AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 906 · 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.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) training data (c) the model
2. 2.📦 What happens during training? (a) it learns patterns (b) it prints labels (c) it takes photos (d) it charges up
3. 3.True or false: showing the time on a clock needs AI that learns from examples. (a) True (b) False
4. 4.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
5. 5.✨ Generative or not: reading number plates? (a) sorts or predicts (b) makes something new
6. 6.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
7. 7.✅ Is this a real check of an AI answer: it uses big words? (a) a real check (b) not a real check
8. 8.🔍 Which is the odd one out? (a) face unlock on a phone (b) a spam filter (c) an image generator (d) a torch
9. 9.Which of these adds to bias? (a) check who is missing (b) ask different people (c) balance the data (d) ignore complaints
10. 10.Which of these is not AI? (a) a spam filter (b) an app translating signs (c) a kitchen weighing scale (d) video suggestions
11. 11.📱 What is the AI doing here: an AI chatbot writing a story about a lost kite? (a) predicting (b) recommending (c) recognising (d) generating
12. 12.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
13. 13.Which of these is a myth about AI? (a) AI learns from data (b) AI can make up facts (c) AI can be wrong (d) AI knows everything
14. 14.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
15. 15.📱 What is the AI doing here: a car camera reading a speed sign? (a) recommending (b) recognising (c) generating (d) predicting
16. 16.⚖️ One-sided or balanced data: stories where every doctor is a man? (a) balanced data (b) one-sided data
17. 17.True or false: “does exactly as coded” describes how a normal program works. (a) True (b) False
18. 18.🤔 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
19. 19.🔍 Which is the odd one out? (a) AI answers need checking (b) long answers are true (c) AI knows everything (d) AI has real feelings
20. 20.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
21. 21.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) one single photo (d) a list of rules only
22. 22.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) the price (d) a sticker on a laptop
23. 23.⚖️ One-sided or balanced data: photos of people from only one age group? (a) one-sided data (b) balanced data
24. 24.🔍 Which is the odd one out? (a) test on many groups (b) copy old unfair choices (c) ignore complaints (d) test on one group only
25. 25.🧮 Which of these is NOT AI? (a) face unlock (b) a spam filter (c) a basic calculator (d) voice typing
26. 26.📱 What is the AI doing here: a video app suggesting what to watch next? (a) predicting (b) recommending (c) generating (d) recognising
27. 27.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
28. 28.Which of these uses AI? (a) a doorbell (b) a calculator (c) a printed timetable (d) face unlock on a phone
29. 29.📚 An AI chatbot names a book that does not exist. This is called… (a) a hallucination (b) a backup (c) a summary (d) a password
30. 30.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
31. 31.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
32. 32.🧪 Why test a model on NEW examples? (a) to delete its data (b) to change its name (c) to see if it works (d) to make it slower
33. 33.Which of these adds to bias? (a) balance the data (b) test on one group only (c) add varied examples (d) test on many groups
34. 34.✨ Generative or not: sorting photos by face? (a) sorts or predicts (b) makes something new
35. 35.✨ What does generative AI do? (a) charges batteries (b) only stores files (c) only adds numbers (d) makes new content
36. 36.True or false: “spots patterns in data” describes how a normal program works. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) correct labels (d) only one kind of example
38. 38.Which of these describes how a normal program works? (a) one set rule per case (b) handles unseen examples (c) learns from examples (d) makes a best guess
39. 39.Which of these is not AI? (a) an app translating signs (b) video suggestions (c) a voice assistant (d) a fan regulator
40. 40.🤖 AI or a normal program: which one “uses rules people wrote”? (a) a normal program (b) AI

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