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Analyzing attacker behavior and generating realistic models to accurately capture the realities of cybersecurity threats is a very challenging task for researchers. Psychological personality and profiling studies provide a broad understanding of personality traits, but lack a level of interactive immersion that enables observers to collect concrete cybersecurity-relevant behavioral data. Participant's intricate actions and interactions with real computer systems are seldom captured in any cybersecurity studies. Our work focuses on capturing human actions and decisions to provide an empirical basis for these types of models. We provide a practical methodology that helps bridge the gap between theory and practice by facilitating construction, experimentation, and data collection for repeatable and scalable human experimentation with realistic cybersecurity scenarios. While our methodology is platform agnostic, we describe state of the art technologies that may be used to satisfy the objectives of each of the stages of the methodology.