AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 716 · 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 is good for training a model? (a) photos in many lights (b) labels added at random (c) wrong labels (d) very few examples
2. 2.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
3. 3.📱 What is the AI doing here: a car camera reading a speed sign? (a) generating (b) recognising (c) recommending (d) predicting
4. 4.Which of these is generative AI (it makes something new)? (a) making up a story (b) reading number plates (c) unlocking with a face (d) spotting spam
5. 5.Which of these is good for training a model? (a) clear, sharp examples (b) labels added at random (c) wrong labels (d) blurry, unclear photos
6. 6.Which of these is a fact about AI? (a) AI is never wrong (b) AI answers need checking (c) AI knows everything (d) AI has real feelings
7. 7.✨ Generative or not: making up a story? (a) makes something new (b) sorts or predicts
8. 8.⚖️ Where does bias in an AI system usually come from? (a) its colour (b) the weather (c) its training data (d) its screen size
9. 9.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it may get it wrong (c) it will be perfect (d) it will turn yellow
10. 10.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) ask it to hurry (b) never do maths (c) copy it straight away (d) check it on paper
11. 11.🤖 AI or a normal program: which one “follows fixed rules”? (a) a normal program (b) AI
12. 12.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
13. 13.True or false: “long answers are true” is a myth about AI. (a) False (b) True
14. 14.⚖️ One-sided or balanced data: photos of people of many ages and skin tones? (a) one-sided data (b) balanced data
15. 15.🔍 Which is the odd one out? (a) a map predicting traffic (b) an image generator (c) an AI chatbot (d) a digital watch
16. 16.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
17. 17.🤖 AI or a normal program: which one “makes a best guess”? (a) AI (b) a normal program
18. 18.True or false: “learns from examples” describes how AI works. (a) False (b) True
19. 19.🛠️ Which does this job need: recognising a friend’s face in photos? (a) a simple rule is enough (b) needs AI (learning)
20. 20.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to make it slower (d) to delete its data
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
22. 22.Which of these is training data? (a) tomorrow’s rain guess (b) naming a new leaf (c) flagging a new email (d) recorded spoken words
23. 23.🧮 Which of these is NOT AI? (a) a basic calculator (b) a spam filter (c) voice typing (d) face unlock
24. 24.✅ Is this a real check of an AI answer: it has a neat layout? (a) not a real check (b) a real check
25. 25.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
26. 26.🎨 This prompt asks a generative AI for: a cheerful tune for Sports Day. What kind of output is that? (a) text (b) music or sound (c) an image
27. 27.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
29. 29.Which of these describes how AI works? (a) never learns from data (b) does exactly as coded (c) uses rules people wrote (d) gives a likely answer
30. 30.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
31. 31.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
32. 32.🧐 Fact or myth: “long answers are true”? (a) a myth (b) a fact
33. 33.🛠️ Which does this job need: telling a cat photo from a dog photo? (a) needs AI (learning) (b) a simple rule is enough
34. 34.Which of these describes how a normal program works? (a) handles unseen examples (b) gives a likely answer (c) makes a best guess (d) uses rules people wrote
35. 35.✅ Is this a real check of an AI answer: try the sum on paper? (a) a real check (b) not a real check
36. 36.True or false: “old emails marked spam” is training data. (a) True (b) False
37. 37.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
38. 38.✨ Generative or not: drafting a letter? (a) makes something new (b) sorts or predicts
39. 39.True or false: “makes a best guess” describes how AI works. (a) True (b) False
40. 40.🛠️ Which does this job need: suggesting the next word as you type? (a) a simple rule is enough (b) needs AI (learning)

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