AI summaryⓘ
The authors studied how special computer tools that watch where commanders look (their gaze) can help them make better decisions in a simulated military control room. They compared tools that used just visual cues with ones that also used other signals (multimodal) and found the multimodal tools worked better. By analyzing eye movement patterns, the authors found that good performance depends on balancing focused and flexible looking strategies. Certain eye movement measurements were linked to how well the commanders did, following patterns known from psychology about attention and stress. This means tracking gaze can give useful clues about how people pay attention when using these smart decision tools.
C5ISRadaptive decision supporteye-trackinggaze metricsrecurrence quantification analysismultimodal interfacesattention allocationYerkes-Dodson lawvisual scanning
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.