Toward theory-driven, quantitative performance measurement in ergonomics science: The abstraction hierarchy as a framework for data analysis

Measurement in ergonomics science has not kept pace with theorizing. As a result, it is rare to find measures of human performance that are simultaneously objective, quantitative, sensitive, and theoretically grounded. This article proposes a new set of measures, based on the abstraction hierarchy (AH) framework, that satisfies all of these criteria. Each level of the AH can be used to define a quantitative state space that can serve as a frame of reference for objective measurement. These state spaces are complementary because they provide different views of the same human-environment behaviour. Collectively, this set of measures can be used to determine if a participant is strongly or weakly coupled to functional or physical distal properties of the work domain. Data from a longitudinal study are used as a case study to test the value of these novel measures. The empirical results show that these AH-based measures provide unique insight into participants' behaviour that was not revealed by many, more tr...