These findings have implications in the design of change-detection support tools for dynamic displays and work procedure in C2 and surveillance.

Using a microworld simulation of maritime decision making, we compared two decision support systems (DSS) in their impact upon recovery from interruption. The Temporal Overview Display (TOD) and Change History Table (CHT) -designed to support temporal awareness and change detection, respectively -have previously proven useful in improving situation awareness; however, evaluation of support tools for multitasking environments should not be limited to the specific aspects of the task that they were designed to augment. Using a combination of performance, self-report, and eye-tracking measures, we find that both DSS counter-intuitively have a negative effect on performance. Resumption lags are increased, elevated post-interruption decision-making times persist for longer, and defensive effectiveness is impaired relative to No-DSS. Eye-tracking measures indicate that in the baseline condition, participants tend to encode the visual display more broadly, where as those in the two DSS conditions may have experienced a degree of attentional tunnelling due to high workload. We suggest that for a support tool to be beneficial it should ease the burden on attentional resources so that these can be used for reconstructing a mental model of the post-interruption scene.

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Detecting task-relevant changes in a visual scene is necessary for successfully monitoring and managing dynamic command and control situations. Change blindness—the failure to notice visual changes—is an important source of human error. Change History EXplicit (CHEX) is a tool developed to aid change detection and maintain situation awareness; and in the current study we test the generality of its ability to facilitate the detection of changes when this subtask is embedded within a broader dynamic decision-making task. A multitasking air-warfare simulation required participants to perform radar-based subtasks, for which change detection was a necessary aspect of the higher-order goal of protecting one’s own ship. In this task, however, CHEX rendered the operator even more vulnerable to attentional failures in change detection and increased perceived workload. Such support was only effective when participants performed a change detection task without concurrent subtasks. Results are interpreted in terms of the NSEEV model of attention behavior (Steelman, McCarley, & Wickens, Hum. Factors 53:142–153, 2011; J. Exp. Psychol. Appl. 19:403–419, 2013), and suggest that decision aids for use in multitasking contexts must be designed to fit within the available workload capacity of the user so that they may truly augment cognition.

In dynamic environments such as air-traffic control, emergency response and security surveillance, there are severe constraints to information processing and decision-making. Human operators must constantly monitor, assess, and integrate incoming information in order to make optimal decisions in such complex environments. In order to maximize operators' performance, there is a need for effective technological support for dynamic decision-making. Eye tracking is one promising avenue that can provide online, nonobtrusive indices of cognitive functioning. Using a simulated maritime decision-making environment, we evaluated whether oculometry may be exploited to foretell the decision made by the operator beforehand. Our results showed that pupil dilation and fixation transitions can reveal the upcoming judgment of the human operator by about half a second before the decision. This finding can be useful to design adaptive support tools for dynamic decision-making by integrating the operator's cognitive state.