Information Technology Reference
In-Depth Information
Chapter 11
Self-regulated Learning with MetaTutor:
Advancing the Science of Learning with
MetaCognitive Tools
Roger Azevedo, Amy Johnson, Amber Chauncey, and Candice Burkett
Cognition and Technology Research Lab, Department of Psychology, Institute for Intelligent
Systems, University of Memphis, Memphis, TN, USA
Introduction
Learning about conceptually rich domains with advanced learning technologies
requires students to regulate their learning (Jacobson, 2008). Current research from
cognitive and learning sciences provides ample evidence that learners have difficulty
learning about these domains (Chi, 2005). This research indicates that the com-
plex nature of the learning content, internal and external conditions, and contextual
environment requirements are particularly difficult because they require students
to regulate their learning (Azevedo, 2008). Regulating one's learning involves
analyzing the learning context, setting and managing meaningful learning goals,
determining which learning strategies to use, assessing whether the strategies are
effective in meeting the learning goals, evaluating emerging understanding of the
topic, and determining whether there are aspects of the learning context which could
be used to facilitate learning. During self-regulated learning (SRL), students need to
deploy several metacognitive processes and make judgments necessary to determine
whether they understand what they are learning, and perhaps modify their plans,
goals, strategies, and effort in relation to dynamically changing contextual condi-
tions. In addition, students must also monitor, modify, and adapt to fluctuations
in their motivational and affective states, and determine how much social support
(if any) may be needed to perform the task. Also, depending on the learning context,
instructional goals, perceived task performance, and progress made toward achiev-
ing the learning goal(s), they may need to adaptively modify certain aspects of their
cognition, metacognition, motivation, and affect (Azevedo & Witherspoon, 2009;
Winne, 2005).
To appear in: In M. S. Khine & I.M. Saleh (Eds.),
New Science of Learning: Computers, Cognition,
and Collaboration in Education
.
