Metacognition and Learning

, Volume 7, Issue 1, pp 45–62 | Cite as

Supporting collaboration with technology: does shared cognition lead to co-regulation in medicine?

  • Susanne P. Lajoie
  • Jingyan Lu


The theoretical distinctions between metacognition, self-regulation and self-regulated learning are often blurred which makes the definition of co-regulation in group learning situations even more difficult. We have started to explore co-regulation in the context of decision making in simulated emergencies where medical teams work together to manage patient cases. Our earlier work has described the relationship between collaborative decision-making in this context as well as discourse patterns that emerge in a simulated medical emergency (Lu & Lajoie, 2008). This paper examines the interactions that occur during this simulation that reflect the relationship between co-regulation and medical decision-making. There are two collaborative learning conditions, a traditional situation where the instructor facilitates collaboration by using a whiteboard to document the group’s construction of a medical argument (the traditional whiteboard condition, TW). The second condition uses technology to facilitate the collaboration, where individuals use laptops and an interactive whiteboard (IW) where they can interact with the problem list as it is being created. Our assumption was that the IW would facilitate communication beyond the teacher–student, to include student–student both within and between the various subgroups. The IW group could document their medical arguments by using a structured template for constructing, annotating and sharing arguments. We found that participants in the IW condition differed from the TW condition in that they engaged in more adaptive decision-making behavior early on in the intervention. Similar overall levels of metacognitive activity were found in both conditions but the pattern and timing of metacognitive categories varied. Specifically, the IW group engaged in more planning and orienting than the TW group at the outset of the problem. Early engagement and co-regulation occurred in the IW group which led to shared understandings and subsequently to effective patient management in latter sessions (11.5% vs. 3.6% in TW). Technology supported greater metacognitive activity overall (44% vs 29% in the non supported group). Furthermore, technology facilitated greater planning (23% vs. 10%) and orienting (10% vs 1%) early in the medical problem solving activity. We refer to specific indicators in the discourse that help operationalize the concept of co-regulation.


Collaboration Medical decision making Distributed cognition Situated learning Simulations 


Author Notes

The authors would like to acknowledge the assistance of Dr. Marguerite Roy in coordinating the metacognitive coding efforts, along with Mr. John Ranelucci and Ms. Ilian Cruz-Panneso for their coding efforts. We also acknowledge Mr. Eric Poitras for his careful editorial advice. We acknowledge Dr. Jeffrey Wiseman for his valuable input as the designer and instructor of the Deteriorating Patient activity and his students for participating in this research. We also acknowledge the granting agency, Social Sciences and Humanities Research Council of Canada for supporting this research.


