AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 711 · 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.✨ What does generative AI do? (a) charges batteries (b) only stores files (c) makes new content (d) only adds numbers
2. 2.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
3. 3.Which of these is bad for training a model? (a) clear, sharp examples (b) copies of one photo (c) correct labels (d) examples of every type
4. 4.📚 An AI chatbot names a book that does not exist. This is called… (a) a hallucination (b) a summary (c) a backup (d) a password
5. 5.True or false: a voice app trained only on adult voices is one-sided data (likely to make a biased model). (a) False (b) True
6. 6.⏩ In machine learning, which comes first: recorded spoken words or what training builds? (a) recorded spoken words (b) what training builds
7. 7.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
8. 8.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) balanced data (b) one-sided data
9. 9.Which of these is good for training a model? (a) wrong labels (b) testing on training data (c) copies of one photo (d) new data for testing
10. 10.🖼️ If an image generator always draws a scientist as a man, that shows… (a) bias from data (b) a fair model (c) a strong battery (d) a broken screen
11. 11.🧐 Fact or myth: “AI can make up facts”? (a) a fact (b) a myth
12. 12.📱 What is the AI doing here: an AI tool making a brand-new tune? (a) generating (b) predicting (c) recognising (d) recommending
13. 13.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
14. 14.True or false: converting metres into centimetres only needs a simple fixed rule. (a) False (b) True
15. 15.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) one single photo (d) a list of rules only
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
17. 17.✨ Generative or not: writing quiz questions? (a) sorts or predicts (b) makes something new
18. 18.💬 What do we call the request you type to a generative AI? (a) a label (b) a prompt (c) a battery (d) a password
19. 19.True or false: counting the words in an essay only needs a simple fixed rule. (a) False (b) True
20. 20.🔍 Which is the odd one out? (a) drafting a letter (b) inventing a recipe (c) composing a new tune (d) unlocking with a face
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
22. 22.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
23. 23.True or false: suggesting the next word as you type only needs a simple fixed rule. (a) True (b) False
24. 24.Which of these describes how AI works? (a) follows fixed rules (b) one set rule per case (c) never learns from data (d) handles unseen examples
25. 25.✅ Is this a real check of an AI answer: it has a neat layout? (a) not a real check (b) a real check
26. 26.True or false: “a drawing of a cat on the Moon” asks for text. (a) True (b) False
27. 27.🛠️ Which does this job need: telling a cat photo from a dog photo? (a) a simple rule is enough (b) needs AI (learning)
28. 28.📱 What is the AI doing here: a camera app naming the flower you point at? (a) predicting (b) recommending (c) recognising (d) generating
29. 29.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) data, model, prediction (d) model, prediction, data
30. 30.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) testing on training data (d) new data for testing
31. 31.🔍 Which is the odd one out? (a) unlocking with a face (b) inventing a recipe (c) spotting a sick leaf (d) sorting photos by face
32. 32.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
33. 33.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
34. 34.🔍 Which is the odd one out? (a) ask different people (b) test on one group only (c) fix wrong labels (d) test on many groups
35. 35.Which of these is not AI? (a) a spam filter (b) an app translating signs (c) a fan regulator (d) voice typing
36. 36.🔍 Which is the odd one out? (a) add varied examples (b) skip testing (c) ask different people (d) test on many groups
37. 37.🔍 Which is the odd one out? (a) clear, sharp examples (b) blurry, unclear photos (c) examples of every type (d) checking labels twice
38. 38.True or false: “match it to the textbook” is a real way to check an AI answer. (a) False (b) True
39. 39.Which of these helps reduce bias? (a) skip testing (b) ignore complaints (c) balance the data (d) use one group only
40. 40.🔍 Which is the odd one out? (a) a microwave timer (b) a fan regulator (c) photos grouped by face (d) a printed timetable

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