Metacognition, as defined by Flavell (1976), is the ability to reason about and explicitly manage one’s own cognitive processes. Winne and Hadwin’s (1998) model of self-regulation relies heavily on metacognitive monitoring and control processes as key components of self regulated learning (SRL). SRL is a theory of active learning that describes how learners are able to set goals, create plans for achieving those goals, continually monitor their progress, and revise their plans to make better progress in achieving these goals (Zimmerman & Schunk, 2011).
Our research focus in this area is to look at relationships between metacognitive, motivational and affective aspects of SRL and their influence on student learning and performance in open-ended learning environments (OELE), with an intention of using this information to scaffold learners into being able to efficiently regulate their own learning.
We ascertain the metacognitive knowledge of learners by detecting and analyzing patterns in their use of cognitive behavioral strategies. An understanding of such strategies, and their specific implementations when applied to concrete tasks, is important for developing one’s ability to adapt existing strategies to new situations or even invent new strategies. Thus, an important goal in developing adaptive scaffolds for learners working in intelligent learning environments is to explicitly teach them strategies for regulating their learning as they solve complex, open-ended problems.
Key Research Objectives:
- To detect and analyze learner’s proficiency in cognitive skills, cognitive strategies, and metacognitive processes while they engage in complex decision-making
- To study the interactions between learners’ behavior (cognitive strategies, metacognitive processes), performance and affective states.