Elsevier

Computers in Human Behavior

Volume 52, November 2015, Pages 628-631
Computers in Human Behavior

What is the state of the art in self-, co- and socially shared regulation in CSCL?

https://doi.org/10.1016/j.chb.2015.05.007Get rights and content

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.

Introduction

This special issue includes five diverse contributions, each addressing from a different perspective the topic of how learners regulate learning in a group. The collection illustrates a variety of methods in contexts where software supports and constrains what information learners share and how they share it. Amidst an extensive background of research on the more general topic of computer supported collaborative learning (CSCL), these five shine light on matters that I recommend be researched more thoroughly. To set a stage for those recommendations about researching regulated learning and CSCL, I first encapsulate each contribution and select some features they exhibit.

Section snippets

Comments on reports in this special issue

Miller and Hadwin (2015) tackle with helpful clarity the central matter of defining forms of regulated activity. They begin with an expansive assertion: Activity in groups is regulated when there is “… intentional, goal directed metacognitive activity in which learners and groups take strategic control of their actions (behavior), thinking (cognitive), and beliefs (motivation, and emotions) in the context of dynamic social interactions” (p. 573). I foreground two features of their claim.

First,

Expanding frontiers in conceptualizations, methodologies and practice

The field is progressively sharpening a shared conceptualization of forms of regulation that adapt an individual’s and a group’s work toward goals. While there is not precision of the sort chemists have when they stipulate conditions of “standard temperature and pressure” for an experiment, the work published here illuminates not only that metacognition is a key ingredient in regulated learning but also that attention to standards used in metacognitive monitoring are key (see Winne, 2011).

Trace

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There are more references available in the full text version of this article.

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Author note: This work was supported by grants to Philip H. Winne from the Canada Research Chairs Program and the Social Sciences and Humanities Research Council of Canada SRG 410-2011-0727.

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