Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 140 · 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) examples of every type (b) labels added at random (c) clear, sharp examples (d) new data for testing
2. 2.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
3. 3.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
5. 5.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
6. 6.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) very few examples (d) checking labels twice
7. 7.🔍 Which is the odd one out? (a) blurry, unclear photos (b) labels added at random (c) photos in many lights (d) wrong labels
8. 8.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
9. 9.True or false: “correct labels” is good for training a model. (a) False (b) True
10. 10.🏷️ 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
11. 11.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
12. 12.🔍 Which is the odd one out? (a) only one kind of example (b) correct labels (c) examples of every type (d) photos in many lights
13. 13.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
14. 14.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
15. 15.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
16. 16.🔍 Which is the odd one out? (a) labels added at random (b) blurry, unclear photos (c) wrong labels (d) examples of every type
17. 17.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
18. 18.True or false: “checking labels twice” is good for training a model. (a) True (b) False
19. 19.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) slower to switch on (d) better at its task
20. 20.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
21. 21.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
22. 22.Which of these is good for training a model? (a) only one kind of example (b) blurry, unclear photos (c) very few examples (d) clear, sharp examples
23. 23.Which of these is bad for training a model? (a) testing on training data (b) examples of every type (c) correct labels (d) many varied examples
24. 24.🏷️ 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
25. 25.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) clean screens (d) learn from data
26. 26.Which of these is bad for training a model? (a) only one kind of example (b) photos in many lights (c) many varied examples (d) correct labels
27. 27.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
28. 28.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
29. 29.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
30. 30.🏷️ 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
31. 31.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) many varied examples (d) copies of one photo
32. 32.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
33. 33.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
34. 34.True or false: “many varied examples” is good for training a model. (a) True (b) False
35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
36. 36.🏷️ 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
37. 37.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
38. 38.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
39. 39.True or false: “testing on training data” is bad for training a model. (a) False (b) True
40. 40.🔍 Which is the odd one out? (a) testing on training data (b) clear, sharp examples (c) new data for testing (d) checking labels twice

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