AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 482 · 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.🧐 Fact or myth: “AI is never wrong”? (a) a myth (b) a fact
2. 2.🔍 Which is the odd one out? (a) video suggestions (b) an AI chatbot (c) a map predicting traffic (d) a digital watch
3. 3.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
4. 4.🧮 Which of these is NOT AI? (a) a basic calculator (b) face unlock (c) voice typing (d) a spam filter
5. 5.🏷️ 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
6. 6.🔍 Which is the odd one out? (a) AI can mix up numbers (b) AI copies data patterns (c) AI answers need checking (d) AI is never wrong
7. 7.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) recommending (b) generating (c) recognising (d) predicting
8. 8.Which of these helps reduce bias? (a) use one group only (b) ignore complaints (c) check who is missing (d) test on one group only
9. 9.Which of these is good for training a model? (a) checking labels twice (b) labels added at random (c) wrong labels (d) very few examples
10. 10.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
11. 11.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
12. 12.🔍 Which is the odd one out? (a) skip testing (b) ignore complaints (c) fix wrong labels (d) test on one group only
13. 13.🧪 Why test a model on NEW examples? (a) to see if it works (b) to make it slower (c) to change its name (d) to delete its data
14. 14.Which of these is bad for training a model? (a) clear, sharp examples (b) examples of every type (c) correct labels (d) blurry, unclear photos
15. 15.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) balanced data (b) one-sided data
16. 16.Which of these uses AI? (a) a doorbell (b) a digital watch (c) a fan regulator (d) an app translating signs
17. 17.Which of these is the model? (a) what training builds (b) old emails marked spam (c) past weather records (d) naming a new leaf
18. 18.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
19. 19.True or false: “AI has real feelings” is a fact about AI. (a) True (b) False
20. 20.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
21. 21.True or false: “a logo idea for the eco club” asks for an image. (a) False (b) True
22. 22.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) trust the AI (b) stop studying (c) trust the textbook (d) share it online
23. 23.🔍 Which is the odd one out? (a) add more of the same (b) test on one group only (c) test on many groups (d) copy old unfair choices
24. 24.🛠️ Which does this job need: counting the words in an essay? (a) a simple rule is enough (b) needs AI (learning)
25. 25.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) one single photo (c) a list of rules only (d) many labelled photos
26. 26.True or false: “a cheerful tune for Sports Day” asks for an image. (a) True (b) False
27. 27.🏷️ 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
28. 28.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) better at its task (d) change colour
29. 29.True or false: “testing on training data” is good for training a model. (a) True (b) False
30. 30.🔍 Which is the odd one out? (a) a printed timetable (b) an AI chatbot (c) a calculator (d) a fan regulator
31. 31.True or false: “flagging a new email” is training data. (a) False (b) True
32. 32.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
33. 33.True or false: “one set rule per case” describes how a normal program works. (a) True (b) False
34. 34.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
35. 35.True or false: an AI chatbot writing a poem about rain is AI recognising something. (a) False (b) True
36. 36.🏠 AI or not AI: an AI chatbot? (a) not AI (b) uses AI
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
38. 38.True or false: “does exactly as coded” describes how a normal program works. (a) False (b) True
39. 39.🎨 This prompt asks a generative AI for: a soft lullaby melody. What kind of output is that? (a) text (b) an image (c) music or sound
40. 40.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data

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