Developing training scenarios that induce a trainee to utilize specific skills is one of the facets of simulation-based training that requires significant effort. Simulation-based training systems have become more complex in recent years. Because of this added complexity, the amount of effort required to create and maintain training scenarios has increased. This paper describes an investigation into automating the scenario generation process. The Automated Scenario Generation System (ASGS) generates the environment for the expected action flow in chronological order from several events and tasks, with estimated time for the entire training mission. When the user defines the training objectives and conditions, the ASGS automatically generates a scenario that includes not only the initial situation but also the sequential environmental conditions that will present the trainee with subsequent situations relevant to the training objectives throughout the entire simulation exercise. The latter is the main contribution of the research, as the flow of the training exercise can take many directions after start, based on the decisions made by the trainees. The system considers the current situation, and strives to present the trainees with subsequent situations that are consistent with the training objectives, yet in a manner that is natural. It takes advantage of contextualization to accomplish this. This scenario includes a degree of randomization to ensure no two equivalent scenarios are identical. This makes it possible to train different groups of trainees sequentially, who may have the same level or training objectives, without using a single scenario repeatedly. The SVSâ„¢ Desktop system is used as the development infrastructure for the ASGS prototype training system. The paper describes and discusses the ASGS prototype, the tests to which the prototype was subjected, the results obtained and conclusions reached.