← Part 1 test: what AI is lesson New set →

AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 164 · 40 questions
TalentJR

AI tip (Name the idea, then answer): Learning from examples → AI; fixed rules → a normal program. Order: training data → model → prediction; good data is many, varied and correctly labelled. Generative AI makes new things and can hallucinate; one-sided data causes bias.

NameDateTime takenScore ___ / 40
  1. 1.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
  2. 2.True or false: “AI can be wrong” is a myth about AI. (a) False (b) True
  3. 3.📱 What is the AI doing here: an online shop showing “you may also like”? (a) recognising (b) predicting (c) generating (d) recommending
  4. 4.🏠 AI or not AI: face unlock on a phone? (a) not AI (b) uses AI
  5. 5.🧐 Fact or myth: “confident means correct”? (a) a fact (b) a myth
  6. 6.📅 An AI gives a date for a history event. How can you check? (a) guess (b) look in your textbook (c) pick a lucky number (d) ask it to repeat
  7. 7.🔍 Which is the odd one out? (a) examples of every type (b) new data for testing (c) photos in many lights (d) wrong labels
  8. 8.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  9. 9.True or false: “spots patterns in data” describes how AI works. (a) False (b) True
  10. 10.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
  11. 11.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
  12. 12.True or false: counting the words in an essay needs AI that learns from examples. (a) False (b) True
  13. 13.🔍 Which is the odd one out? (a) drawing a new picture (b) making up a story (c) predicting rain (d) writing a new poem
  14. 14.⏩ In machine learning, which comes first: the learned patterns or typing a new spoken word? (a) the learned patterns (b) typing a new spoken word
  15. 15.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
  16. 16.🤖 AI or a normal program: which one “handles unseen examples”? (a) a normal program (b) AI
  17. 17.True or false: “typing a new spoken word” is the model. (a) False (b) True
  18. 18.True or false: “one set rule per case” describes how AI works. (a) True (b) False
  19. 19.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  20. 20.True or false: “testing on training data” is bad for training a model. (a) True (b) False
  21. 21.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
  22. 22.✨ Generative or not: making up a story? (a) sorts or predicts (b) makes something new
  23. 23.True or false: “labels added at random” is good for training a model. (a) False (b) True
  24. 24.True or false: “does exactly as coded” describes how a normal program works. (a) True (b) False
  25. 25.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  26. 26.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) examples of every type (d) testing on training data
  27. 27.🏠 AI or not AI: a stopwatch? (a) uses AI (b) not AI
  28. 28.✨ Generative or not: sorting photos by face? (a) makes something new (b) sorts or predicts
  29. 29.Which of these is AI that sorts, spots or predicts (not generative)? (a) suggesting a video (b) creating a cartoon (c) drawing a new picture (d) drafting a letter
  30. 30.True or false: “gives a likely answer” describes how a normal program works. (a) False (b) True
  31. 31.Which of these is not AI? (a) an app translating signs (b) a printed timetable (c) an image generator (d) video suggestions
  32. 32.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
  33. 33.Which of these adds to bias? (a) ask different people (b) add varied examples (c) balance the data (d) skip testing
  34. 34.True or false: “very few examples” is good for training a model. (a) True (b) False
  35. 35.🧐 Fact or myth: “AI can be wrong”? (a) a myth (b) a fact
  36. 36.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  37. 37.📦 What happens during training? (a) it takes photos (b) it learns patterns (c) it charges up (d) it prints labels
  38. 38.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
  39. 39.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
  40. 40.True or false: telling a cat photo from a dog photo only needs a simple fixed rule. (a) True (b) False

Answer key

  1. False
  2. False
  3. recommending
  4. uses AI
  5. a myth
  6. look in your textbook
  7. wrong labels
  8. True
  9. True
  10. bad for training
  11. reduces bias
  12. False
  13. predicting rain
  14. the learned patterns
  15. False
  16. AI
  17. False
  18. False
  19. training data
  20. True
  21. False
  22. makes something new
  23. False
  24. True
  25. a prediction
  26. testing on training data
  27. not AI
  28. sorts or predicts
  29. suggesting a video
  30. False
  31. a printed timetable
  32. training data
  33. skip testing
  34. False
  35. a fact
  36. old emails marked spam
  37. it learns patterns
  38. good for training
  39. good for training
  40. False

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students