Abstract
This research aimed to develop and validate a practical framework for predicting mental workload in both single- and multitask environments with particular consideration of individual factors. To describe mental workload more precisely and completely, a framework for mental workload measures, containing instantaneous workload, average workload, accumulated workload, peak workload, and overall workload was proposed. To model individual factors, 2 new variables (effective workload and ineffective workload) were introduced to conceptually model task- and individual-generated workloads. Under the conceptual model, the operational models for predicting human mental workload for human-computer interaction tasks were developed. The model used a multidimensional approach and allowed the quantification of different aspects of load. Two experimental studies were conducted to validate the proposed model. The results revealed that (a) the framework, which consisted of average workload, accumulated workload, and instantaneous workload could describe workload more precisely than a single overall workload; (b) the proposed mental workload model, which explained 42% of the variance associated with NASA-Task Load index subjective mental workload ratings and explained 78% of the variance associated with performance time, was supported and could be used to predict mental workload; (c) the relationships between the effective/ineffective workload and the 4 independent variables were partially validated. The results showed that both task-related factors and individual-related factors could significantly affect mental workload; (d) mental workload was significantly affected by time pressure. The workload in a self-paced multitask environment was 29% lower than the workload in a system-paced multitask environment in the experiment. The workload in a self-paced, multitask environment was 19% lower than the workload in a system-paced, single-task environment.
