AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 811 · 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.True or false: “one set rule per case” describes how a normal program works. (a) True (b) False
2. 2.🔍 Which is the odd one out? (a) labels added at random (b) many varied examples (c) very few examples (d) blurry, unclear photos
3. 3.🔍 Which is the odd one out? (a) AI has real feelings (b) AI copies data patterns (c) AI can mix up numbers (d) AI answers need checking
4. 4.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
5. 5.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
6. 6.🔍 Which is the odd one out? (a) test on one group only (b) copy old unfair choices (c) ignore complaints (d) add varied examples
7. 7.✨ Is everything a generative AI makes true? (a) no, it can be wrong (b) yes, always (c) only on Mondays
8. 8.✅ Is this a real check of an AI answer: find a trusted source? (a) not a real check (b) a real check
9. 9.🏷️ 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
10. 10.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
11. 11.🔍 Which is the odd one out? (a) creating a cartoon (b) spotting spam (c) drafting a letter (d) drawing a new picture
12. 12.Which of these helps reduce bias? (a) copy old unfair choices (b) ask different people (c) use one group only (d) test on one group only
13. 13.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the price (d) the right answer tag
14. 14.True or false: “tomorrow’s rain guess” is the model. (a) False (b) True
15. 15.Which of these is training data? (a) the trained program (b) past weather records (c) what training builds (d) flagging a new email
16. 16.Which of these is a myth about AI? (a) AI can mix up numbers (b) AI can make up facts (c) AI learns from data (d) confident means correct
17. 17.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) predicting (b) recognising (c) generating (d) recommending
18. 18.🔍 Which is the odd one out? (a) reading number plates (b) drafting a letter (c) predicting rain (d) spotting a sick leaf
19. 19.True or false: a voice app trained only on adult voices is balanced data (fairer for everyone). (a) True (b) False
20. 20.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
21. 21.True or false: a music app suggesting a song you may like is AI predicting something. (a) True (b) False
22. 22.True or false: “AI is never wrong” is a fact about AI. (a) True (b) False
23. 23.🏠 AI or not AI: face unlock on a phone? (a) not AI (b) uses AI
24. 24.📅 An AI gives a date for a history event. How can you check? (a) ask it to repeat (b) pick a lucky number (c) guess (d) look in your textbook
25. 25.🤖 What does AI stand for? (a) app installer (b) actual information (c) artificial intelligence (d) automatic internet
26. 26.📦 What happens during training? (a) it learns patterns (b) it charges up (c) it prints labels (d) it takes photos
27. 27.🤖 Who builds and trains AI systems? (a) people (b) the Moon (c) nobody at all (d) the weather
28. 28.🛠️ Which does this job need: turning spoken words into typed text? (a) a simple rule is enough (b) needs AI (learning)
29. 29.🧐 Fact or myth: “AI can be wrong”? (a) a myth (b) a fact
30. 30.Which of these is bad for training a model? (a) photos in many lights (b) many varied examples (c) very few examples (d) examples of every type
31. 31.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
32. 32.🛠️ Which does this job need: reading messy handwriting? (a) needs AI (learning) (b) a simple rule is enough
33. 33.Which of these describes how a normal program works? (a) learns from examples (b) improves with more data (c) makes a best guess (d) uses rules people wrote
34. 34.🔍 Which is the odd one out? (a) a microwave timer (b) photos grouped by face (c) a stopwatch (d) a fan regulator
35. 35.🏠 AI or not AI: an AI chatbot? (a) not AI (b) uses AI
36. 36.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
37. 37.⏩ In machine learning, which comes first: naming a new fruit photo or old emails marked spam? (a) naming a new fruit photo (b) old emails marked spam
38. 38.Which of these helps reduce bias? (a) skip testing (b) test on one group only (c) add varied examples (d) add more of the same
39. 39.🔍 Which is the odd one out? (a) test on many groups (b) add varied examples (c) ignore complaints (d) balance the data
40. 40.True or false: suggesting the next word as you type needs AI that learns from examples. (a) True (b) False

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students