Tracing Interaction in Distributed Collaborative Learning

Chapter
Part of the Computer-Supported Collaborative Learning Series book series (CULS, volume 12)

Abstract

In order to understand how entanglements of the activities of multiple individuals in technology-mediated environments result in learning, it is necessary to trace out activity that may be distributed across time, space and media. Multiple analytic challenges are encountered, including the distributed nature of the data, the contingent nature of human behavior, understanding nonverbal behavior, selective attention to large data sets, and multi-scale phenomena. This paper offers approach to analysis that was developed in our laboratory to address some of these challenges. In order to unify multiple data sources into one analytic artifact, we found it useful to abstract from media-specific units of analysis (e.g., adjacency pair, reply) and represent our data using “contingency graphs” that capture the potential ways in which one act can be contingent upon another. Contingency graphs serve as abstract transcripts that record distributed interaction in one representation. This chapter describes the contingency graph representation, gives an example of its use in analyzing the development of shared representational practices, and discusses further challenges. Important questions remain concerning the extent to which interactional accounts can remain productive as we grapple with larger data sets and emergent phenomena, and whether a productive interplay between interactional and aggregate accounts are possible that together inform design.

Keywords

Dementia Editing Marin 

Notes

Acknowledgments

The approach to analysis described in this paper was developed over several years in collaboration with Nathan Dwyer and Ravi Vatrapu. This work was supported by the National Science Foundation under CAREER award 0093505.

