Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 581 · 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.🏷️ 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
2. 2.🔍 Which is the odd one out? (a) correct labels (b) clear, sharp examples (c) new data for testing (d) very few examples
3. 3.🏷️ 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
4. 4.🔍 Which is the odd one out? (a) correct labels (b) only one kind of example (c) photos in many lights (d) clear, sharp examples
5. 5.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
6. 6.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
7. 7.🔍 Which is the odd one out? (a) photos in many lights (b) many varied examples (c) copies of one photo (d) correct labels
8. 8.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) one single photo (d) many labelled photos
9. 9.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
10. 10.True or false: “very few examples” is bad for training a model. (a) False (b) True
11. 11.Which of these is bad for training a model? (a) examples of every type (b) wrong labels (c) correct labels (d) checking labels twice
12. 12.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) better at its task (d) forget everything
13. 13.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
14. 14.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
15. 15.🏷️ 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
16. 16.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
17. 17.Which of these is good for training a model? (a) wrong labels (b) blurry, unclear photos (c) only one kind of example (d) photos in many lights
18. 18.True or false: “testing on training data” is good for training a model. (a) True (b) False
19. 19.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) the right answer tag (d) a sticker on a laptop
20. 20.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) clear, sharp examples (d) testing on training data
21. 21.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
22. 22.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
23. 23.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
24. 24.True or false: “wrong labels” is bad for training a model. (a) True (b) False
25. 25.True or false: “photos in many lights” is good for training a model. (a) False (b) True
26. 26.🔍 Which is the odd one out? (a) wrong labels (b) only one kind of example (c) examples of every type (d) very few examples
27. 27.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) charge faster (d) print pages
28. 28.True or false: “new data for testing” is good for training a model. (a) True (b) False
29. 29.Which of these is good for training a model? (a) checking labels twice (b) copies of one photo (c) very few examples (d) blurry, unclear photos
30. 30.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
31. 31.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
32. 32.Which of these is bad for training a model? (a) very few examples (b) many varied examples (c) photos in many lights (d) clear, sharp examples
33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
34. 34.Which of these is bad for training a model? (a) many varied examples (b) checking labels twice (c) testing on training data (d) photos in many lights
35. 35.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) many varied examples (d) blurry, unclear photos
36. 36.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
37. 37.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
38. 38.Which of these is bad for training a model? (a) blurry, unclear photos (b) clear, sharp examples (c) new data for testing (d) photos in many lights
39. 39.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
40. 40.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) correct labels (d) only one kind of example

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