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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 22 · 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.🔁 What is the right order? (a) model, prediction, data (b) data, prediction, model (c) data, model, prediction (d) prediction, data, model
  2. 2.📦 What happens during training? (a) it takes photos (b) it charges up (c) it learns patterns (d) it prints labels
  3. 3.✅ Is this a real check of an AI answer: try the sum on paper? (a) not a real check (b) a real check
  4. 4.True or false: “it has a neat layout” is a real way to check an AI answer. (a) True (b) False
  5. 5.📱 What is the AI doing here: an image generator drawing a robot from a sentence? (a) recommending (b) generating (c) recognising (d) predicting
  6. 6.Which of these uses AI? (a) a calculator (b) a spam filter (c) a microwave timer (d) a printed timetable
  7. 7.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  8. 8.🎨 This prompt asks a generative AI for: a drum beat for a dance. What kind of output is that? (a) text (b) an image (c) music or sound
  9. 9.🧐 Fact or myth: “long answers are true”? (a) a myth (b) a fact
  10. 10.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
  11. 11.Which of these is good for training a model? (a) very few examples (b) photos in many lights (c) only one kind of example (d) labels added at random
  12. 12.Which of these is bad for training a model? (a) examples of every type (b) copies of one photo (c) new data for testing (d) photos in many lights
  13. 13.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
  14. 14.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
  15. 15.True or false: “labelled fruit photos” is training data. (a) True (b) False
  16. 16.True or false: “many varied examples” is good for training a model. (a) False (b) True
  17. 17.✅ Is this a real check of an AI answer: match it to the textbook? (a) not a real check (b) a real check
  18. 18.Which of these helps reduce bias? (a) add more of the same (b) skip testing (c) ask different people (d) copy old unfair choices
  19. 19.🎨 An image generator makes a picture from… (a) your password (b) a phone number (c) the weather (d) a text description
  20. 20.True or false: “check who is missing” helps reduce bias. (a) False (b) True
  21. 21.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
  22. 22.True or false: “ask your teacher” is a real way to check an AI answer. (a) True (b) False
  23. 23.True or false: “AI always checks facts” is a myth about AI. (a) True (b) False
  24. 24.True or false: “a poster of a rainforest” asks for text. (a) True (b) False
  25. 25.✨ Generative or not: sorting photos by face? (a) sorts or predicts (b) makes something new
  26. 26.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  27. 27.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) new data for testing (d) wrong labels
  28. 28.🔍 Which is the odd one out? (a) confident means correct (b) AI is never wrong (c) AI copies data patterns (d) AI has real feelings
  29. 29.True or false: “test on many groups” helps reduce bias. (a) True (b) False
  30. 30.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) balance the data (d) ask different people
  31. 31.True or false: turning your spoken words into typed text is AI recognising something. (a) False (b) True
  32. 32.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  33. 33.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  34. 34.✨ Generative or not: reading number plates? (a) sorts or predicts (b) makes something new
  35. 35.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  36. 36.🧪 Why test a model on NEW examples? (a) to delete its data (b) to see if it works (c) to make it slower (d) to change its name
  37. 37.True or false: “does exactly as coded” describes how AI works. (a) False (b) True
  38. 38.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
  39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
  40. 40.💬 What do we call the request you type to a generative AI? (a) a prompt (b) a password (c) a label (d) a battery

Answer key

  1. data, model, prediction
  2. it learns patterns
  3. a real check
  4. False
  5. generating
  6. a spam filter
  7. False
  8. music or sound
  9. a myth
  10. spam
  11. photos in many lights
  12. copies of one photo
  13. good for training
  14. spam
  15. True
  16. True
  17. a real check
  18. ask different people
  19. a text description
  20. True
  21. True
  22. True
  23. True
  24. False
  25. sorts or predicts
  26. a prediction
  27. wrong labels
  28. AI copies data patterns
  29. True
  30. test on one group only
  31. True
  32. training data
  33. False
  34. sorts or predicts
  35. a prediction
  36. to see if it works
  37. False
  38. spam
  39. spam
  40. a prompt

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