AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 460 · 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.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
2. 2.🔁 What is the right order? (a) data, prediction, model (b) data, model, prediction (c) model, prediction, data (d) prediction, data, model
3. 3.🛠️ Which does this job need: counting the words in an essay? (a) a simple rule is enough (b) needs AI (learning)
4. 4.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) only one kind of example (d) many varied examples
5. 5.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) it was a rainy day (c) the phone was new (d) few child voices in data
6. 6.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
7. 7.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) music or sound (b) an image (c) text
8. 8.🔍 Which is the odd one out? (a) AI can mix up numbers (b) AI is never wrong (c) AI learns from data (d) AI answers need checking
9. 9.Which of these is training data? (a) flagging a new email (b) naming a new fruit photo (c) tomorrow’s rain guess (d) 500 labelled leaf photos
10. 10.True or false: “labels added at random” is bad for training a model. (a) False (b) True
11. 11.🔍 Which is the odd one out? (a) spotting a sick leaf (b) writing quiz questions (c) composing a new tune (d) creating a cartoon
12. 12.Which of these uses AI? (a) a calculator (b) a spam filter (c) a digital watch (d) a stopwatch
13. 13.🔍 Which is the odd one out? (a) face unlock on a phone (b) photos grouped by face (c) an image generator (d) a calculator
14. 14.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
15. 15.⏩ 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
16. 16.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
17. 17.🔍 Which is the odd one out? (a) AI has real feelings (b) confident means correct (c) AI can make up facts (d) AI knows everything
18. 18.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
19. 19.True or false: suggesting the next word as you type needs AI that learns from examples. (a) False (b) True
20. 20.🏠 AI or not AI: a stopwatch? (a) not AI (b) uses AI
21. 21.🧐 Fact or myth: “AI can be wrong”? (a) a fact (b) a myth
22. 22.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
23. 23.True or false: “a logo idea for the eco club” asks for text. (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) photos grouped by face (b) a map predicting traffic (c) face unlock on a phone (d) a kitchen weighing scale
25. 25.🤖 What makes an AI system different from a normal program? (a) it has a screen (b) it is always right (c) it uses electricity (d) it learns from examples
26. 26.True or false: a keyboard guessing your next word is AI generating something new. (a) False (b) True
27. 27.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) True (b) False
28. 28.🔍 Which is the odd one out? (a) suggesting a video (b) spotting spam (c) spotting a sick leaf (d) creating a cartoon
29. 29.Which of these describes how AI works? (a) never learns from data (b) uses rules people wrote (c) same steps every time (d) gives a likely answer
30. 30.✨ Generative or not: composing a new tune? (a) makes something new (b) sorts or predicts
31. 31.🧐 Fact or myth: “confident means correct”? (a) a fact (b) a myth
32. 32.✅ Is this a real check of an AI answer: it uses big words? (a) not a real check (b) a real check
33. 33.Which of these is bad for training a model? (a) new data for testing (b) labels added at random (c) many varied examples (d) checking labels twice
34. 34.Which of these adds to bias? (a) fix wrong labels (b) test on one group only (c) check who is missing (d) ask different people
35. 35.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a password (c) training data (d) a label error
36. 36.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) better at its task (d) forget everything
37. 37.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
38. 38.🏷️ 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
39. 39.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) training data (c) the model
40. 40.🤖 AI or a normal program: which one “does exactly as coded”? (a) AI (b) a normal program

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