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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 194 · 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 does this job need: finding 10% of a price? (a) needs AI (learning) (b) a simple rule is enough
  2. 2.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
  3. 3.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  4. 4.True or false: “wrong labels” is good for training a model. (a) True (b) False
  5. 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
  6. 6.✍️ How does an AI chatbot write its replies? (a) uses magic (b) predicts likely words (c) asks a person (d) copies one website
  7. 7.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) test on one group only (d) balance the data
  8. 8.Which of these describes how AI works? (a) follows fixed rules (b) uses rules people wrote (c) does exactly as coded (d) handles unseen examples
  9. 9.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  10. 10.True or false: “AI learns from data” is a fact about AI. (a) False (b) True
  11. 11.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing a new poem (b) making up a story (c) spotting spam (d) writing quiz questions
  12. 12.📅 An AI gives a date for a history event. How can you check? (a) ask it to repeat (b) look in your textbook (c) pick a lucky number (d) guess
  13. 13.🛠️ Which does this job need: suggesting the next word as you type? (a) needs AI (learning) (b) a simple rule is enough
  14. 14.🎨 This prompt asks a generative AI for: a drum beat for a dance. What kind of output is that? (a) music or sound (b) text (c) an image
  15. 15.⏩ In machine learning, which comes first: 500 labelled leaf photos or typing a new spoken word? (a) 500 labelled leaf photos (b) typing a new spoken word
  16. 16.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
  17. 17.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
  18. 18.Which of these is a fact about AI? (a) AI is never wrong (b) long answers are true (c) AI knows everything (d) AI learns from data
  19. 19.🔍 Which is the odd one out? (a) spotting spam (b) drawing a new picture (c) sorting photos by face (d) spotting a sick leaf
  20. 20.🏷️ 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
  21. 21.Which of these describes how AI works? (a) learns from examples (b) same steps every time (c) never learns from data (d) does exactly as coded
  22. 22.True or false: a keyboard guessing your next word is AI generating something new. (a) True (b) False
  23. 23.📱 What is the AI doing here: a camera app naming the flower you point at? (a) recommending (b) recognising (c) predicting (d) generating
  24. 24.🧐 Fact or myth: “AI learns from data”? (a) a myth (b) a fact
  25. 25.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) prediction, data, model (d) data, prediction, model
  26. 26.Which of these is not AI? (a) photos grouped by face (b) an image generator (c) face unlock on a phone (d) a printed timetable
  27. 27.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  28. 28.Which of these describes how AI works? (a) one set rule per case (b) follows fixed rules (c) gives a likely answer (d) same steps every time
  29. 29.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  30. 30.Which of these uses AI? (a) a calculator (b) a digital watch (c) a microwave timer (d) an image generator
  31. 31.🏠 AI or not AI: a digital watch? (a) not AI (b) uses AI
  32. 32.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
  33. 33.🎨 This prompt asks a generative AI for: a poster of a rainforest. What kind of output is that? (a) text (b) music or sound (c) an image
  34. 34.Which of these is not AI? (a) an app translating signs (b) an AI chatbot (c) a voice assistant (d) a fan regulator
  35. 35.True or false: “wrong labels” is bad for training a model. (a) False (b) True
  36. 36.Which of these is good for training a model? (a) only one kind of example (b) wrong labels (c) very few examples (d) photos in many lights
  37. 37.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  38. 38.True or false: “photos in many lights” is good for training a model. (a) True (b) False
  39. 39.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
  40. 40.True or false: “never learns from data” describes how a normal program works. (a) True (b) False

Answer key

  1. a simple rule is enough
  2. good for training
  3. training data
  4. False
  5. balanced data
  6. predicts likely words
  7. test on one group only
  8. handles unseen examples
  9. False
  10. True
  11. spotting spam
  12. look in your textbook
  13. needs AI (learning)
  14. music or sound
  15. 500 labelled leaf photos
  16. few child voices in data
  17. True
  18. AI learns from data
  19. drawing a new picture
  20. spam
  21. learns from examples
  22. False
  23. recognising
  24. a fact
  25. data, model, prediction
  26. a printed timetable
  27. reduces bias
  28. gives a likely answer
  29. False
  30. an image generator
  31. not AI
  32. bad for training
  33. an image
  34. a fan regulator
  35. True
  36. photos in many lights
  37. training data
  38. True
  39. False
  40. True

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