Bootstrapping learner’s self-regulated learning

Self-regulating learners can be characterized as learners who actively research what they do to learn and how well their goals are achieved by variations in their approaches to learning. Extensive research on how and how well learners understand and apply the scientific method demonstrates that they encounter significant challenges in designing and validly interpreting experiments. I juxtapose these two views to make a case that learners need significant support to carry out a progressive program of research to make self-regulated learning productive. One key to this endeavor is gathering data that can accurately and systematically reflect how learning unfolds. I describe a software system called nStudy that is designed to do this, and I speculate on how software systems like nStudy can play powerful roles in improving learning and simultaneously advancing learning science.