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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 318 · 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: “match it to the textbook” is a real way to check an AI answer. (a) False (b) True
  2. 2.True or false: an image generator drawing a robot from a sentence is AI generating something new. (a) False (b) True
  3. 3.True or false: “a soft lullaby melody” asks for text. (a) True (b) False
  4. 4.True or false: “add varied examples” adds to bias. (a) False (b) True
  5. 5.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  6. 6.True or false: “improves with more data” describes how a normal program works. (a) False (b) True
  7. 7.🧪 Why test a model on NEW examples? (a) to change its name (b) to make it slower (c) to see if it works (d) to delete its data
  8. 8.Which of these is the model? (a) old emails marked spam (b) the trained program (c) 500 labelled leaf photos (d) tomorrow’s rain guess
  9. 9.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
  10. 10.Which of these is training data? (a) tomorrow’s rain guess (b) what training builds (c) naming a new fruit photo (d) past weather records
  11. 11.True or false: “labels added at random” is good for training a model. (a) False (b) True
  12. 12.Which of these is a prediction? (a) what training builds (b) past weather records (c) typing a new spoken word (d) 500 labelled leaf photos
  13. 13.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) prediction, data, model (d) data, prediction, model
  14. 14.🔍 Which is the odd one out? (a) a map predicting traffic (b) a voice assistant (c) an image generator (d) a doorbell
  15. 15.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) predicting (b) recommending (c) generating (d) recognising
  16. 16.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
  17. 17.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
  18. 18.🧮 Is a basic calculator an AI system? (a) yes, it can think (b) yes, it is smart (c) only at night (d) no, it follows rules
  19. 19.🏠 AI or not AI: a digital watch? (a) not AI (b) uses AI
  20. 20.🧐 Fact or myth: “AI can be wrong”? (a) a fact (b) a myth
  21. 21.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) training data (c) the model
  22. 22.True or false: ringing the school bell at 9 am needs AI that learns from examples. (a) False (b) True
  23. 23.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) check it on paper (b) copy it straight away (c) never do maths (d) ask it to hurry
  24. 24.True or false: reading messy handwriting only needs a simple fixed rule. (a) False (b) True
  25. 25.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) skip testing (d) test on many groups
  26. 26.🔍 Which is the odd one out? (a) ignore complaints (b) check who is missing (c) use one group only (d) skip testing
  27. 27.True or false: “it sounds very sure” is NOT a real way to check an AI answer. (a) False (b) True
  28. 28.Which of these is not AI? (a) video suggestions (b) an app translating signs (c) a light switch (d) an AI chatbot
  29. 29.📺 A video app suggests what to watch next. What is the AI doing? (a) printing (b) cooking (c) recommending (d) charging
  30. 30.🔍 Which is the odd one out? (a) an app translating signs (b) a microwave timer (c) video suggestions (d) a spam filter
  31. 31.Which of these helps reduce bias? (a) ignore complaints (b) add more of the same (c) skip testing (d) test on many groups
  32. 32.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
  33. 33.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
  34. 34.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) a song about dogs (d) many labelled photos
  35. 35.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
  36. 36.✨ Generative or not: inventing a recipe? (a) makes something new (b) sorts or predicts
  37. 37.Which of these describes how a normal program works? (a) learns from examples (b) makes a best guess (c) uses rules people wrote (d) spots patterns in data
  38. 38.True or false: an AI chatbot writing a poem about rain is AI recognising something. (a) False (b) True
  39. 39.🏠 AI or not AI: a spam filter? (a) not AI (b) uses AI
  40. 40.Which of these is training data? (a) tomorrow’s rain guess (b) naming a new leaf (c) naming a new fruit photo (d) labelled fruit photos

Answer key

  1. True
  2. True
  3. False
  4. False
  5. what training builds
  6. False
  7. to see if it works
  8. the trained program
  9. one-sided data
  10. past weather records
  11. False
  12. typing a new spoken word
  13. data, model, prediction
  14. a doorbell
  15. recognising
  16. one-sided data
  17. balanced data
  18. no, it follows rules
  19. not AI
  20. a fact
  21. a prediction
  22. False
  23. check it on paper
  24. False
  25. skip testing
  26. check who is missing
  27. True
  28. a light switch
  29. recommending
  30. a microwave timer
  31. test on many groups
  32. needs AI (learning)
  33. bad for training
  34. many labelled photos
  35. AI
  36. makes something new
  37. uses rules people wrote
  38. False
  39. uses AI
  40. labelled fruit photos

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