  1. Azevedo, R., & Witherspoon, A. M. (2009). Self-regulated use of hypermedia. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Handbook of metacognition in education (pp. 319–339). New York: Routledge.Google Scholar
  2. Azevedo, R., Cromley, J. G., & Seibert, D. (2004). Does adaptive scaffolding facilitate students’ ability to regulate their learning with hypermedia. Contemporary Educational Psychology, 29, 344–370.CrossRefGoogle Scholar
  3. Baker, L., & Brown, A. L. (1984). Metacognitive skills and reading. In P. D. Pearson (Ed.), Handbook of reading research (pp. 353–394). New York: Longman.Google Scholar
  4. Baker, D. P., Salas, E., King, H., Battles, J., & Barach, P. (2005). The role of teamwork in the professional education of physicians: current status and assessment recommendations. Joint Commission Journal on Quality and Patient Safety, 31, 185–202.Google Scholar
  5. Bandura, A. (1982). Self-efficacy mechanism in human agency. The American Psychologist, 37, 122–147.CrossRefGoogle Scholar
  6. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs: Prentice-Hall.Google Scholar
  7. Bartsch, K., & Wellman, H. M. (1995). Children talk about the mind. New York: Oxford University Press.Google Scholar
  8. Boekaerts, M., Pintrich, P., & Zeidner, M. (Eds.). (2000). Handbook of self-regulation. San Diego: Academic.Google Scholar
  9. Bowers, C. A., Morgan, B. B., Salas, E., & Prince, C. (1993). Assessment of coordination demand for aircrew coordination and training. Military Psychology, 5, 95–112.CrossRefGoogle Scholar
  10. Brown, J. S., Collins, A. & Duguid, S. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32–42.Google Scholar
  11. Butler, D., & Winne, P. H. (1995). Feedback and self-regulated learning: a theoretical synthesis. Review of Educational Research, 65, 245–281.Google Scholar
  12. Cannon-Bowers, J. A., Salas, E., & Converse, S. (1993). Shared mental models in expert team decision making. In N. J. J. Castellan (Ed.), Individual and group decision making (pp. 221–246). Hillsdale: Erlbaum.Google Scholar
  13. Corno, L., & Mandinach, E. B. (1983). The role of cognitive engagement in classroom learning and motivation. Educational Psychologist, 18(2), 88–108.CrossRefGoogle Scholar
  14. Dinsmore, D. L., Alexander, P. A., & Loughlin, S. M. (2008). Focusing the conceptual lens on metacognition, self-regulation, and self-regulated learning. Educational Psychology Review, 20, 391–409.CrossRefGoogle Scholar
  15. Flavell, J. H. (1971). First discussant’s comments: what is memory development the development of? Human Development, 14, 272–278.CrossRefGoogle Scholar
  16. Greene, J. A., & Azevedo, R. (2009). A macro-level analysis of SRL processes and their relations to the acquisition of a sophisticated mental model of a complex system. Contemporary Educational Psychology, 34(1), 18–29.CrossRefGoogle Scholar
  17. Hacker, D. J., & Bol, L. (2004). Metacognitive theory: Considering the social-cognitive influences. In D. M. McInerney & S. v. Etten (Eds.) Big theories revisited (pp. 275–297). Information Age Publishing.Google Scholar
  18. Iiskala, T., Vauras, V., Lehtinen, E., & Salonen, P. (2011). Socially shared metacognition of dyads of pupils in collaborative mathematical problem-solving processes, Learning and Instruction, 21, 374–393.Google Scholar
  19. Johnson, D. W., & Johnson, R. T. (Eds.). (1999). Learning together and alone: Cooperative, competitive, and individualistic learning (5th ed.). Boston: Allyn & Bacon.Google Scholar
  20. Joint Commission on Accreditation of Healthcare Organizations (2006). Sentinel Event Statistics, 30. Google Scholar
  21. Khoshafian, S., & Buckiewicz, W. (1995). Introduction to groupware, workflow, and workgroup computing. Toronto: Wiley.Google Scholar
  22. Klein, G. A., Orasanu, J., Calderwood, R., & Zsambok, C. E. (1993). Decision making in action: Models and methods. Norwood: Alex.Google Scholar
  23. Lajoie, S. P. (2008). Metacognition, self regulation, and self-regulated learning: a rose by any other name? Educational Psychology Review, 20, 469–475.CrossRefGoogle Scholar
  24. Lories, G., Dardenne, B., & Yzerbyt, V. Y. (1998). From social cognition to metacognition. In V. Y. Yzerbyt, G. Lories, & B. Dardenne (Eds.), Metacognition: Cognition and social dimensions (pp. 1–15). London: Sage.Google Scholar
  25. Lu, J., & Lajoie, S. P. (2008). Supporting medical decision making with argumentation tools. Contemporary Educational Psychology, 33, 425–442.CrossRefGoogle Scholar
