AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 797 · 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 is the odd one out? (a) spotting spam (b) spotting a sick leaf (c) sorting photos by face (d) drafting a letter
2. 2.True or false: an AI chatbot writing a poem about rain is AI predicting something. (a) False (b) True
3. 3.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
4. 4.✨ Generative or not: drawing a new picture? (a) makes something new (b) sorts or predicts
5. 5.✅ Is this a real check of an AI answer: match it to the textbook? (a) a real check (b) not a real check
6. 6.Which of these is a fact about AI? (a) AI has real feelings (b) AI is never wrong (c) AI answers need checking (d) AI always checks facts
7. 7.Which of these is a fact about AI? (a) AI knows everything (b) confident means correct (c) AI can mix up numbers (d) AI has real feelings
8. 8.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) an image (b) music or sound (c) text
9. 9.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
10. 10.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) one single photo (c) many labelled photos (d) a list of rules only
11. 11.Which of these describes how AI works? (a) follows fixed rules (b) one set rule per case (c) uses rules people wrote (d) gives a likely answer
12. 12.🛠️ Which does this job need: adding up the marks on a report card? (a) a simple rule is enough (b) needs AI (learning)
13. 13.🛠️ Does this reduce bias or add to it: check who is missing? (a) reduces bias (b) adds to bias
14. 14.True or false: “improves with more data” describes how a normal program works. (a) False (b) True
15. 15.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
16. 16.📅 An AI gives a date for a history event. How can you check? (a) guess (b) look in your textbook (c) pick a lucky number (d) ask it to repeat
17. 17.✅ Is this a real check of an AI answer: see if the book exists? (a) a real check (b) not a real check
18. 18.True or false: “same steps every time” describes how a normal program works. (a) False (b) True
19. 19.🏠 AI or not AI: photos grouped by face? (a) uses AI (b) not AI
20. 20.True or false: “the trained program” is the model. (a) True (b) False
21. 21.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
22. 22.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) True (b) False
23. 23.True or false: a music app suggesting a song you may like is AI predicting something. (a) False (b) True
24. 24.True or false: “AI always checks facts” is a fact about AI. (a) False (b) True
25. 25.🎨 This prompt asks a generative AI for: a thank-you note to the bus driver. What kind of output is that? (a) text (b) an image (c) music or sound
26. 26.True or false: “testing on training data” is bad for training a model. (a) True (b) False
27. 27.📱 What is the AI doing here: a keyboard guessing your next word? (a) generating (b) recommending (c) predicting (d) recognising
28. 28.Which of these is good for training a model? (a) only one kind of example (b) very few examples (c) testing on training data (d) new data for testing
29. 29.Which of these helps reduce bias? (a) add more of the same (b) copy old unfair choices (c) use one group only (d) add varied examples
30. 30.True or false: finding 10% of a price needs AI that learns from examples. (a) False (b) True
31. 31.🤖 AI or a normal program: which one “gives a likely answer”? (a) AI (b) a normal program
32. 32.True or false: “many varied examples” is good for training a model. (a) False (b) True
33. 33.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
34. 34.True or false: “a logo idea for the eco club” asks for an image. (a) False (b) True
35. 35.Which of these is AI that sorts, spots or predicts (not generative)? (a) inventing a recipe (b) making up a story (c) drafting a letter (d) turning speech to text
36. 36.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to see if it works (d) to delete its data
37. 37.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
38. 38.🔁 What is the right order? (a) model, prediction, data (b) data, prediction, model (c) prediction, data, model (d) data, model, prediction
39. 39.True or false: an online shop showing “you may also like” is AI recommending something. (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) face unlock on a phone (b) photos grouped by face (c) voice typing (d) a microwave timer

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