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.🛠️ Which does this job need: finding 10% of a price? (a) needs AI (learning) (b) a simple rule is enough
- 2.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
- 3.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
- 4.True or false: “wrong labels” is good for training a model. (a) True (b) False
- 5.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) balanced data (b) one-sided data
- 6.✍️ How does an AI chatbot write its replies? (a) uses magic (b) predicts likely words (c) asks a person (d) copies one website
- 7.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) test on one group only (d) balance the data
- 8.Which of these describes how AI works? (a) follows fixed rules (b) uses rules people wrote (c) does exactly as coded (d) handles unseen examples
- 9.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
- 10.True or false: “AI learns from data” is a fact about AI. (a) False (b) True
- 11.Which of these is AI that sorts, spots or predicts (not generative)? (a) writing a new poem (b) making up a story (c) spotting spam (d) writing quiz questions
- 12.📅 An AI gives a date for a history event. How can you check? (a) ask it to repeat (b) look in your textbook (c) pick a lucky number (d) guess
- 13.🛠️ Which does this job need: suggesting the next word as you type? (a) needs AI (learning) (b) a simple rule is enough
- 14.🎨 This prompt asks a generative AI for: a drum beat for a dance. What kind of output is that? (a) music or sound (b) text (c) an image
- 15.⏩ In machine learning, which comes first: 500 labelled leaf photos or typing a new spoken word? (a) 500 labelled leaf photos (b) typing a new spoken word
- 16.🗣️ A voice app understands adults but not children. What is the likely reason? (a) it was a rainy day (b) children speak too fast (c) few child voices in data (d) the phone was new
- 17.True or false: “fix wrong labels” helps reduce bias. (a) True (b) False
- 18.Which of these is a fact about AI? (a) AI is never wrong (b) long answers are true (c) AI knows everything (d) AI learns from data
- 19.🔍 Which is the odd one out? (a) spotting spam (b) drawing a new picture (c) sorting photos by face (d) spotting a sick leaf
- 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
- 21.Which of these describes how AI works? (a) learns from examples (b) same steps every time (c) never learns from data (d) does exactly as coded
- 22.True or false: a keyboard guessing your next word is AI generating something new. (a) True (b) False
- 23.📱 What is the AI doing here: a camera app naming the flower you point at? (a) recommending (b) recognising (c) predicting (d) generating
- 24.🧐 Fact or myth: “AI learns from data”? (a) a myth (b) a fact
- 25.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) prediction, data, model (d) data, prediction, model
- 26.Which of these is not AI? (a) photos grouped by face (b) an image generator (c) face unlock on a phone (d) a printed timetable
- 27.🛠️ Does this reduce bias or add to it: test on many groups? (a) reduces bias (b) adds to bias
- 28.Which of these describes how AI works? (a) one set rule per case (b) follows fixed rules (c) gives a likely answer (d) same steps every time
- 29.True or false: a fruit sorter shown only ripe mangoes is balanced data (fairer for everyone). (a) True (b) False
- 30.Which of these uses AI? (a) a calculator (b) a digital watch (c) a microwave timer (d) an image generator
- 31.🏠 AI or not AI: a digital watch? (a) not AI (b) uses AI
- 32.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
- 33.🎨 This prompt asks a generative AI for: a poster of a rainforest. What kind of output is that? (a) text (b) music or sound (c) an image
- 34.Which of these is not AI? (a) an app translating signs (b) an AI chatbot (c) a voice assistant (d) a fan regulator
- 35.True or false: “wrong labels” is bad for training a model. (a) False (b) True
- 36.Which of these is good for training a model? (a) only one kind of example (b) wrong labels (c) very few examples (d) photos in many lights
- 37.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
- 38.True or false: “photos in many lights” is good for training a model. (a) True (b) False
- 39.True or false: stories with doctors of every gender is one-sided data (likely to make a biased model). (a) True (b) False
- 40.True or false: “never learns from data” describes how a normal program works. (a) True (b) False
Answer key
- a simple rule is enough
- good for training
- training data
- False
- balanced data
- predicts likely words
- test on one group only
- handles unseen examples
- False
- True
- spotting spam
- look in your textbook
- needs AI (learning)
- music or sound
- 500 labelled leaf photos
- few child voices in data
- True
- AI learns from data
- drawing a new picture
- spam
- learns from examples
- False
- recognising
- a fact
- data, model, prediction
- a printed timetable
- reduces bias
- gives a likely answer
- False
- an image generator
- not AI
- bad for training
- an image
- a fan regulator
- True
- photos in many lights
- training data
- True
- False
- True
Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students