AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 328 · 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 is the odd one out? (a) copies of one photo (b) blurry, unclear photos (c) checking labels twice (d) testing on training data
2. 2.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
3. 3.True or false: “same steps every time” describes how AI works. (a) False (b) True
4. 4.🔍 Which is the odd one out? (a) ask different people (b) add more of the same (c) ignore complaints (d) use one group only
5. 5.Which of these is a myth about AI? (a) long answers are true (b) AI can make up facts (c) AI copies data patterns (d) AI can be wrong
6. 6.Which of these describes how AI works? (a) same steps every time (b) uses rules people wrote (c) does exactly as coded (d) spots patterns in data
7. 7.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
8. 8.True or false: a map app guessing how long a trip will take is AI recognising something. (a) True (b) False
9. 9.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
10. 10.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
11. 11.True or false: “recorded spoken words” is training data. (a) True (b) False
12. 12.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) training data (c) a label error (d) a password
13. 13.True or false: “labelled fruit photos” is training data. (a) True (b) False
14. 14.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) checking labels twice (d) blurry, unclear photos
15. 15.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
16. 16.✨ Generative or not: inventing a recipe? (a) sorts or predicts (b) makes something new
17. 17.Which of these is a prediction? (a) recorded spoken words (b) tomorrow’s rain guess (c) the trained program (d) what training builds
18. 18.🤖 AI or a normal program: which one “gives a likely answer”? (a) a normal program (b) AI
19. 19.True or false: reading messy handwriting only needs a simple fixed rule. (a) True (b) False
20. 20.True or false: a camera app naming the flower you point at is AI recommending something. (a) True (b) False
21. 21.✨ Generative or not: making up a story? (a) sorts or predicts (b) makes something new
22. 22.Which of these uses AI? (a) a torch (b) a calculator (c) face unlock on a phone (d) a microwave timer
23. 23.🗣️ 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) few child voices in data (d) the phone was new
24. 24.🏷️ What is a “label” in machine learning? (a) the font size (b) a sticker on a laptop (c) the price (d) the right answer tag
25. 25.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
26. 26.🔍 Which is the odd one out? (a) copies of one photo (b) new data for testing (c) only one kind of example (d) wrong labels
27. 27.Which of these helps reduce bias? (a) test on one group only (b) test on many groups (c) add more of the same (d) use one group only
28. 28.Which of these is good for training a model? (a) correct labels (b) wrong labels (c) very few examples (d) blurry, unclear photos
29. 29.True or false: “very few examples” is bad for training a model. (a) False (b) True
30. 30.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
31. 31.True or false: “learns from examples” describes how AI works. (a) False (b) True
32. 32.True or false: an online shop showing “you may also like” is AI generating something new. (a) True (b) False
33. 33.✨ Generative or not: composing a new tune? (a) sorts or predicts (b) makes something new
34. 34.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
35. 35.True or false: “it answered quickly” is a real way to check an AI answer. (a) False (b) True
36. 36.Which of these adds to bias? (a) ask different people (b) skip testing (c) check who is missing (d) add varied examples
37. 37.📱 What is the AI doing here: a camera app naming the flower you point at? (a) generating (b) predicting (c) recommending (d) recognising
38. 38.🤖 AI or a normal program: which one “learns from examples”? (a) a normal program (b) AI
39. 39.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) only one kind of example (d) many varied examples
40. 40.Which of these describes how a normal program works? (a) learns from examples (b) spots patterns in data (c) follows fixed rules (d) makes a best guess

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