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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 977 · 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.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its training data (c) its colour (d) its screen size
  2. 2.True or false: “labels added at random” is bad for training a model. (a) False (b) True
  3. 3.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  4. 4.True or false: “gives a likely answer” describes how AI works. (a) True (b) False
  5. 5.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  6. 6.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
  7. 7.📺 A video app suggests what to watch next. What is the AI doing? (a) recommending (b) printing (c) cooking (d) charging
  8. 8.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
  9. 9.🧐 Fact or myth: “confident means correct”? (a) a myth (b) a fact
  10. 10.📦 What happens during training? (a) it learns patterns (b) it charges up (c) it takes photos (d) it prints labels
  11. 11.True or false: “a thank-you note to the bus driver” asks for music or sound. (a) True (b) False
  12. 12.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
  13. 13.True or false: “new data for testing” is good for training a model. (a) True (b) False
  14. 14.True or false: “AI answers need checking” is a myth about AI. (a) False (b) True
  15. 15.🔍 Which is the odd one out? (a) add varied examples (b) ask different people (c) ignore complaints (d) check who is missing
  16. 16.🧐 Fact or myth: “AI copies data patterns”? (a) a fact (b) a myth
  17. 17.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction
  18. 18.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name
  19. 19.📱 What is the AI doing here: a keyboard guessing your next word? (a) generating (b) recommending (c) predicting (d) recognising
  20. 20.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
  21. 21.True or false: “a drum beat for a dance” asks for music or sound. (a) True (b) False
  22. 22.🔍 Which is the odd one out? (a) an image generator (b) a fan regulator (c) a calculator (d) a kitchen weighing scale
  23. 23.Which of these is a myth about AI? (a) AI learns from data (b) AI can be wrong (c) AI has real feelings (d) AI can mix up numbers
  24. 24.🤖 What does AI stand for? (a) actual information (b) artificial intelligence (c) automatic internet (d) app installer
  25. 25.True or false: “a cheerful tune for Sports Day” asks for an image. (a) True (b) False
  26. 26.🎨 An image generator makes a picture from… (a) the weather (b) a phone number (c) your password (d) a text description
  27. 27.True or false: “AI learns from data” is a fact about AI. (a) False (b) True
  28. 28.Which of these uses AI? (a) a kitchen weighing scale (b) a torch (c) a printed timetable (d) face unlock on a phone
  29. 29.🔍 Which is the odd one out? (a) a microwave timer (b) a map predicting traffic (c) a spam filter (d) an image generator
  30. 30.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) data, model, prediction (d) model, prediction, data
  31. 31.🔍 Which is the odd one out? (a) examples of every type (b) blurry, unclear photos (c) only one kind of example (d) wrong labels
  32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
  33. 33.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  34. 34.Which of these uses AI? (a) video suggestions (b) a digital watch (c) a light switch (d) a fan regulator
  35. 35.Which of these is good for training a model? (a) only one kind of example (b) many varied examples (c) testing on training data (d) blurry, unclear photos
  36. 36.🔍 Which is the odd one out? (a) check who is missing (b) use one group only (c) test on many groups (d) ask different people
  37. 37.Which of these is bad for training a model? (a) examples of every type (b) clear, sharp examples (c) correct labels (d) copies of one photo
  38. 38.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  39. 39.✅ Is this a real check of an AI answer: try the sum on paper? (a) not a real check (b) a real check
  40. 40.✨ Generative or not: writing quiz questions? (a) sorts or predicts (b) makes something new

Answer key

  1. its training data
  2. True
  3. False
  4. True
  5. 500 labelled leaf photos
  6. bad for training
  7. recommending
  8. True
  9. a myth
  10. it learns patterns
  11. False
  12. adds to bias
  13. True
  14. False
  15. ignore complaints
  16. a fact
  17. training data
  18. to see if it works
  19. predicting
  20. a normal program
  21. True
  22. an image generator
  23. AI has real feelings
  24. artificial intelligence
  25. False
  26. a text description
  27. True
  28. face unlock on a phone
  29. a microwave timer
  30. data, model, prediction
  31. examples of every type
  32. not spam
  33. True
  34. video suggestions
  35. many varied examples
  36. use one group only
  37. copies of one photo
  38. False
  39. a real check
  40. makes something new

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