On Supporting Users’ Reflection During Small Groups Synchronous Collaboration
During computer-mediated synchronous collaboration there is need for supporting reflection of the partners involved. In this paper we study techniques for determining the state of an evolving collaborative process, while the activity is in progress, making the users aware of this state. For this reason, a State of Collaboration (SoC) indicator has been defined, which is calculated using a combination of machine-learning and statistical techniques. Subse-quently a study was performed during which SoC was presented to a number of groups of collaborating partners engaged in problem-solving activities. It was found that this group awareness mechanism influenced in a significant way the behavior of the groups in which it was used. This study has wider implications to the design of groupware and in particular towards gaining an insight into the effect of group awareness mechanisms on computer-mediated collaborative learning.
Keywordscollaborative problem solving small group interaction synchronous collaboration computer supported collaborative learning interaction analysis
Unable to display preview. Download preview PDF.
- 1.Stahl, G.: Rediscovering CSCL. In: Koschmann, T., Hall, R., Miyake, N. (eds.) CSCL2: Carrying Forward the Conversation. Lawrence Erlbaum Associates, Hillsdale (2001)Google Scholar
- 2.Kahrimanis, G., Papasalouros, A., Avouris, N., Retalis, S.: A Model for Interoperability in Computer Supported Collaborative Learning. In: Proc. ICALT 2006 - 6th IEEE International Conference on Advanced Learning Technologies, Kerkrade, Netherlands, July 5-7 (2006)Google Scholar
- 3.Stahl, G.: Group cognition in computer-assisted collaborative learning. Journal of Computer Assisted Learning, 79–90 (2005)Google Scholar
- 4.Dewan, P.: Architectures for Collaborative Applications. In: Beaudouin-Lafon (ed.) Computer Supported Cooperative Work, ch. 7, pp. 169–193. JohnWiley & Sons Ltd (1999)Google Scholar
- 7.Xenos, M., Avouris, N., Komis, V., Stavrinoudis, D., Margaritis, M.: Synchronous Collaboration in Distance Education: A Case Study on a CS Course. In: Proc. IEEE ICALT 2004, Joensuu, FI (2004)Google Scholar
- 8.Voyiatzaki, E., Christakoudis, C., Margaritis, M., Avouris, N.: Algorithms Teaching in Secondary Education: A collaborative Approach. In: Proc. ED-Media 2004, Lugano, pp. 2781–2789 (June 2004)Google Scholar
- 9.Harrer, A., Kahrimanis, G., Zeini, S., Bollen, L., Avouris, N.: Is there a way to e-Bologna? Cross-National Collaborative Activities in University Courses. In: 1st European Conference on Technology Enhanced Learning, Crete, Greece, October 1-4 (2006)Google Scholar
- 10.Avouris, N., Margaritis, M., Komis, V.: Modelling interaction during small-groups synchronous problem-solving activities: The Synergo approach. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds.) ITS 2004. LNCS, vol. 3220. Springer, Heidelberg (2004)Google Scholar
- 11.Avouris, N., Komis, V., Fiotakis, G., Margaritis, M., Tselios, N.: Tools for Interaction and Collaboration Analysis of learning activities. In: Proc. CBLIS 2003, Nicosia, Cyprus (2003)Google Scholar
- 12.Witten, I.H., Frank, E.: Data Mining: Practical Machine-Learning Tools. Academic Press, San Diego (2000)Google Scholar
- 13.Hall, M.A.: Correlation-based Feature Selection for Machine Learning. Ph.D. diss. Dept. of Computer Science, Waikato Univ. (1998)Google Scholar
- 14.Margaritis, M., Avouris, N., Komis, V.: Methods and Tools for representation of Collaborative Learning activities. In: Proc. ETPE 2004, Athens (September 2004)Google Scholar