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AI for Students Worksheet: Final Test

AI for students lesson 24: Final test: AI for students · Set 786 · 40 questions
TalentJR

AI tip (Know it, prompt it, check it): Find the topic: what AI is, prompts, honest use, checking, privacy, age rules, fakes, credit, study, apps or projects. Use that lesson’s rule and read every option before you choose. For number questions, write the calculation first: words over = written − limit, accuracy = correct ÷ total × 100.

NameDateTime takenScore ___ / 40
  1. 1.✍️ Which prompt is clearer?
    A: “Food ideas?”
    B: “Suggest 5 healthy tiffin ideas for a 10-year-old, without nuts.”
    (a) Prompt A (b) Prompt B
  2. 2.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) True (b) False
  3. 3.📝 Honest use or copying: entering its poem in a writing competition as yours? (a) honest use (b) not honest
  4. 4.🛠️ Which does this job need: switching on a street light at 6 pm? (a) a simple rule is enough (b) needs AI (learning)
  5. 5.True or false: “labelled fruit photos” is the model. (a) False (b) True
  6. 6.⚖️ Where does bias in an AI system usually come from? (a) its training data (b) its screen size (c) its colour (d) the weather
  7. 7.Which of these is stage 1 (try it yourself)? (a) attempt it on paper (b) solve a new one alone (c) try a similar sum alone (d) do one more on your own
  8. 8.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
  9. 9.🔎 Before sharing a surprising post, which comes first — notice your feelings or report it if fake? (a) notice your feelings (b) report it if fake
  10. 10.True or false: stories where every doctor is a man is balanced data (fairer for everyone). (a) True (b) False
  11. 11.🛠️ Which is the improved prompt?
    A: “What is a noun?”
    B: “Explain what a noun is with 3 examples from a school day.”
    (a) Prompt A (b) Prompt B
  12. 12.True or false: sorting names in A to Z order only needs a simple fixed rule. (a) True (b) False
  13. 13.🖼️ Warning sign or good sign: a background that bends? (a) a good sign (b) a warning sign
  14. 14.🧐 Fact or myth: “AI can be wrong”? (a) a myth (b) a fact
  15. 15.🔍 Which is the odd one out? (a) a named author (b) no trusted source (c) shadows going two ways (d) a background that bends
  16. 16.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  17. 17.Which of these is the input? (a) the typed reply (b) your spoken words (c) the label “cat” (d) the trained AI part
  18. 18.🎂 Ask an adult first, or fine to do yourself: buying an add-on inside an app? (a) fine to do yourself (b) ask an adult first
  19. 19.True or false: “AI answers need checking” is a fact about AI. (a) True (b) False
  20. 20.True or false: “long answers are true” is a myth about AI. (a) True (b) False
  21. 21.🔍 Which is the odd one out? (a) “share before it’s gone” (b) six fingers on a hand (c) no trusted source (d) many trusted sources
  22. 22.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a strong battery (c) a fair model (d) a broken screen
  23. 23.🧩 “Act as a patient science teacher.” This sets the… (a) example (b) format (c) word limit (d) role
  24. 24.🖼️ Which sign can show a picture was AI-made? (a) a calm sky (b) six fingers on a hand (c) a named photographer (d) a clear caption
  25. 25.True or false: “in a formal tone” sets the style or tone. (a) False (b) True
  26. 26.🛠️ Which is the improved prompt?
    A: “Explain what a noun is with 3 examples from a school day.”
    B: “What is a noun?”
    (a) Prompt A (b) Prompt B
  27. 27.📺 A video app suggests what to watch next. What is the AI doing? (a) cooking (b) printing (c) charging (d) recommending
  28. 28.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
  29. 29.📖 An AI chatbot gives a quote and a source. What should you do? (a) add more quotes (b) delete your notes (c) copy it straight away (d) check the source is real
  30. 30.🔒 What happens to what you type into many AI apps? (a) it vanishes forever (b) it becomes secret (c) it turns into music (d) it may be stored
  31. 31.Which of these is stage 2 (ask for help)? (a) try the sum yourself (b) have a go on your own (c) solve a new one alone (d) ask how to start
  32. 32.🛠️ Which does this job need: suggesting the next word as you type? (a) a simple rule is enough (b) needs AI (learning)
  33. 33.🔍 Which is the odd one out? (a) asks your class level (b) asks for a password (c) urges you to click links (d) asks to keep a secret
  34. 34.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  35. 35.Which of these is bad for training a model? (a) examples of every type (b) wrong labels (c) many varied examples (d) photos in many lights
  36. 36.🛠️ Does this make a weak prompt better: add exclamation marks? (a) not a fix (b) a good fix
  37. 37.✍️ Clear or vague: “Make a checklist of 8 things to pack for a school trip to the hills.”? (a) vague (b) clear
  38. 38.✨ Generative or not: composing a new tune? (a) sorts or predicts (b) makes something new
  39. 39.📝 Honest use or copying: asking it to explain a sum you got wrong? (a) not honest (b) honest use
  40. 40.🖼️ Warning sign or good sign: too good to be true? (a) a warning sign (b) a good sign

Answer key

  1. Prompt B
  2. False
  3. not honest
  4. a simple rule is enough
  5. False
  6. its training data
  7. attempt it on paper
  8. False
  9. notice your feelings
  10. False
  11. Prompt B
  12. True
  13. a warning sign
  14. a fact
  15. a named author
  16. the trained program
  17. your spoken words
  18. ask an adult first
  19. True
  20. True
  21. many trusted sources
  22. bias from data
  23. role
  24. six fingers on a hand
  25. True
  26. Prompt A
  27. recommending
  28. adds to bias
  29. check the source is real
  30. it may be stored
  31. ask how to start
  32. needs AI (learning)
  33. asks your class level
  34. training data
  35. wrong labels
  36. not a fix
  37. clear
  38. makes something new
  39. honest use
  40. a warning sign

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