← 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 634 · 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: “500 labelled leaf photos” is training data. (a) False (b) True
  2. 2.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
  3. 3.Which of these is the model? (a) flagging a new email (b) labelled fruit photos (c) 500 labelled leaf photos (d) the learned patterns
  4. 4.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) children speak too fast (d) few child voices in data
  5. 5.Which of these describes how AI works? (a) same steps every time (b) never learns from data (c) spots patterns in data (d) does exactly as coded
  6. 6.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
  7. 7.True or false: “long answers are true” is a fact about AI. (a) True (b) False
  8. 8.True or false: “match it to the textbook” is a real way to check an AI answer. (a) False (b) True
  9. 9.Which of these is bad for training a model? (a) checking labels twice (b) correct labels (c) testing on training data (d) examples of every type
  10. 10.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) predicting (b) generating (c) recommending (d) recognising
  11. 11.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
  12. 12.True or false: reading messy handwriting needs AI that learns from examples. (a) False (b) True
  13. 13.Which of these is not AI? (a) voice typing (b) a stopwatch (c) a map predicting traffic (d) face unlock on a phone
  14. 14.True or false: “AI can mix up numbers” is a fact about AI. (a) True (b) False
  15. 15.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  16. 16.Which of these helps reduce bias? (a) check who is missing (b) skip testing (c) add more of the same (d) ignore complaints
  17. 17.✅ Is this a real check of an AI answer: it has a neat layout? (a) a real check (b) not a real check
  18. 18.True or false: “a poster of a rainforest” asks for an image. (a) True (b) False
  19. 19.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
  20. 20.🔍 Which is the odd one out? (a) a digital watch (b) a torch (c) a kitchen weighing scale (d) face unlock on a phone
  21. 21.Which of these uses AI? (a) a doorbell (b) a printed timetable (c) a stopwatch (d) a voice assistant
  22. 22.Which of these describes how AI works? (a) one set rule per case (b) follows fixed rules (c) learns from examples (d) never learns from data
  23. 23.✨ Generative or not: making up a story? (a) makes something new (b) sorts or predicts
  24. 24.True or false: a music app suggesting a song you may like is AI recognising something. (a) False (b) True
  25. 25.📱 What is the AI doing here: a keyboard guessing your next word? (a) generating (b) recognising (c) recommending (d) predicting
  26. 26.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
  27. 27.True or false: “labelled fruit photos” is training data. (a) True (b) False
  28. 28.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) bias from data (d) a fair model
  29. 29.🛠️ Which does this job need: counting the words in an essay? (a) a simple rule is enough (b) needs AI (learning)
  30. 30.🤖 AI or a normal program: which one “spots patterns in data”? (a) AI (b) a normal program
  31. 31.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  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.✅ Is this a real check of an AI answer: it is long and detailed? (a) not a real check (b) a real check
  34. 34.True or false: “flagging a new email” is the model. (a) False (b) True
  35. 35.True or false: “a cheerful tune for Sports Day” asks for music or sound. (a) True (b) False
  36. 36.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
  37. 37.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  38. 38.Which of these is a fact about AI? (a) AI knows everything (b) AI always checks facts (c) AI has real feelings (d) AI can mix up numbers
  39. 39.Which of these is good for training a model? (a) labels added at random (b) wrong labels (c) blurry, unclear photos (d) correct labels
  40. 40.True or false: “improves with more data” describes how AI works. (a) True (b) False

Answer key

  1. True
  2. a normal program
  3. the learned patterns
  4. few child voices in data
  5. spots patterns in data
  6. True
  7. False
  8. True
  9. testing on training data
  10. recognising
  11. False
  12. True
  13. a stopwatch
  14. True
  15. 500 labelled leaf photos
  16. check who is missing
  17. not a real check
  18. True
  19. a normal program
  20. face unlock on a phone
  21. a voice assistant
  22. learns from examples
  23. makes something new
  24. False
  25. predicting
  26. bad for training
  27. True
  28. bias from data
  29. a simple rule is enough
  30. AI
  31. one-sided data
  32. a real check
  33. not a real check
  34. False
  35. True
  36. True
  37. what training builds
  38. AI can mix up numbers
  39. correct labels
  40. True

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