Predicting User Performance and Errors: Automated Usability Evaluation Through Computational Introspection of Model-Based User Interfaces (T-Labs Series in Telecommunication Services)
In order to achieve this, cognitive processes that link UI properties to usability aspects like effectiveness (user error) and efficiency (task completion time) are established empirically, are explained through cognitive modeling, and are validated in the course of this treatise. In the case of user error, the book develops an extended model of sequential action control based on the Memory for Goals theory and it is confirmed in different behavioral domains and experimental paradigms.
This new model of user cognition and behavior is implemented using the MeMo workbench and integrated with the model-based application framework MASP in order to provide automated usability predictions from early software development stages on. Finally, the validity of the resulting integrated system is confirmed by empirical data from a new application, eliciting unexpected behavioral patterns.