Adaptation to Context as Core Component of Self-Regulated Learning: The Example of Complexity and Epistemic Beliefs

Abstract

In this chapter we raise two important issues regarding the metacognitive self-regulation of learning with technologies: First, adaptation to the external context is a core component of self-regulated learning. Empirical research regarding task complexity and text complexity – two exemplary external conditions – shows that learners systematically adapt their whole self-regulated learning process within a hypermedia learning environment to these contextual conditions. Therefore, careful construction and evaluation of learning tasks and learning content is warranted. In this context communicating and teaching the demands of complex learning scenarios deserves special attention. Second, learner characteristics play an important role in self-regulated learning and adaptation. Empirical research regarding epistemic beliefs – one exemplary learner characteristic – shows that learners with absolutistic beliefs will plan and execute different learning processes than those with sophisticated beliefs; these differences are especially pronounced under conditions of high complexity. Given the general superiority of the learning and adaptation processes of more sophisticated learners such beliefs should be a learning goal of their own and should be explicitly addressed in learning scenarios.KeywordsTask ComplexityLearning ContentEpistemic BeliefText ComplexityMetacognitive AwarenessThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.