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Issue No.06 - November/December (2009 vol.15)
pp: 1073-1080
Sabrina Bresciani , University of Lugano (USI)
Martin J. Eppler , University of St. Gallen (HSG)
ABSTRACT
A great corpus of studies reports empirical evidence of how information visualization supports comprehension and analysis of data. The benefits of visualization for synchronous group knowledge work, however, have not been addressed extensively. Anecdotal evidence and use cases illustrate the benefits of synchronous collaborative information visualization, but very few empirical studies have rigorously examined the impact of visualization on group knowledge work. We have consequently designed and conducted an experiment in which we have analyzed the impact of visualization on knowledge sharing in situated work groups. Our experimental study consists of evaluating the performance of 131 subjects (all experienced managers) in groups of 5 (for a total of 26 groups), working together on a real-life knowledge sharing task. We compare (1) the control condition (no visualization provided), with two visualization supports: (2) optimal and (3) suboptimal visualization (based on a previous survey). The facilitator of each group was asked to populate the provided interactive visual template with insights from the group, and to organize the contributions according to the group consensus. We have evaluated the results through both objective and subjective measures. Our statistical analysis clearly shows that interactive visualization has a statistically significant, objective and positive impact on the outcomes of knowledge sharing, but that the subjects seem not to be aware of this. In particular, groups supported by visualization achieved higher productivity, higher quality of outcome and greater knowledge gains. No statistically significant results could be found between an optimal and a suboptimal visualization though (as classified by the pre-experiment survey). Subjects also did not seem to be aware of the benefits that the visualizations provided as no difference between the visualization and the control conditions was found for the self-reported measures of satisfaction and participation. An implication of our study for information visualization applications is to extend them by using real-time group annotation functionalities that aid in the group sense making process of the represented data.
INDEX TERMS
Laboratory Studies, Visual Knowledge Representation, Collaborative and Distributed Visualization, synchronous situated collaboration, group work, experiment, knowledge sharing
CITATION
Sabrina Bresciani, Martin J. Eppler, "The Benefits of Synchronous Collaborative Information Visualization: Evidence from an Experimental Evaluation", IEEE Transactions on Visualization & Computer Graphics, vol.15, no. 6, pp. 1073-1080, November/December 2009, doi:10.1109/TVCG.2009.188
REFERENCES
[1] K. Andrews, Evaluating Information Visualisations. In AVI 2006 Workshop BELIV'06, Venice, Italy, pages 1-5, 2006.
[2] M. Beer and A. R. Eisenstat, The Silent Killers of Strategy Implementation and Learning. Sloan Management Review, 41: 29-40, Summer 2000, 2000.
[3] M. Bitter-Rijpkema,R. Martens, and W. Jochems, Supporting knowledge elicitation for learning in virtual teams. Educational Technology & Society, 5: 113-118, 2002.
[4] S. Bresciani, A. F. Blackwell, and M. Eppler, A Collaborative Dimensions Framework: Understanding the Mediating Role of Conceptual Visualizations in Collaborative Knowledge Work. In HICCS 2008, Hawaii, pages 180-189, 2008.
[5] R. O. Briggs, B. A. Reinig, and G. de Vreede, Meeting Satisfaction for Technology-Supported Groups: an Empirical Validation of a Goal-Attainment Model. Small Group Research, 37: 585-611, 2006.
[6] D. T. Campbell and C. J. Stanley, Experimental and quasi-experimental design for research. Chicago, USA: Rand McNally College Pub. Co., 1966.
[7] S. K. Card, J. Mackinlay, and B. Shneiderman, Readings in Information Visualization: Using Vision to Think. San Francisco, CA: Morgan Kaufmann, ed., 1999.
[8] J. M. Carey and C. J. Kacmar, The impact of communication mode and task complexity on small group performance and member satisfaction. Computers in Human Behavior, 13: 23-49, 1997.
[9] P. R. Carlile, A Pragmatic View of Knowledge and Boundaries: Boundary Objects in New Product Development. Organization Science, 13: 442-455, Jul/Aug 2002, 2002.
