🤖 AI Summary
This study addresses the degradation of operational effectiveness in high-risk C5ISR command environments caused by suboptimal attention allocation. Conducted within a high-fidelity military command simulation, it pioneers the application of recurrence quantification analysis (RQA) to model dynamic attention patterns, integrating eye-tracking data with multimodal adaptive decision support tools to investigate the relationship between gaze dynamics and task performance. Results demonstrate that multimodal guidance significantly outperforms purely visual guidance. Specifically, mean diagonal line length exhibits a negative correlation with performance, while entropy shows a positive correlation. Moreover, recurrence rate and determinism follow an inverted U-shaped relationship, aligning with the Yerkes–Dodson law. These findings uncover a nonlinear mechanism linking gaze patterns to task performance, offering theoretical and methodological foundations for intelligent command decision-aid systems.
📝 Abstract
Modern command, control, communications, computers, cyber, intelligence, surveillance, and reconnaissance (C5ISR) environments place substantial attentional demands on mission commanders. Failures in attention allocation in these high-risk settings can have severe operational consequences. This study investigates the efficacy of gaze-driven, attention-guided adaptive decision support tools, including visual-only and multimodal designs, in a high-fidelity simulated military command center. To characterize gaze and attentional dynamics during interaction with these tools, recurrence quantification analysis was applied to eye-tracking data. Stepwise regression using the Bayesian information criterion was then used to identify recurrence-based gaze metrics associated with performance. Results showed that the multimodal adaptive decision support tool was associated with significantly higher performance than the visual-only attention-guided tool. Average diagonal line length showed a negative linear association with performance, whereas entropy showed a positive linear association. Recurrence rate, determinism, and entropy also showed nonlinear quadratic relationships with performance. In particular, recurrence rate and determinism followed an inverted-U pattern consistent with the Yerkes-Dodson law. These findings suggest that effective performance in dynamic C5ISR contexts depends on a balance between structured and flexible visual scanning, and that recurrence-based gaze metrics can help characterize attentional dynamics during interaction with adaptive decision support systems.