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5 - The Group as Paradigmatic Unit of Analysis: The Contested Relationship of Computer-Supported Collaborative Learning to the Learning Sciences

from PART 1 - PAST

Published online by Cambridge University Press:  05 February 2016

By
Gerry Stahl
Edited by
Michael A. Evans ,
Martin J. Packer  and
R. Keith Sawyer
Gerry Stahl
Affiliation:
Drexel University
Michael A. Evans
Affiliation:
North Carolina State University
Martin J. Packer
Affiliation:
Universidad de los Andes, Colombia
R. Keith Sawyer
Affiliation:
University of North Carolina, Chapel Hill
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Summary

This chapter looks at the relationship of two historically and institutionally related research communities: Computer-Supported Collaborative Learning (CSCL) and the Learning Sciences (LS). It presents them from the perspective of the author as a participant in those communities during the past twenty years. It reviews the institutional history of their relationship within the International Society of the Learning Sciences (ISLS). The question is then posed: Do CSCL or LS represent a new paradigm of educational research? Trends in the history of philosophy and social theory are reviewed to motivate a contemporary paradigm. A post-cognitive educational paradigm is proposed that focuses on group interaction as the unit of analysis. Finally, the author's CSCL research agenda is described as an illustration of a candidate approach. In conclusion, it is proposed that CSCL research should focus on the analysis of group processes and practices, and that the analysis at this level should be considered foundational for LS.

A Participant's View of LS and CSCL

LS and CSCL are not easy to distinguish clearly. There are no objective or fixed definitions of these two fields. They are best understood as communities of researchers. Despite their fluidity, they do seem to evolve over time. The shifting nature of the communities appears differently to different participants and is often negotiated in discussions among them. In this chapter, I discuss the relationship between the CSCL and LS communities from the perspective of my own participation in them.

CSCL is post-disciplinary, requiring a mix of academic backgrounds. I came to CSCL from philosophy and computer science. In the 1960s and early 1970s, I studied twentieth-century continental philosophy and social theory at MIT, Northwestern, Heidelberg, and Frankfurt, but supported myself as a mathematics teacher and computer programmer. In the early 1990s, I studied computer science academically, specializing in artificial intelligence (AI), design theory, human–computer interaction (HCI), and computer-supported cooperative work (CSCW) at the University of Colorado in Boulder. On graduation in 1993, I decided to apply computer science to educational innovation. When Timothy Koschmann spent a year at Boulder during 1997/98 while I was starting my career as a research professor, I participated in his course on CSCL and he introduced me to local conversation analysts, whose courses I also attended. Koschmann was instrumental in organizing the first seven CSCL conferences and editing the seminal CSCL book (Koschmann, 1996).

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Reflections on the Learning Sciences , pp. 76 - 102
Publisher: Cambridge University Press
Print publication year: 2016

