Measuring Self-Regulated Learning

Research on self-regulated learning (SRL) and measurement protocols used in this chapter are relatively new and inherently intertwined enterprises. Each helps to bootstrap the other. One adopts the view that a measurement protocol is an intervention in an environment, disturbing it in a fashion that causes data to be generated. Using that data and logic of causal inference, he/she infers properties and qualities of a target of measurement. Thus, measurement involves understandings about a target, its environment, and causal relationships that connect the two. Under this view, measurement is akin to model building and model testing, and thus, all measures of SRL are reflections of a model of SRL. SRL has dual qualities as an aptitude and an event. It is situated within a broad range of environmental plus mental factors and potentials, and manifests itself in recursively applied forms of metacognitive monitoring and metacognitive control that change information over time as learners engage with a task.