AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 589 · 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.Which of these is the model? (a) 500 labelled leaf photos (b) naming a new fruit photo (c) the trained program (d) recorded spoken words
2. 2.🤖 AI or a normal program: which one “handles unseen examples”? (a) AI (b) a normal program
3. 3.✨ Generative or not: writing a new poem? (a) sorts or predicts (b) makes something new
4. 4.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) clean screens (d) learn from data
5. 5.🤖 Who builds and trains AI systems? (a) the weather (b) the Moon (c) nobody at all (d) people
6. 6.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
7. 7.🤖 What makes an AI system different from a normal program? (a) it is always right (b) it learns from examples (c) it uses electricity (d) it has a screen
8. 8.Which of these describes how AI works? (a) improves with more data (b) same steps every time (c) follows fixed rules (d) one set rule per case
9. 9.True or false: “improves with more data” describes how a normal program works. (a) True (b) False
10. 10.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) better at its task (d) slower to switch on
11. 11.🧪 Why test a model on NEW examples? (a) to make it slower (b) to delete its data (c) to see if it works (d) to change its name
12. 12.🔍 Which is the odd one out? (a) ignore complaints (b) ask different people (c) balance the data (d) test on many groups
13. 13.🔍 Which is the odd one out? (a) a spam filter (b) an app translating signs (c) an image generator (d) a stopwatch
14. 14.🤖 AI or a normal program: which one “learns from examples”? (a) a normal program (b) AI
15. 15.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
16. 16.✨ Generative or not: drafting a letter? (a) makes something new (b) sorts or predicts
17. 17.🔍 Which is the odd one out? (a) labels added at random (b) new data for testing (c) blurry, unclear photos (d) only one kind of example
18. 18.🔍 Which is the odd one out? (a) long answers are true (b) AI can be wrong (c) confident means correct (d) AI has real feelings
19. 19.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
20. 20.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
21. 21.🔍 Which is the odd one out? (a) new data for testing (b) checking labels twice (c) only one kind of example (d) photos in many lights
22. 22.Which of these is bad for training a model? (a) many varied examples (b) photos in many lights (c) checking labels twice (d) copies of one photo
23. 23.True or false: “AI copies data patterns” is a fact about AI. (a) True (b) False
24. 24.🔍 Which is the odd one out? (a) long answers are true (b) AI copies data patterns (c) AI is never wrong (d) AI knows everything
25. 25.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a strong battery (b) a broken screen (c) a fair model (d) bias from data
26. 26.📱 What is the AI doing here: a book app suggesting a story like your last one? (a) recognising (b) predicting (c) generating (d) recommending
27. 27.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
28. 28.True or false: translating a sentence into Hindi needs AI that learns from examples. (a) False (b) True
29. 29.True or false: turning your spoken words into typed text is AI generating something new. (a) False (b) True
30. 30.🤖 AI or a normal program: which one “improves with more data”? (a) a normal program (b) AI
31. 31.🛠️ Which does this job need: switching on a street light at 6 pm? (a) needs AI (learning) (b) a simple rule is enough
32. 32.Which of these is bad for training a model? (a) only one kind of example (b) correct labels (c) new data for testing (d) photos in many lights
33. 33.True or false: “old emails marked spam” is training data. (a) False (b) True
34. 34.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
35. 35.True or false: recognising a friend’s face in photos needs AI that learns from examples. (a) False (b) True
36. 36.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data
37. 37.🤔 An AI answer sounds very confident. Does that mean it is right? (a) no, check it anyway (b) yes, always (c) yes, if it is long
38. 38.✨ Generative or not: spotting spam? (a) makes something new (b) sorts or predicts
39. 39.🔍 Which is the odd one out? (a) add varied examples (b) copy old unfair choices (c) test on one group only (d) skip testing
40. 40.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training

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