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References

Akkerman, S., Bossche, P. V. d., Admiraal, W., Gijselaers, W., Segers, M., Simons, R.-J., et al. (2007). Reconsidering group cognition: From conceptual confusion to a boundary area between cognitive and socio-cultural perspectives?Educational Research Review, 2, 39–63.CrossRefGoogle Scholar
Barron, B. (2003). When smart groups fail. The Journal of the Learning Sciences, 12(3), 307–359.CrossRefGoogle Scholar
Behrend, S. D., Singer, J., & Roschelle, J. (1988). A methodology for the analysis of collaborative learning in a physics microworld. In Proceedings of the International Conference on Intelligent Tutoring Systems, Montreal, Canada(pp. 48–53).Google Scholar
Bruner, J. (1990). Entry into meaning. In J. Bruner (Ed.), Acts of meaning (pp. 67–97). Cambridge, MA: Harvard University Press.Google Scholar
Çakir, M. P., & Stahl, G. (2013). The integration of mathematics discourse, graphical reasoning and symbolic expression by a virtual math team. In Martinovic, D., Freiman, V., & Karadag, Z. (Eds.), Visual mathematics and cyberlearning. New York: Springer. Retrieved from http://GerryStahl.net/pub/visualmath.pdf.Google Scholar
Çakir, M. P., Zemel, A., & Stahl, G. (2009). The joint organization of interaction within a multimodal CSCL medium. International Journal of Computer-Supported Collaborative Learning, 4(2), 115–149.Google Scholar
Charles, E. S., & Shumar, W. (2009). Student and team agency in VMT. In Stahl, G. (Ed.), Studying virtual math teams. (pp. 207–224). New York: Springer. Retrieved from http://GerryStahl.net/vmt/book/11.pdf.Google Scholar
Cole, M. (1996). Cultural psychology: A once and future discipline. Cambridge, MA: Harvard University Press.Google Scholar
Damsa, C. (2014). The multi-layered nature of small-group learning: Productive interactions in object-oriented collaboration. International Journal of Computer-Supported Collaborative Learning, 9(3), 247–281.CrossRefGoogle Scholar
Dennett, D. C. (1991). Consciousness explained. Boston: Little, Brown.Google Scholar
Dillenbourg, P., Baker, M., Blaye, A., & O'Malley, C. (1996). The evolution of research on collaborative learning. In Reimann, P. & Spada, H. (Eds.), Learning in humans and machines: Towards an interdisciplinary learning science (pp. 189–211). Oxford: Elsevier. Retrieved from http://tecfa.unige.ch/tecfa/publicat/dil-papers-2/Dil.7.1.10.pdf.Google Scholar
Dreyfus, H. (1992). What computers still can't do: A critique of artificial reason. Cambridge, MA: MIT Press.Google Scholar
Emirbayer, M., & Mische, A. (1998). What is agency?American Journal of Sociology, 103(4), 962–1023.CrossRefGoogle Scholar
Engeström, Y. (1987). Learning by expanding: An activity-theoretical approach to developmental research. Helsinki, Finland: Orienta-Kosultit Oy.Google Scholar
Garfinkel, H. (1967). Studies in ethnomethodology. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Garfinkel, H., & Sacks, H. (1970). On formal structures of practical actions. In Mckinney, J. & Tiryakian, E. (Eds.), Theoretical sociology: Perspectives and developments. (pp. 337–366). New York: Appleton-Century-Crofts.Google Scholar
Hegel, G. W. F. (1807/1967). Phenomenology of spirit (Baillie, J. B., Trans.). New York: Harper & Row.Google Scholar
Heidegger, M. (1927/1996). Being and time: A translation of Sein und Zeit (Stambaugh, J., Trans.). Albany: State University of New York Press.Google Scholar
Jeong, H., & Hmelo-Silver, C. (2010). An overview of CSCL methodologies. In Proceedings of the 9th International Conference of the Learning Sciences, Chicago (pp. 921–928).
Jeong, H., Hmelo-Silver, C. E., & Yu, Y. (2014). An examination of CSCL methodological practices and the influence of theoretical frameworks 2005–2009. International Journal of Computer-Supported Collaborative Learning, 9(3), 305–334.CrossRefGoogle Scholar
Kapur, M., & Kinzer, C. K. (2009). Productive failure in CSCL groups. International Journal of Computer-Supported Collaborative Learning, 4(1), 21–46.CrossRefGoogle Scholar
Kienle, A., & Wessner, M. (2006). The CSCL community in its first decade: Development, continuity, connectivity. International Journal of Computer-Supported Collaborative Learning, 1(1), 9–33.CrossRefGoogle Scholar
Koschmann, T. (Ed.). (1996). CSCL: Theory and practice of an emerging paradigm. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Koschmann, T. (2001). Revisiting the paradigms of instructional technology. In Proceedings of the 18th Annual Conference of the Australian Society for Computers in Learning in Tertiary Education, Melbourne, Australia (pp. 15–22).
