In this empirical study, the user performance of the Elastic Windows approach is compared to the independent overlapping windows in task environment setup, switching and task executions. The results indicate that multi-window operations provided by hierarchical window organization improve users performance as the complexity of the task environment increases.
The subject pool of the study included graduate computer science students. Although none of the subjects had any experience with the Elastic Windows approach initially, with a short training they were able to outperform the approach they were using frequently. However, these results do not suggest that novice computer users are expected to perform similarly since subjects had considerable general knowledge of computers.
The four task execution types selected in the experiment are basic types, yet I do not claim that they cover all the variety of task execution types users perform. So, generalization of the results beyond the tasks presented here would lead to a mistake. However, my observations are such that Elastic Windows is expected to yield faster performance for tasks dealing with many pieces of information due to its multi-window capability.
The experiment was carried on a high resolution screen with a large display. Since the expected uses are applications with large complex information, such a display configuration is feasible. Yet, these results can not be translated to small low resolution displays.
In conclusion, these results suggest that the design principles of Elastic Windows can be successfully applied in a number of applications where users need to handle multiple pieces of information in complex tasks.