The Empirical Study on Self-Regulation, Co-Regulation, and Socially Shared Regulation in Computer-Supported Collaborative Learning

Author(s):  
Lanqin Zheng ◽  
Junhui Yu
Author(s):  
Sanna Järvelä ◽  
Hanna Järvenoja ◽  
Jonna Malmberg

AbstractSelf-regulation is critical for successful learning, and socially shared regulation contributes to productive collaborative learning. The problem is that the psychological processes at the foundation of regulation are invisible and, thus, very challenging to understand, support, and influence. The aim of this paper is to review the progress in socially shared regulation research data collection methods for trying to understand the complex process of regulation in the social learning context, for example, collaborative learning and computer-supported collaborative learning. We highlight the importance of tracing the sequential and temporal characteristics of regulation in learning by focusing on data for individual- and group-level shared regulatory activities that use technological research tools and by gathering in-situ data about students’ challenges that provoke regulation of learning. We explain how we understand regulation in a social context, argue why methodological progress is needed, and review the progress made in researching regulation of learning.


2013 ◽  
Vol 12 (3) ◽  
pp. 267-286 ◽  
Author(s):  
Sanna Järvelä ◽  
Hanna Järvenoja ◽  
Jonna Malmberg ◽  
Allyson F. Hadwin

Socially shared regulation of learning refers to processes by which group members regulate their collective activity. Successful individuals regulate their motivational, cognitive, and metacognitive engagement. Our hypothesis is that successful groups also share in regulating group processes. Following our earlier conceptual and empirical work on the social aspect of motivating and regulating learning (Hadwin & Järvelä, 2011; Järvenoja & Järvelä, 2009; Järvelä, Volet, & Järvenoja, 2010), our research questions are as follows: (a) What challenges do individuals and groups report experiencing during collaborative group work? (b) How do students collectively regulate these challenges at the time, and in future collaborations? (c) How do collaborative learning outcomes compare between groups with varying degrees of emerging shared regulation? We present an empirical study in which 18 graduate students worked in collaborative teams of 3–4 over an 8-week period. The nStudy (Winne, Hadwin, & Beaudoin, 2010) software was used for collaborative planning and work, as well as face-to-face and online collaboration between team members. Data included individual and collaborative statements about collaborative challenges, collaborative statements about contextual and future regulation strategies, collaborative learning performance, and log file traces of students’ contributions to collaborative chat discussions and planning activities. Findings indicated that the students expressed multiple challenges resulting in 3 kinds of regulation over time profiles: strong, progressive, and weak shared regulation. We also conclude that successful collaboration not only requires self-regulation but also allows each team member to support fellow team members to successfully regulate their learning and the team to come together to collectively regulate learning.


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