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AI for Students Worksheet: Final Test

AI for students lesson 24: Final test: AI for students · Set 746 · 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 does this job need: suggesting the next word as you type? (a) a simple rule is enough (b) needs AI (learning)
  2. 2.🔍 Which is the odd one out? (a) AI is never wrong (b) confident means correct (c) AI can be wrong (d) long answers are true
  3. 3.📚 Smart or poor way to study with AI: never checking mistakes? (a) poor study (b) smart study
  4. 4.📏 Nisha wants a 60-word answer split into 2 equal points. How many words should each point have?
  5. 5.Which of these is a myth about AI? (a) AI can be wrong (b) AI can make up facts (c) AI has real feelings (d) AI copies data patterns
  6. 6.True or false: “a drawing of a cat on the Moon” asks for music or sound. (a) True (b) False
  7. 7.📝 What is the best way to use AI for a hard maths chapter? (a) avoid the chapter (b) ask it to do all sums (c) ask it to explain (d) copy its answers
  8. 8.🤖 What does AI stand for? (a) actual information (b) app installer (c) automatic internet (d) artificial intelligence
  9. 9.True or false: “gives a likely answer” describes how a normal program works. (a) False (b) True
  10. 10.True or false: a clay model you built is your own work (no credit needed). (a) True (b) False
  11. 11.🔍 Which is the odd one out? (a) a printed timetable (b) an AI chatbot (c) an image generator (d) face unlock on a phone
  12. 12.🔍 Which is the odd one out? (a) add exclamation marks (b) add unrelated details (c) give an example (d) write it in capitals
  13. 13.True or false: “asking the same AI again” is NOT a real way to check an AI answer. (a) False (b) True
  14. 14.🤖 AI or a normal program: which one “improves with more data”? (a) AI (b) a normal program
  15. 15.🚩 A study chatbot says it may be wrong. Is that a red flag? (a) normal (b) a red flag
  16. 16.True or false: sorting names in A to Z order needs AI that learns from examples. (a) False (b) True
  17. 17.Which of these is a prediction? (a) the trained program (b) typing a new spoken word (c) recorded spoken words (d) old emails marked spam
  18. 18.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) labels added at random (d) clear, sharp examples
  19. 19.Which of these is good for training a model? (a) new data for testing (b) blurry, unclear photos (c) wrong labels (d) testing on training data
  20. 20.✍️ Clear or vague: “Fix it.”? (a) clear (b) vague
  21. 21.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  22. 22.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
  23. 23.🔍 Which is the odd one out? (a) AI learns from data (b) AI can make up facts (c) AI knows everything (d) AI can mix up numbers
  24. 24.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) a prediction (c) training data
  25. 25.True or false: a car camera reading a speed sign is AI recognising something. (a) False (b) True
  26. 26.📦 Meera collected 80 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
  27. 27.Which of these adds to bias? (a) add varied examples (b) test on many groups (c) check who is missing (d) ignore complaints
  28. 28.🔒 What can you safely ask an AI chatbot? (a) a friend’s phone number (b) a science doubt (c) your bank PIN (d) your home address
  29. 29.💬 Does this request help you learn, or do the work for you? “write my essay” (a) does it for you (b) helps you learn
  30. 30.🪜 Before asking AI for steps on homework, you should first… (a) ask for the answer (b) copy a friend (c) try it yourself (d) give up
  31. 31.True or false: “Like this: 2 + 3 = 5” is the format part of a prompt. (a) True (b) False
  32. 32.📅 An AI gives a date for a history event. How can you check? (a) ask it to repeat (b) guess (c) pick a lucky number (d) look in your textbook
  33. 33.Which of these requests helps you learn? (a) “finish my homework” (b) “define ‘orbit’ for me” (c) “answer all 10 sums” (d) “write my project”
  34. 34.True or false: “in very simple words” sets the reading level. (a) False (b) True
  35. 35.🛠️ Does this make a weak prompt better: say what it is for? (a) not a fix (b) a good fix
  36. 36.Which of these should be kept private — never share it with an AI chatbot? (a) a riddle to solve (b) your home address (c) a topic for a quiz (d) a grammar doubt
  37. 37.True or false: “correct labels” is good for training a model. (a) True (b) False
  38. 38.🎯 Meera’s handwriting reader is 60% accurate. If it is tested on 30 new handwritten letters, how many should it get right?
  39. 39.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
  40. 40.⏩ When you use an AI app, which happens first: you hum a tune or the reply appears? (a) you hum a tune (b) the reply appears

Answer key

  1. needs AI (learning)
  2. AI can be wrong
  3. poor study
  4. 30
  5. AI has real feelings
  6. False
  7. ask it to explain
  8. artificial intelligence
  9. False
  10. True
  11. a printed timetable
  12. give an example
  13. True
  14. AI
  15. normal
  16. False
  17. typing a new spoken word
  18. clear, sharp examples
  19. new data for testing
  20. vague
  21. the trained program
  22. not spam
  23. AI knows everything
  24. the model
  25. True
  26. 64
  27. ignore complaints
  28. a science doubt
  29. does it for you
  30. try it yourself
  31. False
  32. look in your textbook
  33. “define ‘orbit’ for me”
  34. True
  35. a good fix
  36. your home address
  37. True
  38. 18
  39. balanced data
  40. you hum a tune

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