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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 708 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
  2. 2.🔍 Which is the odd one out? (a) AI can make up facts (b) AI learns from data (c) AI answers need checking (d) long answers are true
  3. 3.📱 What is the AI doing here: a shop guessing how many umbrellas will sell? (a) generating (b) predicting (c) recommending (d) recognising
  4. 4.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) better at its task (d) forget everything
  5. 5.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
  6. 6.True or false: “ignore complaints” helps reduce bias. (a) False (b) True
  7. 7.✍️ How does an AI chatbot write its replies? (a) copies one website (b) asks a person (c) predicts likely words (d) uses magic
  8. 8.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a list of rules only (d) a song about dogs
  9. 9.🔍 Which is the odd one out? (a) spotting a sick leaf (b) making up a story (c) writing quiz questions (d) drawing a new picture
  10. 10.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
  11. 11.True or false: a weather app guessing tomorrow’s rain is AI generating something new. (a) True (b) False
  12. 12.📱 What is the AI doing here: turning your spoken words into typed text? (a) recognising (b) predicting (c) generating (d) recommending
  13. 13.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
  14. 14.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
  15. 15.🤖 Who builds and trains AI systems? (a) the weather (b) the Moon (c) people (d) nobody at all
  16. 16.True or false: “follows fixed rules” describes how AI works. (a) True (b) False
  17. 17.Which of these describes how a normal program works? (a) same steps every time (b) gives a likely answer (c) improves with more data (d) handles unseen examples
  18. 18.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
  19. 19.True or false: “use one group only” adds to bias. (a) False (b) True
  20. 20.🛠️ Which does this job need: sorting names in A to Z order? (a) a simple rule is enough (b) needs AI (learning)
  21. 21.Which of these helps reduce bias? (a) fix wrong labels (b) ignore complaints (c) copy old unfair choices (d) skip testing
  22. 22.📦 What happens during training? (a) it learns patterns (b) it takes photos (c) it charges up (d) it prints labels
  23. 23.Which of these is training data? (a) flagging a new email (b) tomorrow’s rain guess (c) typing a new spoken word (d) 500 labelled leaf photos
  24. 24.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  25. 25.True or false: photos of people from only one age group is balanced data (fairer for everyone). (a) True (b) False
  26. 26.🧮 Is a basic calculator an AI system? (a) yes, it is smart (b) only at night (c) yes, it can think (d) no, it follows rules
  27. 27.Which of these uses AI? (a) a kitchen weighing scale (b) voice typing (c) a printed timetable (d) a microwave timer
  28. 28.🔍 Which is the odd one out? (a) confident means correct (b) AI has real feelings (c) AI is never wrong (d) AI answers need checking
  29. 29.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) sleeping (b) predicting (c) singing (d) drawing
  30. 30.Which of these is a fact about AI? (a) AI is never wrong (b) AI has real feelings (c) AI knows everything (d) AI copies data patterns
  31. 31.🔍 Which is the odd one out? (a) inventing a recipe (b) unlocking with a face (c) reading number plates (d) suggesting a video
  32. 32.🤖 AI or a normal program: which one “never learns from data”? (a) AI (b) a normal program
  33. 33.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  34. 34.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) ask it to hurry (b) copy it straight away (c) never do maths (d) check it on paper
  35. 35.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
  36. 36.Which of these is good for training a model? (a) clear, sharp examples (b) very few examples (c) only one kind of example (d) wrong labels
  37. 37.🤖 AI or a normal program: which one “handles unseen examples”? (a) a normal program (b) AI
  38. 38.Which of these describes how AI works? (a) one set rule per case (b) does exactly as coded (c) spots patterns in data (d) same steps every time
  39. 39.True or false: “test on one group only” adds to bias. (a) False (b) True
  40. 40.Which of these is the model? (a) what training builds (b) naming a new leaf (c) naming a new fruit photo (d) labelled fruit photos

Answer key

  1. not spam
  2. long answers are true
  3. predicting
  4. better at its task
  5. True
  6. False
  7. predicts likely words
  8. many labelled photos
  9. spotting a sick leaf
  10. False
  11. False
  12. recognising
  13. good for training
  14. good for training
  15. people
  16. False
  17. same steps every time
  18. not spam
  19. True
  20. a simple rule is enough
  21. fix wrong labels
  22. it learns patterns
  23. 500 labelled leaf photos
  24. training data
  25. False
  26. no, it follows rules
  27. voice typing
  28. AI answers need checking
  29. predicting
  30. AI copies data patterns
  31. inventing a recipe
  32. a normal program
  33. training data
  34. check it on paper
  35. False
  36. clear, sharp examples
  37. AI
  38. spots patterns in data
  39. True
  40. what training builds

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