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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 573 · 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.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  2. 2.🧪 Why test a model on NEW examples? (a) to change its name (b) to make it slower (c) to delete its data (d) to see if it works
  3. 3.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a label error (d) a prediction
  4. 4.📚 An AI chatbot names a book that does not exist. This is called… (a) a backup (b) a summary (c) a password (d) a hallucination
  5. 5.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) model, prediction, data (d) data, prediction, model
  6. 6.🤖 What makes an AI system different from a normal program? (a) it uses electricity (b) it learns from examples (c) it is always right (d) it has a screen
  7. 7.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
  8. 8.🧠 Machine learning is a way for computers to… (a) print pages (b) clean screens (c) learn from data (d) charge faster
  9. 9.Which of these is a fact about AI? (a) AI has real feelings (b) AI always checks facts (c) AI knows everything (d) AI can make up facts
  10. 10.Which of these helps reduce bias? (a) use one group only (b) test on one group only (c) add more of the same (d) ask different people
  11. 11.⏩ In machine learning, which comes first: the learned patterns or typing a new spoken word? (a) the learned patterns (b) typing a new spoken word
  12. 12.🔍 Which is the odd one out? (a) spotting a sick leaf (b) unlocking with a face (c) predicting rain (d) writing a new poem
  13. 13.Which of these is a prediction? (a) past weather records (b) flagging a new email (c) what training builds (d) 500 labelled leaf photos
  14. 14.📱 What is the AI doing here: turning your spoken words into typed text? (a) recognising (b) generating (c) predicting (d) recommending
  15. 15.🎨 An image generator makes a picture from… (a) the weather (b) a phone number (c) your password (d) a text description
  16. 16.🔢 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) check it on paper (d) never do maths
  17. 17.Which of these describes how AI works? (a) does exactly as coded (b) learns from examples (c) follows fixed rules (d) never learns from data
  18. 18.🔍 Which is the odd one out? (a) face unlock on a phone (b) a stopwatch (c) a light switch (d) a calculator
  19. 19.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
  20. 20.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it may get it wrong (c) it will shut down (d) it will be perfect
  21. 21.🎨 This prompt asks a generative AI for: a logo idea for the eco club. What kind of output is that? (a) music or sound (b) text (c) an image
  22. 22.🔍 Which is the odd one out? (a) AI answers need checking (b) confident means correct (c) AI can make up facts (d) AI can mix up numbers
  23. 23.🔍 Which is the odd one out? (a) reading number plates (b) drafting a letter (c) creating a cartoon (d) making up a story
  24. 24.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
  25. 25.Which of these is the model? (a) the trained program (b) past weather records (c) old emails marked spam (d) 500 labelled leaf photos
  26. 26.🤖 What does AI stand for? (a) automatic internet (b) app installer (c) artificial intelligence (d) actual information
  27. 27.✅ Is this a real check of an AI answer: see if the book exists? (a) not a real check (b) a real check
  28. 28.✅ Is this a real check of an AI answer: it is long and detailed? (a) not a real check (b) a real check
  29. 29.True or false: “same steps every time” describes how a normal program works. (a) False (b) True
  30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
  31. 31.📦 What happens during training? (a) it prints labels (b) it charges up (c) it takes photos (d) it learns patterns
  32. 32.Which of these is AI that sorts, spots or predicts (not generative)? (a) reading number plates (b) writing a new poem (c) creating a cartoon (d) drawing a new picture
  33. 33.🔍 Which is the odd one out? (a) a stopwatch (b) photos grouped by face (c) a light switch (d) a calculator
  34. 34.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  35. 35.True or false: “makes a best guess” describes how AI works. (a) False (b) True
  36. 36.True or false: “AI learns from data” is a myth about AI. (a) False (b) True
  37. 37.True or false: “ignore complaints” adds to bias. (a) False (b) True
  38. 38.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
  39. 39.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
  40. 40.🔍 Which is the odd one out? (a) AI has real feelings (b) long answers are true (c) AI knows everything (d) AI answers need checking

Answer key

  1. a prediction
  2. to see if it works
  3. a prediction
  4. a hallucination
  5. data, model, prediction
  6. it learns from examples
  7. good for training
  8. learn from data
  9. AI can make up facts
  10. ask different people
  11. the learned patterns
  12. writing a new poem
  13. flagging a new email
  14. recognising
  15. a text description
  16. check it on paper
  17. learns from examples
  18. face unlock on a phone
  19. its training data
  20. it may get it wrong
  21. an image
  22. confident means correct
  23. reading number plates
  24. few child voices in data
  25. the trained program
  26. artificial intelligence
  27. a real check
  28. not a real check
  29. True
  30. not spam
  31. it learns patterns
  32. reading number plates
  33. photos grouped by face
  34. balanced data
  35. True
  36. False
  37. True
  38. True
  39. bad for training
  40. AI answers need checking

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