← Part 1 test: what AI is lesson New set →

AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 215 · 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.🧐 Fact or myth: “AI always checks facts”? (a) a fact (b) a myth
  2. 2.True or false: spotting spam emails by their patterns only needs a simple fixed rule. (a) False (b) True
  3. 3.True or false: “long answers are true” is a myth about AI. (a) True (b) False
  4. 4.💬 What do we call the request you type to a generative AI? (a) a battery (b) a label (c) a prompt (d) a password
  5. 5.Which of these adds to bias? (a) balance the data (b) check who is missing (c) ask different people (d) skip testing
  6. 6.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
  7. 7.Which of these is training data? (a) naming a new fruit photo (b) flagging a new email (c) 500 labelled leaf photos (d) typing a new spoken word
  8. 8.📱 What is the AI doing here: a car camera reading a speed sign? (a) recognising (b) recommending (c) generating (d) predicting
  9. 9.True or false: “a poster of a rainforest” asks for an image. (a) False (b) True
  10. 10.🔍 Which is the odd one out? (a) an AI chatbot (b) an image generator (c) a voice assistant (d) a microwave timer
  11. 11.True or false: “AI knows everything” is a fact about AI. (a) True (b) False
  12. 12.🧐 Fact or myth: “AI is never wrong”? (a) a myth (b) a fact
  13. 13.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
  14. 14.🛠️ Which does this job need: counting the words in an essay? (a) needs AI (learning) (b) a simple rule is enough
  15. 15.🧪 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
  16. 16.Which of these is training data? (a) past weather records (b) the trained program (c) naming a new fruit photo (d) what training builds
  17. 17.🏠 AI or not AI: a doorbell? (a) not AI (b) uses AI
  18. 18.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  19. 19.🏠 AI or not AI: face unlock on a phone? (a) uses AI (b) not AI
  20. 20.🔍 Which is the odd one out? (a) confident means correct (b) AI can be wrong (c) AI is never wrong (d) long answers are true
  21. 21.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) recognising (b) generating (c) predicting (d) recommending
  22. 22.Which of these describes how AI works? (a) one set rule per case (b) handles unseen examples (c) never learns from data (d) same steps every time
  23. 23.🔍 Which is the odd one out? (a) a voice assistant (b) face unlock on a phone (c) a map predicting traffic (d) a light switch
  24. 24.✅ Is this a real check of an AI answer: match it to the textbook? (a) a real check (b) not a real check
  25. 25.True or false: “a drum beat for a dance” asks for text. (a) True (b) False
  26. 26.🔍 Which is the odd one out? (a) spotting a sick leaf (b) spotting spam (c) suggesting a video (d) making up a story
  27. 27.True or false: “the trained program” is the model. (a) False (b) True
  28. 28.🔍 Which is the odd one out? (a) long answers are true (b) AI has real feelings (c) AI is never wrong (d) AI can make up facts
  29. 29.True or false: ringing the school bell at 9 am only needs a simple fixed rule. (a) True (b) False
  30. 30.True or false: “ask different people” helps reduce bias. (a) False (b) True
  31. 31.True or false: “photos in many lights” is good for training a model. (a) False (b) True
  32. 32.🎨 An image generator makes a picture from… (a) a text description (b) the weather (c) a phone number (d) your password
  33. 33.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
  34. 34.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a prediction (c) a label error (d) a password
  35. 35.True or false: “recorded spoken words” is training data. (a) True (b) False
  36. 36.True or false: “AI always checks facts” is a fact about AI. (a) True (b) False
  37. 37.🥭 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 be perfect (d) it will turn yellow
  38. 38.🤖 AI or a normal program: which one “improves with more data”? (a) a normal program (b) AI
  39. 39.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  40. 40.🔍 Which is the odd one out? (a) use one group only (b) test on one group only (c) ignore complaints (d) balance the data

Answer key

  1. a myth
  2. False
  3. True
  4. a prompt
  5. skip testing
  6. bad for training
  7. 500 labelled leaf photos
  8. recognising
  9. True
  10. a microwave timer
  11. False
  12. a myth
  13. reduces bias
  14. a simple rule is enough
  15. to see if it works
  16. past weather records
  17. not AI
  18. training data
  19. uses AI
  20. AI can be wrong
  21. generating
  22. handles unseen examples
  23. a light switch
  24. a real check
  25. False
  26. making up a story
  27. True
  28. AI can make up facts
  29. True
  30. True
  31. True
  32. a text description
  33. bad for training
  34. a prediction
  35. True
  36. False
  37. it may get it wrong
  38. AI
  39. True
  40. balance the data

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students