Shared Regulation in CSCL

Summary

Contributors: Tugce Aldemir (Penn State), Yu Xia (Penn State), Marcela Borge (Penn State)

Collaborative learning has been defined as a form of collective cognition where individuals come together to create shared meaning by collectively synthesizing ideas and negotiating what is known for creating new knowledge (Roschelle & Teasley 1995; Stahl, 2006). From this perspective, the construction of new knowledge is contextually bound within the language and actions of the group and therefore does not exist in the head of anyone individual member (Brown et al, 1989; Stahl et al., 2006).

Similar to the significant role self-regulation plays in an individual’s learning, metacognitive knowledge and regulation at the level of the group can help teams optimize their collaborative learning experiences (Borge & White, 2016; Zimmerman & Schunk, 2001). Socially shared regulation (SSR) is a complex regulatory process at the level of the group. SSR can be intertwined with other forms of regulation such as self- and co-regulation as groups work towards a shared goal (Järvelä & Hadwin, 2013). When groups engage in socially shared regulation, they extend their regulatory activity from the “I” to the “we” level to jointly regulate social learning processes and outcomes (Järvelä & Hadwin, 2013). They work together to complement and negotiate shared perceptions and goals for the task; they coordinate strategic enactment of the task and collectively monitor group progress and products; and they make changes when needed to optimize collaboration in and across tasks (Järvelä et al., 2020).

Given the importance of metacognition and socially shared regulation, the design and implementation of pedagogical interventions and guidance to help learners develop socio-metacognitive expertise, the ability to understand, monitor, and regulate collaborative processes has become a very important research agenda for CSCL; several attempts have been made to address this issue (e.g. Webster & Hadwin, 2013; Kreijns et al., 2003). In CSCL this agenda has included the development of digital tools to enhance shared regulation and knowledge of collaborative processes. Webster and Hadwin (2013) developed a collaborative scripting tool that required learners to provide information about their emotions and the strategies they planned to use to regulate a collaborative activity. Adaptive Instrument for Regulation of Emotions (AIRE) was developed by Järvenoja et al. (2013) to identify socio-emotional challenges affecting group performance and individual and group level regulatory strategies. Järvelä and Hadwin (2013) created a series of tools to help learners externalize their learning processes and prompt regulatory behaviors. These tools were combined to develop the S-REG tool that aims to help learners develop awareness and regulatory skills at both individual and group levels. Borge et al. (2018) developed a series of cognitive tools and an online intervention to help students develop socio-metacognitive expertise. They tested the instructional model behind the intervention for the purposes of designing an online tool, called CREATE, to support socio-metacognitive development.

The previous research has expanded our view on shared regulation. However, this type of research is still in its infancy and more work needs to be done to understand how these forms of knowledge and regulation can enhance collaborative learning and how we can best support them.

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Syllabi and Slides

Shared Regulation in CSCL slides by Sanna Järvelä

Video Resources

Watch the full webinar on Shared Regulation in CSCL featuring Sanna Järvelä:

