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AI for Students Worksheet: Final Test

AI for students lesson 24: Final test: AI for students · Set 229 · 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.©️ Whose work is it: a cartoon from a comic? (a) someone else’s work (b) my own work
  2. 2.©️ Whose work is it: a story I made up? (a) someone else’s work (b) my own work
  3. 3.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
  4. 4.Which of these helps reduce bias? (a) ignore complaints (b) skip testing (c) add varied examples (d) copy old unfair choices
  5. 5.Which of these makes a weak prompt better? (a) leave out the topic (b) type it twice (c) add your class level (d) make it vaguer
  6. 6.True or false: “asks to meet in person” is normal for a study chatbot. (a) False (b) True
  7. 7.📚 Smart or poor way to study with AI: check summaries in books? (a) smart study (b) poor study
  8. 8.✍️ Which prompt is clearer?
    A: “Tell me about laws.”
    B: “Describe how a bill becomes a law in India in 5 simple steps.”
    (a) Prompt A (b) Prompt B
  9. 9.True or false: “use one group only” adds to bias. (a) False (b) True
  10. 10.True or false: reading your school’s rules on AI is fine to do by yourself. (a) True (b) False
  11. 11.🔍 Which is the odd one out? (a) wrong labels (b) only one kind of example (c) copies of one photo (d) clear, sharp examples
  12. 12.True or false: “Explain how rainbows form.” is the task part of a prompt. (a) False (b) True
  13. 13.💬 Rule-based or learning chatbot: “learns from examples”? (a) learning (b) rule-based
  14. 14.📖 Is this a good source to check an AI answer against: a funny meme? (a) a good source (b) not a good source
  15. 15.🔎 Checking an AI answer: which do you do first — find the same topic or fix your notes? (a) find the same topic (b) fix your notes
  16. 16.Which of these is a poor way to study with AI? (a) mix AI and real practice (b) answer before peeking (c) redo wrong questions (d) copying cards unread
  17. 17.Which of these is normal for a study chatbot? (a) asks to keep a secret (b) asks for photos of you (c) asks for your address (d) offers a quiz
  18. 18.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its training data (d) its colour
  19. 19.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) data, model, prediction (d) model, prediction, data
  20. 20.🧮 Is a basic calculator an AI system? (a) no, it follows rules (b) only at night (c) yes, it can think (d) yes, it is smart
  21. 21.🧩 Which part of a prompt is this? “Act as a friendly maths tutor.” (a) role (b) context (c) example (d) format
  22. 22.True or false: “a story about a brave ant” asks for text. (a) False (b) True
  23. 23.🛠️ Which is the improved prompt?
    A: “Speaking tips.”
    B: “Give 4 tips to speak confidently in assembly, in simple words.”
    (a) Prompt A (b) Prompt B
  24. 24.Which of these is a prediction? (a) the trained program (b) what training builds (c) old emails marked spam (d) naming a new leaf
  25. 25.Which of these is a fact about AI? (a) AI always checks facts (b) AI copies data patterns (c) AI knows everything (d) confident means correct
  26. 26.True or false: “in 2 lines only” sets the style or tone. (a) False (b) True
  27. 27.🔍 Which is the odd one out? (a) a stopwatch (b) voice typing (c) a kitchen weighing scale (d) a digital watch
  28. 28.🔎 Before sharing a surprising post, which comes first — check the author or share only if true? (a) check the author (b) share only if true
  29. 29.Which of these is the model? (a) the trained program (b) flagging a new email (c) typing a new spoken word (d) recorded spoken words
  30. 30.✍️ Which prompt is clearer?
    A: “Write a polite 3-line message asking my teacher for extra practice sheets.”
    B: “Write a message.”
    (a) Prompt A (b) Prompt B
  31. 31.True or false: “naming a new fruit photo” is the model. (a) True (b) False
  32. 32.©️ Whose work is it: a poet’s famous poem? (a) my own work (b) someone else’s work
  33. 33.🧩 Which part of a prompt is this? “I have a test on Friday.” (a) example (b) task (c) context (d) role
  34. 34.True or false: “I have a test on Friday.” is the context part of a prompt. (a) True (b) False
  35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
  36. 36.©️ Does this need credit: a chart you made from your own data? (a) your own work (b) needs credit
  37. 37.🔍 Which is the odd one out? (a) my own survey results (b) a photo I took (c) a map from an atlas (d) a clay model I built
  38. 38.🔍 Which is the odd one out? (a) your live location (b) a maths sum to explain (c) your home address (d) a friend’s secret
  39. 39.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  40. 40.🎯 Vihaan’s recycling sorter was tested on 25 new waste photos and got 22 right. What is its accuracy in percent?

Answer key

  1. someone else’s work
  2. my own work
  3. bad for training
  4. add varied examples
  5. add your class level
  6. False
  7. smart study
  8. Prompt B
  9. True
  10. True
  11. clear, sharp examples
  12. True
  13. learning
  14. not a good source
  15. find the same topic
  16. copying cards unread
  17. offers a quiz
  18. its training data
  19. data, model, prediction
  20. no, it follows rules
  21. role
  22. True
  23. Prompt B
  24. naming a new leaf
  25. AI copies data patterns
  26. False
  27. voice typing
  28. check the author
  29. the trained program
  30. Prompt A
  31. False
  32. someone else’s work
  33. context
  34. True
  35. not spam
  36. your own work
  37. a map from an atlas
  38. a maths sum to explain
  39. training data
  40. 88

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