Learning Analytics for Self-Regulated Learning

Abstract

The Winne-Hadwin (1998) model of self-regulated learning (SRL), elaborated by Winne’s (2011, in press) model of cognitive operations, provides a framework for conceptualizing key issues concerning kinds of data and analyses of data for generating learning analyt- ics about SRL. Trace data are recommended as observable indicators that support valid inferences about a learner’s metacognitive monitoring and metacognitive control that constitute SRL. Characteristics of instrumentation for gathering ambient trace data via software learners can use to carry out everyday studying are described. Critical issues are discussed regarding what to trace about SRL, attributes of instrumentation for gathering ambient trace data, computational issues arising when analyzing trace and complementary data, the scheduling and delivery of learning analytics, and kinds of information to convey in learning analytics that support productive SRL.