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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 561 · 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.True or false: “AI always checks facts” is a fact about AI. (a) False (b) True
  2. 2.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  3. 3.Which of these is bad for training a model? (a) correct labels (b) clear, sharp examples (c) only one kind of example (d) checking labels twice
  4. 4.✅ Is this a real check of an AI answer: it has a neat layout? (a) a real check (b) not a real check
  5. 5.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) checking labels twice (d) only one kind of example
  6. 6.True or false: a car camera reading a speed sign is AI predicting something. (a) True (b) False
  7. 7.🎨 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
  8. 8.🧐 Fact or myth: “AI knows everything”? (a) a myth (b) a fact
  9. 9.Which of these is generative AI (it makes something new)? (a) drawing a new picture (b) predicting rain (c) unlocking with a face (d) reading number plates
  10. 10.True or false: translating a sentence into Hindi needs AI that learns from examples. (a) False (b) True
  11. 11.📺 A video app suggests what to watch next. What is the AI doing? (a) printing (b) recommending (c) charging (d) cooking
  12. 12.Which of these describes how AI works? (a) follows fixed rules (b) does exactly as coded (c) improves with more data (d) never learns from data
  13. 13.True or false: “AI can be wrong” is a fact about AI. (a) True (b) False
  14. 14.🧐 Fact or myth: “AI can make up facts”? (a) a fact (b) a myth
  15. 15.✨ What does generative AI do? (a) only adds numbers (b) only stores files (c) makes new content (d) charges batteries
  16. 16.Which of these is training data? (a) flagging a new email (b) old emails marked spam (c) the trained program (d) what training builds
  17. 17.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) never do maths (b) ask it to hurry (c) copy it straight away (d) check it on paper
  18. 18.True or false: “makes a best guess” describes how a normal program works. (a) False (b) True
  19. 19.Which of these is training data? (a) the learned patterns (b) typing a new spoken word (c) what training builds (d) labelled fruit photos
  20. 20.Which of these is good for training a model? (a) copies of one photo (b) blurry, unclear photos (c) labels added at random (d) correct labels
  21. 21.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) one-sided data (b) balanced data
  22. 22.True or false: “handles unseen examples” describes how a normal program works. (a) False (b) True
  23. 23.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  24. 24.🏷️ 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) not spam (b) spam
  25. 25.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) balance the data (d) skip testing
  26. 26.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
  27. 27.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
  28. 28.True or false: “same steps every time” describes how AI works. (a) True (b) False
  29. 29.🔍 Which is the odd one out? (a) a map predicting traffic (b) a stopwatch (c) an image generator (d) video suggestions
  30. 30.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) better at its task (d) slower to switch on
  31. 31.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the textbook (b) stop studying (c) trust the AI (d) share it online
  32. 32.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
  34. 34.🛠️ Which does this job need: counting the words in an essay? (a) a simple rule is enough (b) needs AI (learning)
  35. 35.True or false: a map app guessing how long a trip will take is AI predicting something. (a) True (b) False
  36. 36.Which of these is training data? (a) naming a new leaf (b) 500 labelled leaf photos (c) tomorrow’s rain guess (d) flagging a new email
  37. 37.⏩ In machine learning, which comes first: naming a new fruit photo or 500 labelled leaf photos? (a) naming a new fruit photo (b) 500 labelled leaf photos
  38. 38.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
  39. 39.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will be perfect (d) it will shut down
  40. 40.Which of these describes how AI works? (a) follows fixed rules (b) uses rules people wrote (c) does exactly as coded (d) makes a best guess

Answer key

  1. False
  2. the model
  3. only one kind of example
  4. not a real check
  5. only one kind of example
  6. False
  7. text
  8. a myth
  9. drawing a new picture
  10. True
  11. recommending
  12. improves with more data
  13. True
  14. a fact
  15. makes new content
  16. old emails marked spam
  17. check it on paper
  18. False
  19. labelled fruit photos
  20. correct labels
  21. one-sided data
  22. False
  23. True
  24. not spam
  25. skip testing
  26. True
  27. True
  28. False
  29. a stopwatch
  30. better at its task
  31. trust the textbook
  32. True
  33. not spam
  34. a simple rule is enough
  35. True
  36. 500 labelled leaf photos
  37. 500 labelled leaf photos
  38. many labelled photos
  39. it may get it wrong
  40. makes a best guess

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