학술논문

Tools Designed to Support Self-Regulated Learning in Online Learning Environments: A Systematic Review
Document Type
Periodical
Source
IEEE Transactions on Learning Technologies IEEE Trans. Learning Technol. Learning Technologies, IEEE Transactions on. 15(4):508-522 Aug, 2022
Subject
Computing and Processing
General Topics for Engineers
Process control
Monitoring
Visualization
Bibliographies
Analytical models
Task analysis
Systematics
Learning analytics
massive open online courses (MOOCs)
online
self-regulated learning (SRL)
tools
Language
ISSN
1939-1382
2372-0050
Abstract
Self-regulated learning (SRL) is a crucial higher-order skill required by learners of the 21st century, who will need to become lifelong learners to adapt to the continually changing environments. Literature provides examples of tools for scaffolding SRL in online environments. In this article, we provide the state-of-the-art concerning tools that support SRL in terms of theoretical models underpinning development, supported SRL processes, tool functionalities, used data and visualizations. We reviewed 42 articles published between 2008 and 2020, including information from 25 tools designed to support SRL. Our findings indicate that: 1) many of the studies do not explicitly specify the SRL theoretical model used to guide the design process of the tool; 2) goal setting, monitoring, and self-evaluation are the most prevalent SRL processes supported through functionalities, such as content navigation, user input forms, collaboration features, and recommendations; 3) the relationship between tool functionalities and SRL processes are rarely described; and 4) few tools assess the impact on learners’ SRL process and learning performance. Finally, we highlight some lessons learned that might contribute to implementing future tools that support learners’ SRL processes.