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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 528 · 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.✅ Is this a real check of an AI answer: find a trusted source? (a) a real check (b) not a real check
  2. 2.Which of these adds to bias? (a) check who is missing (b) add more of the same (c) add varied examples (d) balance the data
  3. 3.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
  4. 4.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will turn yellow (d) it will be perfect
  5. 5.True or false: an AI chatbot writing a poem about rain is AI predicting something. (a) True (b) False
  6. 6.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
  7. 7.Which of these is not AI? (a) a stopwatch (b) a voice assistant (c) video suggestions (d) a spam filter
  8. 8.Which of these is training data? (a) 500 labelled leaf photos (b) tomorrow’s rain guess (c) flagging a new email (d) the learned patterns
  9. 9.🧪 Why test a model on NEW examples? (a) to see if it works (b) to delete its data (c) to change its name (d) to make it slower
  10. 10.🔍 Which is the odd one out? (a) new data for testing (b) correct labels (c) blurry, unclear photos (d) clear, sharp examples
  11. 11.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
  12. 12.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) predicting (b) generating (c) recognising (d) recommending
  13. 13.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) ask different people (d) skip testing
  14. 14.🛠️ Which does this job need: suggesting the next word as you type? (a) a simple rule is enough (b) needs AI (learning)
  15. 15.True or false: “testing on training data” is good for training a model. (a) False (b) True
  16. 16.True or false: “copies of one photo” is good for training a model. (a) True (b) False
  17. 17.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) model, prediction, data (d) data, model, prediction
  18. 18.📦 What happens during training? (a) it takes photos (b) it prints labels (c) it learns patterns (d) it charges up
  19. 19.⏩ In machine learning, which comes first: what training builds or typing a new spoken word? (a) what training builds (b) typing a new spoken word
  20. 20.Which of these describes how AI works? (a) never learns from data (b) same steps every time (c) learns from examples (d) does exactly as coded
  21. 21.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  22. 22.🤖 AI or a normal program: which one “does exactly as coded”? (a) a normal program (b) AI
  23. 23.🔍 Which is the odd one out? (a) drawing a new picture (b) making up a story (c) inventing a recipe (d) spotting spam
  24. 24.🧮 Is a basic calculator an AI system? (a) only at night (b) yes, it is smart (c) no, it follows rules (d) yes, it can think
  25. 25.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
  26. 26.🔍 Which is the odd one out? (a) blurry, unclear photos (b) very few examples (c) many varied examples (d) only one kind of example
  27. 27.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
  28. 28.True or false: “never learns from data” describes how a normal program works. (a) False (b) True
  29. 29.🔍 Which is the odd one out? (a) long answers are true (b) AI learns from data (c) AI can be wrong (d) AI can make up facts
  30. 30.🔍 Which is the odd one out? (a) a map predicting traffic (b) voice typing (c) a stopwatch (d) an AI chatbot
  31. 31.Which of these is a fact about AI? (a) long answers are true (b) confident means correct (c) AI knows everything (d) AI can mix up numbers
  32. 32.Which of these is good for training a model? (a) very few examples (b) labels added at random (c) only one kind of example (d) examples of every type
  33. 33.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its screen size (d) its training data
  34. 34.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
  35. 35.🔍 Which is the odd one out? (a) face unlock on a phone (b) a light switch (c) a calculator (d) a doorbell
  36. 36.Which of these is generative AI (it makes something new)? (a) spotting a sick leaf (b) spotting spam (c) suggesting a video (d) drawing a new picture
  37. 37.🔍 Which is the odd one out? (a) use one group only (b) balance the data (c) ignore complaints (d) test on one group only
  38. 38.True or false: “same steps every time” describes how AI works. (a) True (b) False
  39. 39.🔍 Which is the odd one out? (a) AI can make up facts (b) AI always checks facts (c) confident means correct (d) AI is never wrong
  40. 40.Which of these describes how a normal program works? (a) makes a best guess (b) learns from examples (c) spots patterns in data (d) does exactly as coded

Answer key

  1. a real check
  2. add more of the same
  3. training data
  4. it may get it wrong
  5. False
  6. AI
  7. a stopwatch
  8. 500 labelled leaf photos
  9. to see if it works
  10. blurry, unclear photos
  11. balanced data
  12. recognising
  13. ask different people
  14. needs AI (learning)
  15. False
  16. False
  17. data, model, prediction
  18. it learns patterns
  19. what training builds
  20. learns from examples
  21. training data
  22. a normal program
  23. spotting spam
  24. no, it follows rules
  25. few child voices in data
  26. many varied examples
  27. True
  28. True
  29. long answers are true
  30. a stopwatch
  31. AI can mix up numbers
  32. examples of every type
  33. its training data
  34. not spam
  35. face unlock on a phone
  36. drawing a new picture
  37. balance the data
  38. False
  39. AI can make up facts
  40. does exactly as coded

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