Manipulatable models for investigating processing of dynamic diagrams

Abstract

Existing approaches for collecting process data on human diagram comprehension have limited effectiveness. Analogue models that allow participants to manipulate diagram components offer powerful ways to capture the non-verbal and dynamic aspects of processing that are not available with some other approaches. Examples drawn from a variety of different domains illustrate the utility of model manipulation for revealing otherwise inaccessible aspects of how people process animated diagrams of complex content. © 2010 Springer-Verlag.