Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 518 · 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.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the font size (c) the price (d) a sticker on a laptop
2. 2.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
3. 3.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it may get it wrong (c) it will shut down (d) it will be perfect
4. 4.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) print pages (d) learn from data
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
6. 6.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
7. 7.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
8. 8.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
9. 9.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
10. 10.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
11. 11.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
12. 12.🔍 Which is the odd one out? (a) examples of every type (b) very few examples (c) blurry, unclear photos (d) wrong labels
13. 13.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
14. 14.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
15. 15.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
16. 16.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
17. 17.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
18. 18.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a song about dogs (d) a list of rules only
19. 19.Which of these is bad for training a model? (a) very few examples (b) new data for testing (c) many varied examples (d) checking labels twice
20. 20.Which of these is good for training a model? (a) examples of every type (b) testing on training data (c) blurry, unclear photos (d) copies of one photo
21. 21.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) checking labels twice (d) wrong labels
22. 22.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
23. 23.🔍 Which is the odd one out? (a) only one kind of example (b) blurry, unclear photos (c) wrong labels (d) checking labels twice
24. 24.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
25. 25.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
26. 26.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
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.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
29. 29.Which of these is bad for training a model? (a) checking labels twice (b) only one kind of example (c) examples of every type (d) clear, sharp examples
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
31. 31.True or false: “copies of one photo” is good for training a model. (a) False (b) True
32. 32.Which of these is bad for training a model? (a) many varied examples (b) testing on training data (c) clear, sharp examples (d) examples of every type
33. 33.Which of these is bad for training a model? (a) wrong labels (b) many varied examples (c) clear, sharp examples (d) examples of every type
34. 34.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
35. 35.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
36. 36.True or false: “labels added at random” is bad for training a model. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) only one kind of example (b) labels added at random (c) copies of one photo (d) clear, sharp examples
38. 38.True or false: “very few examples” is bad for training a model. (a) True (b) False
39. 39.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) slower to switch on (d) better at its task
40. 40.🏷️ 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

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