Cognitive performance modeling based on general systems performance theory

Abstract

General Systems Performance Theory (GSPT) was initially motivated by problems associated with quantifying different aspects of human performance. It has proved to be invaluable for measurement development and understanding quantitative relationships between human subsystem capacities and performance in complex tasks. It is now desired to bring focus to the application of GSPT to modeling of cognitive system performance. Previous studies involving two complex tasks (i.e., driving and performing laparoscopic surgery) and incorporating measures that are clearly related to cognitive performance (information processing speed and short-term memory capacity) were revisited. A GSPT-derived method of task analysis and performance prediction termed Nonlinear Causal Resource Analysis (NCRA) was employed to determine the demand on basic cognitive performance resources required to support different levels of complex task performance. This approach is presented as a means to determine a cognitive workload profile and the subsequent computation of a single number measure of cognitive workload (CW). Computation of CW may be a viable alternative to measuring it. Various possible "more basic" performance resources that contribute to cognitive system performance are discussed. It is concluded from this preliminary exploration that a GSPT-based approach can contribute to defining cognitive performance models that are useful for both individual subjects and specific groups (e.g., military pilots).