Measuring Decision-Making Competence in Immersive Cybersecurity Training: A Telemetry-Based Virtual Reality Incident Triage Study

Abstract

In many Operational Technology (OT) and Industrial Control Systems (ICS) environments, the people running these systems are dealing with cyber issues far more often than they used to, and the impact when something goes wrong is noticeably greater. Even so, much of the training they receive still looks the same as it did years ago—slides, briefings, or walk-throughs that don’t resemble the pressure or uncertainty they face when a real incident unfolds. This study looks at whether a hands-on, immersive simulation—built in virtual reality and able to adjust to a participant’s actions while capturing performance data—can help OT cybersecurity personnel think more clearly under pressure and improve the way they make decisions during fast-moving situations. Grounded in andragogy, experiential learning, transformative learning, and cognitive load theory, the research employs a mixed-methods explanatory sequential design. The quantitative phase examines whether AI-driven adaptivity predicts measurable gains in decision-making competence, operationalized through behavioral telemetry and structured performance assessments, while controlling for professional experience. The qualitative phase explores how participants made sense of the scenario—what felt realistic, what generated pressure, and how the system’s behavior shaped their decisions. Throughout the process, data such as reaction times, eye-movement patterns, and task results will be used both to adjust the scenario as it unfolds and to give participants material to reflect on afterward. The study is expected to offer practical guidance for building more responsive immersive training tools and to shed light on how people think and act when the demands of a cybersecurity event are compressed into a virtual environment. The broader goal is to support stronger preparation for the workforce responsible for safeguarding critical infrastructure.