Classifying data in a multi-taxonomic hierarchy with multiple windows and filtering: An empirical investigation using the IS'97 curriculum model

The process of classifying information can be a complex task, especially when there are multiple taxonomies. Creating effective user interfaces for searching large, multi-taxonomic hierarchies for information classification purposes is a relevant problem facing human-computer interaction (HCI) researchers and practitioners. This thesis evaluated the effectiveness of overview and zoom capabilities in facilitating the task of classifying information in multi-taxonomic hierarchies. Usability tests of alternative interface designs were conducted within an experimental context. The experimental task involves classifying objectives for an information systems course into the multi-taxonomic hierarchies of the IS'97 curriculum model. Overview and zoom capability was operationalized by a multiwindow interface design, and the addition of dynamic query features was used to further increase the level of overview and zoom. Partial support was found for asserting increased levels of overview and zoom lead to increase subjective satisfaction, lower error rates, and less time required to complete the experimental task.