Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 536 · 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.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) only one kind of example (d) examples of every type
2. 2.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
3. 3.True or false: “only one kind of example” is good for training a model. (a) False (b) True
4. 4.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
5. 5.🏷️ 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
6. 6.📚 Usually, more good examples make a model… (a) better at its task (b) slower to switch on (c) forget everything (d) change colour
7. 7.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
8. 8.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
9. 9.Which of these is good for training a model? (a) wrong labels (b) photos in many lights (c) blurry, unclear photos (d) very few examples
10. 10.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
11. 11.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
12. 12.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
13. 13.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) learn from data (d) clean screens
14. 14.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the font size (d) the right answer tag
15. 15.Which of these is good for training a model? (a) copies of one photo (b) labels added at random (c) checking labels twice (d) testing on training data
16. 16.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it will shut down (d) it may get it wrong
17. 17.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
18. 18.True or false: “correct labels” is bad for training a model. (a) False (b) True
19. 19.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
20. 20.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
21. 21.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
22. 22.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
23. 23.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
24. 24.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
25. 25.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
26. 26.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
27. 27.Which of these is good for training a model? (a) clear, sharp examples (b) copies of one photo (c) blurry, unclear photos (d) very few examples
28. 28.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
29. 29.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
30. 30.🏷️ 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
31. 31.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
32. 32.Which of these is good for training a model? (a) many varied examples (b) wrong labels (c) blurry, unclear photos (d) testing on training data
33. 33.🔍 Which is the odd one out? (a) photos in many lights (b) checking labels twice (c) testing on training data (d) new data for testing
34. 34.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) very few examples (d) many varied examples
35. 35.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a list of rules only (d) a song about dogs
36. 36.🔍 Which is the odd one out? (a) many varied examples (b) blurry, unclear photos (c) new data for testing (d) examples of every type
37. 37.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
38. 38.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
39. 39.🔍 Which is the odd one out? (a) copies of one photo (b) photos in many lights (c) new data for testing (d) clear, sharp examples
40. 40.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training

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