Koschmann, T. (2002). Dewey's contribution to the foundations of CSCL research. In Stahl, G. (Ed.), Computer support for collaborative learning: Foundations for a CSCL community: Proceedings of CSCL 2002 (pp. 17–22). Boulder, CO: Lawrence Erlbaum.Google Scholar
Koschmann, T., Stahl, G., & Zemel, A. (2009). “You can divide the thing into two parts”: Analyzing referential, mathematical and technological practice in the VMT environment. In Proceedings of the International Conference on Computer Support for Collaborative Learning (CSCL 2009), Rhodes, Greece. Retrieved from http://GerryStahl.net/pub/cscl2009tim.pdf.
Kuhn, T. (1972). The structure of scientific revolutions, 2nd ed. Chicago: University of Chicago Press.Google Scholar
Lakatos, I. (1976). Proofs and refutations: The logic of mathematical discovery. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Latour, B. (1990). Drawing things together. In Lynch, M. & Woolgar, S. (Eds.), Representation in scientific practice. Cambridge, MA: MIT Press.Google Scholar
Latour, B. (1992). Where are the missing masses? The sociology of a few mundane artifacts. In Bijker, W. E. & Law, J. (Eds.), Shaping technology/building society. (pp. 225–227). Cambridge, MA: MIT Press.Google Scholar
Linell, P. (2009). With respect to Bakhtin: Some trends in contemporary dialogical theories. In K. Junefelt & P. Nordin (Eds.), Proceedings of the Second International Interdisciplinary Conference on Perspectives and Limits of Dialogism in Mikhail Bakhtin. Stockholm University, Sweden.
Lonchamp, J. (2012). Computational analysis and mapping of ijCSCL content. International Journal of Computer-Supported Collaborative Learning, 7(4), 475–497.CrossRefGoogle Scholar
Marx, K. (1867/1976). Capital, Vol. I (Fowkes, B., Trans.). New York,: Vintage.Google Scholar
Medina, R., & Suthers, D. D. (2013). Inscriptions becoming representations in representational practices. The Journal of the Learning Sciences, 22(1), 33–69.CrossRefGoogle Scholar
Medina, R., Suthers, D. D., & Vatrapu, R. (2009). Representational practices in VMT. In Stahl, G. (Ed.), Studying virtual math teams (pp. 185–205). New York: Springer. Retrieved from http://GerryStahl.net/vmt/book/10.pdf.Google Scholar
Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Pathak, S. A., Kim, B., Jacobson, M. J., & Zhang, B. H. (2011). Learning the physics of electricity: A qualitative analysis of collaborative processes involved in productive failure. International Journal of Computer-Supported Collaborative Learning, 6(1), 57–73.CrossRefGoogle Scholar
Roschelle, J. (1992). Learning by collaborating: Convergent conceptual change. Journal of the Learning Sciences, 2(3), 235–276.CrossRefGoogle Scholar
Roschelle, J. (1996). Learning by collaborating: Convergent conceptual change. In Koschmann, T. (Ed.), CSCL: Theory and practice of an emerging paradigm (pp. 209–248). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Roschelle, J., & Teasley, S. (1995). The construction of shared knowledge in collaborative problem solving. In O'Malley, C. (Ed.), Computer-supported collaborative learning (pp. 69–197). Berlin, Germany: Springer Verlag.Google Scholar
Sarmiento, J., & Stahl, G. (2008). Extending the joint problem space: Time and sequence as essential features of knowledge building. In Proceedings of the International Conference of the Learning Sciences (ICLS 2008), Utrecht, Netherlands. Retrieved from http://GerryStahl.net/pub/icls2008johann.pdf.
Sawyer, R. K. (Ed.). (2006). Cambridge handbook of the learning sciences. Cambridge, UK: Cambridge University Press.Google Scholar
Schegloff, E. A. (2007). Sequence organization in interaction: A primer in conversation analysis. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Schwartz, D. (1995). The emergence of abstract representations in dyad problem solving. Journal of the Learning Sciences, 4(3), 321–354.CrossRefGoogle Scholar
Simon, H. (1981). The sciences of the artificial, 2nd ed. Cambridge, MA: MIT Press.Google Scholar
Simon, H. (2001). Learning to research about learning. In Carver, S. & Klahr, D. (Eds.), Cognition and instruction: Twenty-five years of progress (pp. 205–226). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Singer, J., Behrend, S. D., & Roschelle, J. (1988). Children's collaborative use of a computer microworld. In Proceedings of the Second Conference on Computer-Supported Cooperative work, Portland, OR (pp. 271–281).CrossRef
Stahl, G. (2006). Group cognition: Computer support for building collaborative knowledge. Cambridge, MA: MIT Press. Retrieved from http://GerryStahl.net/elibrary/gc.Google Scholar
Stahl, G. (2009). Studying virtual math teams. New York: Springer. Retrieved from http://GerryStahl.net/elibrary/svmt.CrossRefGoogle Scholar
