The purpose of this applied project was to research potential methods for conducting performance and evaluation observations on users of Positive Train Control (PTC) and recommend the most effective measures of performance (MOPs) and measures of efficiency (MOEs) of those users. I conducted a study to collect and analyze what data could be observed and examined most effectively to produce causal explanations of behaviors when utilizing the PTC system. This study was done through literature review, interviews of PTC users and trainers, and through direct observations as I rode on trains watching crews interact with the system. Additionally, I researched several studies on human computer interface (HCI) usability studies of various software applications. Based upon the results, I recommend that direct-participant observations be employed and apply both the system and individual MOPs and MOEs identified in the report to track user’s proficiency. The data collected from these observations can be centralized and used to identify behavioral trends, drive corrective actions, create future policies as well as training content. These observations will address the need to have structured observations which allow observers to focus undistracted on the specific behaviors that affect train operations. This database would also identify employees that may need additional or refresher training.