AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 852 · 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.✅ Is this a real check of an AI answer: it answered quickly? (a) a real check (b) not a real check
2. 2.🔁 What is the right order? (a) prediction, data, model (b) data, model, prediction (c) model, prediction, data (d) data, prediction, model
3. 3.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
4. 4.🔍 Which is the odd one out? (a) copy old unfair choices (b) skip testing (c) test on many groups (d) use one group only
5. 5.Which of these describes how a normal program works? (a) gives a likely answer (b) follows fixed rules (c) spots patterns in data (d) handles unseen examples
6. 6.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its screen size (c) its colour (d) its training data
7. 7.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
8. 8.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
9. 9.🔍 Which is the odd one out? (a) reading number plates (b) inventing a recipe (c) drawing a new picture (d) drafting a letter
10. 10.Which of these is the model? (a) what training builds (b) old emails marked spam (c) naming a new fruit photo (d) typing a new spoken word
11. 11.True or false: “it uses big words” is a real way to check an AI answer. (a) False (b) True
12. 12.✨ Generative or not: spotting spam? (a) sorts or predicts (b) makes something new
13. 13.True or false: “wrong labels” is good for training a model. (a) False (b) True
14. 14.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
15. 15.Which of these describes how a normal program works? (a) handles unseen examples (b) spots patterns in data (c) improves with more data (d) uses rules people wrote
16. 16.💬 What do we call the request you type to a generative AI? (a) a password (b) a prompt (c) a label (d) a battery
17. 17.🔍 Which is the odd one out? (a) examples of every type (b) new data for testing (c) blurry, unclear photos (d) correct labels
18. 18.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
19. 19.Which of these is a fact about AI? (a) AI has real feelings (b) AI learns from data (c) AI knows everything (d) AI is never wrong
20. 20.True or false: mangoes both raw and ripe is balanced data (fairer for everyone). (a) False (b) True
21. 21.🤖 AI or a normal program: which one “spots patterns in data”? (a) AI (b) a normal program
22. 22.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) it was a rainy day (c) few child voices in data (d) children speak too fast
23. 23.True or false: “gives a likely answer” describes how a normal program works. (a) True (b) False
24. 24.Which of these is good for training a model? (a) copies of one photo (b) clear, sharp examples (c) wrong labels (d) testing on training data
25. 25.True or false: “copies of one photo” is good for training a model. (a) True (b) False
26. 26.Which of these is bad for training a model? (a) blurry, unclear photos (b) new data for testing (c) clear, sharp examples (d) correct labels
27. 27.True or false: an AI chatbot writing a poem about rain is AI generating something new. (a) False (b) True
28. 28.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
29. 29.True or false: “old emails marked spam” is the model. (a) True (b) False
30. 30.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
31. 31.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
32. 32.True or false: suggesting the next word as you type needs AI that learns from examples. (a) True (b) False
33. 33.True or false: a video app suggesting what to watch next is AI predicting something. (a) True (b) False
34. 34.🤖 What does AI stand for? (a) app installer (b) actual information (c) automatic internet (d) artificial intelligence
35. 35.🔍 Which is the odd one out? (a) checking labels twice (b) new data for testing (c) only one kind of example (d) examples of every type
36. 36.True or false: “very few examples” is good for training a model. (a) False (b) True
37. 37.🏷️ 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
38. 38.🏠 AI or not AI: a map predicting traffic? (a) uses AI (b) not AI
39. 39.🤖 AI or a normal program: which one “learns from examples”? (a) AI (b) a normal program
40. 40.Which of these is the model? (a) recorded spoken words (b) 500 labelled leaf photos (c) labelled fruit photos (d) the trained program

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