TY - JOUR
T1 - Synthesizing Cognitive Load and Self-regulation Theory
T2 - a Theoretical Framework and Research Agenda
AU - EFG-MRE
AU - de Bruin, Anique B.H.
AU - Roelle, Julian
AU - Carpenter, Shana K.
AU - Baars, Martine
AU - Ackerman, Rakefet
AU - Biwer, Felicitas
AU - Endres, Tino
AU - Hoogerheide, Vincent
AU - Hui, Luotong
AU - van Gog, Tamara
AU - Janssen, Eva
AU - van Merriënboer, Jeroen
AU - Paas, Fred
AU - Podolskiy, Andrey
AU - Renkl, Alexander
AU - Richter, Juliane
AU - Saveleva, Daria
AU - Scheiter, Katharina
AU - Sepp, Stoo
AU - Sidi, Yael
AU - Stebner, Ferdinand
AU - Trypke, Melanie
AU - Waldeyer, Julia
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12/1
Y1 - 2020/12/1
N2 - An exponential increase in the availability of information over the last two decades has asked for novel theoretical frameworks to examine how students optimally learn under these new learning conditions, given the limitations of human processing ability. In this special issue and in the current editorial introduction, we argue that such a novel theoretical framework should integrate (aspects of) cognitive load theory and self-regulated learning theory. We describe the effort monitoring and regulation (EMR) framework, which outlines how monitoring and regulation of effort are neglected but essential aspects of self-regulated learning. Moreover, the EMR framework emphasizes the importance of optimizing cognitive load during self-regulated learning by reducing the unnecessary load on the primary task or distributing load optimally between the primary learning task and metacognitive aspects of the learning task. Three directions for future research that derive from the EMR framework and that are discussed in this editorial introduction are: (1) How do students monitor effort? (2) How do students regulate effort? and (3) How do we optimize cognitive load during self-regulated learning tasks (during and after the primary task)? Finally, the contributions to the current special issue are introduced.
AB - An exponential increase in the availability of information over the last two decades has asked for novel theoretical frameworks to examine how students optimally learn under these new learning conditions, given the limitations of human processing ability. In this special issue and in the current editorial introduction, we argue that such a novel theoretical framework should integrate (aspects of) cognitive load theory and self-regulated learning theory. We describe the effort monitoring and regulation (EMR) framework, which outlines how monitoring and regulation of effort are neglected but essential aspects of self-regulated learning. Moreover, the EMR framework emphasizes the importance of optimizing cognitive load during self-regulated learning by reducing the unnecessary load on the primary task or distributing load optimally between the primary learning task and metacognitive aspects of the learning task. Three directions for future research that derive from the EMR framework and that are discussed in this editorial introduction are: (1) How do students monitor effort? (2) How do students regulate effort? and (3) How do we optimize cognitive load during self-regulated learning tasks (during and after the primary task)? Finally, the contributions to the current special issue are introduced.
KW - Cognitive load
KW - Effort
KW - Effort regulation
KW - Judgments of learning
KW - Monitoring
KW - Self-regulated learning
UR - http://www.scopus.com/inward/record.url?scp=85095692692&partnerID=8YFLogxK
U2 - 10.1007/s10648-020-09576-4
DO - 10.1007/s10648-020-09576-4
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AN - SCOPUS:85095692692
SN - 1040-726X
VL - 32
SP - 903
EP - 915
JO - Educational Psychology Review
JF - Educational Psychology Review
IS - 4
ER -