Novice-Expert Differences in the Cognitive Representation of System Features: Mental Models and Verbalizable Knowledge

Abstract

The relationship between users' mental models and their verbalizable knowledge of a system were investigated in a field study. Trained and untrained users of a new phone system rated the similarity of use of nine phone features. Their ratings of the features were used in a multidimensional scaling technique and hierarchical cluster analysis to obtain their mental models of the system. Individuals' ratings of features on unidimensional scales about the use of the features and scores obtained on a knowledge test were reflected in their mental models. Mental models of the two novice groups' were very similar except for the perception of one feature; it was more accurately depicted in the mental model of users who attended than those who did not attend a training program. Trainers' and system designers' mental models of the phone system were evaluated to determine an “appropriate” expert mental model. A comparison of the “expert” mental model to the novices' mental models suggested that several features were inaccurately perceived by the novices. Using the discrepancies between the expert and novices' mental models to design training programs for systems is discussed. A novel way to design or redesign systems based on novices' mental models of systems is proposed.