Designing Biases That Augment Socio-Cognitive Interactions

  • Pierre Dillenbourg
Part of the Computer-Supported Collaborative Learning Series book series (CULS, volume 5)


This chapter questions the assumption that the best environment for computer-supported collaborative learning is the one that most closely reproduces the features of face-to-face collaboration. Empirical studies have failed to establish the superiority of group interaction with richer media. Instead, the chapter explores media features that do not exist in face-to-face interactions and explains how these features might augment group cognition. The first feature, the persistency of the information display, turns the medium into a shared working memory. The second feature, storing the context in which the message is emitted, should enhance the construction of a shared understanding. The third feature, the display of a graphical summary of group interactions, is expected to facilitate group regulation. In these three examples, the medium is more than a neutral wire. It constitutes a functional component within the distributed cognitive system formed by the learners and the collaborative environment.


Augmented Reality Collaborative Learning Latent Semantic Analysis Computer Support Collaborative Learn Collaboration Script 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Anderson, A. H., O'Malley, C., Doherty-Sneddon, G., Langton, S., Newlands, A., Mullin, J., & Fleming, A. M., & Van der Velden, J. (1997). The impact of VMC on collaborative problem solving: An analysis of Task Performance, communicative process, and user satisfaction. In K.E. Finn, Sellen, A.J. et al. (Eds.). Video-mediated communication: Computers, cognition, and work, 133–155. Mahwah, N.J.: Lawrence Erlbaum Associates, Inc., Publishers.Google Scholar
  2. Anderson, A. H., Smallwood, L., MacDonald, R. Mullin, J. Fleming, A. and O'Malley, C. (2000): Video Data and Video Links in Mediated Communication: What do Users value ? International Journal of Human-Computer Studies, 52, 165–187.CrossRefGoogle Scholar
  3. Aronson, E., Blaney, N., Sikes, J., Stephan, G., & Snapp, M. (1978). The Jigsaw Classroom. Beverly Hills, CA: Sage Publication.Google Scholar
  4. Azuma, R. (1993). “Tracking Requirements for Augmented Reality.” Communications of the ACM 36(7): 50–51.CrossRefGoogle Scholar
  5. Baker, M.J. & Lund, K. (1996) Flexibly structuring the interaction in a CSCL environment. In P. Brna, A. Paiva & J. Self (Eds), Proceedings of the European Conference on Artificial Intelligence in Education. Lisbon, Portugal, Sept. 20–Oct. 2, pp. 401–407.Google Scholar
  6. Barros, B. & Verdejo, F. (2000) Analysing student interaction processes in order to improve collaboration: The DEGREE approach. Journal of Artificial Intelligence in Education, 11, 211–241.Google Scholar
  7. Blaye, A. (1988) Confrontation socio-cognitive et résolution de problèmes. Doctoral dissertation, Centre de Recherche en Psychologie Cognitive, Université de Provence, France.Google Scholar
  8. Carles, L. (2001) Benefits and limits of Video Channel on Mediated Interactions. Internal Report, Geneva Interaction Lab.Google Scholar
  9. Chi M.T.H., Bassok, M., Lewis, M.W., Reimann, P. & Glaser, R. (1989) Self-Explanations: How Students Study and Use Examples in Learning to Solve Problems. Cognitive Science, 13, 145–182.CrossRefGoogle Scholar
  10. Churchill, E.F, Trevor, J, Bly, S., Nelson, L. & Cubranic D. (2000). Anchored Conversations. Chatting in the Context of a Document. In Proceedings of CHI 2000 Conference on Human Factors in Computing Systems, ACM Press, pp. 454–461.Google Scholar
  11. Clark, H.H. & Brennan S.E. (1991) Grounding in Communication. In L. Resnick, J. Levine & S. Teasley (Eds.), Perspectives on Socially Shared Cognition (127–149). Hyattsville, MD: American Psychological Association.Google Scholar
  12. Clark, H.H. & Wilkes-Gibbs, D. (1986). Referring as a collaborative process. Cognition, 22:1–39.CrossRefGoogle Scholar
  13. Constantino-Gonzales, M. A., Suthers, D., Icaza, J. (2001). Designing and Evaluating a Collaboration Coach: Knowledge and Reasoning. In J. D. Moore, C. L. Redfield, & W. L. Johnson (Eds.) Artificial Intelligence in Education: AI-ED in the Wired and Wireless Future (10th International Conference on Artificial Intelligence in Education), Amsterdam: IOS press, May 19–23, San Antonio Texas, pp. 176–187.Google Scholar
