Development of shared mental models: Structuring distributed naturalistic decision making in a synchronous computer-mediated work environment

Decision making is an inherent part of everyday work and learning processes. Superior decision outcomes can be achieved by structuring decision processes, encouraging domain experts to work collaboratively, providing visualization of decisions as they develop, and providing decision makers with time and flexibility to better understand problems and to project outcomes. Evaluation of distributed synchronous virtual teamwork environments has eluded researchers. The theoretical foundation of this study was Adaptive Structuration Theory (AST) enhanced by a distributed cognition framework. Discourse analysis was used to explore ways to evaluate effectiveness of newly-formed time-constrained self-directed virtual teams using computer-mediated communication (CMC) to solve ill-defined problems. Measures of work process performance were percentages of meeting time devoted to Situation Assessment, Resource Coordination, Idea Generation, and Model Building. Ten measures of work outcome for each of six teams were taken to assess change in decision model quality over time. The data informing this study were obtained during an elective computer science course. The author's course design focused on human-computer interaction (HCI) aspects of use, design, and deployment of computer-supported collaborative work (CSCW) and computer-supported collaborative learning (CSCL) systems. Participants were randomly assigned to teams that remained intact throughout the semester. Teams assumed various roles during policy and software-design scenarios. Networked TeamEC™ decision-modeling software enabled team problem solving. NetMeeting provided connectivity, application sharing, and text chat for intra-team communication to simulate distributed virtual meetings. Discourse analysis revealed process performance patterns and development of shared mental models of problem solutions. The outcome variable (Model Score) improved over time for all teams, but degree of improvement varied greatly among teams. Qualitative analysis of group process variables indicated variance was due to how well teams understood scenario-role requirements and managed available resources. Time usage by process variable was analyzed to measure critical resource use to discover “best practice” guidelines for distributed synchronous teamwork. A Naturalistic Decision Making (NDM) approach extended collaborative experiential learning to complex applied knowledge domains in order to improve problem solving and critical thinking skills. Constructivist learner-centered course design facilitated a clear task focus enabling participants to learn new work practices applicable to classroom and workplace.