The Effect of Different Styles of Human-Machine Interaction on the Nature of Operator Mental Models

The well-known Sheridan and Verplank scale of human-machine interaction suggests that there will be considerable differences in the kind of mental model operators will acquire of systems which they control. This paper reports the use of observing responses and Markov modelling to try to identify such differences in mental models. The method detects differences in the way in which operators allocate attention to aspects of the system as a function of the Sheridan-Verplank level of interaction. Such differences are believed to reflect differences in the causal properties embodied in the mental models.