AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 532 · 40 questions

AI tip (Name the idea, then answer): Learning from examples → AI; fixed rules → a normal program. Order: training data → model → prediction; good data is many, varied and correctly labelled. Generative AI makes new things and can hallucinate; one-sided data causes bias.

1. 1.True or false: “AI can make up facts” is a myth about AI. (a) False (b) True
2. 2.✅ Is this a real check of an AI answer: try the sum on paper? (a) not a real check (b) a real check
3. 3.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) a list of rules only (d) one single photo
4. 4.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) the font size (d) a sticker on a laptop
5. 5.Which of these is generative AI (it makes something new)? (a) spotting a sick leaf (b) drafting a letter (c) predicting rain (d) spotting spam
6. 6.🔍 Which is the odd one out? (a) labels added at random (b) testing on training data (c) very few examples (d) correct labels
7. 7.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing quiz questions (b) inventing a recipe (c) creating a cartoon (d) spotting a sick leaf
8. 8.🔍 Which is the odd one out? (a) AI copies data patterns (b) AI can mix up numbers (c) long answers are true (d) AI answers need checking
9. 9.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
10. 10.📅 An AI gives a date for a history event. How can you check? (a) pick a lucky number (b) guess (c) ask it to repeat (d) look in your textbook
11. 11.⚖️ One-sided or balanced data: neat and messy writing from many people? (a) one-sided data (b) balanced data
12. 12.Which of these describes how a normal program works? (a) spots patterns in data (b) one set rule per case (c) learns from examples (d) handles unseen examples
13. 13.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
14. 14.🛠️ Does this reduce bias or add to it: test on one group only? (a) adds to bias (b) reduces bias
15. 15.🔍 Which is the odd one out? (a) AI knows everything (b) AI is never wrong (c) AI can make up facts (d) AI has real feelings
16. 16.True or false: “flagging a new email” is a prediction. (a) True (b) False
17. 17.🏷️ 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
18. 18.True or false: “five quiz questions on fractions” asks for text. (a) False (b) True
19. 19.True or false: “fix wrong labels” adds to bias. (a) False (b) True
20. 20.🏷️ 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
21. 21.True or false: spotting spam emails by their patterns needs AI that learns from examples. (a) True (b) False
22. 22.🛠️ Which does this job need: recognising a bird from its song? (a) a simple rule is enough (b) needs AI (learning)
23. 23.🔍 Which is the odd one out? (a) reading number plates (b) making up a story (c) sorting photos by face (d) predicting rain
24. 24.🛠️ Which does this job need: suggesting the next word as you type? (a) a simple rule is enough (b) needs AI (learning)
25. 25.🏠 AI or not AI: an AI chatbot? (a) not AI (b) uses AI
26. 26.✍️ How does an AI chatbot write its replies? (a) uses magic (b) predicts likely words (c) asks a person (d) copies one website
27. 27.🔍 Which is the odd one out? (a) writing quiz questions (b) composing a new tune (c) inventing a recipe (d) unlocking with a face
28. 28.Which of these adds to bias? (a) ask different people (b) check who is missing (c) test on one group only (d) balance the data
29. 29.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
30. 30.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
31. 31.Which of these is good for training a model? (a) labels added at random (b) correct labels (c) wrong labels (d) very few examples
32. 32.True or false: “handles unseen examples” describes how AI works. (a) True (b) False
33. 33.True or false: “long answers are true” is a fact about AI. (a) False (b) True
34. 34.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
35. 35.True or false: “AI always checks facts” is a myth about AI. (a) False (b) True
36. 36.Which of these describes how AI works? (a) spots patterns in data (b) one set rule per case (c) same steps every time (d) uses rules people wrote
37. 37.True or false: “labelled fruit photos” is the model. (a) False (b) True
38. 38.Which of these is a fact about AI? (a) AI knows everything (b) AI can be wrong (c) long answers are true (d) AI has real feelings
39. 39.🛠️ Which does this job need: switching on a street light at 6 pm? (a) a simple rule is enough (b) needs AI (learning)
40. 40.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data

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