A cognitive collaborative model to improve performance in engineering teams-a study of team outcomes and mental model sharing

Working collaboratively in teams is an essential element in systems engineering: Interdisciplinary teams are formed to tackle large-scale, heterogeneous problems requiring skill and knowledge across a wide array of engineering and technical disciplines. While this is widely accepted as necessary, little attention is given to the problem of ensuring effective collaboration across the diverse team. Attention is given to the processes that will be followed, and tools are provided to aid communication; but the critical cognitive aspects that ensure that the team works effectively and efficiently towards a common objective are frequently absent. Instead, managers and team members assume that their disparate mental models have no impact on their collaborative efforts, or that any cognitive dissonance will evaporate naturally and organically. In reality, neither assumption is true, and if these issues are not directly addressed, a team will fall into cooperative rather than collaborative work, which is less effective and efficient. We introduce a framework, the Cognitive Collaborative Model, that explicitly promotes the cognitive collaborative processes necessary for effective engineering teams, and demonstrate its effectiveness in controlled system design and development experiments. Further, we investigate whether this improvement is due to convergence of the individual team member mental models into a shared, or team, mental model, often cited as the basis for high-performing teams. Finally, we propose a novel multistage evaluation process for mental model convergence using concept maps and Pathfinder analysis.