Sponsor: National Science Foundation
PI: Amlan Mukherjee
This research uses recent advances in simulations and data analysis techniques to investigate the cognitive and engineering aspects of decision making in complex dynamic construction management scenarios. Expertise plays a crucial role in managing crisis scenarios that call for critical decision making under constraints of time, resource, and rapidly unfolding events. An example of such a crisis scenario is managing complex heavy construction projects. In such scenarios, effective decision making requires knowledge of complex inter-relationships between several simultaneous events and preparing for the uncertainty and risks arising from feedbacks in time and space. Such knowledge is inductively constructed by assimilating and organizing experiential knowledge into patterns of information that are difficult to formalize or analytically perceive. The researchers propose to investigate the dynamics and variation of such cognitive knowledge organization patterns, or mental models, of decision making, specifically among construction managers.
The goal of this research effort will be to use an interdisciplinary approach to understand how expert and novice construction managers differ in their knowledge organization, information processing, risk assessment, and decision making in construction management crisis scenarios. Interactive, adaptive simulations of critical construction scenarios will be developed in collaboration with construction management firms, and expert and novice construction managers will be tested in them to capture human-subject interaction data that will be analyzed to develop mental models of expertise. In addition, an instructional interface will be integrated into the simulation using pedagogical agents, and it will be deployed in the construction management curriculum to test its effectiveness as a training environment for novice decision makers. This will also allow the researchers to investigate how novices construct knowledge in simulated training environments.