[10] C. Chen and Y. Yu, Empirical studies of information visualization: a meta-analysis. International Journal of Human-Computer Studies, 53: 851-866, 2000.
[11] M. C. Chuah and S. F. Roth, Visualizing Common Ground. In Seventh International Conference on Information Visualization (IV'03), London, U.K., pages 365- 372, 2003.
[12] J. M. Clark and A. Paivio, Dual coding theory and education. Educational Psychology Review, 37: 250-263, 1991.
[13] G. DeSanctis and M. S. Poole, Use of group decision support systems as an appropriation process. In Proceedings of the Twenty-Second Annual Hawaii International Conference on System Sciences, Kailua-Kona, HI, USA, pages 149-157, 1989.
[14] M. Eppler and J. Mengis, Das Management von Wissensdialogen Zeitschrift für Organisationsentwicklung, 4/05: 14-23, 2005.
[15] M. J. Eppler, Facilitating Knowledge Communication through Joint Interactive Visualization. In I-KNOW '04, Graz, Austria, 2004.
[16] M. J. Eppler and K. Platts, Visual Strategizing: The Systematic Use of Visualization in the Strategic Planning Process. Long Range Planning LRP - International Journal of Strategic Management, 42: 42-74, February 2009, 2009.
[17] J. Fjermestad and S. R. Hiltz, An assessment of group support systems experiment research: methodology and results. Journal of Management Information Systems, 15: 143, 1998.
[18] J. Greenberg and E. C. Tomlinson, Situated Experiments in Organizations: Transplanting the Lab to the Field. Journal of Management, 30: 703-724, 2004.
[19] G. W. Harrison and J. A. List, Field Experiments. Journal of Economic Literature, 42: 1009-1055, 2004.
[20] K. Henderson, On Line and On Paper: Visual Representations, Visual Culture, and Computer Graphics in Design Engineering Baskerville, U.S.A.: The MIT Press, 1998
[21] P. Isenberg and S. Carpendale, Interactive Tree Comparison for Co-located Collaborative Information Visualization. IEEE Transactions on Visualization and Computer Graphics, 13: 1232-1239, November/December 2007.
[22] J. H. Larkin and H. Simon, Why a Diagram is (Sometimes) Worth Ten Thousand Words. Cognitive Science, 11: 65-99, 1987.
[23] G. Mark, K. Carpenter, and A. Kobsa, A Model of Synchronous Collaborative Information Visualization. In Seventh International Conference on Information Visualization (IV'03), London, U.K. , pages 373-381, 2003.
[24] G. Mark, A. Kobsa, and V. Gonzalez, Do Four Eyes See Better than Two? Collaborative versus Individual Discovery in Data Visualization Systems. In Sixth International Conference on Information Visualisation (IV'02), pages 249 - 255, 2002.
[25] J. E. McGrath, Groups: interaction and performance Englewood Cliffs, NJ: Prentice-Hall, 1984.
[26] R. J. Mejias, M. M. Shepherd, D. R. Vogel, and L. Lazaneo, Consensus and perceived satisfaction levels: A cross-cultural comparison of GSS and non-GSS outcomes within and between the United Stated and Mexico. Journal of Management Information Systems 13: 137-161, Winter 1996/1997, 1996.
[27] J. Mengis, Integrating Knowledge through Communication: An Analysis of Expert-Decision Maker Interactions. In Institute of Corporate Communication. PhD Lugano, Switzerland: University of Lugano (USI): 460, 2007.
[28] A. M. O'Donnell, D. F. Dansereau, and R. H. Hall, Knowledge Maps as Scaffolds for Cognitive Processing. Educational Psychology Review, 14: 71-86, March 2002 2002.
[29] S. Paul, P. Seetharamanb, I. Samarah, and P. P. Mykytyn, Impact of heterogeneity and collaborative conflict management style on the performance of synchronous global virtual teams. Information & Management, 41: 303-321, January 2004, 2004.
