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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 244 · 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.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name
  2. 2.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
  3. 3.🤖 What does AI stand for? (a) actual information (b) automatic internet (c) app installer (d) artificial intelligence
  4. 4.True or false: recognising a bird from its song needs AI that learns from examples. (a) True (b) False
  5. 5.📦 What happens during training? (a) it charges up (b) it takes photos (c) it prints labels (d) it learns patterns
  6. 6.Which of these is not AI? (a) video suggestions (b) a map predicting traffic (c) a calculator (d) an AI chatbot
  7. 7.📱 What is the AI doing here: a keyboard guessing your next word? (a) recognising (b) predicting (c) recommending (d) generating
  8. 8.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
  9. 9.✨ Generative or not: spotting a sick leaf? (a) sorts or predicts (b) makes something new
  10. 10.🏠 AI or not AI: a digital watch? (a) not AI (b) uses AI
  11. 11.✍️ How does an AI chatbot write its replies? (a) uses magic (b) copies one website (c) predicts likely words (d) asks a person
  12. 12.📱 What is the AI doing here: a video app suggesting what to watch next? (a) recognising (b) predicting (c) recommending (d) generating
  13. 13.🏠 AI or not AI: an AI chatbot? (a) uses AI (b) not AI
  14. 14.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  15. 15.True or false: “fix wrong labels” adds to bias. (a) True (b) False
  16. 16.Which of these is a prediction? (a) naming a new leaf (b) 500 labelled leaf photos (c) past weather records (d) old emails marked spam
  17. 17.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  18. 18.🧐 Fact or myth: “AI learns from data”? (a) a myth (b) a fact
  19. 19.True or false: “use one group only” helps reduce bias. (a) True (b) False
  20. 20.🧐 Fact or myth: “AI can be wrong”? (a) a myth (b) a fact
  21. 21.True or false: “ask different people” adds to bias. (a) True (b) False
  22. 22.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  23. 23.Which of these uses AI? (a) a fan regulator (b) a torch (c) a printed timetable (d) a map predicting traffic
  24. 24.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
  25. 25.🤖 What makes an AI system different from a normal program? (a) it learns from examples (b) it has a screen (c) it is always right (d) it uses electricity
  26. 26.🔍 Which is the odd one out? (a) drafting a letter (b) writing quiz questions (c) composing a new tune (d) sorting photos by face
  27. 27.🧮 Which of these is NOT AI? (a) face unlock (b) a spam filter (c) a basic calculator (d) voice typing
  28. 28.✨ Generative or not: writing a new poem? (a) makes something new (b) sorts or predicts
  29. 29.📱 What is the AI doing here: an online shop showing “you may also like”? (a) predicting (b) generating (c) recognising (d) recommending
  30. 30.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
  31. 31.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
  32. 32.True or false: “improves with more data” describes how AI works. (a) False (b) True
  33. 33.🔍 Which is the odd one out? (a) AI knows everything (b) long answers are true (c) AI can be wrong (d) AI is never wrong
  34. 34.⏩ In machine learning, which comes first: tomorrow’s rain guess or labelled fruit photos? (a) tomorrow’s rain guess (b) labelled fruit photos
  35. 35.🧐 Fact or myth: “confident means correct”? (a) a myth (b) a fact
  36. 36.Which of these is AI that sorts, spots or predicts (not generative)? (a) inventing a recipe (b) spotting a sick leaf (c) composing a new tune (d) writing a new poem
  37. 37.✨ Generative or not: unlocking with a face? (a) makes something new (b) sorts or predicts
  38. 38.True or false: “a summary of chapter 3” asks for text. (a) True (b) False
  39. 39.True or false: “a logo idea for the eco club” asks for an image. (a) True (b) False
  40. 40.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) only one kind of example (d) examples of every type

Answer key

  1. to see if it works
  2. bad for training
  3. artificial intelligence
  4. True
  5. it learns patterns
  6. a calculator
  7. predicting
  8. reduces bias
  9. sorts or predicts
  10. not AI
  11. predicts likely words
  12. recommending
  13. uses AI
  14. False
  15. False
  16. naming a new leaf
  17. training data
  18. a fact
  19. False
  20. a fact
  21. False
  22. 500 labelled leaf photos
  23. a map predicting traffic
  24. False
  25. it learns from examples
  26. sorting photos by face
  27. a basic calculator
  28. makes something new
  29. recommending
  30. AI
  31. bad for training
  32. True
  33. AI can be wrong
  34. labelled fruit photos
  35. a myth
  36. spotting a sick leaf
  37. sorts or predicts
  38. True
  39. True
  40. examples of every type

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