Stahl, G. (2010). Group cognition as a foundation for the new science of learning. In Khine, M. S. & Saleh, I. M. (Eds.), New science of learning: Cognition, computers and collaboration in education (pp. 23–44). New York: Springer. Retrieved from http://GerryStahl.net/pub/scienceoflearning.pdf.Google Scholar
Stahl, G. (2011). How a virtual math team structured its problem solving. In N. Miyake, H. Spada, & G. Stahl (Eds.), Proceedings of the connecting computer-supported collaborative learning to policy and practice: CSCL 2011 Conference Proceedings (pp. 256–263). Lulu: ISLS. Retrieved from http://GerryStahl.net/pub/cscl2011stahl.pdf.
Stahl, G. (2012). Dynamic-geometry activities with GeoGebra for virtual math teams. Retrieved from http://GerryStahl.net/elibrary/topics/activities.pdf.
Stahl, G. (2013a). Learning across levels. International Journal of Computer-Supported Collaborative Learning, 8(1), 1–12.CrossRefGoogle Scholar
Stahl, G. (2013b). Resources for connecting levels of learning. Retrieved from http://GerryStahl.net/pub/resources.pdf.
Stahl, G. (2013c). Translating Euclid: Designing a human-centered mathematics. San Rafael, CA: Morgan & Claypool Publishers. Retrieved from http://GerryStahl.net/elibrary/euclid.
Stahl, G. (2015a). Constructing dynamic triangles together: The development of mathematical group cognition. New York: Cambridge University Press. Retrieved from http://GerryStahl.net/elibrary/analysis.
Stahl, G. (2015b). The construction crew game. Retrieved from http://GerryStahl.net/elibrary/topics/game.pdf; http://ggbtu.be/b154045.
Stahl, G., & Öner, D. (2013). Resources for connecting levels of learning. In Proceedings of the International Conference of Computer-Supported Collaborative Learning (CSCL 2013), Madison, WI. Retrieved from http://GerryStahl.net/pub/cscl2013resources.pdf.
Stahl, G., Zhou, N., Çakir, M. P., & Sarmiento-Klapper, J. W. (2011). Seeing what we mean: Co-experiencing a shared virtual world. In Proceedings of the connecting computer-supported collaborative learning to policy and practice: CSCL 2011 Conference Proceedings, Lulu: ISLS (pp. 534–541). Retrieved from http://GerryStahl.net/pub/cscl2011.pdf.
Suchman, L., & Trigg, R. (1991). Understanding practice: Video as a medium for reflection and design. In Greenbaum, J. & Kyng, M. (Eds.), Design at work: Cooperative design of computer systems (pp. 65–90). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Suchman, L. A. (2007). Human-machine reconfigurations: Plans and situated actions, 2nd ed. Cambridge, UK: Cambridge University Press.Google Scholar
Suthers, D. D. (2006). Technology affordances for intersubjective meaning making: A research agenda for CSCL. International Journal of Computer-Supported Collaborative Learning, 1(3), 315–337.CrossRefGoogle Scholar
Tang, K.-Y. (2014). Contemporary intellectual structure of CSCL empirical research (2007–2012): A co-citation network analysisInternational Journal of Computer-Supported Collaborative Learning, 9(3), 335–363.CrossRefGoogle Scholar
Te(asley, S. D., & Roschelle, J. (1993). Constructing a joint problem space: The computer as a tool for sharing knowledge. In Lajoie, S. P. & Derry, S. J. (Eds.), Computers as cognitive tools (pp. 229–258). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Trausan-Matu, S., Dascalu, M., & Rebedea, T. (2014). Polycafe: Automatic support for the polyphonic analysis of CSCL chats. International Journal of Computer-Supported Collaborative Learning, 9(2), 127–156.CrossRefGoogle Scholar
Vygotsky, L. (1930/1978). Mind in society. Cambridge, MA: Harvard University Press.Google Scholar
Wee, J. D., & Looi, C.-K. (2009). A model for analyzing math knowledge building in VMT. In Stahl, G. (Ed.), Studying virtual math teams (pp. 475–497). New York: Springer. Retrieved from http://GerryStahl.net/vmt/book/25.pdf.Google Scholar
Zemel, A., Çakir, M. P., & Stahl, G. (2009). Understanding and analyzing chat in CSCL as reading's work. In Proceedings of the International Conference on Computer Support for Collaborative Learning (CSCL 2009), Rhodes, Greece. Retrieved from http://GerryStahl.net/pub/cscl2009zemel.pdf.
Zemel, A., & Koschmann, T. (2013). Recalibrating reference within a dual-space interaction environment. International Journal of Computer-Supported Collaborative Learning, 8(1), 65–87.CrossRefGoogle Scholar
Zhou, N., Zemel, A., & Stahl, G. (2008). Questioning and responding in online small groups engaged in collaborative math problem solving. In Proceedings of the International Conference of the Learning Sciences (ICLS 2008), Utrecht, Netherlands. Retrieved from http://GerryStahl.net/pub/icls2008nan.pdf.

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