Predicting user error for ambient systems by integrating model-based UI development and cognitive modeling

With the move to ubiquitous computing, user interfaces (UI) are no longer bound to specific devices. While this problem can be tackled using the model-based UI development (MBUID) process, the usability of the device-specific interfaces is still an open question. We are presenting a combined system that integrates MBUID with a cognitive modeling framework in order to provide usability predictions at development time. Because of their potential impact, our focus within usability problems lies on user errors. These are captured in a cognitive model that capitalizes on meta-information provided by the MBUID system such as the abstract role of a UI element within a task sequence (e.g., input, output, command). The free parameters of the cognitive model were constrained using data from two previous studies. A validation experiment featuring a new application and UI yielded an unexpected error pattern that was nonetheless consistent with the model predictions.