Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 215 · 40 questions

AI tip (Show, label, learn): Machine learning learns patterns from many labelled examples — a label is the right answer tag on each example. Good for training: many varied examples, correct labels, every type the model will meet, and separate new data for testing. Bad for training: very few examples, wrong or random labels, only one kind of example, blurry examples, testing on the training data.

1. 1.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
2. 2.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) only one kind of example (d) correct labels
3. 3.🏷️ 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) not spam (b) spam
4. 4.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) forget everything (d) slower to switch on
5. 5.Which of these is bad for training a model? (a) examples of every type (b) many varied examples (c) checking labels twice (d) very few examples
6. 6.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
7. 7.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) many labelled photos (d) a song about dogs
8. 8.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
9. 9.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) many varied examples (d) blurry, unclear photos
10. 10.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) wrong labels (d) new data for testing
11. 11.True or false: “only one kind of example” is good for training a model. (a) True (b) False
12. 12.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) many varied examples (d) copies of one photo
13. 13.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
14. 14.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
15. 15.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) print pages (d) learn from data
16. 16.True or false: “examples of every type” is good for training a model. (a) False (b) True
17. 17.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
18. 18.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
19. 19.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
20. 20.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
21. 21.🔍 Which is the odd one out? (a) clear, sharp examples (b) copies of one photo (c) correct labels (d) photos in many lights
22. 22.Which of these is good for training a model? (a) blurry, unclear photos (b) clear, sharp examples (c) very few examples (d) testing on training data
23. 23.🔍 Which is the odd one out? (a) testing on training data (b) wrong labels (c) blurry, unclear photos (d) new data for testing
24. 24.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
25. 25.True or false: “many varied examples” is bad for training a model. (a) True (b) False
26. 26.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the price (d) the font size
27. 27.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
28. 28.🔍 Which is the odd one out? (a) many varied examples (b) very few examples (c) copies of one photo (d) testing on training data
29. 29.True or false: “very few examples” is bad for training a model. (a) False (b) True
30. 30.🔍 Which is the odd one out? (a) blurry, unclear photos (b) only one kind of example (c) examples of every type (d) labels added at random
31. 31.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
32. 32.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
33. 33.🔍 Which is the odd one out? (a) very few examples (b) clear, sharp examples (c) only one kind of example (d) wrong labels
34. 34.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
35. 35.🔍 Which is the odd one out? (a) examples of every type (b) new data for testing (c) photos in many lights (d) labels added at random
36. 36.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
38. 38.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
39. 39.Which of these is bad for training a model? (a) many varied examples (b) checking labels twice (c) copies of one photo (d) photos in many lights
40. 40.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False

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