| Abstract: | The concept of mental workload has long been recognized as an important factor in individual performance within complex systems. It is documented that either overload or underload may degrade performance, and further affect the efficiency of the whole system. Therefore, systems designers need some explicit models to predict the mental workload imposed on individuals by the system at an early design phase so that alternative system designs can be evaluated. In examining mental-workload literature, it is found that few predictive mental-workload models have considered factors specific to individuals. This research aims to develop a practical framework for predicting mental workload in both single- and multi-task environments considering such individual factors. In order to describe mental workload more precisely and more completely, a framework for mentalworkload definitions, which contains instantaneous workload, average workload, accumulated workload, peak workload and overall workload, is proposed. In order to model individual factors, two new variables, i.e. effective workload and ineffective workload, are introduced to model the taskgenerated workload and individual-generated workload. The extension of the model to multi-task environments is also discussed. The proposed conceptual models are domain-independent and could be used to guide the development of operational models for different specific tasks. |
