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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 860 · 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: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  2. 2.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  3. 3.⏩ In machine learning, which comes first: 500 labelled leaf photos or the trained program? (a) 500 labelled leaf photos (b) the trained program
  4. 4.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a label error (c) a prediction (d) a password
  5. 5.💬 What do we call the request you type to a generative AI? (a) a password (b) a battery (c) a label (d) a prompt
  6. 6.True or false: “it has a neat layout” is NOT a real way to check an AI answer. (a) True (b) False
  7. 7.🔍 Which is the odd one out? (a) AI answers need checking (b) AI can make up facts (c) AI is never wrong (d) AI can be wrong
  8. 8.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) a prediction (c) the model
  9. 9.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) balanced data (b) one-sided data
  10. 10.🔍 Which is the odd one out? (a) drawing a new picture (b) writing quiz questions (c) creating a cartoon (d) predicting rain
  11. 11.🔍 Which is the odd one out? (a) photos in many lights (b) labels added at random (c) very few examples (d) copies of one photo
  12. 12.True or false: reading messy handwriting only needs a simple fixed rule. (a) False (b) True
  13. 13.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
  14. 14.🤖 AI or a normal program: which one “makes a best guess”? (a) AI (b) a normal program
  15. 15.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  16. 16.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
  17. 17.Which of these is a myth about AI? (a) AI knows everything (b) AI answers need checking (c) AI copies data patterns (d) AI learns from data
  18. 18.True or false: “gives a likely answer” describes how a normal program works. (a) True (b) False
  19. 19.True or false: recognising a friend’s face in photos only needs a simple fixed rule. (a) False (b) True
  20. 20.Which of these helps reduce bias? (a) test on one group only (b) test on many groups (c) copy old unfair choices (d) ignore complaints
  21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
  22. 22.True or false: a keyboard guessing your next word is AI predicting something. (a) False (b) True
  23. 23.✨ What does generative AI do? (a) only adds numbers (b) makes new content (c) charges batteries (d) only stores files
  24. 24.🔍 Which is the odd one out? (a) suggesting a video (b) sorting photos by face (c) unlocking with a face (d) making up a story
  25. 25.✨ Is everything a generative AI makes true? (a) only on Mondays (b) no, it can be wrong (c) yes, always
  26. 26.True or false: suggesting the next word as you type needs AI that learns from examples. (a) False (b) True
  27. 27.Which of these uses AI? (a) a calculator (b) photos grouped by face (c) a kitchen weighing scale (d) a light switch
  28. 28.🤖 AI or a normal program: which one “same steps every time”? (a) a normal program (b) AI
  29. 29.🔍 Which is the odd one out? (a) a map predicting traffic (b) an app translating signs (c) an image generator (d) a fan regulator
  30. 30.✨ Generative or not: suggesting a video? (a) sorts or predicts (b) makes something new
  31. 31.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
  32. 32.🤖 Who builds and trains AI systems? (a) nobody at all (b) the Moon (c) the weather (d) people
  33. 33.🔍 Which is the odd one out? (a) copies of one photo (b) only one kind of example (c) very few examples (d) examples of every type
  34. 34.True or false: “only one kind of example” is good for training a model. (a) True (b) False
  35. 35.True or false: an image generator drawing a robot from a sentence is AI generating something new. (a) False (b) True
  36. 36.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
  37. 37.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) few child voices in data (c) children speak too fast (d) it was a rainy day
  38. 38.True or false: translating a sentence into Hindi only needs a simple fixed rule. (a) True (b) False
  39. 39.🎨 This prompt asks a generative AI for: a cheerful tune for Sports Day. What kind of output is that? (a) an image (b) text (c) music or sound
  40. 40.🔍 Which is the odd one out? (a) predicting rain (b) writing a new poem (c) suggesting a video (d) spotting spam

Answer key

  1. False
  2. False
  3. 500 labelled leaf photos
  4. a prediction
  5. a prompt
  6. True
  7. AI is never wrong
  8. a prediction
  9. balanced data
  10. predicting rain
  11. photos in many lights
  12. False
  13. a prediction
  14. AI
  15. training data
  16. False
  17. AI knows everything
  18. False
  19. False
  20. test on many groups
  21. spam
  22. True
  23. makes new content
  24. making up a story
  25. no, it can be wrong
  26. True
  27. photos grouped by face
  28. a normal program
  29. a fan regulator
  30. sorts or predicts
  31. False
  32. people
  33. examples of every type
  34. False
  35. True
  36. good for training
  37. few child voices in data
  38. False
  39. music or sound
  40. writing a new poem

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