AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 818 · 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) add more of the same (b) check who is missing (c) test on many groups (d) fix wrong labels
2. 2.Which of these describes how a normal program works? (a) same steps every time (b) improves with more data (c) learns from examples (d) handles unseen examples
3. 3.Which of these is AI that sorts, spots or predicts (not generative)? (a) sorting photos by face (b) writing quiz questions (c) drawing a new picture (d) inventing a recipe
4. 4.🏠 AI or not AI: an AI chatbot? (a) not AI (b) uses AI
5. 5.🔍 Which is the odd one out? (a) predicting rain (b) suggesting a video (c) creating a cartoon (d) spotting a sick leaf
6. 6.✍️ How does an AI chatbot write its replies? (a) copies one website (b) uses magic (c) asks a person (d) predicts likely words
7. 7.📚 An AI chatbot names a book that does not exist. This is called… (a) a password (b) a backup (c) a summary (d) a hallucination
8. 8.Which of these is not AI? (a) a map predicting traffic (b) video suggestions (c) a digital watch (d) photos grouped by face
9. 9.🔍 Which is the odd one out? (a) a voice assistant (b) a calculator (c) a spam filter (d) face unlock on a phone
10. 10.Which of these is a prediction? (a) recorded spoken words (b) labelled fruit photos (c) tomorrow’s rain guess (d) the trained program
11. 11.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) many labelled photos (c) one single photo (d) a song about dogs
12. 12.🎨 An image generator makes a picture from… (a) a text description (b) a phone number (c) the weather (d) your password
13. 13.Which of these is bad for training a model? (a) very few examples (b) photos in many lights (c) correct labels (d) checking labels twice
14. 14.True or false: “flagging a new email” is training data. (a) False (b) True
15. 15.Which of these describes how a normal program works? (a) handles unseen examples (b) spots patterns in data (c) gives a likely answer (d) uses rules people wrote
16. 16.🧮 Which of these is NOT AI? (a) face unlock (b) a basic calculator (c) a spam filter (d) voice typing
17. 17.💬 What do we call the request you type to a generative AI? (a) a battery (b) a label (c) a password (d) a prompt
18. 18.🏠 AI or not AI: a spam filter? (a) not AI (b) uses AI
19. 19.📱 What is the AI doing here: a camera app naming the flower you point at? (a) recommending (b) predicting (c) generating (d) recognising
20. 20.🤖 Who builds and trains AI systems? (a) the weather (b) nobody at all (c) people (d) the Moon
21. 21.Which of these uses AI? (a) a kitchen weighing scale (b) a fan regulator (c) a doorbell (d) photos grouped by face
22. 22.Which of these is good for training a model? (a) wrong labels (b) many varied examples (c) testing on training data (d) only one kind of example
23. 23.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
24. 24.✨ Generative or not: making up a story? (a) makes something new (b) sorts or predicts
25. 25.🧐 Fact or myth: “AI answers need checking”? (a) a fact (b) a myth
26. 26.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
27. 27.Which of these is the model? (a) the learned patterns (b) old emails marked spam (c) naming a new fruit photo (d) past weather records
28. 28.True or false: “very few examples” is bad for training a model. (a) True (b) False
29. 29.Which of these is generative AI (it makes something new)? (a) writing quiz questions (b) spotting spam (c) predicting rain (d) unlocking with a face
30. 30.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
31. 31.True or false: reading messy handwriting needs AI that learns from examples. (a) False (b) True
32. 32.🔍 Which is the odd one out? (a) many varied examples (b) photos in many lights (c) testing on training data (d) new data for testing
33. 33.🛠️ Which does this job need: recognising a bird from its song? (a) a simple rule is enough (b) needs AI (learning)
34. 34.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
35. 35.True or false: “same steps every time” describes how a normal program works. (a) False (b) True
36. 36.🤖 AI or a normal program: which one “handles unseen examples”? (a) AI (b) a normal program
37. 37.📅 An AI gives a date for a history event. How can you check? (a) guess (b) ask it to repeat (c) pick a lucky number (d) look in your textbook
38. 38.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
39. 39.True or false: an AI chatbot writing a poem about rain is AI predicting something. (a) True (b) False
40. 40.True or false: a map app guessing how long a trip will take is AI predicting something. (a) True (b) False

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