VIEW: A Visualization-Based Mental Model Elicitation Workstation

Abstract

We describe a Visualization and Interactive Elicitation Workstation (VIEW) prototype, developed to support knowledge elicitation (KE) and mental model research and designed to meet five key objectives: 1) capturing both explicit and implicit knowledge; 2) providing perceptually-rich elicitation stimuli; 3) minimizing KE-imposed distortions; 4) supporting a variety of techniques to capture the range of Structures comprising the expert's mental model; and 5) capturing the expert's movement within and among these structures. These considerations led to a design which combines an inteructive KE module supporting direct, indirect, and observational KE techniques, with a visuulizution module providing a variety of graphical displays (e.g., maps and overlays, decision trees, bar graphs, etc.) and supporting a hyper linkbased navigation among them. VIEW supports observational KE by tracking the expert's use of the daerent displays during decision-making. VIEW supports direct and indirect KE by providing an interactive datacollection and analysis environment and using the graphical displays as the elicitation stimuli. The complete VIEW design supports repertory grid analysis, proximity scaling techniques, and a variety of direct techniques. Depending on the technique used, different characteristics of the display-stimuli are elicited (e.g., similarities or differences among displays, etc.). From these data the structure and content of the expert's mental models can be inferred. The VIEW workstation thus provides a mental model visualization and elicitation environment which can be used to investigate a variety of phenomena, including novicdexpert and individual differences, development and degradation of expertise over time, and the impact of different types of training. A Windows95-based VIEW prototype was developed for Army battlefield management, but the principles extend to any domain where effective decision-making depends on the integration of diverse data and knowledge sources to maintain a complex and flexible mental model in a dynamic environment.The human is the most important part of any system, yet we still have the least amount of objective, real-time information on the status of this critical element.We are currently developing a simple, non-invasive, rugged monitor for performance-capacity tracking, prediction, and management. The hardware for this system is based on a patented activitymonitoring apparatus with configurable filters. This monitor looks like a wristwatch and requires no electrical or optical connections with the individual. An algorithm resident in this "actigraph" will extract a sleep and wakefulness time series from motor activity, while another will process these data according to a sleep and performance model (SPM) that calculates and displays the individual's predicted cognitive effectiveness along with sleep-history data. Stand-alone SPM versions have also been developed and will be used as PC-based decision aids, alone and in conjunction with the SPM monitor.Data on Phase I actigraph h...

ABAIS: Affect and Belief Adaptive Interface System

“…VIEW is a knowledge elicitation workstation developed at Charles River Analytics (Hudlicka et al, 1999) which provides an integrated toolkit for interactive, visualization-based knowledge elicitation. VIEW supports both direct KE methods (e.g., protocol analysis, critical decision method, inferential analysis, etc.)…”

“…The domain characterization (a partial ontological analysis), yielded the cues, situations, and actions summarized in table 3.2.2.1-1 and figure 3.2.2.1-1. For a more extensive elicitation effort required for a Phase II, other methods would be used, including repertory grid analysis, which has been shown to be an efficient method for eliciting large numbers of individual knowledge constructs and schema components (Hudlicka, 1996;Hudlicka et al, 1999).…”