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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 890 · 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: “AI has real feelings” is a myth about AI. (a) False (b) True
  2. 2.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
  3. 3.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  4. 4.True or false: “makes a best guess” describes how a normal program works. (a) True (b) False
  5. 5.True or false: “it sounds very sure” is NOT a real way to check an AI answer. (a) True (b) False
  6. 6.🔍 Which is the odd one out? (a) AI has real feelings (b) confident means correct (c) AI answers need checking (d) AI is never wrong
  7. 7.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
  8. 8.True or false: “a thank-you note to the bus driver” asks for text. (a) False (b) True
  9. 9.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  10. 10.True or false: “labelled fruit photos” is the model. (a) True (b) False
  11. 11.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) recommending (b) predicting (c) generating (d) recognising
  12. 12.📱 What is the AI doing here: a book app suggesting a story like your last one? (a) generating (b) recommending (c) recognising (d) predicting
  13. 13.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
  14. 14.🏷️ 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
  15. 15.🔍 Which is the odd one out? (a) a microwave timer (b) a light switch (c) a voice assistant (d) a torch
  16. 16.Which of these describes how a normal program works? (a) gives a likely answer (b) learns from examples (c) follows fixed rules (d) spots patterns in data
  17. 17.True or false: showing the time on a clock needs AI that learns from examples. (a) True (b) False
  18. 18.True or false: a shop guessing how many umbrellas will sell is AI predicting something. (a) False (b) True
  19. 19.True or false: “only one kind of example” is good for training a model. (a) True (b) False
  20. 20.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
  21. 21.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) few child voices in data (d) the phone was new
  22. 22.🛠️ Which does this job need: switching on a street light at 6 pm? (a) needs AI (learning) (b) a simple rule is enough
  23. 23.🔍 Which is the odd one out? (a) AI has real feelings (b) AI is never wrong (c) AI can make up facts (d) long answers are true
  24. 24.✨ Generative or not: composing a new tune? (a) makes something new (b) sorts or predicts
  25. 25.Which of these is generative AI (it makes something new)? (a) sorting photos by face (b) predicting rain (c) composing a new tune (d) unlocking with a face
  26. 26.True or false: “a summary of chapter 3” asks for music or sound. (a) False (b) True
  27. 27.True or false: spotting spam emails by their patterns needs AI that learns from examples. (a) True (b) False
  28. 28.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it prints labels (d) it takes photos
  29. 29.🔍 Which is the odd one out? (a) checking labels twice (b) copies of one photo (c) labels added at random (d) testing on training data
  30. 30.📱 What is the AI doing here: a video app suggesting what to watch next? (a) recognising (b) generating (c) predicting (d) recommending
  31. 31.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a password (d) a prediction
  32. 32.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) labels added at random (d) photos in many lights
  33. 33.Which of these is generative AI (it makes something new)? (a) sorting photos by face (b) writing a new poem (c) suggesting a video (d) predicting rain
  34. 34.✨ Generative or not: creating a cartoon? (a) sorts or predicts (b) makes something new
  35. 35.🤖 Who builds and trains AI systems? (a) nobody at all (b) the Moon (c) people (d) the weather
  36. 36.Which of these is a fact about AI? (a) AI is never wrong (b) AI can make up facts (c) AI always checks facts (d) AI knows everything
  37. 37.Which of these is the model? (a) the trained program (b) flagging a new email (c) naming a new fruit photo (d) old emails marked spam
  38. 38.Which of these is the model? (a) recorded spoken words (b) tomorrow’s rain guess (c) past weather records (d) what training builds
  39. 39.True or false: “the trained program” is the model. (a) False (b) True
  40. 40.🔍 Which is the odd one out? (a) only one kind of example (b) examples of every type (c) new data for testing (d) correct labels

Answer key

  1. True
  2. bad for training
  3. a prediction
  4. False
  5. True
  6. AI answers need checking
  7. AI
  8. True
  9. training data
  10. False
  11. recognising
  12. recommending
  13. needs AI (learning)
  14. not spam
  15. a voice assistant
  16. follows fixed rules
  17. False
  18. True
  19. False
  20. False
  21. few child voices in data
  22. a simple rule is enough
  23. AI can make up facts
  24. makes something new
  25. composing a new tune
  26. False
  27. True
  28. it learns patterns
  29. checking labels twice
  30. recommending
  31. a prediction
  32. labels added at random
  33. writing a new poem
  34. makes something new
  35. people
  36. AI can make up facts
  37. the trained program
  38. what training builds
  39. True
  40. only one kind of example

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