Command & Control in Virtual Environments: Laboratory Experimentation to Compare Virtual with Physical
Abstract
Research in command and control is advancing rapidly through a campaign of laboratory experimentation using the ELICIT (Experimental Laboratory for counterterrorism intelligence game Investigating Collaboration Information-sharing, and Trust) multiplayer online counterterrorism intelligence game. In most ELICIT experiments, participants play the game through a Web interface and interact with one another solely through textual information exchange. This mirrors in large part the network centric environment associated with most counterterrorism intelligence work in practice, and it reflects what appears to be a widespread assumption about how to organize such work: in a physically distributed, virtual manner. Such reflection is consistent with considerable research (e.g., in Educational Psychology) prescribing such distributed, virtual environments for work performance. Alternatively, substantial research (e.g., Media Richness Theory) suggests instead that a more personal, physical environment offers potential to improve performance. Hence we have a theoretical conflict with potential to affect how the important work of counterterrorism intelligence is organized. The research described in this article addresses this theoretical conflict through a series of experiments to assess the comparative performance of people working in physical, face-to-face versus textual, virtual environments. Exercising great care to match experiment conditions and control for factors other than task environment, results elucidate important comparative performance effects and suggest compelling follow-on experiments as well as practical implications.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2010
- Accession Number
- ADA524136
Entities
People
- Alicemary A. Adams
- Bryan J. Hudgens
- June G. Lee
- Mark E. Nissen
- Ramez Andraus Jr.
- Richard D. Bergin
Organizations
- Naval Postgraduate School