Automated metrics will allow user interfaces to be partially evaluated early in the development process. They allow potential problems to be identified and corrected prior to user testing, saving both time and money. As a result, improved interfaces can be developed without additional costs. Both task-independent and task-sensitive automated metrics appear promising. Task-independent metrics should prove most useful for predicting user preferences and somewhat useful for predicting user performance. Task-sensitive metrics should prove useful for predicting both user preferences and performance. Several metrics are introduced and research directions are discussed.
All Science Journal Classification (ASJC) codes
- Medicine (miscellaneous)