Title
A framework for self-regulated digital learning (SRDL).
Abstract
This article develops a framework for self-regulated digital learning, which supports for self-regulated learning (SRL) in e-learning systems. The framework emphasizes 8 features: learning plan, records/e-portfolio and sharing, evaluation, human feedback, machine feedback, visualization of goals/procedures/concepts, scaffolding, and agents. Each feature facilitates or supports one or more SRL skills, including planning, monitoring and evaluating learning, applying appropriate cognitive strategies, and setting standards of products or performance. The implementation in domain-general and -specific systems as illustrated by web-based inquiry and problem-solving are discussed. Examples and learning effects are elicited from the literature to demonstrate various designs. Approaches for designing SRL systems, educational implications, and new directions for future research incorporating SRL into digital learning are presented.
Year
DOI
Venue
2018
10.1111/jcal.12264
JOURNAL OF COMPUTER ASSISTED LEARNING
Keywords
Field
DocType
e-learning,feedback,inquiry,metacognition
Digital learning,E learning,Independent study,Visualization,Computer science,Knowledge management,Metacognition,Multimedia,Instructional design,Electronic publishing
Journal
Volume
Issue
ISSN
34.0
5.0
0266-4909
Citations 
PageRank 
References 
2
0.41
23
Authors
6
Name
Order
Citations
PageRank
Miao-Hsuan Yen131.42
Sufen Chen2585.43
Chia-Yu Wang3151.76
H.-L. Chen420.41
Ying-shao Hsu55211.72
T.-C. Liu620.41