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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 363 · 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 good for training a model? (a) correct labels (b) wrong labels (c) only one kind of example (d) blurry, unclear photos
  2. 2.Which of these describes how a normal program works? (a) spots patterns in data (b) does exactly as coded (c) learns from examples (d) gives a likely answer
  3. 3.🧐 Fact or myth: “AI knows everything”? (a) a fact (b) a myth
  4. 4.🔍 Which is the odd one out? (a) reading number plates (b) drafting a letter (c) inventing a recipe (d) composing a new tune
  5. 5.True or false: “examples of every type” is bad for training a model. (a) True (b) False
  6. 6.True or false: “test on many groups” adds to bias. (a) False (b) True
  7. 7.Which of these is generative AI (it makes something new)? (a) spotting a sick leaf (b) predicting rain (c) writing a new poem (d) turning speech to text
  8. 8.True or false: translating a sentence into Hindi only needs a simple fixed rule. (a) False (b) True
  9. 9.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the font size (c) a sticker on a laptop (d) the price
  10. 10.🎨 This prompt asks a generative AI for: a soft lullaby melody. What kind of output is that? (a) an image (b) music or sound (c) text
  11. 11.True or false: a handwriting app shown only neat writing is balanced data (fairer for everyone). (a) True (b) False
  12. 12.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
  13. 13.📅 An AI gives a date for a history event. How can you check? (a) ask it to repeat (b) pick a lucky number (c) guess (d) look in your textbook
  14. 14.🔍 Which is the odd one out? (a) check who is missing (b) add more of the same (c) test on one group only (d) copy old unfair choices
  15. 15.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  16. 16.✨ Generative or not: drafting a letter? (a) makes something new (b) sorts or predicts
  17. 17.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
  18. 18.✨ Generative or not: creating a cartoon? (a) makes something new (b) sorts or predicts
  19. 19.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
  20. 20.True or false: “asking the same AI again” is a real way to check an AI answer. (a) True (b) False
  21. 21.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
  22. 22.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) music or sound (b) text (c) an image
  23. 23.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
  24. 24.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
  25. 25.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the AI (b) share it online (c) trust the textbook (d) stop studying
  26. 26.🔍 Which is the odd one out? (a) video suggestions (b) a stopwatch (c) photos grouped by face (d) voice typing
  27. 27.True or false: photos of people of many ages and skin tones is one-sided data (likely to make a biased model). (a) True (b) False
  28. 28.🧪 Why test a model on NEW examples? (a) to delete its data (b) to change its name (c) to make it slower (d) to see if it works
  29. 29.🔍 Which is the odd one out? (a) examples of every type (b) labels added at random (c) blurry, unclear photos (d) testing on training data
  30. 30.True or false: sorting names in A to Z order only needs a simple fixed rule. (a) False (b) True
  31. 31.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
  32. 32.🔍 Which is the odd one out? (a) checking labels twice (b) photos in many lights (c) wrong labels (d) correct labels
  33. 33.Which of these is generative AI (it makes something new)? (a) reading number plates (b) unlocking with a face (c) spotting spam (d) creating a cartoon
  34. 34.Which of these is generative AI (it makes something new)? (a) drawing a new picture (b) turning speech to text (c) sorting photos by face (d) suggesting a video
  35. 35.🤖 AI or a normal program: which one “does exactly as coded”? (a) a normal program (b) AI
  36. 36.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
  37. 37.True or false: turning spoken words into typed text only needs a simple fixed rule. (a) True (b) False
  38. 38.📦 What happens during training? (a) it learns patterns (b) it takes photos (c) it prints labels (d) it charges up
  39. 39.📱 What is the AI doing here: an AI chatbot writing a poem about rain? (a) recognising (b) recommending (c) predicting (d) generating
  40. 40.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) training data (c) a prediction

Answer key

  1. correct labels
  2. does exactly as coded
  3. a myth
  4. reading number plates
  5. False
  6. False
  7. writing a new poem
  8. False
  9. the right answer tag
  10. music or sound
  11. False
  12. False
  13. look in your textbook
  14. check who is missing
  15. the model
  16. makes something new
  17. good for training
  18. makes something new
  19. False
  20. False
  21. bad for training
  22. text
  23. needs AI (learning)
  24. adds to bias
  25. trust the textbook
  26. a stopwatch
  27. False
  28. to see if it works
  29. examples of every type
  30. True
  31. AI
  32. wrong labels
  33. creating a cartoon
  34. drawing a new picture
  35. a normal program
  36. spam
  37. False
  38. it learns patterns
  39. generating
  40. training data

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