[30] R. Phaal and G. Muller, Towards Visual Strategy: An Architectural Framework for Roadmapping. In PICMET 2007, Portland, Oregon -USA, 2007.
[31] B. A. Reinig, R. O. Briggs, and J. F. J. Nunameker, On the measurement of Idea Quality. Journal of Management Information Systems, 23: 143-161, 2007.
[32] G. Robertson, R. Fernandez, D. Fisher, B. Lee, and J. Stasko, Effectiveness of Animation in Trend Visualization. IEEE Transactions on Visualization and Computer Graphics, 14: 1325-1332, November/December 2008, 2008.
[33] A. C. Robinson, Collaborative Synthesis of Visual Analytic Results. In Visual Analytics Science and Technology, VAST '08. IEEE Symposium on, Columbus, OH, pages 67-74, 2008.
[34] Y. Rogers, H. Brignull, and M. Scaife, Designing Dynamic Interactive Visualisations to Support Collaboration and Cognition. In Sixth International Conference on Information Visualisation (IV'02), London, U.K., pages 39 - 48, 2002.
[35] J. Roos, V. Bart, and M. Statler, Playing Seriously with Strategy Long Range Planning, 37: 549- 568, 2004.
[36] B. Shneiderman, Computer Science: Science 2.0. Science, 319: 1349-1350, 2008.
[37] B. Shneiderman, The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. In IEEE Visual Languages, Boulder, CO, pages 336-343, 1996.
[38] B. Shneiderman and C. Plaisant, Strategies for Evaluating Information Visualization Tools: Multi-dimensional In-depth Long-term Case Studies. In AVI 2006 Workshop BELIV'06, Venice, Italy, 2006.
[39] S. L. Star and J. R. Griesemer, Institutional Ecology, 'Translations' and Boundary Objects: Amateurs and Professionals in Berkeley's Museum of Vertebrate Zoology, 1907-39. Social Studies of Science, 19: 387-420, 1989.
[40] D. D. Suthers, Collaborative Knowledge Construction through Shared Representations. In 38th Hawaii International Conference on System Sciences (HICSS), Big Island, HI, USA, 2005.
[41] B. C. Y. Tan, K.-K. Wei, R. T. Watson, and R. Walczuch, Reducing status effects with computer-mediated communication: Evidence from two Distinct National Cultures. Journal of Management Information Systems, 15: 119-141, June 1998, 1998.
[42] J. J. Thomas and K. A. Cook, Illuminating the path: the research and development agenda for visual analytics. Los Alamitos, CA: Institute of Electrical and Electronics Engineers; National Visualization and Analytics Center; United States. Dept. of Homeland Security. IEEE Computer Society, 2005.
[43] E. R. Tufte, Envisioning Information. Cheshire, Connecticut: Graphic Press, 1990.
[44] E. R. Tufte, Visual Explanations. Images and Quantities, Evidence and Narrative. Cheshire, Connecticut: Graphic Press, 1997.
[45] B. Tversky, Visuospatial reasoning. In Handbook of Reasoning, K. Holyoak, and R. Morrison Eds. Cambridge, UK: Cambridge University Press, pages 209-249, 2005.
[46] C. Ware, Information Visualization (2nd Edition). San Francisco CA: Morgan Kaufmann, 2004.
[47] Z. Wen, and M. X. Zhou, Evaluating the Use of Data Transformation for Information Visualization. IEEE Transaction on Visualization and Computer Graphics, 14: 1309-1316, November/December 2008, 2008.
[48] L. Yang, G. Sun, and M. Eppler, Making Strategy Work: A Literature Review on the Factors influencing Strategy Implementation. In ICA Working Paper #2/2008 Lugano, Switzerland: University of Lugano (USI): 46, 2008.
[49] R. W. Zmud, R. J. Mejias, B. A. Reinig, and I. M. Martinez-Martinez, Participation equality: Measurement within collaborative electronic environments: a three country study. In Purdue CIBER working papers, 2002.
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