A Comparison of Alternatives for Automated Decision Support in a Multi-Task Environment

Abstract

Complex, multi-task work environments that require humans to “juggle” many simultaneous tasks are becoming more widespread. How can automated capabilities best support the operator in these environments? We grouped the cognitive workload associated with multi-task management into two broad areas: 1) creating, maintaining, and updating an awareness of the status of all of the active tasks, and 2) choosing actions from among these active tasks based on overall goals. We then developed automated decision support for each of these aspects of workload and assessed which type of support was more effective in improving performance. Our findings indicate that, in a simulated air traffic control environment, the effort associated with creating and maintaining situation awareness was overwhelmingly responsible for the operator's workload. The results suggest that effective decision support in this environment should focus on helping the operator maintain awareness of the changing status of the active tasks, not on setting priorities or choosing among alternative tasks.