研究目的
Investigating the benefit of using eye tracking in future air traffic control training for operational monitoring, specifically to train novices in appropriate attention allocation during automation failures.
研究成果
The study aims to provide insights into training eye movement behavior for operational monitoring in future ATCOs, potentially enhancing their ability to detect automation failures and take over control effectively. If successful, it could lead to improved training methods integrating eye tracking.
研究不足
The study is planned and not yet implemented; limitations may include the low-fidelity nature of the simulation, potential ceiling or floor effects in scenarios, and the need for further development of the MonT tool. Generalizability to real-world ATC environments may be constrained.
1：Experimental Design and Method Selection:
A general training design with treatment (training on attention allocation based on a normative model) and control (no training) groups. Baseline and post-training tasks are used.
2：Sample Selection and Data Sources:
Students and job applicants with no prior ATC experience from DFS (German Air Navigation Service Provider). A power analysis will determine sample size.
3：List of Experimental Equipment and Materials:
Eye Follower System by LC Technologies, Inc. (120 Hz), simulation tool MonT (Monitoring Test), software NYAN for data management.
4：Experimental Procedures and Operational Workflow:
Both groups perform the target task (MonT simulation) initially. Treatment group receives training on the model; control group does not. Both groups perform the task again. Eye movements are recorded using the eye tracker.
5：Data Analysis Methods:
Eye movement parameters (fixation count, gaze duration, time to first fixation) measured for relevant areas of interest (AOIs). Performance measures (reaction times, detection rates, false rates) and subjective questionnaires (complacency, self-efficacy, personality) are analyzed.
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