AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 375 · 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.📚 Usually, more good examples make a model… (a) better at its task (b) forget everything (c) slower to switch on (d) change colour
2. 2.🤖 AI or a normal program: which one “never learns from data”? (a) a normal program (b) AI
3. 3.True or false: “a drum beat for a dance” asks for music or sound. (a) False (b) True
4. 4.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) adds to bias (b) reduces bias
5. 5.True or false: converting metres into centimetres only needs a simple fixed rule. (a) False (b) True
6. 6.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a prediction (c) training data (d) a label error
7. 7.🤖 What does AI stand for? (a) artificial intelligence (b) actual information (c) app installer (d) automatic internet
8. 8.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
9. 9.True or false: a fruit sorter shown only ripe mangoes is one-sided data (likely to make a biased model). (a) True (b) False
10. 10.Which of these describes how a normal program works? (a) learns from examples (b) spots patterns in data (c) makes a best guess (d) uses rules people wrote
11. 11.✨ What does generative AI do? (a) only stores files (b) makes new content (c) charges batteries (d) only adds numbers
12. 12.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
13. 13.Which of these describes how AI works? (a) uses rules people wrote (b) one set rule per case (c) same steps every time (d) handles unseen examples
14. 14.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
15. 15.True or false: “AI can be wrong” is a myth about AI. (a) False (b) True
16. 16.True or false: “skip testing” adds to bias. (a) False (b) True
17. 17.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) one-sided data (b) balanced data
18. 18.🔍 Which is the odd one out? (a) a stopwatch (b) a microwave timer (c) a fan regulator (d) an app translating signs
19. 19.🔁 What is the right order? (a) prediction, data, model (b) data, model, prediction (c) data, prediction, model (d) model, prediction, data
20. 20.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
21. 21.Which of these is good for training a model? (a) very few examples (b) labels added at random (c) only one kind of example (d) examples of every type
22. 22.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) photos in many lights (d) copies of one photo
23. 23.📱 What is the AI doing here: a phone unlocking when it sees your face? (a) generating (b) predicting (c) recommending (d) recognising
24. 24.🎨 This prompt asks a generative AI for: a cartoon of a dancing elephant. What kind of output is that? (a) an image (b) music or sound (c) text
25. 25.Which of these is AI that sorts, spots or predicts (not generative)? (a) composing a new tune (b) writing quiz questions (c) predicting rain (d) making up a story
26. 26.Which of these is a prediction? (a) the learned patterns (b) past weather records (c) the trained program (d) naming a new fruit photo
27. 27.True or false: “it answered quickly” is a real way to check an AI answer. (a) True (b) False
28. 28.⏩ In machine learning, which comes first: naming a new fruit photo or what training builds? (a) naming a new fruit photo (b) what training builds
29. 29.📚 An AI chatbot names a book that does not exist. This is called… (a) a password (b) a hallucination (c) a summary (d) a backup
30. 30.🤖 AI or a normal program: which one “improves with more data”? (a) AI (b) a normal program
31. 31.True or false: “a story about a brave ant” asks for text. (a) False (b) True
32. 32.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
33. 33.True or false: “asking the same AI again” is NOT a real way to check an AI answer. (a) True (b) False
34. 34.⏩ In machine learning, which comes first: typing a new spoken word or old emails marked spam? (a) typing a new spoken word (b) old emails marked spam
35. 35.True or false: “match it to the textbook” is a real way to check an AI answer. (a) True (b) False
36. 36.🧐 Fact or myth: “AI can be wrong”? (a) a fact (b) a myth
37. 37.True or false: “the trained program” is the model. (a) False (b) True
38. 38.🛠️ Does this reduce bias or add to it: skip testing? (a) reduces bias (b) adds to bias
39. 39.True or false: “labelled fruit photos” is training data. (a) False (b) True
40. 40.Which of these is generative AI (it makes something new)? (a) reading number plates (b) unlocking with a face (c) making up a story (d) predicting rain

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