ABSTRACT
This chapter reviews what the field already knows about self-regulated learning in connection with autonomous learning, and to summarize future directions for increasing knowledge and bettering practice regarding self-regulated learning in the workplace by encouraging efficient self-regulation. In recent years, organizations have given individuals much autonomy in their own training and development with expectation that individuals are continuously improving in their day-to-day jobs. As a result, self-regulation, which is the process by which individuals pursue desired outcomes through thoughts and actions, is of import to both researchers and practitioners interested in autonomous learning. The first question an autonomous learner likely faces is deciding what to learn. After determining what to learn, the next step is to decide how to learn. Self-regulation theories are particularly suited to understanding processes related to autonomous learning. The dynamic processes that make computational theorizing important when considering self-regulation and autonomous learning also make the empirical side of the problem complicated.
