Cognitive load assessment study of interfaces for dynamic tasks

In human-computer collaborative systems, interface information presentation directly influences operator decision-making and task effectiveness. Aiming at the dynamic tasks under extreme weather conditions, the interface cognitive load assessment was studied. Four interface designs with varying information levels (Level 1 to Level 4) were developed, which were quantitatively analyzed using a dynamic task cognitive load assessment method. The theoretical analysis showed that Level 3 and Level 4 interfaces had significantly better Evaluated Information Load in Dynamic task (EIL^D) values than Level 1 and Level 2. To verify the analysis result, the human-in-the-loop experiments were then conducted on the four interfaces under two task intensities: Low Task Intensity (LTI) and High Task Intensity (HTI). A multi-modal assessment approach was used, with metrics including task performance, subjective ratings and physiological eye-tracking data. The experimental results corroborated these findings, showing that operators using the Level 3 and Level 4 interfaces reported lower subjective cognitive load and achieved superior task performance. Notably, eye-tracking data demonstrated that the Level 3 interface was particularly effective in reducing operators' visual search pressure and enhancing information acquisition efficiency. By integrating theoretical modeling with empirical data, this study concluded that the Level 3 interface offered the best human factors adaptability in dynamic tasks under extreme weather conditions, provided an optimal solution for mitigating cognitive load and improving performance in dynamic tasks, offering a valuable reference for advanced interface design.