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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 324 · 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.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) never do maths (b) copy it straight away (c) check it on paper (d) ask it to hurry
  2. 2.🔍 Which is the odd one out? (a) spotting spam (b) spotting a sick leaf (c) writing quiz questions (d) reading number plates
  3. 3.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  4. 4.📚 An AI chatbot names a book that does not exist. This is called… (a) a hallucination (b) a backup (c) a summary (d) a password
  5. 5.🏠 AI or not AI: a spam filter? (a) uses AI (b) not AI
  6. 6.🔍 Which is the odd one out? (a) an app translating signs (b) a printed timetable (c) a voice assistant (d) voice typing
  7. 7.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  8. 8.✨ Generative or not: unlocking with a face? (a) sorts or predicts (b) makes something new
  9. 9.True or false: “very few examples” is bad for training a model. (a) False (b) True
  10. 10.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
  11. 11.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  12. 12.🔍 Which is the odd one out? (a) fix wrong labels (b) add varied examples (c) ask different people (d) add more of the same
  13. 13.True or false: “what training builds” is a prediction. (a) True (b) False
  14. 14.Which of these is the model? (a) recorded spoken words (b) typing a new spoken word (c) past weather records (d) the learned patterns
  15. 15.✍️ How does an AI chatbot write its replies? (a) predicts likely words (b) copies one website (c) uses magic (d) asks a person
  16. 16.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) training data (d) a password
  17. 17.Which of these describes how AI works? (a) same steps every time (b) uses rules people wrote (c) spots patterns in data (d) follows fixed rules
  18. 18.True or false: “never learns from data” describes how a normal program works. (a) False (b) True
  19. 19.True or false: suggesting the next word as you type only needs a simple fixed rule. (a) False (b) True
  20. 20.True or false: a shop guessing how many umbrellas will sell is AI generating something new. (a) True (b) False
  21. 21.🔦 Is a torch with an on/off switch AI? (a) only if it is bright (b) no (c) yes
  22. 22.True or false: recognising a bird from its song needs AI that learns from examples. (a) True (b) False
  23. 23.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
  24. 24.Which of these adds to bias? (a) test on many groups (b) skip testing (c) ask different people (d) add varied examples
  25. 25.True or false: “the trained program” is a prediction. (a) True (b) False
  26. 26.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) photos in many lights (d) very few examples
  27. 27.Which of these describes how a normal program works? (a) same steps every time (b) spots patterns in data (c) makes a best guess (d) handles unseen examples
  28. 28.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  29. 29.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
  30. 30.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) balanced data (b) one-sided data
  31. 31.Which of these is the model? (a) the trained program (b) tomorrow’s rain guess (c) naming a new fruit photo (d) 500 labelled leaf photos
  32. 32.💬 What do we call the request you type to a generative AI? (a) a password (b) a label (c) a battery (d) a prompt
  33. 33.Which of these adds to bias? (a) balance the data (b) add varied examples (c) use one group only (d) test on many groups
  34. 34.True or false: “makes a best guess” describes how a normal program works. (a) False (b) True
  35. 35.🧐 Fact or myth: “AI knows everything”? (a) a fact (b) a myth
  36. 36.🔍 Which is the odd one out? (a) labels added at random (b) very few examples (c) checking labels twice (d) copies of one photo
  37. 37.True or false: recognising a friend’s face in photos needs AI that learns from examples. (a) True (b) False
  38. 38.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  39. 39.True or false: spotting spam emails by their patterns needs AI that learns from examples. (a) False (b) True
  40. 40.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training

Answer key

  1. check it on paper
  2. writing quiz questions
  3. reduces bias
  4. a hallucination
  5. uses AI
  6. a printed timetable
  7. adds to bias
  8. sorts or predicts
  9. True
  10. good for training
  11. training data
  12. add more of the same
  13. False
  14. the learned patterns
  15. predicts likely words
  16. a prediction
  17. spots patterns in data
  18. True
  19. False
  20. False
  21. no
  22. True
  23. makes something new
  24. skip testing
  25. False
  26. very few examples
  27. same steps every time
  28. a prediction
  29. False
  30. one-sided data
  31. the trained program
  32. a prompt
  33. use one group only
  34. False
  35. a myth
  36. checking labels twice
  37. True
  38. the model
  39. True
  40. good for training

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