We discuss our current efforts at developing automatic scenario generation software. We begin by explaining the rationale, and then review successful previous efforts. We discuss the lessons-learned from the past work, and the conceptual pieces that are required to generate operationally-valid scenarios that support effective training. We then present the conceptual design of our scenario generation approach, which uses novel procedural modeling approaches to ensure operational and training requirements are adequately met.Scenario-based training (SBT) is a highly-effective strategy for preparing individuals and teams for complex task domains. For maximum efficacy, SBT systems must include robust libraries of varied scenarios; however, the creation of validated, effective scenarios is time-consuming and must be carried out by highly-trained domain specialists, qualified instructors, and technology experts. The process is challenging and time-consuming, and therefore expensive. Thus, in practice, scenario libraries often fail to cover the optimal range of possible mission contexts. One way to facilitate the creation of more robust scenario libraries may be to automate the process of scenario generation. Automated scenario generation must be supported by appropriate algorithmic modeling approaches, as well as research-based heuristics to ensure that scenario outputs are domain-valid and pedagogically effective. In this paper, we explore both of these issues. From the perspective of computer science, we review procedural modeling techniques that can support automated scenario generation. From the perspective of training science, we discuss guidelines and research approaches for developing objective guidelines to ensure scenario effectiveness.