AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 419 · 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 a fact about AI? (a) long answers are true (b) AI knows everything (c) AI learns from data (d) AI is never wrong
2. 2.Which of these is a myth about AI? (a) AI can make up facts (b) AI is never wrong (c) AI answers need checking (d) AI copies data patterns
3. 3.🔍 Which is the odd one out? (a) testing on training data (b) only one kind of example (c) checking labels twice (d) wrong labels
4. 4.🗣️ A voice app understands adults but not children. What is the likely reason? (a) few child voices in data (b) children speak too fast (c) it was a rainy day (d) the phone was new
5. 5.Which of these is a myth about AI? (a) AI always checks facts (b) AI can be wrong (c) AI learns from data (d) AI copies data patterns
6. 6.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) clear, sharp examples (d) very few examples
7. 7.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
8. 8.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
9. 9.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
10. 10.🔍 Which is the odd one out? (a) a torch (b) a map predicting traffic (c) a doorbell (d) a fan regulator
11. 11.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
12. 12.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
13. 13.🔦 Is a torch with an on/off switch AI? (a) only if it is bright (b) no (c) yes
14. 14.Which of these describes how a normal program works? (a) spots patterns in data (b) improves with more data (c) makes a best guess (d) same steps every time
15. 15.🛠️ Which does this job need: sorting names in A to Z order? (a) a simple rule is enough (b) needs AI (learning)
16. 16.True or false: “write a poem about the monsoon” asks for music or sound. (a) True (b) False
17. 17.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) True (b) False
18. 18.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
19. 19.🎨 This prompt asks a generative AI for: five quiz questions on fractions. What kind of output is that? (a) an image (b) text (c) music or sound
20. 20.🎨 This prompt asks a generative AI for: a drum beat for a dance. What kind of output is that? (a) text (b) an image (c) music or sound
21. 21.✨ Generative or not: suggesting a video? (a) makes something new (b) sorts or predicts
22. 22.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
23. 23.Which of these is not AI? (a) a voice assistant (b) a light switch (c) photos grouped by face (d) an image generator
24. 24.🌍 An AI chatbot says the Earth has two moons. Your textbook says one. What now? (a) share it online (b) trust the AI (c) trust the textbook (d) stop studying
25. 25.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
26. 26.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
27. 27.Which of these is training data? (a) naming a new leaf (b) what training builds (c) the trained program (d) 500 labelled leaf photos
28. 28.Which of these is training data? (a) typing a new spoken word (b) recorded spoken words (c) what training builds (d) the learned patterns
29. 29.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
30. 30.Which of these is a prediction? (a) past weather records (b) labelled fruit photos (c) flagging a new email (d) 500 labelled leaf photos
31. 31.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) False (b) True
32. 32.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
33. 33.True or false: “a drawing of a cat on the Moon” asks for an image. (a) False (b) True
34. 34.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) predicting (c) drawing (d) sleeping
35. 35.True or false: “many varied examples” is bad for training a model. (a) True (b) False
36. 36.True or false: “a thank-you note to the bus driver” asks for an image. (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) add varied examples (d) use one group only
38. 38.True or false: an AI chatbot writing a poem about rain is AI recognising something. (a) False (b) True
39. 39.🤖 What does AI stand for? (a) app installer (b) automatic internet (c) artificial intelligence (d) actual information
40. 40.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data

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