MATB for assessing different mental workload levels

Area of Science:

• Aviation Psychology
• Human Factors Engineering
• Cognitive Performance Measurement

Background:

• The Multi-Attribute Task Battery (MATB) is a widely used computerized flight simulator for assessing aviation-related tasks.
• MATB involves simultaneous execution of sub-tasks such as system monitoring, tracking, communications, and resource management.
• Its customizable design allows for manipulation of mental workload through parameters like test duration, sub-task number, event rates, and overlap.

Purpose of the Study:

• To assess the main characteristics of MATB design for evaluating responses to varying workload levels.
• To review existing literature on MATB configurations and their effects on performance and workload.
• To provide recommendations for standardizing MATB use to improve research reproducibility.

Main Methods:

• A systematic review of 19 articles analyzing the effects of low and high workload using MATB.
• Analysis of study configurations, including test duration, number of sub-tasks, event rates, and overlap.
• Examination of performance metrics, perceived workload scores (e.g., NASA-TLX), and neurophysiological responses.

Main Results:

• MATB shows potential in detecting performance degradation under increased workload.
• Higher event rates, increased multitasking, and greater task overlap are associated with higher perceived workload and decreased performance, particularly in tracking.
• No significant effect of time-on-task on performance or workload was observed.
• Reported test durations range from 12-60 minutes, with level durations of 4-15 minutes.

Conclusions:

• MATB is a valuable simulation tool for studying mental workload in pilots under various operational and physiological constraints.
• Conflicting results in current literature highlight the need for standardized MATB configurations, descriptions, and training protocols.
• Standardization will enhance the reproducibility and comparability of studies, crucial for advancing human-machine interaction research in aviation.