AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 111 · 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.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) data, model, prediction (d) model, prediction, data
2. 2.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
3. 3.True or false: “what training builds” is a prediction. (a) True (b) False
4. 4.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) blurry, unclear photos (d) checking labels twice
5. 5.✨ Generative or not: drawing a new picture? (a) sorts or predicts (b) makes something new
6. 6.Which of these helps reduce bias? (a) use one group only (b) test on many groups (c) add more of the same (d) test on one group only
7. 7.True or false: a phone unlocking when it sees your face is AI recognising something. (a) False (b) True
8. 8.🤖 Who builds and trains AI systems? (a) people (b) the Moon (c) nobody at all (d) the weather
9. 9.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
10. 10.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) False (b) True
11. 11.Which of these is bad for training a model? (a) wrong labels (b) many varied examples (c) new data for testing (d) correct labels
12. 12.Which of these describes how a normal program works? (a) makes a best guess (b) uses rules people wrote (c) learns from examples (d) spots patterns in data
13. 13.🔍 Which is the odd one out? (a) reading number plates (b) creating a cartoon (c) turning speech to text (d) unlocking with a face
14. 14.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
15. 15.Which of these is a prediction? (a) 500 labelled leaf photos (b) what training builds (c) recorded spoken words (d) naming a new fruit photo
16. 16.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
17. 17.True or false: “a cheerful tune for Sports Day” asks for text. (a) True (b) False
18. 18.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
19. 19.⏩ In machine learning, which comes first: naming a new fruit photo or the learned patterns? (a) naming a new fruit photo (b) the learned patterns
20. 20.🔍 Which is the odd one out? (a) test on one group only (b) test on many groups (c) skip testing (d) copy old unfair choices
21. 21.Which of these is the model? (a) flagging a new email (b) the trained program (c) recorded spoken words (d) 500 labelled leaf photos
22. 22.✨ Generative or not: spotting a sick leaf? (a) sorts or predicts (b) makes something new
23. 23.Which of these describes how AI works? (a) one set rule per case (b) follows fixed rules (c) makes a best guess (d) uses rules people wrote
24. 24.🔍 Which is the odd one out? (a) checking labels twice (b) copies of one photo (c) many varied examples (d) examples of every type
25. 25.🎨 This prompt asks a generative AI for: a cheerful tune for Sports Day. What kind of output is that? (a) text (b) an image (c) music or sound
26. 26.Which of these describes how a normal program works? (a) gives a likely answer (b) learns from examples (c) never learns from data (d) improves with more data
27. 27.✨ Is everything a generative AI makes true? (a) only on Mondays (b) yes, always (c) no, it can be wrong
28. 28.True or false: “a cartoon of a dancing elephant” asks for an image. (a) True (b) False
29. 29.Which of these uses AI? (a) a microwave timer (b) a kitchen weighing scale (c) an app translating signs (d) a calculator
30. 30.🧐 Fact or myth: “AI answers need checking”? (a) a fact (b) a myth
31. 31.Which of these is not AI? (a) video suggestions (b) an AI chatbot (c) a light switch (d) a map predicting traffic
32. 32.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a prediction (c) a label error (d) training data
33. 33.🤖 Does an AI system think and feel like a person? (a) yes, it gets sad (b) only on weekends (c) yes, just like us (d) no, it finds patterns
34. 34.True or false: “flagging a new email” is a prediction. (a) True (b) False
35. 35.🛠️ Which does this job need: sorting names in A to Z order? (a) needs AI (learning) (b) a simple rule is enough
36. 36.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
37. 37.Which of these describes how a normal program works? (a) handles unseen examples (b) improves with more data (c) one set rule per case (d) learns from examples
38. 38.True or false: “what training builds” is training data. (a) True (b) False
39. 39.Which of these helps reduce bias? (a) use one group only (b) check who is missing (c) copy old unfair choices (d) ignore complaints
40. 40.🔍 Which is the odd one out? (a) inventing a recipe (b) writing quiz questions (c) spotting spam (d) making up a story

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