References

  1. Barcellini, F., Détienne, F., Burkhardt, J.-M., & Sack, W. (2005). Thematic coherence and quotation practices in OSS design-oriented online discussions. In Proceedings of the 2005 international ACM SIGGROUP conference on supporting group work (GROUP ‘05) (pp. 177–186). Sanibel Island: ACM Press.CrossRefGoogle Scholar
  2. Berkowitz, M. W., & Gibbs, J. C. (1979). A preliminary manual for coding transactive features of dyadic discussion.Google Scholar
  3. Blumer, H. (1969). Symbolic interactionism. Berkeley: University of California Press.Google Scholar
  4. Bronckart, J. P. (1995). Theories of action, speech, natural language, and discourse. In J. V. Wertsch, P. D. Rio, & A. Alvarez (Eds.), Sociocultural studies of mind (pp. 75–91). New York: Cambridge University Press.CrossRefGoogle Scholar
  5. Brundell, P., Knight, D., Adolphs, S., Carter, R., Clarke, D., Crabtree, A., et al. (2008). The experience of using the digital replay system for social science research. In Proceedings of the 4th International e-Social Science Conference. University of Manchester, ESRC NCeSS.Google Scholar
  6. Castells, M. (2001). The internet galaxy: Reflections on the internet, business, and society. New York: Oxford University Press.Google Scholar
  7. Dillenbourg, P. (1999). What do you mean by “collaborative learning”? In P. Dillenbourg (Ed.), Collaborative learning: Cognitive and computational approaches (pp. 1–19). Amsterdam: Elsevier.Google Scholar
  8. Dwyer, N., & Suthers, D. D. (2006). Consistent practices in artifact-mediated collaboration. International Journal of Computer-Supported Collaborative Learning, 1(4), 481–511.CrossRefGoogle Scholar
  9. Dyke, G., & Lund, K. (2009). Tatiana: An environment to support the CSCL analysis process. In C. O’Malley, D. D. Suthers, P. Reimann, & A. Dimitracopoulou (Eds.), Computer supported collaborative learning practices: CSCL 2009 conference proceedings (pp. 58–67). Rhodes: International Society of the Learning Sciences.Google Scholar
  10. Edwards, D. (1997). Discourse and cognition. London: SAGE.Google Scholar
  11. Garfinkel, H. (1967). Studies in ethnomethodology. Englewood Cliffs: Prentice-Hall.Google Scholar
  12. Gibson, J. J. (1977). The theory of affordances. In R. Shaw & J. Bransford (Eds.), Perceiving, acting, and knowing. Hilsdale: Lawrence Erlbaum.Google Scholar
  13. Hamilton, E., & Feenberg, A. (2005). The technical codes of online education. E-Learning, 2(2), 104–121.CrossRefGoogle Scholar
  14. Hmelo-Silver, C. E., Rebecca, J., Liu, L., & Chernobilsky, E. this volume. Representational tools for understanding complex computer-supported collaborative learning environments. In S. Puntambekar, G. Erkens, & C. E. Hmelo-Silver (Eds.), Analyzing interactions in CSCL: Methods, approaches and issues (pp. 83–105). New York: Springer.Google Scholar
  15. Hutchins, E. (1995). Cognition in the wild. Cambridge: MIT Press.Google Scholar
  16. Jones, C., Dirckinck-Holmfeld, L., & Lindstrom, B. (2006). A relational, indirect, meso-level approach to CSCL design in the next decade. Computer-Supported Collaborative Learning, 1(1), 35–56.CrossRefGoogle Scholar
  17. Joseph, S., Lid, V., & Suthers, D. D. (2007). Transcendent communities. In C. Chinn, G. Erkens, & S. Puntambekar (Eds.), The computer supported collaborative learning (CSCL) conference 2007 (pp. 317–319). New Brunswick: International Society of the Learning Sciences.Google Scholar
  18. Koschmann, T. (2002). Dewey’s contribution to the foundations of CSCL research. In Proceedings of computer supported collaborative learning 2002 (pp. 17–22). Boulder: International Society of the Learning Sciences.Google Scholar
  19. Koschmann, T., Stahl, G., & Zemel, A. (2007). The video analyst’s manifesto (or the implications of Garfinkel’s policies for studying practice within design-based research). In R. Goldman, R. Pea, B. Barron, & S. J. Derry (Eds.), Video research in the learning sciences. Mahwah: Lawrence Erlbaum.Google Scholar
  20. Koschmann, T., Zemel, A., Conlee-Stevens, M., Young, N., Robbs, J., & Barnhart, A. (2005). How do people learn: Member’s methods and communicative mediation. In R. Bromme, F. W. Hesse, & H. Spada (Eds.), Barriers and biases in computer-mediated knowledge communication (and how they may be overcome) (pp. 265–294). Amsterdam: Kluwer Academic.CrossRefGoogle Scholar
  21. Latour, B. (1990). Drawing things together. In M. Lynch & S. Woolgar (Eds.), Representation in scientific practice. Cambridge: MIT Press.Google Scholar
  22. Latour, B. (2005). Reassembing the social: An introduction to actor-network-theory. New York: Oxford University Press.Google Scholar
  23. Lee, A. S., & Baskerville, R. L. (2003). Generalizing generalizability in information systems research. Information Systems Research, 14(3), 221–243.CrossRefGoogle Scholar
  24. Marin, A., & Wellman, B. (2010). Social network analysis: An introduction. In P. Carrington & J. Scott (Eds.), Handbook of social network analysis. London: Sage.Google Scholar
  25. Medina, R., Suthers, D., & Vatrapu, R. (2009). Inscriptions becoming representations. In C. O’Malley, P. Reimann, D. Suthers, & A. Dimitracopoulou (Eds.), Computer supported ­collaborative learning practices: CSCL 2009 conference proceedings (pp. 18–27). Rhodes: International Society of the Learning Sciences.Google Scholar
