Implementation
Clusters in the Classroom
Given a set of items — countries, images, books, movies, or songs — how can we group them?
In this simple kinesthetic activity, we arrange students based on their imagined grades in math and PE, gradually forming larger and larger groups to reveal clusters of similar students. This introduces a popular hierarchical clustering algorithm, which we then apply in the following activities with real data to make the learning more meaningful and goal-oriented.
Relevance to everyday life
When working with data, we often only know the characteristics of items and want to group similar ones together. This happens in everyday life more often than we realize—for example, a store might look at customers’ shopping habits and group similar shoppers to offer more personalized promotions. There are many ways to do this; in this activity, we explore one of the simpler clustering methods.
Connection with the curriculum
The activity can be incorporated into various subjects, as clustering is a fundamental task in data analysis and appears in many contexts. It also serves as a nice introduction to other activities involving clustering real-world data.