AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 746 · 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.🏠 AI or not AI: a doorbell? (a) not AI (b) uses AI
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.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) a sticker on a laptop (d) the price
4. 4.Which of these is generative AI (it makes something new)? (a) reading number plates (b) spotting spam (c) drafting a letter (d) suggesting a video
5. 5.🔍 Which is the odd one out? (a) composing a new tune (b) drawing a new picture (c) drafting a letter (d) unlocking with a face
6. 6.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
7. 7.True or false: reading messy handwriting needs AI that learns from examples. (a) False (b) True
8. 8.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
9. 9.🛠️ Which does this job need: reading messy handwriting? (a) a simple rule is enough (b) needs AI (learning)
10. 10.🛠️ Which does this job need: counting the words in an essay? (a) a simple rule is enough (b) needs AI (learning)
11. 11.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) training data (c) a password (d) a label error
12. 12.Which of these is bad for training a model? (a) correct labels (b) checking labels twice (c) photos in many lights (d) testing on training data
13. 13.✅ Is this a real check of an AI answer: try the sum on paper? (a) not a real check (b) a real check
14. 14.🧐 Fact or myth: “AI is never wrong”? (a) a myth (b) a fact
15. 15.True or false: suggesting the next word as you type only needs a simple fixed rule. (a) False (b) True
16. 16.Which of these is a fact about AI? (a) AI knows everything (b) AI always checks facts (c) confident means correct (d) AI answers need checking
17. 17.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) blurry, unclear photos (d) clear, sharp examples
18. 18.True or false: “fix wrong labels” adds to bias. (a) True (b) False
19. 19.✨ Generative or not: reading number plates? (a) makes something new (b) sorts or predicts
20. 20.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
21. 21.True or false: recognising a friend’s face in photos only needs a simple fixed rule. (a) True (b) False
22. 22.🗣️ A voice app understands adults but not children. What is the likely reason? (a) the phone was new (b) children speak too fast (c) it was a rainy day (d) few child voices in data
23. 23.Which of these is good for training a model? (a) examples of every type (b) blurry, unclear photos (c) only one kind of example (d) copies of one photo
24. 24.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, model, prediction (d) data, prediction, model
25. 25.🤖 AI or a normal program: which one “improves with more data”? (a) AI (b) a normal program
26. 26.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
27. 27.🔍 Which is the odd one out? (a) very few examples (b) checking labels twice (c) wrong labels (d) testing on training data
28. 28.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
29. 29.Which of these describes how AI works? (a) does exactly as coded (b) improves with more data (c) same steps every time (d) one set rule per case
30. 30.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
31. 31.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
32. 32.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
33. 33.Which of these adds to bias? (a) ask different people (b) check who is missing (c) add varied examples (d) add more of the same
34. 34.📱 What is the AI doing here: a map app guessing how long a trip will take? (a) generating (b) predicting (c) recommending (d) recognising
35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
36. 36.True or false: showing the time on a clock only needs a simple fixed rule. (a) False (b) True
37. 37.📅 An AI gives a date for a history event. How can you check? (a) pick a lucky number (b) look in your textbook (c) ask it to repeat (d) guess
38. 38.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
39. 39.🤖 AI or a normal program: which one “makes a best guess”? (a) AI (b) a normal program
40. 40.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model

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