👩‍🏫 How to Explain by Age Group

• Elementary (K–5)

  • “Data labeling is like putting name tags on things, like calling a picture of a dog “dog” so the computer knows what it is. It helps AI learn by giving it clues.”

• Middle School (6–8)

  • “When we label data, we’re telling the AI what it’s looking at, like marking an email as “spam” or tagging a photo with “tree.” It uses these labels to learn how to spot patterns.”

• High School (9–12)

  • "Data labeling is the process of annotating raw data with categories or descriptions so AI can learn from it. High-quality labels are critical for training accurate models in tasks like classification, sentiment analysis, or object recognition.”

🚀 Classroom Expeditions

Mini-journeys into AI thinking.

• Elementary (K–5)

  • Give students a set of pictures and have them group and label them. Then explain: “This is what we do for computers when we want them to learn.”

• Middle School (6–8)

  • Let students create their own mini-datasets by labeling sets of sample text or images. Then talk about how AI uses these to “practice.”

• High School (9–12)

  • Assign a mini project where students label a dataset (like class survey responses or image categories). Then analyze how quality and consistency affect AI accuracy.