AI for Kids Worksheet: Part 1 Test
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.
NameDateTime takenScore ___ / 40
- 1.🎨 This prompt asks a generative AI for: a thank-you note to the bus driver. What kind of output is that? (a) text (b) an image (c) music or sound
- 2.Which of these describes how AI works? (a) follows fixed rules (b) never learns from data (c) makes a best guess (d) does exactly as coded
- 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) few child voices in data (c) children speak too fast (d) the phone was new
- 4.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) copy it straight away (b) ask it to hurry (c) check it on paper (d) never do maths
- 5.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) clean screens (d) learn from data
- 6.📦 What happens during training? (a) it takes photos (b) it prints labels (c) it learns patterns (d) it charges up
- 7.True or false: “learns from examples” describes how AI works. (a) False (b) True
- 8.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to delete its data (d) to change its name
- 9.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) model, prediction, data (d) data, model, prediction
- 10.🤖 AI or a normal program: which one “gives a likely answer”? (a) a normal program (b) AI
- 11.True or false: “it has a neat layout” is a real way to check an AI answer. (a) False (b) True
- 12.Which of these is AI that sorts, spots or predicts (not generative)? (a) drawing a new picture (b) writing a new poem (c) drafting a letter (d) turning speech to text
- 13.True or false: “ignore complaints” adds to bias. (a) True (b) False
- 14.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
- 15.🛠️ Which does this job need: translating a sentence into Hindi? (a) a simple rule is enough (b) needs AI (learning)
- 16.True or false: a map app guessing how long a trip will take is AI predicting something. (a) False (b) True
- 17.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
- 18.🔍 Which is the odd one out? (a) a stopwatch (b) a calculator (c) an AI chatbot (d) a fan regulator
- 19.🔍 Which is the odd one out? (a) test on many groups (b) check who is missing (c) use one group only (d) fix wrong labels
- 20.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
- 21.📅 An AI gives a date for a history event. How can you check? (a) guess (b) look in your textbook (c) pick a lucky number (d) ask it to repeat
- 22.True or false: “confident means correct” is a myth about AI. (a) True (b) False
- 23.True or false: a keyboard guessing your next word is AI recognising something. (a) False (b) True
- 24.🔍 Which is the odd one out? (a) new data for testing (b) checking labels twice (c) only one kind of example (d) photos in many lights
- 25.Which of these is bad for training a model? (a) many varied examples (b) new data for testing (c) checking labels twice (d) blurry, unclear photos
- 26.🛠️ Does this reduce bias or add to it: test on one group only? (a) reduces bias (b) adds to bias
- 27.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
- 28.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
- 29.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
- 30.🔍 Which is the odd one out? (a) AI is never wrong (b) AI learns from data (c) AI can mix up numbers (d) AI can make up facts
- 31.Which of these uses AI? (a) a light switch (b) a printed timetable (c) a fan regulator (d) an AI chatbot
- 32.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a prediction (c) a password (d) a label error
- 33.🤖 AI or a normal program: which one “one set rule per case”? (a) AI (b) a normal program
- 34.True or false: neat and messy writing from many people is one-sided data (likely to make a biased model). (a) False (b) True
- 35.True or false: a book app suggesting a story like your last one is AI recognising something. (a) False (b) True
- 36.True or false: “write a poem about the monsoon” asks for text. (a) True (b) False
- 37.Which of these is training data? (a) old emails marked spam (b) the learned patterns (c) what training builds (d) typing a new spoken word
- 38.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) only one kind of example (d) checking labels twice
- 39.🔍 Which is the odd one out? (a) face unlock on a phone (b) an image generator (c) an AI chatbot (d) a doorbell
- 40.True or false: recognising a bird from its song only needs a simple fixed rule. (a) True (b) False
Answer key
- text
- makes a best guess
- few child voices in data
- check it on paper
- learn from data
- it learns patterns
- True
- to see if it works
- data, model, prediction
- AI
- False
- turning speech to text
- True
- the trained program
- needs AI (learning)
- True
- False
- an AI chatbot
- use one group only
- bad for training
- look in your textbook
- True
- False
- only one kind of example
- blurry, unclear photos
- adds to bias
- False
- 500 labelled leaf photos
- False
- AI is never wrong
- an AI chatbot
- a prediction
- a normal program
- False
- False
- True
- old emails marked spam
- checking labels twice
- a doorbell
- False
Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students