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Objective: The objective of the study was to examine pilots' automation monitoring strategies and performance on highly automated commercial flight decks. Background: A considerable body of research and operational experience has documented breakdowns in pilot-automation coordination on modern flight decks. These breakdowns are often considered symptoms of monitoring failures even though, to date, only limited and mostly anecdotal data exist concerning pilots' monitoring strategies and performance. Method: Twenty experienced B-747-400 airline pilots flew a 1-hr scenario involving challenging automation-related events on a full-mission simulator. Behavioral, mental model, and eye-tracking data were collected. Results: The findings from this study confirm that pilots monitor basic flight parameters to a much greater extent than visual indications of the automation configuration. More specifically, they frequently fail to verify manual mode selections or notice automatic mode changes. In other cases, they do not process mode annunciations in sufficient depth to understand their implications for aircraft behavior. Low system observability and gaps in pilots' understanding of complex automation modes were shown to contribute to these problems. Conclusion: Our findings describe and explain shortcomings in pilot's automation monitoring strategies and performance based on converging behavioral, eye-tracking, and mental model data. They confirm that monitoring failures are one major contributor to breakdowns in pilot-automation interaction. Application: The findings from this research can inform the design of improved training programs and automation interfaces that support more effective system monitoring.

A fundamental challenge in studying cognitive systems in context is how to move from the specific work setting studied to a more general understanding of distributed cognitive work and how to support it. We present a series of cognitive field studies that illustrate one response to this challenge. Our focus was on how nuclear power plant (NPP) operators monitor plant state during normal operating conditions. We studied operators at two NPPs with different control room interfaces. We identified strong consistencies with respect to factors that made monitoring difficult and the strategies that operators have developed to facilitate monitoring. We found that what makes monitoring difficult is not the need to identify subtle abnormal indications against a quiescent background, but rather the need to identify and pursue relevant findings against a noisy background. Operators devised proactive strategies to make important information more salient or reduce meaningless change, create new information, and off-load some cognitive processing onto the interface. These findings emphasize the active problem-solving nature of monitoring, and highlight the use of strategies for knowledge-driven monitoring and the proactive adaptation of the interface to support monitoring. Potential applications of this research include control room design for process control and alarm systems and user interfaces for complex systems.