  14. Corti, D. (to appear). Digital Annotations: Collaboration Patterns and Common Ground. Journal of the ACM.Google Scholar
  15. Daft, R.L. & Lengel, R.H. (1984). Information richness: a new approach to managerial behavior and organizational design. In: Cummings, L.L. & Staw, B.M. (Eds.), Research in organizational behavior 6, (191–233). Homewood, IL: JAI Press.Google Scholar
  16. DeLièvre, B. (2000). Etude de l'effet de quatre modalités de tutorat sur l'usage des outils d'aide dans un dispositif informatisé d'apprentissage à distance, Thèse de doctorat non publiée. Université de Mons-Hainaut, Belgique.Google Scholar
  17. Dillenbourg, P. & Traum, P. (1999). Does a shared screen make a shared understanding ? C. Hoadley et J. Roschelle (Eds), Proceedings of the Third Computer-Supported Collaborative Learning Conference, pp. 127–135, Stanford, Dec. 1999.Google Scholar
  18. Dillenbourg, P. (2002). Over-scripting CSCL: The risks of blending collaborative learning with instructional design. In P. A. Kirschner (Ed). Three worlds of CSCL Can I support CSCL (pp. 61–91). Heerlen, Open Universiteit Nederland.Google Scholar
  19. Dillenbourg, P., Baker, M., Blaye, A. & O'Malley, C. (1995) The evolution of research on collaborative learning. In E. Spada & P. Reiman (Eds) Learning in Humans and Machine: Towards an interdisciplinary learning science. (pp. 189–211) Oxford: Elsevier.Google Scholar
  20. Dillenbourg, P., Ott, D., Wehrle, T., Bourquin, Y., Jermann, P., Corti, D. & Salo, P. (2002). The socio-cognitive functions of community mirrors. In F. Flückiger, C. Jutz, P. Schulz and L. Cantoni (Eds). Proceedings of the 4th International Conference on New Educational Environments. Lugano, May 8–11, 2002.Google Scholar
  21. Doise, W. & Mugny, G. (1984) The social development of the intellect. Oxford: Pergamon Press.Google Scholar
  22. Donath, J. Karahalios, K. & Viegas, F. (1999) Visualizing Conversations. Proceedings of HICSS-32, Maui, HT, January 5–8, 1999.Google Scholar
  23. Erickson, T., Smith, D.N., Kellogg, W.A., Laff, M.R., Richards, J.T. & Bradner, E. (1999). Socially Translucent Systems: Social Proxies, Persistent Conversation, and the Design of ‘Babble'. In Proceedings of CHl'99 Conference on Human Factors in Computing Systems. New York: ACM Press.Google Scholar
  24. Fussell, S. R., Kraut, R. E., & Siegel, J. (2000). Coordination of Communication: Effects of Shared Visual Context on Collaborative Work. Proceedings of CSCW 2000 (pp. 21–30).Google Scholar
  25. Gaßner, K (2001). Architecture of a Cooperative Discussion Environment based on Visual Languages. In P. Dillenbourg, A. Eurelings, & Kai Hakkarainen (Eds) Proceedings of the European Conference on Computer-Supported Collaborative Learning (Euro-CSCL 2001). pp. 261–268. Maastricht, The Netherlands, March.Google Scholar
  26. Gaßner, K., Jansen, M., Harrer, A., Herrmann, K. & Hoppe, H.U. (2003). Analysis methods for collaborative models and activities. In Wasson, Ludvigsen and Hoppe (Eds). Designing for change in networked learning environments. Proceedings of the International Conference on Computer Supported Collaborative Learning (CSCL2003). (pp. 269–378). CSCL Series. Kluwer Academic Publishers, DordrechtGoogle Scholar
  27. Gaver, W. & Sellen, A. & Heath, C. & Luff, P. (1993): One is not enough: Multiple Views in a Media Space. Proceedings of INTERCHI'93, ACM.Google Scholar
  28. Glaus, R. (2002) Apport de la vidéoconférence sur la représentationd es émotions et de l'implication à la tâche dans une situation de travail collaboratif. Unpublished master theses. TECFA, University of Geneva. Available under Scholar
  29. Gutwin, C. and Greenberg, S. (1999). The Effects of Workspace Awareness Support on the Usability of Real-Time Distributed Groupware. ACM Transactions on Computer-Human Interaction, 6(3), 243–281, September.CrossRefGoogle Scholar
  30. Hansen, T, Dirckinck-Holmfeld, L, Lewis, R & Rugelj, J. (1999) Using telemtics for Collaborative Knowldge Construction. In P. Dillenbourg (Ed) Collaborative learning: Cognitive and Computational Approaches (pp. 169–198) Oxford: Pergamon.Google Scholar
