AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 955 · 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 helps reduce bias? (a) ignore complaints (b) add more of the same (c) skip testing (d) fix wrong labels
2. 2.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
3. 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) the phone was new (c) children speak too fast (d) few child voices in data
4. 4.🤖 Who builds and trains AI systems? (a) people (b) nobody at all (c) the weather (d) the Moon
5. 5.True or false: voices of children and adults from many regions is one-sided data (likely to make a biased model). (a) False (b) True
6. 6.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
7. 7.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
8. 8.Which of these helps reduce bias? (a) copy old unfair choices (b) skip testing (c) ask different people (d) ignore complaints
9. 9.Which of these describes how AI works? (a) never learns from data (b) improves with more data (c) does exactly as coded (d) same steps every time
10. 10.🔍 Which is the odd one out? (a) a fan regulator (b) a voice assistant (c) a doorbell (d) a digital watch
11. 11.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
12. 12.True or false: “makes a best guess” describes how AI works. (a) False (b) True
13. 13.True or false: “labels added at random” is good for training a model. (a) False (b) True
14. 14.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it takes photos (d) it prints labels
15. 15.🔍 Which is the odd one out? (a) many varied examples (b) new data for testing (c) blurry, unclear photos (d) examples of every type
16. 16.🔍 Which is the odd one out? (a) writing quiz questions (b) predicting rain (c) creating a cartoon (d) drafting a letter
17. 17.🔍 Which is the odd one out? (a) wrong labels (b) new data for testing (c) examples of every type (d) photos in many lights
18. 18.Which of these is good for training a model? (a) only one kind of example (b) examples of every type (c) very few examples (d) wrong labels
19. 19.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a fair model (d) a strong battery
20. 20.🔍 Which is the odd one out? (a) a digital watch (b) a stopwatch (c) a printed timetable (d) a map predicting traffic
21. 21.True or false: an AI tool making a brand-new tune is AI generating something new. (a) False (b) True
22. 22.💬 What do we call the request you type to a generative AI? (a) a password (b) a battery (c) a label (d) a prompt
23. 23.Which of these describes how a normal program works? (a) gives a likely answer (b) follows fixed rules (c) spots patterns in data (d) learns from examples
24. 24.🧪 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
25. 25.🔍 Which is the odd one out? (a) spotting a sick leaf (b) turning speech to text (c) spotting spam (d) drawing a new picture
26. 26.✨ Generative or not: writing a new poem? (a) makes something new (b) sorts or predicts
27. 27.Which of these is bad for training a model? (a) clear, sharp examples (b) blurry, unclear photos (c) photos in many lights (d) examples of every type
28. 28.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
29. 29.Which of these is the model? (a) the learned patterns (b) tomorrow’s rain guess (c) naming a new leaf (d) old emails marked spam
30. 30.Which of these is a fact about AI? (a) AI learns from data (b) confident means correct (c) long answers are true (d) AI is never wrong
31. 31.Which of these is a prediction? (a) recorded spoken words (b) the trained program (c) old emails marked spam (d) naming a new leaf
32. 32.🏠 AI or not AI: a spam filter? (a) not AI (b) uses AI
33. 33.Which of these is bad for training a model? (a) examples of every type (b) new data for testing (c) only one kind of example (d) checking labels twice
34. 34.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
35. 35.True or false: “the trained program” is the model. (a) True (b) False
36. 36.True or false: “recorded spoken words” is the model. (a) True (b) False
37. 37.⏩ In machine learning, which comes first: tomorrow’s rain guess or 500 labelled leaf photos? (a) tomorrow’s rain guess (b) 500 labelled leaf photos
38. 38.🤖 AI or a normal program: which one “same steps every time”? (a) a normal program (b) AI
39. 39.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
40. 40.Which of these uses AI? (a) a digital watch (b) an image generator (c) a stopwatch (d) a printed timetable

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