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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 468 · 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.Which of these is a prediction? (a) recorded spoken words (b) 500 labelled leaf photos (c) the trained program (d) flagging a new email
  2. 2.True or false: turning your spoken words into typed text is AI recommending something. (a) True (b) False
  3. 3.True or false: “copy old unfair choices” adds to bias. (a) False (b) True
  4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
  5. 5.✅ Is this a real check of an AI answer: match it to the textbook? (a) not a real check (b) a real check
  6. 6.🏷️ 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
  7. 7.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) very few examples (d) new data for testing
  8. 8.🛠️ Which does this job need: finding 10% of a price? (a) needs AI (learning) (b) a simple rule is enough
  9. 9.True or false: “confident means correct” is a myth about AI. (a) True (b) False
  10. 10.🔍 Which is the odd one out? (a) a voice assistant (b) a spam filter (c) a light switch (d) voice typing
  11. 11.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) ask it to hurry (b) copy it straight away (c) never do maths (d) check it on paper
  12. 12.📱 What is the AI doing here: an AI chatbot writing a poem about rain? (a) recognising (b) recommending (c) predicting (d) generating
  13. 13.Which of these is good for training a model? (a) new data for testing (b) very few examples (c) copies of one photo (d) testing on training data
  14. 14.🏠 AI or not AI: an image generator? (a) uses AI (b) not AI
  15. 15.Which of these is training data? (a) the trained program (b) the learned patterns (c) naming a new leaf (d) recorded spoken words
  16. 16.📱 What is the AI doing here: a camera app naming the flower you point at? (a) recognising (b) generating (c) predicting (d) recommending
  17. 17.✨ Generative or not: writing a new poem? (a) sorts or predicts (b) makes something new
  18. 18.True or false: “typing a new spoken word” is the model. (a) True (b) False
  19. 19.🤖 Does an AI system think and feel like a person? (a) only on weekends (b) yes, just like us (c) yes, it gets sad (d) no, it finds patterns
  20. 20.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
  21. 21.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
  22. 22.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  23. 23.🔍 Which is the odd one out? (a) fix wrong labels (b) ask different people (c) copy old unfair choices (d) balance the data
  24. 24.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
  25. 25.🔍 Which is the odd one out? (a) use one group only (b) check who is missing (c) add more of the same (d) skip testing
  26. 26.⏩ In machine learning, which comes first: recorded spoken words or naming a new leaf? (a) recorded spoken words (b) naming a new leaf
  27. 27.🔍 Which is the odd one out? (a) examples of every type (b) copies of one photo (c) testing on training data (d) only one kind of example
  28. 28.🏷️ 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
  29. 29.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  30. 30.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  31. 31.Which of these describes how AI works? (a) does exactly as coded (b) handles unseen examples (c) follows fixed rules (d) one set rule per case
  32. 32.🔍 Which is the odd one out? (a) face unlock on a phone (b) a voice assistant (c) an AI chatbot (d) a calculator
  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.🔍 Which is the odd one out? (a) sorting photos by face (b) drafting a letter (c) writing quiz questions (d) inventing a recipe
  35. 35.🔍 Which is the odd one out? (a) a printed timetable (b) a digital watch (c) a doorbell (d) voice typing
  36. 36.True or false: “past weather records” is the model. (a) True (b) False
  37. 37.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) share it online (b) trust the textbook (c) stop studying (d) trust the AI
  38. 38.🔍 Which is the odd one out? (a) long answers are true (b) AI always checks facts (c) AI can be wrong (d) AI is never wrong
  39. 39.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) better at its task (d) forget everything
  40. 40.True or false: “uses rules people wrote” describes how AI works. (a) False (b) True

Answer key

  1. flagging a new email
  2. False
  3. True
  4. not spam
  5. a real check
  6. not spam
  7. very few examples
  8. a simple rule is enough
  9. True
  10. a light switch
  11. check it on paper
  12. generating
  13. new data for testing
  14. uses AI
  15. recorded spoken words
  16. recognising
  17. makes something new
  18. False
  19. no, it finds patterns
  20. True
  21. False
  22. balanced data
  23. copy old unfair choices
  24. False
  25. check who is missing
  26. recorded spoken words
  27. examples of every type
  28. spam
  29. the model
  30. False
  31. handles unseen examples
  32. a calculator
  33. False
  34. sorting photos by face
  35. voice typing
  36. False
  37. trust the textbook
  38. AI can be wrong
  39. better at its task
  40. False

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