  31. Herring, S. C. (1999). Interactional coherence in CMC. Proceedings of the 32 nd Hawai'i International Conference on System Sciences. IEEE Computer Society Press.Google Scholar
  32. Hollan, J. & Stornetta, S. (1992). Beyond being there. Proceedings of the International Conference on Computer-Human Interaction (CHI'92), pp. 119–125.Google Scholar
  33. Inaba, A. & Okamoto, T (1996) Development of the intelligent discussion support system for collaborative learning. Proceedings of Ed-Telecom’ 96. (pp 494–503), Bostoo.Google Scholar
  34. Jermann, P. & Dillenbourg, P. (2003) Elaborating New Arguments Through A CSCL Script. In Andriessen, G., Baker, M. and Suthers D. (Eds) Arguing to learn: Confronting Cognitions in Computer-Supported Collaborative Learning environments. CSCL Series, Kluwer.Google Scholar
  35. Jermann, P. (2002) Task and interaction regulation in controlling a traffic simulation. In G. Stahl (Ed.) Computer Support for Collaborative Learning. Proceedings of CSCL 2002, Boulder (pp. 601–602). Lawrence Erlbaum, Hillsdale, NJ.Google Scholar
  36. Landauer, T. K., Foltz, P. W., Laham, D. (1998). An introduction to Latent Semantic Analysis. Discourse Processes, 25, 259–284.CrossRefGoogle Scholar
  37. Nickerson, R.S. (1993) On the distribution of cognition: some reflections. In G. Salomon. (Ed). Distributed cognitions. Psychological and educational considerations (pp. 229–262) Cambridge, USA: Cambridge University Press.Google Scholar
  38. O'Donnell, A. M., & Dansereau, D. F. (1992). Scripted cooperation in student dyads: A method for analyzing and enhancing academic learning and performance. In R. Hertz-Lazarowitz and N. Miller (Eds.), Interaction in cooperative groups: The theoretical anatomy of group learning (pp. 120–141). London: Cambridge University Press.Google Scholar
  39. Olson, J. S., Olson, G. M., & Meader, D. K. (1995). What mix of video and audio is useful for remote real-time work. Proceedings of the Conference on Human Factors in Computing Systems (pp.362–368). Denver, CO: Academic Press.Google Scholar
  40. Ott, D. & Dillenbourg P. (2002). Grounding through proximity in a 3D Collaborative Environment. In F. Flückiger, C. Jutz, P. Schulz and L. Cantoni (Eds). Proceedings of the 4 th International Conference on New Educational Environments. Lugano, May 8–11, 2002.Google Scholar
  41. Palincsar A.S. and Brown A.L. (1984) Reciprocal Teaching of Comprehension-Fostering and Comprehension-Monitoring Activities. Cognition and Instruction, vol.1, no.2, pp. 117–175.CrossRefGoogle Scholar
  42. Philips, B. (2000) Should I take Turns ? In Proceedings of the CHI2000 Conference on Human Factors in Computing Systems ( pp. 341–342).Google Scholar
  43. Roschelle, J. (1992) Learning by Collaborating: Convergent Conceptual Change. Journal of the Learning Sciences, 2, 235–276.CrossRefGoogle Scholar
  44. Scott, J. (1991). Social Network Analysis: A Handbook. Newbury Park, CA: Sage Publications.Google Scholar
  45. Suthers, D., and Hundhausen, C. (2003). An Empirical Study of the Effects of Representational Guidance on Collaborative Learning. Journal of the Learning Sciences, 12(2), 183–219.CrossRefGoogle Scholar
  46. Suthers, D., Connelly, J., Lesgold, A., Paolucci, M., Toth, E., Toth, J., and Weiner, A. (2001). Representational and Advisory Guidance for Students Learning Scientific Inquiry. In Forbus, K. D., and Feltovich, P. J. (2001). Smart machines in education: The coming revolution in educational technology. Menlo Park, CA: AAAl/Mit Press, pp. 7–35.Google Scholar
  47. Veerman, A. L., & T. Treasure-Jones (1999). Software for problem solving through collaborative argumentation. In P. Coirier & J. E. B. Andriessen (Eds.), Foundations of argumentative text processing (p. 203–230). Amsterdam, Amsterdam University Press.Google Scholar
  48. Viegas, F. & Donath, J. (1999). Chat circles. In Proceedings of the CHI 1999 Conference on Human Factors in Computing Systems. New York, ACM Press, pp. 9–16Google Scholar
  49. Zeller, P. & Dillenbourg, P. (1997) Effet du type d'activité sur les stratégies d'exploration d'un hyperdocument. Sciences et techniques éducatives, 4(4), p. 413–435.Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Pierre Dillenbourg

There are no affiliations available

Personalised recommendations