This paper describes the motivations, method, and architecture for Adaptive Scenario Management (ASM). Current scenario-based simulation training systems lack the capacity to dynamically adapt training content to rapidly changing learner needs. Further, current simulation-based training systems are incapable of dynamically generating and maintaining scenarios in an instructionally sound manner. Scenarios developed in current simulation systems are hand-crafted, static representations of training and mission contexts. We describe the results of a research and development initiative that addresses these problems through the design of an adaptive training capability for distributed mission operations (DMO). We designed a structured method for adaptive scenario management that includes the following important activities: (i) performing pre-training assessment, (ii) generating/authoring scenarios and drills, (iii) configuring drills and scenarios for execution of training, (iv) executing simulation-based training, and (v) performing post-training assessment. Key to the effectiveness of the method is the use of a Mission Essential Competencies (MEC)-based approach to performance assessment and scenario content design. An integrated performance assessment approach that ensures scenario reconfiguration and adaptation are driven by scientifically determined metrics and instrumentation methods is outlined in this paper. Finally, the paper (a) describes an ASM application architecture, (b) outlines a knowledge-based approach for automated scenario generation that underlies the ASM method and the ASM architecture, and (c) provides illustrative examples of the ASM knowledge-based approach that is being tested and validated at an Air Force Research Laboratory DMO training facility. The ASM has the potential for broader use with Air Force and other DoD and commercial training applications.