Abstract
In this chapter we argue that psychological measurement in the field of motivation and emotion is marked by a considerable degree of ambiguity, partly because these phenomena are poorly defined, but mainly because they are dynamic – motivation and emotion are about changes in behavior – while measurement designs and techniques are predominantly addressing individual differences, which are typically assumed to be stable. Building on recent work, which has distinguished between differential and temporal approaches to measurement and prediction (see Roe, 2014), we discuss the merits and limitations of prevailing differential methods. Next, we consider how researchers have tried to overcome the challenge of dynamic measurement with the help of state-trait models, and note that there are conceptual and logical problems, limiting the use of these models. To overcome these problems we propose a new measurement model, which focuses on individuals’ dynamic trajectories, defined with reference to a time frame of length L, starting at moment M, and comprising N observations. We show how this model can be used to describe subjects’ motivational states and to redefine traits in a dynamic way. The logic and utility of this approach is illustrated for work engagement – a well-investigated phenomenon in the current literature on work motivation.