AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 458 · 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.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing a new poem (b) writing quiz questions (c) turning speech to text (d) drawing a new picture
2. 2.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a fair model (b) bias from data (c) a strong battery (d) a broken screen
3. 3.True or false: an AI chatbot writing a poem about rain is AI predicting something. (a) True (b) False
4. 4.Which of these helps reduce bias? (a) copy old unfair choices (b) balance the data (c) skip testing (d) add more of the same
5. 5.✍️ How does an AI chatbot write its replies? (a) asks a person (b) predicts likely words (c) copies one website (d) uses magic
6. 6.✨ Generative or not: sorting photos by face? (a) makes something new (b) sorts or predicts
7. 7.🎨 This prompt asks a generative AI for: a logo idea for the eco club. What kind of output is that? (a) an image (b) music or sound (c) text
8. 8.Which of these describes how a normal program works? (a) handles unseen examples (b) improves with more data (c) spots patterns in data (d) never learns from data
9. 9.Which of these is AI that sorts, spots or predicts (not generative)? (a) creating a cartoon (b) writing quiz questions (c) spotting spam (d) drafting a letter
10. 10.True or false: a car camera reading a speed sign is AI recognising something. (a) True (b) False
11. 11.Which of these uses AI? (a) a doorbell (b) voice typing (c) a torch (d) a microwave timer
12. 12.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
13. 13.Which of these is good for training a model? (a) correct labels (b) copies of one photo (c) very few examples (d) blurry, unclear photos
14. 14.True or false: “write a poem about the monsoon” asks for text. (a) False (b) True
15. 15.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) stop studying (b) trust the AI (c) share it online (d) trust the textbook
16. 16.True or false: “photos in many lights” is good for training a model. (a) False (b) True
17. 17.True or false: finding 10% of a price only needs a simple fixed rule. (a) True (b) False
18. 18.✅ Is this a real check of an AI answer: match it to the textbook? (a) not a real check (b) a real check
19. 19.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
20. 20.Which of these is good for training a model? (a) wrong labels (b) checking labels twice (c) blurry, unclear photos (d) testing on training data
21. 21.🛠️ Which does this job need: showing the time on a clock? (a) a simple rule is enough (b) needs AI (learning)
22. 22.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
23. 23.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
24. 24.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a list of rules only (d) a song about dogs
25. 25.🛠️ Which does this job need: converting metres into centimetres? (a) a simple rule is enough (b) needs AI (learning)
26. 26.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to make it slower (d) to see if it works
27. 27.🔍 Which is the odd one out? (a) composing a new tune (b) suggesting a video (c) drafting a letter (d) writing a new poem
28. 28.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
29. 29.True or false: an AI chatbot writing a story about a lost kite is AI recommending something. (a) False (b) True
30. 30.True or false: reading messy handwriting only needs a simple fixed rule. (a) True (b) False
31. 31.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the font size (c) a sticker on a laptop (d) the price
32. 32.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) copies of one photo (d) new data for testing
33. 33.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
34. 34.✨ Generative or not: suggesting a video? (a) sorts or predicts (b) makes something new
35. 35.🛠️ Which does this job need: switching on a street light at 6 pm? (a) a simple rule is enough (b) needs AI (learning)
36. 36.Which of these describes how AI works? (a) does exactly as coded (b) uses rules people wrote (c) one set rule per case (d) handles unseen examples
37. 37.Which of these describes how a normal program works? (a) uses rules people wrote (b) learns from examples (c) gives a likely answer (d) spots patterns in data
38. 38.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
39. 39.📱 What is the AI doing here: a keyboard guessing your next word? (a) predicting (b) generating (c) recommending (d) recognising
40. 40.🤖 AI or a normal program: which one “gives a likely answer”? (a) a normal program (b) AI

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