Scholars have lamented that current methods of assessing student performance do not align with contemporary views of learning as situated within students, contexts, and time. Here, we introduce and describe one theoretical--psychometric paradigm--termed "dynamic measurement"--designed to provide a valid representation of the way students respond to school-based instruction by estimating the learning potential of those students given their observed learning trajectory. We examine the century-long history of dynamic measurement, from its nascent theoretical beginnings, through its limited initial implementations, to the current development of a specialized modeling framework that allows it to be applied to large-scale educational data. We illustrate how dynamic measurement models (DMMs) can realize the goals of modern theory and measurement using a large longitudinal dataset of mathematics assessment data (i.e., 11,368 students nested within 98 schools and measured at 6 time points). These historical review and methodological demonstrations show the value of dynamic measurement, including better modeling of complex and contextually dependent influences on student learning.