Abstract for: Improving Decision Making and Learning in Dynamic Tasks Through Structured Debriefing-based Interactive Learning Environments
How to improve people’s decision making in dynamic tasks? The thesis of this article is that decision making and learning in dynamic tasks can be improved by helping individuals develop more accurate mental models of dynamic tasks through training with system dynamics–based interactive learning environments (ILEs) that include systematic debriefing. A laboratory experiment is reported in which participants managed a dynamic task by playing the roles of fishing fleet managers. The two experimental groups used ILEs with outcome-oriented debriefing, and process-oriented debriefing. The control group used the same ILE but without debriefing. A comprehensive model consisting of five evaluation criteria was developed and used. The evaluation criteria were task performance, decision time, decisions strategy, structural knowledge, and heuristics knowledge. It was found that process-oriented debriefing improved subjects’ task performance, helped users learn more about the decision domain and develop heuristics. Contrary to our hypothesis, outcome–oriented debriefing helped users to become more efficient in decision making and apply more arbitrary-consistent type of decision strategies.