AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 158 · 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.📅 An AI gives a date for a history event. How can you check? (a) look in your textbook (b) guess (c) pick a lucky number (d) ask it to repeat
2. 2.True or false: “gives a likely answer” describes how a normal program works. (a) True (b) False
3. 3.✨ Generative or not: spotting a sick leaf? (a) sorts or predicts (b) makes something new
4. 4.✨ Generative or not: composing a new tune? (a) sorts or predicts (b) makes something new
5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
6. 6.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
7. 7.🤖 AI or a normal program: which one “one set rule per case”? (a) a normal program (b) AI
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
9. 9.📱 What is the AI doing here: an image generator drawing a robot from a sentence? (a) generating (b) recommending (c) recognising (d) predicting
10. 10.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
11. 11.🤖 AI or a normal program: which one “spots patterns in data”? (a) a normal program (b) AI
12. 12.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
13. 13.✅ Is this a real check of an AI answer: see if the book exists? (a) a real check (b) not a real check
14. 14.Which of these is bad for training a model? (a) examples of every type (b) testing on training data (c) correct labels (d) photos in many lights
15. 15.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
16. 16.🤖 AI or a normal program: which one “uses rules people wrote”? (a) AI (b) a normal program
17. 17.Which of these describes how AI works? (a) never learns from data (b) improves with more data (c) follows fixed rules (d) uses rules people wrote
18. 18.✨ Generative or not: spotting spam? (a) makes something new (b) sorts or predicts
19. 19.Which of these is good for training a model? (a) very few examples (b) correct labels (c) blurry, unclear photos (d) only one kind of example
20. 20.🔍 Which is the odd one out? (a) face unlock on a phone (b) a printed timetable (c) an AI chatbot (d) an app translating signs
21. 21.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) only one kind of example (d) clear, sharp examples
22. 22.🤖 Who builds and trains AI systems? (a) the weather (b) people (c) nobody at all (d) the Moon
23. 23.True or false: “naming a new fruit photo” is training data. (a) True (b) False
24. 24.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) music or sound (b) text (c) an image
25. 25.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a list of rules only (d) a song about dogs
26. 26.🤔 An AI answer sounds very confident. Does that mean it is right? (a) yes, if it is long (b) yes, always (c) no, check it anyway
27. 27.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
28. 28.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
29. 29.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
30. 30.📱 What is the AI doing here: an AI chatbot writing a poem about rain? (a) recommending (b) predicting (c) recognising (d) generating
31. 31.Which of these is a myth about AI? (a) AI learns from data (b) AI can make up facts (c) AI copies data patterns (d) confident means correct
32. 32.⏩ 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
33. 33.🤖 What does AI stand for? (a) app installer (b) automatic internet (c) actual information (d) artificial intelligence
34. 34.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
35. 35.True or false: “a picture of a castle made of mangoes” asks for music or sound. (a) True (b) False
36. 36.🎨 An image generator makes a picture from… (a) the weather (b) your password (c) a phone number (d) a text description
37. 37.True or false: “recorded spoken words” is the model. (a) True (b) False
38. 38.Which of these is bad for training a model? (a) examples of every type (b) blurry, unclear photos (c) many varied examples (d) clear, sharp examples
39. 39.🛠️ Does this reduce bias or add to it: ask different people? (a) reduces bias (b) adds to bias
40. 40.✅ Is this a real check of an AI answer: it answered quickly? (a) a real check (b) not a real check

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