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AI for Students Worksheet: Final Test

AI for students lesson 24: Final test: AI for students · Set 282 · 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 of these is the model? (a) naming a new leaf (b) what training builds (c) past weather records (d) labelled fruit photos
  2. 2.🔍 Which is the odd one out? (a) your phone number (b) a grammar doubt (c) your name and school (d) a one-time password
  3. 3.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  4. 4.Which of these describes how a normal program works? (a) never learns from data (b) learns from examples (c) improves with more data (d) gives a likely answer
  5. 5.🔁 Learning a hard sum with AI: which should you do first — ask for one hint or have a go on your own? (a) ask for one hint (b) have a go on your own
  6. 6.🔍 Which is the odd one out? (a) a photo I took (b) a picture I drew (c) a song on the radio (d) a tune I made up
  7. 7.Which of these is a fact about AI? (a) AI always checks facts (b) AI can be wrong (c) confident means correct (d) AI is never wrong
  8. 8.🧩 “Explain volcanoes.” Which part would make it clear who it is for? (a) context (b) a password (c) more capitals (d) a random emoji
  9. 9.📰 Before you share a shocking news post, you should… (a) forward to all (b) check trusted sources (c) add more emojis (d) share it fast
  10. 10.🖼️ Warning sign or good sign: a background that bends? (a) a good sign (b) a warning sign
  11. 11.Which of these uses AI? (a) a stopwatch (b) an app translating signs (c) a fan regulator (d) a doorbell
  12. 12.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  13. 13.🧩 Which part of a prompt says WHAT you want done? (a) the format (b) the task (c) the role (d) the example
  14. 14.🔍 Which is the odd one out? (a) a microwave timer (b) a torch (c) a printed timetable (d) photos grouped by face
  15. 15.🧩 Why add an example to a prompt? (a) to hide the task (b) to make it longer (c) to show the style (d) to confuse the AI
  16. 16.True or false: a video app suggesting what to watch next is AI recommending something. (a) False (b) True
  17. 17.🧪 You can plan a simple AI project with… (a) nothing at all (b) paper and examples (c) only a big robot (d) a secret password
  18. 18.✅ Is this a real check of an AI answer: it has a neat layout? (a) not a real check (b) a real check
  19. 19.🏠 AI or not AI: a doorbell? (a) uses AI (b) not AI
  20. 20.🖼️ Warning sign or good sign: no trusted source? (a) a good sign (b) a warning sign
  21. 21.True or false: “in 2 lines only” sets a length limit. (a) False (b) True
  22. 22.🛠️ Which does this job need: adding up the marks on a report card? (a) needs AI (learning) (b) a simple rule is enough
  23. 23.⏩ In machine learning, which comes first: typing a new spoken word or what training builds? (a) typing a new spoken word (b) what training builds
  24. 24.True or false: “Sample: Q: 4 × 2? A: 8” is the format part of a prompt. (a) True (b) False
  25. 25.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) children speak too fast (d) the phone was new
  26. 26.Which of these is AI that sorts, spots or predicts (not generative)? (a) inventing a recipe (b) sorting photos by face (c) making up a story (d) drawing a new picture
  27. 27.Which of these is a prediction? (a) what training builds (b) old emails marked spam (c) naming a new fruit photo (d) recorded spoken words
  28. 28.True or false: making practice questions to test yourself is an honest way to use AI for homework. (a) True (b) False
  29. 29.©️ What does “giving credit” mean? (a) saying who made it (b) hiding the source (c) adding a filter (d) paying with a card
  30. 30.Which of these is NOT a good source to check against? (a) a library book (b) a science museum site (c) the same chatbot again (d) your school textbook
  31. 31.🔍 Which is the odd one out? (a) many varied examples (b) examples of every type (c) correct labels (d) only one kind of example
  32. 32.Which of these is good for training a model? (a) checking labels twice (b) wrong labels (c) testing on training data (d) copies of one photo
  33. 33.Which of these is okay to share with an AI chatbot? (a) your phone number (b) a story idea (c) your school ID number (d) a friend’s secret
  34. 34.©️ Whose work is it: a poem I wrote? (a) my own work (b) someone else’s work
  35. 35.💬 Rule-based or learning chatbot: “fails on new wording”? (a) rule-based (b) learning
  36. 36.📋 Planning an AI project: which comes first — tag each photo by type or let it learn patterns? (a) tag each photo by type (b) let it learn patterns
  37. 37.Which of these is the input? (a) the patterns it learned (b) the generated picture (c) the trained AI part (d) a photo you upload
  38. 38.🔍 Which is the odd one out? (a) a poem I wrote (b) my own survey results (c) a cartoon from a comic (d) a photo I took
  39. 39.🧐 Fact or myth: “AI has real feelings”? (a) a fact (b) a myth
  40. 40.🤖 AI or a normal program: which one “handles unseen examples”? (a) a normal program (b) AI

Answer key

  1. what training builds
  2. a grammar doubt
  3. reduces bias
  4. never learns from data
  5. have a go on your own
  6. a song on the radio
  7. AI can be wrong
  8. context
  9. check trusted sources
  10. a warning sign
  11. an app translating signs
  12. True
  13. the task
  14. photos grouped by face
  15. to show the style
  16. True
  17. paper and examples
  18. not a real check
  19. not AI
  20. a warning sign
  21. True
  22. a simple rule is enough
  23. what training builds
  24. False
  25. few child voices in data
  26. sorting photos by face
  27. naming a new fruit photo
  28. True
  29. saying who made it
  30. the same chatbot again
  31. only one kind of example
  32. checking labels twice
  33. a story idea
  34. my own work
  35. rule-based
  36. tag each photo by type
  37. a photo you upload
  38. a cartoon from a comic
  39. a myth
  40. AI

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