AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 673 · 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.True or false: “follows fixed rules” describes how AI works. (a) True (b) False
2. 2.🏠 AI or not AI: video suggestions? (a) not AI (b) uses AI
3. 3.🤖 Who builds and trains AI systems? (a) nobody at all (b) the weather (c) people (d) the Moon
4. 4.⏩ In machine learning, which comes first: what training builds or naming a new fruit photo? (a) what training builds (b) naming a new fruit photo
5. 5.True or false: turning spoken words into typed text only needs a simple fixed rule. (a) False (b) True
6. 6.🔍 Which is the odd one out? (a) examples of every type (b) wrong labels (c) photos in many lights (d) new data for testing
7. 7.🔍 Which is the odd one out? (a) use one group only (b) ignore complaints (c) ask different people (d) add more of the same
8. 8.🏷️ 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
9. 9.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
10. 10.Which of these is bad for training a model? (a) many varied examples (b) only one kind of example (c) correct labels (d) new data for testing
11. 11.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) text (b) music or sound (c) an image
12. 12.Which of these describes how a normal program works? (a) spots patterns in data (b) follows fixed rules (c) handles unseen examples (d) improves with more data
13. 13.⚖️ One-sided or balanced data: a handwriting app shown only neat writing? (a) balanced data (b) one-sided data
14. 14.True or false: an AI chatbot writing a poem about rain is AI recognising something. (a) False (b) True
15. 15.True or false: “five quiz questions on fractions” asks for text. (a) True (b) False
16. 16.✅ Is this a real check of an AI answer: ask your teacher? (a) a real check (b) not a real check
17. 17.True or false: “add varied examples” helps reduce bias. (a) False (b) True
18. 18.True or false: “same steps every time” describes how a normal program works. (a) True (b) False
19. 19.Which of these is the model? (a) tomorrow’s rain guess (b) the learned patterns (c) typing a new spoken word (d) flagging a new email
20. 20.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
21. 21.🔍 Which is the odd one out? (a) composing a new tune (b) creating a cartoon (c) writing quiz questions (d) sorting photos by face
22. 22.🧮 Which of these is NOT AI? (a) voice typing (b) a basic calculator (c) a spam filter (d) face unlock
23. 23.🧐 Fact or myth: “confident means correct”? (a) a myth (b) a fact
24. 24.Which of these describes how AI works? (a) one set rule per case (b) handles unseen examples (c) does exactly as coded (d) same steps every time
25. 25.🤖 What makes an AI system different from a normal program? (a) it learns from examples (b) it has a screen (c) it uses electricity (d) it is always right
26. 26.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) not spam (b) spam
27. 27.Which of these is training data? (a) recorded spoken words (b) flagging a new email (c) naming a new fruit photo (d) the learned patterns
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: “add more of the same” helps reduce bias. (a) False (b) True
30. 30.⏩ In machine learning, which comes first: the learned patterns or naming a new fruit photo? (a) the learned patterns (b) naming a new fruit photo
31. 31.Which of these is a prediction? (a) the learned patterns (b) naming a new fruit photo (c) old emails marked spam (d) recorded spoken words
32. 32.⏩ In machine learning, which comes first: labelled fruit photos or naming a new leaf? (a) labelled fruit photos (b) naming a new leaf
33. 33.🔍 Which is the odd one out? (a) AI has real feelings (b) AI can make up facts (c) AI copies data patterns (d) AI can be wrong
34. 34.True or false: “test on one group only” helps reduce bias. (a) True (b) False
35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
36. 36.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) add more of the same (b) use one group only (c) fix wrong labels (d) test on one group only
38. 38.🔍 Which is the odd one out? (a) an app translating signs (b) face unlock on a phone (c) photos grouped by face (d) a kitchen weighing scale
39. 39.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
40. 40.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training

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