Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 104 · 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: “wrong labels” is bad for training a model. (a) True (b) False
2. 2.🔍 Which is the odd one out? (a) copies of one photo (b) checking labels twice (c) testing on training data (d) labels added at random
3. 3.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
4. 4.🔍 Which is the odd one out? (a) blurry, unclear photos (b) copies of one photo (c) correct labels (d) only one kind of example
5. 5.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) wrong labels (d) checking labels twice
6. 6.🔍 Which is the odd one out? (a) new data for testing (b) clear, sharp examples (c) testing on training data (d) examples of every type
7. 7.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) learn from data (d) print pages
8. 8.True or false: “only one kind of example” is good for training a model. (a) False (b) True
9. 9.🥭 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
10. 10.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) photos in many lights (d) testing on training data
11. 11.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
13. 13.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
14. 14.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) a list of rules only (d) one single photo
15. 15.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) forget everything (d) slower to switch on
16. 16.Which of these is bad for training a model? (a) many varied examples (b) new data for testing (c) examples of every type (d) very few examples
17. 17.🏷️ 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
18. 18.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
19. 19.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
20. 20.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
21. 21.🔍 Which is the odd one out? (a) examples of every type (b) checking labels twice (c) photos in many lights (d) labels added at random
22. 22.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
23. 23.True or false: “many varied examples” is good for training a model. (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) blurry, unclear photos (b) new data for testing (c) wrong labels (d) labels added at random
25. 25.Which of these is bad for training a model? (a) only one kind of example (b) correct labels (c) new data for testing (d) photos in many lights
26. 26.🔍 Which is the odd one out? (a) new data for testing (b) photos in many lights (c) blurry, unclear photos (d) checking labels twice
27. 27.Which of these is bad for training a model? (a) many varied examples (b) examples of every type (c) correct labels (d) blurry, unclear photos
28. 28.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
29. 29.Which of these is bad for training a model? (a) labels added at random (b) clear, sharp examples (c) many varied examples (d) photos in many lights
30. 30.True or false: “wrong labels” is good for training a model. (a) False (b) True
31. 31.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) many varied examples (d) wrong labels
32. 32.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) only one kind of example (d) many varied examples
33. 33.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
34. 34.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
35. 35.🏷️ 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
36. 36.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
37. 37.True or false: “very few examples” is bad for training a model. (a) True (b) False
38. 38.True or false: “testing on training data” is good for training a model. (a) True (b) False
39. 39.Which of these is good for training a model? (a) copies of one photo (b) blurry, unclear photos (c) only one kind of example (d) new data for testing
40. 40.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training

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