AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 378 · 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.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
2. 2.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) one-sided data (b) balanced data
3. 3.True or false: “spots patterns in data” describes how a normal program works. (a) False (b) True
4. 4.🎨 This prompt asks a generative AI for: five quiz questions on fractions. What kind of output is that? (a) music or sound (b) an image (c) text
5. 5.Which of these is a prediction? (a) what training builds (b) past weather records (c) naming a new fruit photo (d) 500 labelled leaf photos
6. 6.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
7. 7.Which of these describes how AI works? (a) does exactly as coded (b) follows fixed rules (c) one set rule per case (d) gives a likely answer
8. 8.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
9. 9.True or false: a camera app naming the flower you point at is AI recommending something. (a) True (b) False
10. 10.Which of these is the model? (a) recorded spoken words (b) what training builds (c) old emails marked spam (d) naming a new leaf
11. 11.🔍 Which is the odd one out? (a) add varied examples (b) check who is missing (c) test on many groups (d) copy old unfair choices
12. 12.🧮 Which of these is NOT AI? (a) voice typing (b) a basic calculator (c) a spam filter (d) face unlock
13. 13.Which of these is not AI? (a) photos grouped by face (b) an AI chatbot (c) a torch (d) voice typing
14. 14.Which of these is good for training a model? (a) photos in many lights (b) testing on training data (c) copies of one photo (d) labels added at random
15. 15.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
16. 16.🛠️ Does this reduce bias or add to it: balance the data? (a) adds to bias (b) reduces bias
17. 17.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) the phone was new (d) few child voices in data
18. 18.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) many labelled photos (d) a song about dogs
19. 19.Which of these is not AI? (a) a spam filter (b) a kitchen weighing scale (c) an AI chatbot (d) photos grouped by face
20. 20.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
21. 21.⏩ In machine learning, which comes first: recorded spoken words or the trained program? (a) recorded spoken words (b) the trained program
22. 22.🤖 AI or a normal program: which one “spots patterns in data”? (a) AI (b) a normal program
23. 23.True or false: “a logo idea for the eco club” asks for music or sound. (a) False (b) True
24. 24.True or false: “recorded spoken words” is training data. (a) True (b) False
25. 25.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) better at its task (d) forget everything
26. 26.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) wrong labels (d) new data for testing
27. 27.Which of these is training data? (a) naming a new fruit photo (b) tomorrow’s rain guess (c) what training builds (d) labelled fruit photos
28. 28.🛠️ Which does this job need: counting the words in an essay? (a) needs AI (learning) (b) a simple rule is enough
29. 29.Which of these is a myth about AI? (a) AI has real feelings (b) AI answers need checking (c) AI can make up facts (d) AI copies data patterns
30. 30.⏩ In machine learning, which comes first: what training builds or typing a new spoken word? (a) what training builds (b) typing a new spoken word
31. 31.✨ What does generative AI do? (a) only stores files (b) charges batteries (c) only adds numbers (d) makes new content
32. 32.True or false: “it sounds very sure” is a real way to check an AI answer. (a) False (b) True
33. 33.🤖 Does an AI system think and feel like a person? (a) yes, just like us (b) no, it finds patterns (c) only on weekends (d) yes, it gets sad
34. 34.✨ Generative or not: making up a story? (a) makes something new (b) sorts or predicts
35. 35.True or false: “AI can make up facts” is a fact about AI. (a) False (b) True
36. 36.🔍 Which is the odd one out? (a) skip testing (b) balance the data (c) ask different people (d) add varied examples
37. 37.Which of these is not AI? (a) face unlock on a phone (b) a light switch (c) an app translating signs (d) a voice assistant
38. 38.True or false: “it answered quickly” is a real way to check an AI answer. (a) False (b) True
39. 39.Which of these is not AI? (a) video suggestions (b) a printed timetable (c) voice typing (d) an app translating signs
40. 40.True or false: “many varied examples” is good for training a model. (a) True (b) False

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