AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 145 · 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.🏠 AI or not AI: a torch? (a) uses AI (b) not AI
2. 2.🔍 Which is the odd one out? (a) AI can mix up numbers (b) AI always checks facts (c) AI learns from data (d) AI can be wrong
3. 3.📱 What is the AI doing here: a music app suggesting a song you may like? (a) predicting (b) recommending (c) generating (d) recognising
4. 4.🛠️ Does this reduce bias or add to it: ignore complaints? (a) reduces bias (b) adds to bias
5. 5.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
6. 6.True or false: “ask your teacher” is a real way to check an AI answer. (a) True (b) False
7. 7.Which of these uses AI? (a) a stopwatch (b) a calculator (c) video suggestions (d) a torch
8. 8.⏩ In machine learning, which comes first: typing a new spoken word or what training builds? (a) typing a new spoken word (b) what training builds
9. 9.Which of these is good for training a model? (a) only one kind of example (b) new data for testing (c) blurry, unclear photos (d) wrong labels
10. 10.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) False (b) True
11. 11.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) music or sound (b) text (c) an image
12. 12.True or false: “it has a neat layout” is a real way to check an AI answer. (a) True (b) False
13. 13.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
14. 14.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) the model (c) a prediction
15. 15.Which of these is generative AI (it makes something new)? (a) unlocking with a face (b) suggesting a video (c) drafting a letter (d) turning speech to text
16. 16.True or false: “write a poem about the monsoon” asks for text. (a) True (b) False
17. 17.📱 What is the AI doing here: an online shop showing “you may also like”? (a) generating (b) predicting (c) recognising (d) recommending
18. 18.🏷️ 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
19. 19.Which of these is AI that sorts, spots or predicts (not generative)? (a) composing a new tune (b) writing a new poem (c) unlocking with a face (d) making up a story
20. 20.True or false: “a logo idea for the eco club” asks for text. (a) True (b) False
21. 21.🤖 AI or a normal program: which one “one set rule per case”? (a) a normal program (b) AI
22. 22.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to delete its data (d) to change its name
23. 23.🛠️ Which does this job need: translating a sentence into Hindi? (a) a simple rule is enough (b) needs AI (learning)
24. 24.Which of these is generative AI (it makes something new)? (a) spotting a sick leaf (b) turning speech to text (c) composing a new tune (d) predicting rain
25. 25.True or false: suggesting the next word as you type needs AI that learns from examples. (a) False (b) True
26. 26.Which of these describes how a normal program works? (a) learns from examples (b) gives a likely answer (c) uses rules people wrote (d) handles unseen examples
27. 27.True or false: “photos in many lights” is good for training a model. (a) False (b) True
28. 28.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
29. 29.✨ Generative or not: writing a new poem? (a) makes something new (b) sorts or predicts
30. 30.✨ Is everything a generative AI makes true? (a) only on Mondays (b) yes, always (c) no, it can be wrong
31. 31.Which of these is bad for training a model? (a) photos in many lights (b) clear, sharp examples (c) many varied examples (d) wrong labels
32. 32.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
33. 33.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
34. 34.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) False (b) True
35. 35.True or false: “AI can be wrong” is a myth about AI. (a) True (b) False
36. 36.Which of these is a prediction? (a) 500 labelled leaf photos (b) old emails marked spam (c) the learned patterns (d) flagging a new email
37. 37.True or false: “learns from examples” describes how AI works. (a) False (b) True
38. 38.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) ask different people (d) ignore complaints
39. 39.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) one-sided data (b) balanced data
40. 40.True or false: “very few examples” is bad for training a model. (a) True (b) False

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