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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 154 · 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 bad for training a model? (a) examples of every type (b) clear, sharp examples (c) only one kind of example (d) checking labels twice
  2. 2.🔍 Which is the odd one out? (a) AI learns from data (b) AI can mix up numbers (c) AI copies data patterns (d) AI knows everything
  3. 3.Which of these describes how AI works? (a) one set rule per case (b) gives a likely answer (c) follows fixed rules (d) does exactly as coded
  4. 4.True or false: translating a sentence into Hindi needs AI that learns from examples. (a) True (b) False
  5. 5.📦 What happens during training? (a) it takes photos (b) it prints labels (c) it charges up (d) it learns patterns
  6. 6.🧮 Which of these is NOT AI? (a) a basic calculator (b) a spam filter (c) voice typing (d) face unlock
  7. 7.Which of these is good for training a model? (a) copies of one photo (b) new data for testing (c) only one kind of example (d) wrong labels
  8. 8.Which of these is good for training a model? (a) blurry, unclear photos (b) many varied examples (c) labels added at random (d) testing on training data
  9. 9.Which of these is not AI? (a) a map predicting traffic (b) an app translating signs (c) a calculator (d) a voice assistant
  10. 10.🔍 Which is the odd one out? (a) testing on training data (b) very few examples (c) labels added at random (d) clear, sharp examples
  11. 11.📱 What is the AI doing here: a car camera reading a speed sign? (a) recommending (b) generating (c) recognising (d) predicting
  12. 12.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to change its name (d) to delete its data
  13. 13.🤖 AI or a normal program: which one “never learns from data”? (a) a normal program (b) AI
  14. 14.🧐 Fact or myth: “AI can make up facts”? (a) a myth (b) a fact
  15. 15.True or false: “the learned patterns” is training data. (a) False (b) True
  16. 16.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, model, prediction (d) data, prediction, model
  17. 17.🏠 AI or not AI: an app translating signs? (a) not AI (b) uses AI
  18. 18.True or false: “asking the same AI again” is NOT a real way to check an AI answer. (a) True (b) False
  19. 19.True or false: “does exactly as coded” describes how AI works. (a) False (b) True
  20. 20.True or false: “a picture of a castle made of mangoes” asks for an image. (a) False (b) True
  21. 21.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) copies of one photo (d) checking labels twice
  22. 22.🔍 Which is the odd one out? (a) a fan regulator (b) a kitchen weighing scale (c) a map predicting traffic (d) a doorbell
  23. 23.Which of these describes how AI works? (a) learns from examples (b) follows fixed rules (c) same steps every time (d) one set rule per case
  24. 24.🔍 Which is the odd one out? (a) a stopwatch (b) an image generator (c) a kitchen weighing scale (d) a torch
  25. 25.🔍 Which is the odd one out? (a) long answers are true (b) AI has real feelings (c) AI can mix up numbers (d) AI is never wrong
  26. 26.✅ Is this a real check of an AI answer: redo the maths yourself? (a) a real check (b) not a real check
  27. 27.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  28. 28.True or false: “it is long and detailed” is NOT a real way to check an AI answer. (a) False (b) True
  29. 29.Which of these is training data? (a) the trained program (b) the learned patterns (c) what training builds (d) labelled fruit photos
  30. 30.Which of these describes how AI works? (a) one set rule per case (b) never learns from data (c) uses rules people wrote (d) improves with more data
  31. 31.Which of these is a fact about AI? (a) AI always checks facts (b) AI can make up facts (c) AI knows everything (d) long answers are true
  32. 32.🔍 Which is the odd one out? (a) check who is missing (b) fix wrong labels (c) ignore complaints (d) test on many groups
  33. 33.Which of these describes how AI works? (a) uses rules people wrote (b) same steps every time (c) one set rule per case (d) makes a best guess
  34. 34.🏷️ 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
  35. 35.🔍 Which is the odd one out? (a) a doorbell (b) photos grouped by face (c) a calculator (d) a microwave timer
  36. 36.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) the weather (c) its screen size (d) its colour
  37. 37.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) balance the data (d) use one group only
  38. 38.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) drawing (c) predicting (d) sleeping
  39. 39.True or false: “correct labels” is good for training a model. (a) True (b) False
  40. 40.Which of these is the model? (a) past weather records (b) what training builds (c) naming a new fruit photo (d) naming a new leaf

Answer key

  1. only one kind of example
  2. AI knows everything
  3. gives a likely answer
  4. True
  5. it learns patterns
  6. a basic calculator
  7. new data for testing
  8. many varied examples
  9. a calculator
  10. clear, sharp examples
  11. recognising
  12. to see if it works
  13. a normal program
  14. a fact
  15. False
  16. data, model, prediction
  17. uses AI
  18. True
  19. False
  20. True
  21. copies of one photo
  22. a map predicting traffic
  23. learns from examples
  24. an image generator
  25. AI can mix up numbers
  26. a real check
  27. training data
  28. True
  29. labelled fruit photos
  30. improves with more data
  31. AI can make up facts
  32. ignore complaints
  33. makes a best guess
  34. not spam
  35. photos grouped by face
  36. its training data
  37. balance the data
  38. predicting
  39. True
  40. what training builds

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