Over the past year, several hundred Army officers have discussed tactical and military management scenarios using an electronic collaborative learning environment. The scenarios were either Think Like a Commander scenarios developed at Ft. Leavenworth or Tacit Knowledge of Military Leadership scenarios developed jointly by the Army Research Institute and Yale University. A standard threaded discussion platform was modified to allow participants to automatically find semantically similar notes and relevant reference material in an online library using Latent Semantic Analysis, a machine learning algorithm for text understanding.

Greater equality of participation has long been known to be an outcome of electronic discussion groups with anonymity enhancing this effect. These effects were replicated here as well in discussions involving officers of the same rank. However, we also found that electronic discussions produced higher quality initial and final solutions to complex military scenarios than comparable face-to-face discussions. The quality of the responses was graded by military experts and by an automated grading program developed by Knowledge Analysis Technologies. The automatic grading system exhibited reliability as high as the military experts.

Two forces appear to drive the superior performance and greater learning evidenced in the online environment: (1) peer pressure knowing that others will read and comment on one s solution produces more thoughtful and complete responses even under conditions of anonymity; (2) learning from peers reading, reacting and commenting on each other s notes produces a superior final solution over face-to-face discussion. Lower ranking officers (i.e., Lieutenants and Captains) demonstrated greater learning from the online discussion than did Lt. Colonels, whose initial responses were nearly optimal at the outset.

We discuss these results as well as planned enhancements to the online environment to create an even more effective e-learning environment.