AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 228 · 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: “balance the data” helps reduce bias. (a) False (b) True
2. 2.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it may get it wrong (c) it will turn yellow (d) it will shut down
3. 3.🛠️ Does this reduce bias or add to it: balance the data? (a) reduces bias (b) adds to bias
4. 4.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) data, model, prediction (d) prediction, data, model
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
6. 6.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
7. 7.True or false: “a logo idea for the eco club” asks for music or sound. (a) False (b) True
8. 8.🏠 AI or not AI: a stopwatch? (a) uses AI (b) not AI
9. 9.⏩ In machine learning, which comes first: recorded spoken words or the trained program? (a) recorded spoken words (b) the trained program
10. 10.Which of these describes how a normal program works? (a) makes a best guess (b) spots patterns in data (c) uses rules people wrote (d) improves with more data
11. 11.🛠️ Which does this job need: sorting names in A to Z order? (a) needs AI (learning) (b) a simple rule is enough
12. 12.Which of these helps reduce bias? (a) ignore complaints (b) test on one group only (c) fix wrong labels (d) copy old unfair choices
13. 13.True or false: “skip testing” adds to bias. (a) False (b) True
14. 14.True or false: leaves from every season of the year is balanced data (fairer for everyone). (a) True (b) False
15. 15.📱 What is the AI doing here: turning your spoken words into typed text? (a) generating (b) predicting (c) recommending (d) recognising
16. 16.🛠️ What helps make an AI system fairer? (a) fewer tests (b) more varied data (c) one group only (d) ignoring mistakes
17. 17.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
18. 18.✅ Is this a real check of an AI answer: match it to the textbook? (a) a real check (b) not a real check
19. 19.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) the model (c) training data
20. 20.Which of these is generative AI (it makes something new)? (a) suggesting a video (b) spotting spam (c) making up a story (d) spotting a sick leaf
21. 21.🔍 Which is the odd one out? (a) AI can be wrong (b) AI can make up facts (c) AI answers need checking (d) AI always checks facts
22. 22.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) better at its task (d) forget everything
23. 23.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) a fair model (c) a strong battery (d) bias from data
24. 24.Which of these is bad for training a model? (a) examples of every type (b) checking labels twice (c) testing on training data (d) many varied examples
25. 25.🏠 AI or not AI: a kitchen weighing scale? (a) uses AI (b) not AI
26. 26.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) very few examples (b) only one kind of example (c) clear, sharp examples (d) testing on training data
28. 28.🧐 Fact or myth: “long answers are true”? (a) a fact (b) a myth
29. 29.True or false: “AI learns from data” is a fact about AI. (a) False (b) True
30. 30.📱 What is the AI doing here: an image generator drawing a robot from a sentence? (a) predicting (b) recommending (c) generating (d) recognising
31. 31.🤖 What does AI stand for? (a) automatic internet (b) actual information (c) app installer (d) artificial intelligence
32. 32.🧐 Fact or myth: “AI is never wrong”? (a) a fact (b) a myth
33. 33.Which of these describes how a normal program works? (a) makes a best guess (b) one set rule per case (c) handles unseen examples (d) gives a likely answer
34. 34.📱 What is the AI doing here: a weather app guessing tomorrow’s rain? (a) recognising (b) generating (c) recommending (d) predicting
35. 35.⏩ In machine learning, which comes first: past weather records or typing a new spoken word? (a) past weather records (b) typing a new spoken word
36. 36.Which of these is a fact about AI? (a) AI can make up facts (b) AI has real feelings (c) AI always checks facts (d) AI is never wrong
37. 37.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
38. 38.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a password (c) a prediction (d) training data
39. 39.⚖️ One-sided or balanced data: photos of people from only one age group? (a) balanced data (b) one-sided data
40. 40.🏷️ 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

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