A Nonlinear Dynamic System Modeling of Stress Regulation and Emotional Behavior in Higher Education

Stress regulation and emotional behavior in higher education are commonly examined using descriptive statistical models that lack a mechanistic dynamical structure. However, academic stress exhibits nonlinear behaviors, including threshold effects, burnout, and adaptive responses, that are not adequately captured by linear models. This study adopts a nonlinear dynamical systems perspective to model stress regulation and emotional behavior in higher education. The primary aim of this study is to develop a physics-inspired nonlinear state-space framework that rigorously models stress-emotion coupling and adaptive regulation in higher education. The protocol establishes a nonlinear state-space model describing stress, emotional activation, and regulatory capacity. Users can implement the protocol to simulate system dynamics and evaluate stability under varying academic conditions. The framework incorporates nonlinear stability analyses and stochastic simulations to investigate resilience, instability, and burnout-related transitions. Simulation results demonstrate nonlinear stability, resilience effects, and regime transitions that are not captured by conventional linear models. The results indicate that stress regulation in higher education behaves as a nonlinear dynamical system. By integrating nonlinear dynamics, energy landscape modeling, and adaptive regulation theory, this work provides a unified predictive framework that explains resilience, instability, and recovery processes in academic environments. The framework provides a foundation for future studies of student wellbeing and burnout risk. The framework is relevant to researchers and practitioners interested in student well-being and stress regulation.