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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 584 · 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.📅 An AI gives a date for a history event. How can you check? (a) guess (b) ask it to repeat (c) look in your textbook (d) pick a lucky number
  2. 2.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  3. 3.✨ Generative or not: turning speech to text? (a) makes something new (b) sorts or predicts
  4. 4.🛠️ Which does this job need: switching on a street light at 6 pm? (a) a simple rule is enough (b) needs AI (learning)
  5. 5.🔍 Which is the odd one out? (a) test on one group only (b) check who is missing (c) test on many groups (d) balance the data
  6. 6.🤔 An AI answer sounds very confident. Does that mean it is right? (a) no, check it anyway (b) yes, if it is long (c) yes, always
  7. 7.🔍 Which is the odd one out? (a) photos grouped by face (b) a calculator (c) a digital watch (d) a torch
  8. 8.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a strong battery (d) a broken screen
  9. 9.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) copy it straight away (b) never do maths (c) ask it to hurry (d) check it on paper
  10. 10.Which of these uses AI? (a) a light switch (b) a doorbell (c) a map predicting traffic (d) a calculator
  11. 11.True or false: telling a cat photo from a dog photo only needs a simple fixed rule. (a) True (b) False
  12. 12.True or false: “AI can mix up numbers” is a myth about AI. (a) False (b) True
  13. 13.True or false: “asking the same AI again” is NOT a real way to check an AI answer. (a) False (b) True
  14. 14.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
  15. 15.Which of these is not AI? (a) voice typing (b) video suggestions (c) a voice assistant (d) a calculator
  16. 16.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  17. 17.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
  18. 18.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
  19. 19.True or false: “uses rules people wrote” describes how a normal program works. (a) False (b) True
  20. 20.True or false: “makes a best guess” describes how a normal program works. (a) False (b) True
  21. 21.🔍 Which is the odd one out? (a) confident means correct (b) AI is never wrong (c) AI learns from data (d) long answers are true
  22. 22.🔍 Which is the odd one out? (a) writing a new poem (b) composing a new tune (c) unlocking with a face (d) inventing a recipe
  23. 23.Which of these uses AI? (a) a calculator (b) a printed timetable (c) voice typing (d) a microwave timer
  24. 24.True or false: “one set rule per case” describes how AI works. (a) False (b) True
  25. 25.True or false: “new data for testing” is good for training a model. (a) True (b) False
  26. 26.True or false: telling a cat photo from a dog photo needs AI that learns from examples. (a) False (b) True
  27. 27.📱 What is the AI doing here: a map app guessing how long a trip will take? (a) recognising (b) generating (c) recommending (d) predicting
  28. 28.True or false: “new data for testing” is bad for training a model. (a) False (b) True
  29. 29.Which of these is a fact about AI? (a) AI knows everything (b) AI has real feelings (c) AI can make up facts (d) long answers are true
  30. 30.🧮 Which of these is NOT AI? (a) a spam filter (b) face unlock (c) voice typing (d) a basic calculator
  31. 31.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
  32. 32.✨ Generative or not: predicting rain? (a) sorts or predicts (b) makes something new
  33. 33.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
  34. 34.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) clean screens (d) learn from data
  35. 35.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  36. 36.🎨 This prompt asks a generative AI for: a summary of chapter 3. What kind of output is that? (a) music or sound (b) an image (c) text
  37. 37.🧐 Fact or myth: “AI always checks facts”? (a) a myth (b) a fact
  38. 38.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the AI (b) trust the textbook (c) share it online (d) stop studying
  39. 39.🎨 An image generator makes a picture from… (a) your password (b) the weather (c) a phone number (d) a text description
  40. 40.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training

Answer key

  1. look in your textbook
  2. balanced data
  3. sorts or predicts
  4. a simple rule is enough
  5. test on one group only
  6. no, check it anyway
  7. photos grouped by face
  8. bias from data
  9. check it on paper
  10. a map predicting traffic
  11. False
  12. False
  13. True
  14. bad for training
  15. a calculator
  16. the learned patterns
  17. False
  18. False
  19. True
  20. False
  21. AI learns from data
  22. unlocking with a face
  23. voice typing
  24. False
  25. True
  26. True
  27. predicting
  28. False
  29. AI can make up facts
  30. a basic calculator
  31. the model
  32. sorts or predicts
  33. a normal program
  34. learn from data
  35. reduces bias
  36. text
  37. a myth
  38. trust the textbook
  39. a text description
  40. good for training

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