Listen to the Shared Regulation in CSCL webinar

Reading

Basic Reading:
  • Borge, M., Ong, Y. S., & Rosé, C. P. (2018). Learning to monitor and regulate collective thinking processes. International Journal of Computer-Supported Collaborative Learning, 13(1), 61-92.
  • Hadwin, A. & Järvelä, S. (2011). Social aspects of self-regulated learning: Where social and self meet in the strategic regulation of learning. Teachers College Records, 113(2), 235-239.
  • Hadwin, A., Järvelä, S., & Miller, M. (2011). Self-regulated, co-regulated, and socially shared regulation of learning. In B. Zimmerman & D. Schunk (Eds.), Handbook of Self-Regulation of Learning and Performance, pp. 65-84. New York: Routledge.
  • Järvelä, S., & Hadwin, A. F. (2013). New frontiers: Regulating learning in CSCL. Educational Psychologist, 48(1), 25-39.
  • Järvelä, S., Hadwin, A., Malmberg, J., & Miller, M. (2018). Contemporary perspectives of regulated learning in collaboration. In International handbook of the learning sciences (pp. 127-136). Routledge.
  • Järvelä, S., Järvenoja, H., Malmberg, J. & Hadwin, A. (2013). Exploring socially-shared regulation in the context of collaboration. The Journal of Cognitive Education and Psychology, 12(3), 267-286. [Access Online]
Additional Reading:
  • Borge, M., & White, B. (2016). Toward the development of socio-metacognitive expertise: An approach to developing collaborative competence. Cognition and Instruction, 34(4), 323-360.
  • Borge, M., & Shimoda, T. (2019). Designing a computer-supported-collective regulation system: A theoretically informed approach. Technology, Instruction, Cognition, & Learning, 11(2-3), 193-217.
  • Isohätälä, J., Järvenoja, H., & Järvelä, S. (2017). Socially shared regulation of learning and participation in social interaction in collaborative learning. International Journal of Educational Research, 81, 11-24.
  • Hadwin, A. F., Järvelä, S., & Miller, M. (2018). Self-regulation, co-regulation and shared regulation in collaborative learning environments (pp. 83-106). In D. Schunk, & J. Greene, (Eds.). Handbook of Self-Regulation of Learning and Performance (2nd) Ed. New York, NY: Routledge.
  • Järvelä, S., Järvenoja, H., & Malmberg, J. (2019). Capturing the dynamic and cyclical nature of regulation: Methodological Progress in understanding socially shared regulation in learning. International Journal of Computer-Supported Collaborative Learning, 14(4), 425-441. https://doi.org/10.1007/s11412-019-09313-2
  • Järvelä, S., Kirschner, P. A., Hadwin, A., Järvenoja, H., Malmberg, J., Miller, M., & Laru, J. (2016). Socially shared regulation of learning in CSCL: Understanding and prompting individual-and group-level shared regulatory activities. International Journal of Computer-Supported Collaborative Learning, 11(3), 263-280.
  • Järvelä, S., Malmberg, J., Sobocinski, M. & Kirschner, P. (2020, in press). Metacognition in collaborative learning. In Cress, U., Wise, A., Rose, C., & Oshima, J. (Eds), International Handbook of Computer Supported Collaborative Learning. Springer.
  • Splichal, J. M., Oshima, J., & Oshima, R. (2018). Regulation of collaboration in project-based learning mediated by CSCL scripting reflection. Computers & Education, 125, 132-145.

Learning Scientists Who Have Researched This Topic

  • Marcela Borge
  • Carmen Gress
  • Allyson Fiona Hadwin
  • Sanna Järvelä
  • Hanna Järvenoja
  • Paul A. Kirschner
  • Mary McCaslin
  • Mariel Miller
  • Jun Oshima
  • Philip H.Winne
Summary References:
  • Borge, M., & White, B. Y. (2016). Toward the development of socio-metacognitive expertise: An approach to developing collaborative competence. Cognition and Instruction, 34(4), 323–360.
  • Borge, M., Ong, Y. S., & Rosé, C. P. (2018). Learning to monitor and regulate collective thinking processes. International Journal of Computer-Supported Collaborative Learning, 13(1), 61-92.
  • Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational researcher, 18(1), 32-42.
  • Järvelä, S., & Hadwin, A. F. (2013). New frontiers: Regulating learning in CSCL. Educational Psychologist, 48(1), 25–39.
  • Järvelä, S., Malmberg, J., Sobocinski, M. & Kirschner, P. (2020, in press). Metacognition in collaborative learning. In Cress, U., Wise, A., Rose, C., & Oshima, J. (Eds), International Handbook of Computer Supported Collaborative Learning. Springer.
  • Järvenoja, H., Volet, S., & Järvelä, S. (2013). Regulation of emotions in socially challenging learning situations: An instrument to measure the adaptive and social nature of the regulation process. Educational Psychology, 33(1), 31-58.
  • Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of the research. Computers in human behavior, 19(3), 335-353.
  • Roschelle, J., & Teasley, S. D. (1995). The construction of shared knowledge in collaborative problem solving. In C. E. O’Malley (Ed.), Computer-supported collaborative learning (pp. 69–97). New York: Springer.
  • Stahl, G., Koschmann, T., & Suthers, D. (2006). Computer-supported collaborative learning: An historical perspective. In R. K. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 409-426). Cambridge, UK: Cambridge University Press.
  • Webster, E. A., & Hadwin, A. F. (2013). Regulating emotions during computer-supported collaborative problem solving. Presented at the annual conference of the Canadian Society for the Study of Education, Victoria, British Columbia. Accessed from https://www.slideshare.net/edd101/webster-csse-2013-poster.
  • Zimmerman, B. J., & Schunk, D. H. (2001). Self-regulated learning and academic achievement: Theoretical perspectives (2nd Eds.). Routledge.