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AI for Students Worksheet: Final Test

AI for students lesson 24: Final test: AI for students · Set 641 · 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.True or false: a photo you took on the school trip is your own work (no credit needed). (a) False (b) True
  2. 2.✨ Generative or not: making up a story? (a) makes something new (b) sorts or predicts
  3. 3.🪜 Before asking AI for steps on homework, you should first… (a) try it yourself (b) give up (c) ask for the answer (d) copy a friend
  4. 4.Which of these is a good sign (but still check)? (a) six fingers on a hand (b) no date or author (c) matches the textbook (d) no trusted source
  5. 5.📏 What kind of constraint is “in 2 lines only”? (a) what to include (b) a reading level (c) a style or tone (d) a length limit
  6. 6.Which of these adds to bias? (a) add more of the same (b) add varied examples (c) ask different people (d) test on many groups
  7. 7.📚 An AI chatbot names a book that does not exist. This is called… (a) a password (b) a backup (c) a summary (d) a hallucination
  8. 8.🎯 Tara’s fruit sorter was tested on 4 new fruit photos and got 3 right. What is its accuracy in percent?
  9. 9.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
  10. 10.✍️ Clear or vague: “Food ideas?”? (a) vague (b) clear
  11. 11.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) predicting (b) recommending (c) recognising (d) generating
  12. 12.🤖 AI or a normal program: which one “improves with more data”? (a) AI (b) a normal program
  13. 13.🏠 AI or not AI: a calculator? (a) uses AI (b) not AI
  14. 14.📝 You used AI to get ideas for a project. What is honest? (a) say it is all yours (b) hide it (c) say how you used it (d) blame the AI
  15. 15.True or false: “very few examples” is good for training a model. (a) False (b) True
  16. 16.Which of these is a good source to check against? (a) a random comment (b) a government website (c) an anonymous post (d) a forwarded message
  17. 17.True or false: “matches key words” describes a rule-based chatbot. (a) False (b) True
  18. 18.Which of these should be kept private — never share it with an AI chatbot? (a) a topic for a quiz (b) a one-time password (c) a maths sum to explain (d) a word you don’t know
  19. 19.🔁 Learning a hard sum with AI: which should you do first — ask for one hint or try a similar sum alone? (a) ask for one hint (b) try a similar sum alone
  20. 20.🧮 Is a basic calculator an AI system? (a) yes, it can think (b) only at night (c) yes, it is smart (d) no, it follows rules
  21. 21.🔒 Keep it private or okay to share with an AI chatbot: a bank card number? (a) okay to share (b) keep it private
  22. 22.True or false: a quote from a library book in your essay is your own work (no credit needed). (a) True (b) False
  23. 23.⏩ When you use an AI app, which happens first: the answer is shown or the model makes a guess? (a) the answer is shown (b) the model makes a guess
  24. 24.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI learns from data (c) AI answers need checking (d) AI knows everything
  25. 25.🔒 An AI chatbot asks for your home address. What should you do? (a) give a friend’s (b) say no, tell an adult (c) share it quickly (d) share half of it
  26. 26.True or false: joining an online AI contest is fine to do by yourself. (a) True (b) False
  27. 27.Which of these is a myth about AI? (a) AI is never wrong (b) AI answers need checking (c) AI can make up facts (d) AI can be wrong
  28. 28.🛠️ Does this make a weak prompt better: say the format you want? (a) not a fix (b) a good fix
  29. 29.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
  30. 30.📖 Is this a good source to check an AI answer against: an anonymous post? (a) not a good source (b) a good source
  31. 31.🤖 What makes an AI system different from a normal program? (a) it learns from examples (b) it is always right (c) it uses electricity (d) it has a screen
  32. 32.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
  33. 33.🔍 Which is the odd one out? (a) suggesting a video (b) drafting a letter (c) writing quiz questions (d) making up a story
  34. 34.Which of these is a fact about AI? (a) AI knows everything (b) AI can make up facts (c) confident means correct (d) AI has real feelings
  35. 35.True or false: a shop guessing how many umbrellas will sell is AI recommending something. (a) False (b) True
  36. 36.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
  37. 37.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) test on one group only (d) fix wrong labels
  38. 38.📷 The app replies “neem leaf”. That reply is the… (a) output (b) training data (c) input
  39. 39.🧐 Fact or myth: “AI can be wrong”? (a) a myth (b) a fact
  40. 40.🧪 You can plan a simple AI project with… (a) only a big robot (b) a secret password (c) paper and examples (d) nothing at all

Answer key

  1. True
  2. makes something new
  3. try it yourself
  4. matches the textbook
  5. a length limit
  6. add more of the same
  7. a hallucination
  8. 75
  9. one-sided data
  10. vague
  11. predicting
  12. AI
  13. not AI
  14. say how you used it
  15. False
  16. a government website
  17. True
  18. a one-time password
  19. ask for one hint
  20. no, it follows rules
  21. keep it private
  22. False
  23. the model makes a guess
  24. AI knows everything
  25. say no, tell an adult
  26. False
  27. AI is never wrong
  28. a good fix
  29. reduces bias
  30. not a good source
  31. it learns from examples
  32. True
  33. suggesting a video
  34. AI can make up facts
  35. False
  36. its training data
  37. fix wrong labels
  38. output
  39. a fact
  40. paper and examples

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