What is the statistical method used to analyze the results of a card sorting session?

The statistical method commonly used to analyze the results of a card sorting session is monothetic agglomerative cluster analysis. This technique is particularly useful for card sorting because it groups items (or cards) based on their similarities as determined by the participants' sorting choices.

In a card sorting session, users organize items into groups that make sense to them, often reflecting their mental model of the information. Monothetic agglomerative cluster analysis focuses on how items can be grouped in a way that captures those user-driven categorizations. The process involves starting with each item as its own cluster and then progressively merging clusters based on their similarity until a predetermined number of clusters or a certain level of similarity is achieved.

Using this methodology ensures that the final clusters reflect the participants' perspectives on how the information should be organized, aligning with user expectations and enhancing usability in the design of information architectures. This focus on user-driven grouping is what makes this method particularly effective for analyzing card sort data.