or false: reading messy handwriting only needs a simple fixed rule. (a) True (b) False
  35. 35.🛠️ Which does this job need: translating a sentence into Hindi? (a) needs AI (learning) (b) a simple rule is enough
  36. 36.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) copy it straight away (b) never do maths (c) ask it to hurry (d) check it on paper
  37. 37.Which of these describes how AI works? (a) never learns from data (b) does exactly as coded (c) spots patterns in data (d) follows fixed rules
  38. 38.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) one group only (d) ignoring mistakes
  39. 39.🎨 This prompt asks a generative AI for: a cartoon of a dancing elephant. What kind of output is that? (a) music or sound (b) text (c) an image
  40. 40.🎨 This prompt asks a generative AI for: a summary of chapter 3. What kind of output is that? (a) text (b) music or sound (c) an image

Answer key

  1. False
  2. balanced data
  3. labelled fruit photos
  4. training data
  5. True
  6. True
  7. predicting
  8. spam
  9. it learns from examples
  10. False
  11. confident means correct
  12. a fan regulator
  13. a normal program
  14. a kitchen weighing scale
  15. a normal program
  16. one set rule per case
  17. a prediction
  18. no, it follows rules
  19. no, it can be wrong
  20. True
  21. not AI
  22. AI learns from data
  23. balanced data
  24. predicting
  25. AI is never wrong
  26. True
  27. many labelled photos
  28. True
  29. AI
  30. AI has real feelings
  31. False
  32. 500 labelled leaf photos
  33. voice typing
  34. False
  35. needs AI (learning)
  36. check it on paper
  37. spots patterns in data
  38. more varied data
  39. an image
  40. text

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