  26. Medina, R., & Suthers, D. D. (2008). Bringing Representational Practice From Log to Light. In International Conference for the Learning Sciences. Utrecht.Google Scholar
  27. Medina, R., & Suthers, D. D. (2009). Using a contingency graph to discover representational practices in an online collaborative environment. Research and Practice in Technology Enhanced Learning, 4(3), 281–305.CrossRefGoogle Scholar
  28. Norman, D. A. (1999). Affordance, conventions, and design. Interactions, 6, 38–42. May-June.CrossRefGoogle Scholar
  29. Reimann, P. (2009). Time is precious: Variable- and event-centred approaches to process analysis in CSCL research. Computer Supported Collaborative Learning, 4(3), 239–257.CrossRefGoogle Scholar
  30. Reimann, P., Yacef, K., & Kay, J. this volume. Analyzing collaborative interactions with data mining methods for the benefit of learning. In S. Puntambekar, G. Erkens, & C. E. Hmelo-Silver (Eds.), Analyzing interactions in CSCL: Methods, approaches and issues (pp. 161–185). New York: Springer.Google Scholar
  31. Renninger, K., & Shumar, W. (2002). Building virtual communities. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  32. Sacks, H., Schegloff, E. A., & Jefferson, G. (1974). A simplest systematics for the organization of turn-taking for conversation. Language, 50(4), 696–735.CrossRefGoogle Scholar
  33. Shipman, F. M., III, & McCall, R. (1994). Supporting knowledge-base evolution with incremental formalization, CHI94 (pp. 285–291). Boston: ACM.Google Scholar
  34. Stahl, G. (2006). Group cognition: Computer support for collaborative knowledge building. Cambridge: MIT Press.Google Scholar
  35. Star, S. L., & Griesemer, J. R. (1989). Institutional ecology, ‘translations’ and boundary objects: Amateurs and rofessionals in Berkeley’s museum of vertebrate zoology. Social Studies of Science, 19(3), 387–420.CrossRefGoogle Scholar
  36. Suthers, D. D. (2006a). A qualitative analysis of collaborative knowledge construction through shared representations. Research and Practice in Technology Enhanced Learning, 1(2), 1–28.Google Scholar
  37. Suthers, D. D. (2006b). Technology affordances for intersubjective meaning-making: A research agenda for CSCL. International Journal of Computers Supported Collaborative Learning, 1(3), 315–337.CrossRefGoogle Scholar
  38. Suthers, D. D., Chu, K.-H., & Joseph, S. (2009). Bridging Socio-Technical Capital in an Online Learning Environment. In Proceedings of the 42nd Hawai’i International Conference on the System Sciences (HICSS-42), January 5–8, 2009, Waikoloa, Hawai’i (CD-ROM). New Brunswick: Institute of Electrical and Electronics Engineers, Inc. (IEEE).Google Scholar
  39. Suthers, D. D., Dwyer, N., Medina, R., & Vatrapu, R. (2007a). A framework for eclectic analysis of collaborative interaction. In C. Chinn, G. Erkens, & S. Puntambekar (Eds.), The computer supported collaborative learning (CSCL) conference 2007 (pp. 694–703). New Brunswick: International Society of the Learning Sciences.Google Scholar
  40. Suthers, D. D., Dwyer, N., Vatrapu, R., & Medina, R. (2007b). An abstract transcript notation for analyzing interactional construction of meaning in online learning. In Proceedings of the 40th Hawai’i International Conference on the System Sciences (HICSS-34), (CD-ROM). New Brunswick: Institute of Electrical and Electronics Engineers, Inc. (IEEE).Google Scholar
  41. Suthers, D. D., Harada, V. H., Doane, W. E. J., Yukawa, J., Harris, B., & Lid, V. (2004). Technology-supported systemic reform: An initial evaluation and reassessment. In Paper presented at the proceedings of the sixth international conference of the learning sciences (pp. 537–544). Santa Monica: International Society of the Learning Sciences.Google Scholar
  42. Suthers, D. D., & Hundhausen, C. (2003). An experimental study of the effects of representational guidance on collaborative learning. Journal of the Learning Sciences, 12(2), 183–219.CrossRefGoogle Scholar
  43. Suthers, D. D., Hundhausen, C. D., & Girardeau, L. E. (2003). Comparing the roles of representations in face-to-face and online computer supported collaborative learning. Computers and Education, 41, 335–351.CrossRefGoogle Scholar
  44. Suthers, D. D., Medina, R., Vatrapu, R., & Dwyer, N. (2007c). Information sharing is incongruous with collaborative convergence: The case for interaction. In C. Chinn, G. Erkens, & S. Puntambekar (Eds.), The computer supported collaborative learning (CSCL) conference 2007 (pp. 714–716). New Brunswick: International Society of the Learning Sciences.Google Scholar
  45. Suthers, D. D., Vatrapu, R., Medina, R., Joseph, S., & Dwyer, N. (2008). Beyond threaded discussion: Representational guidance in asynchronous collaborative learning environments. Computers and Education, 50(4), 1103–1127.CrossRefGoogle Scholar
  46. Suthers, D. D., Yukawa, J., & Harada, V. H. (2007d). An activity system analysis of a tripartite technology-supported partnership for school reform. Research and Practice in Technology Enhanced Learning, 2(2), 1–29.CrossRefGoogle Scholar
  47. Teasley, S. D., & Roschelle, J. (1993). Constructing a joint problem space: The computer as a tool for sharing knowledge. In S. P. Lajoie & S. J. Derry (Eds.), Computers as cognitive tools (pp. 229–258). Hillsdale: Lawrence Erlbaum.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Laboratory for Interactive Learning Technologies, Department of Information and Computer SciencesUniversity of Hawai’iManoaUSA

Personalised recommendations