  26. McCaslin, M. (2004). Coregulation of opportunity, activity, and identity in student motivation. In D. McInerney & S. Van Etten (Eds.), Big theories revisited, Vol. 4 (pp. 249–274). Greenwich: Information Age.Google Scholar
  27. Meijer, J., Veenman, M. V. J., & van Hout-Wolters, B. H. A. M. (2006). Metacognitive activities in text-studying and problem-solving: development of a taxonomy. Educational Research and Evaluation, 12(3), 209–237.CrossRefGoogle Scholar
  28. Olekalns, M., & Smith, P. L. (2005). Moments in time: metacognition, trust, and outcomes in dyadic negotiations. Personality and Social Psychology Bulletin, 31(12), 1696–1707.CrossRefGoogle Scholar
  29. Orasanu, J. (2005). Crew collaboration in space: A naturalistic decision-making perspective. Aviation, Space, and Environmental Medicine, 76(6), II, Supplement B154–163.Google Scholar
  30. Paris, S. G., & Paris, A. H. (2001). Classroom applications of research on self-regulated learning. Educational Psychologist, 36(2), 89–101.CrossRefGoogle Scholar
  31. Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16, 385–407.Google Scholar
  32. Reusser, K. (2001). In N.J. Smelser, P. Baltes and F.E. Weine (Eds.), International encyclopedia of the social and behavioral sciences (pp. 2058–2062). Oxford, UK: Pergamon/Elsevier Science.Google Scholar
  33. 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.CrossRefGoogle Scholar
  34. Salonen, P., Vauras, M., & Efklides, A. (2005). Social interaction: what can it tell us about metacognition and coregulation in learning? European Psychologist, 10(3), 199–208.CrossRefGoogle Scholar
  35. Schunk, D., & Zimmerman, B. (1994). Self-regulation of learning and performance. Hillsdale: Erlbaum.Google Scholar
  36. Veenman, M., Van Hout-Wolters, B., & Afflerbach, P. (2006). Metacognition and learning: conceptual and methodological considerations. Metacognition and Learning, 1, 3–14.CrossRefGoogle Scholar
  37. Volet, S., Summers, M., & Thurman, J. (2009). High-level co-regulation in collaborative learning: how does it emerge and how is it sustained? Learning and Instruction, 19, 128–143.CrossRefGoogle Scholar
  38. Winne, P. H. (2001). Self-regulated learning viewed from models of information processing. In B. J. Zimmerman & D. Schunk (Eds.), Self-regulated learning and academic achievement: Theoretical perspectives (pp. 153–189). Mahwah: Erlbaum.Google Scholar
  39. Winne, P., & Hadwin, A. (2008). The weave of motivation and self-regulated learning. In D. Schunk & B. Zimmerman (Eds.), Motivation and self-regulated learning: Theory, research, and applications (pp. 297–314). Mahwah: Erlbaum.Google Scholar
  40. Winne, P. H., & Perry, N. E. (2000). Measuring self-regulated learning. In M. Boekaerts, P. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 531–566). San Diego: Academic.Google Scholar
  41. Wiseman, J., & Snell, L. (2008). The deteriorating patient: a realistic but ‘low-tech’ simulation of emergency decision-making. The Clinical Teacher, 5, 93–97.CrossRefGoogle Scholar
  42. Wright, M. C., Phillips-Bute, B. G., Petrusa, E. R., Griffin, K. L., Hobbs, G. W. & Taekman, J. M. (2009). Assessing teamwork in medical education and practice: Relating behavioural teamwork ratings and clinical performance, Medical Teacher, 31(1), 30–38.Google Scholar
  43. Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81, 329–339.CrossRefGoogle Scholar
  44. Zimmerman, B. (2001). Theories of self-regulated learning and academic achievement: an overview and analysis. In B. Zimmerman & D. Schunk (Eds.), Self-regulated learning and academic achievement: Theoretical perspectives (pp. 1–37). Mahwah: Erlbaum.Google Scholar
  45. Zimmerman, B. J. (2004). Sociocultural influence and students’ development of academic self-regulation: A social-cognitive perspective. In D. M. McInerney, & S. v. Etten (Eds.), Big theories revisited. Information Age Publishing.Google Scholar
  46. Zimmerman, B. (2006). Development and adaptation of expertise: The role of self-regulatory processes and beliefs. In K. Ericsson, N. Charness, P. Feltovich, & R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance (pp. 705–722). New York: Cambridge University Press.Google Scholar
  47. Zimmerman, B., & Schunk, D. (2001). Self-regulated learning and academic achievement (2nd ed.). Mahwah: Erlbaum.Google Scholar

Copyright information

© Springer Science + Business Media, LLC 2011

Authors and Affiliations

  1. 1.McGill UniversityMontrealCanada
  2. 2.The University of Hong KongPokfulamHong Kong

Personalised recommendations