Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6838091 | Computers in Human Behavior | 2015 | 4 Pages |
Abstract
Articles in this special issue on regulation of learning in computer-supported collaborative learning apply tools across the spectrum of qualitative and quantitative methods to investigate self-, co- and socially shared regulation of learning. As well, a careful consideration of each of these constructs is provided. I briefly review these contributions to identify unique and forward-looking approaches to research in this vibrant area of research. A particular opportunity is recommended for future research regarding the use of process mining, sequence mining, social network analysis and an as-yet to be invented amalgam of these methods in constructing intelligent software agents that could guide participants in CSCL to assemble an optimum mix of self-, co- and socially shared regulation of learning.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Philip H. Winne,