Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 240 · 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: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
2. 2.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
3. 3.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) learn from data (d) clean screens
4. 4.Which of these is good for training a model? (a) testing on training data (b) labels added at random (c) copies of one photo (d) correct labels
5. 5.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
6. 6.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
7. 7.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
8. 8.True or false: “correct labels” is bad for training a model. (a) True (b) False
9. 9.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) blurry, unclear photos (d) many varied examples
10. 10.🏷️ 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
11. 11.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
12. 12.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
13. 13.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
14. 14.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) slower to switch on (d) forget everything
15. 15.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
16. 16.Which of these is bad for training a model? (a) wrong labels (b) many varied examples (c) photos in many lights (d) new data for testing
17. 17.🔍 Which is the odd one out? (a) new data for testing (b) blurry, unclear photos (c) very few examples (d) wrong labels
18. 18.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
19. 19.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
20. 20.🔍 Which is the odd one out? (a) copies of one photo (b) checking labels twice (c) correct labels (d) photos in many lights
21. 21.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
22. 22.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
23. 23.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) correct labels (d) only one kind of example
24. 24.🔍 Which is the odd one out? (a) examples of every type (b) copies of one photo (c) labels added at random (d) very few examples
25. 25.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
26. 26.🔍 Which is the odd one out? (a) testing on training data (b) blurry, unclear photos (c) very few examples (d) photos in many lights
27. 27.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
28. 28.🔍 Which is the odd one out? (a) new data for testing (b) testing on training data (c) checking labels twice (d) correct labels
29. 29.True or false: “labels added at random” is bad for training a model. (a) False (b) True
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
31. 31.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
32. 32.🥭 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 be perfect (d) it will shut down
33. 33.🏷️ 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
34. 34.True or false: “very few examples” is good for training a model. (a) False (b) True
35. 35.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) copies of one photo (d) new data for testing
36. 36.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
37. 37.Which of these is good for training a model? (a) copies of one photo (b) labels added at random (c) wrong labels (d) clear, sharp examples
38. 38.🏷️ 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
39. 39.Which of these is good for training a model? (a) checking labels twice (b) very few examples (c) blurry, unclear photos (d) testing on training data
40. 40.🔍 Which is the odd one out? (a) examples of every type (b) correct labels (c) only one kind of example (d) photos in many lights

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