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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 261 · 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.🏠 AI or not AI: an app translating signs? (a) not AI (b) uses AI
  2. 2.Which of these is training data? (a) flagging a new email (b) tomorrow’s rain guess (c) labelled fruit photos (d) the learned patterns
  3. 3.Which of these is bad for training a model? (a) many varied examples (b) examples of every type (c) new data for testing (d) blurry, unclear photos
  4. 4.True or false: “correct labels” is good for training a model. (a) False (b) True
  5. 5.True or false: suggesting the next word as you type only needs a simple fixed rule. (a) False (b) True
  6. 6.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
  7. 7.🏠 AI or not AI: a light switch? (a) uses AI (b) not AI
  8. 8.🛠️ Which does this job need: adding up the marks on a report card? (a) needs AI (learning) (b) a simple rule is enough
  9. 9.⏩ 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
  10. 10.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
  11. 11.🔍 Which is the odd one out? (a) use one group only (b) fix wrong labels (c) test on one group only (d) copy old unfair choices
  12. 12.🛠️ Which does this job need: showing the time on a clock? (a) needs AI (learning) (b) a simple rule is enough
  13. 13.Which of these is a myth about AI? (a) AI knows everything (b) AI copies data patterns (c) AI can be wrong (d) AI answers need checking
  14. 14.✨ Generative or not: turning speech to text? (a) sorts or predicts (b) makes something new
  15. 15.✨ Generative or not: predicting rain? (a) makes something new (b) sorts or predicts
  16. 16.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  17. 17.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
  18. 18.🤖 Does an AI system think and feel like a person? (a) yes, it gets sad (b) only on weekends (c) yes, just like us (d) no, it finds patterns
  19. 19.Which of these describes how a normal program works? (a) same steps every time (b) learns from examples (c) handles unseen examples (d) improves with more data
  20. 20.Which of these helps reduce bias? (a) add more of the same (b) ignore complaints (c) test on many groups (d) copy old unfair choices
  21. 21.🤖 AI or a normal program: which one “makes a best guess”? (a) a normal program (b) AI
  22. 22.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) copy old unfair choices (d) add varied examples
  23. 23.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
  24. 24.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  25. 25.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) better at its task (d) slower to switch on
  26. 26.✅ Is this a real check of an AI answer: see if the book exists? (a) not a real check (b) a real check
  27. 27.🎨 This prompt asks a generative AI for: a summary of chapter 3. What kind of output is that? (a) text (b) an image (c) music or sound
  28. 28.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
  29. 29.True or false: an AI chatbot writing a poem about rain is AI generating something new. (a) True (b) False
  30. 30.📦 What happens during training? (a) it charges up (b) it takes photos (c) it prints labels (d) it learns patterns
  31. 31.🧮 Which of these is NOT AI? (a) voice typing (b) a spam filter (c) face unlock (d) a basic calculator
  32. 32.✅ Is this a real check of an AI answer: redo the maths yourself? (a) a real check (b) not a real check
  33. 33.📱 What is the AI doing here: a map app guessing how long a trip will take? (a) generating (b) predicting (c) recommending (d) recognising
  34. 34.🔍 Which is the odd one out? (a) creating a cartoon (b) sorting photos by face (c) writing quiz questions (d) writing a new poem
  35. 35.True or false: counting the words in an essay only needs a simple fixed rule. (a) False (b) True
  36. 36.📺 A video app suggests what to watch next. What is the AI doing? (a) recommending (b) printing (c) cooking (d) charging
  37. 37.Which of these describes how a normal program works? (a) gives a likely answer (b) makes a best guess (c) spots patterns in data (d) never learns from data
  38. 38.🔍 Which is the odd one out? (a) photos grouped by face (b) a microwave timer (c) a calculator (d) a fan regulator
  39. 39.📱 What is the AI doing here: a car camera reading a speed sign? (a) predicting (b) generating (c) recognising (d) recommending
  40. 40.True or false: “add varied examples” adds to bias. (a) False (b) True

Answer key

  1. uses AI
  2. labelled fruit photos
  3. blurry, unclear photos
  4. True
  5. False
  6. balanced data
  7. not AI
  8. a simple rule is enough
  9. 500 labelled leaf photos
  10. good for training
  11. fix wrong labels
  12. a simple rule is enough
  13. AI knows everything
  14. sorts or predicts
  15. sorts or predicts
  16. training data
  17. bad for training
  18. no, it finds patterns
  19. same steps every time
  20. test on many groups
  21. AI
  22. add varied examples
  23. spam
  24. False
  25. better at its task
  26. a real check
  27. text
  28. False
  29. True
  30. it learns patterns
  31. a basic calculator
  32. a real check
  33. predicting
  34. sorting photos by face
  35. True
  36. recommending
  37. never learns from data
  38. photos grouped by face
  39. recognising
  40. False

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