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Verbal Equity, Cognitive Specialization, and Performance

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Published:09 November 2014Publication History

ABSTRACT

In this paper, patterns of communication are examined in order to unpack the extent to which verbal equity is a critical factor in determining group success. A microanalysis of 20 teams working to complete a complex, information dependent, collaborative task was conducted. Interaction analysis methods were used as means to determine patterns of interaction and the sophistication of cognitive activity that teams engaged in. Findings suggest that verbal equity may not be as important as previous research indicates. A more critical variable may be cognitive specialization. The authors explain their findings by drawing on theories of cognition, thereby contributing to a better understanding of collective intelligence.

References

  1. Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183--198.Google ScholarGoogle ScholarCross RefCross Ref
  2. Borge, M., Ganoe, C., Shih, S., and Carroll, J. (2012). Patterns of team processes and breakdowns in information analysis tasks. In Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work. (CSCW '12). ACM, New York, New York. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Brown T. , Miller, C. (2000). Communication networks in task-performing groups: effects of task complexity, time pressure, and interpersonal dominance. Small Group Res. 31(2):131--57Google ScholarGoogle ScholarCross RefCross Ref
  4. Carroll, J., Borge, M., & Shih, S. (2013). Cognitive Artifacts as a Window on Design. Journal of Visual Languages and Computing (2013), http://dx.doi.org/10.1016/j.jvlc.2013.05.001i Google ScholarGoogle ScholarCross RefCross Ref
  5. Convertino, G., Mentis, H., Bhambare, P., Ferro, C., Carroll, J. M., & Rosson, M. B. (2008). Comparing media in emergency planning. In Proceedings of the 5th International ISCRAM Conference, Washington, DC.Google ScholarGoogle Scholar
  6. Convertino, G., Mentis, H. M., Rosson, M. B., Slavkovic, A., & Carroll, J. M. (2009). Supporting content and process common ground in computer-supported teamwork. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 2339--2348). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Cooke, N.J., DeJoode, J.A., Pedersen, H.K., Gorman, J.C., Connor, O.O., & Kiekel, P.A. (2004). The role of individual and team cognition in uninhabited air vechicle command-and-control. Technical Report for AFOSR Grant Nos. F49620-01--1-0261and F49620-03--1-00248.Google ScholarGoogle Scholar
  8. Dillenbourg, P., & Traum, D. (1999). The long road from a shared screen to a shared understanding. Paper presented at the Proceedings of the Computer Support for Collaborative Learning (CSCL) 1999 Conference, Palo Alto, California. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Fiore, S., Rosen, M., Smith-Jentsch, K., & Salas, E. (2010). Toward an Understanding of Macrocognition in Teams: Predicting Processes in Complex Collaborative Contexts. Human Factors.Google ScholarGoogle Scholar
  10. Harris, A., Rick, J., Bonnett, V., Yuill, N., Fleck, R., Marshall, P., & Rogers, Y. (2009, June). Around the table: are multiple-touch surfaces better than single-touch for children's collaborative interactions?. In Proceedings of the 9th international conference on Computer supported collaborative learning-Volume 1 (pp. 335--344). International Society of the Learning Sciences. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Jordan, B., & Henderson, A. (1995). Interaction analysis: Foundations and practice. The journal of the learning sciences, 4(1), 39--103.Google ScholarGoogle Scholar
  12. Kaput, J. J. (1989). Linking representations in the symbol systems of algebra. In S. Wagner, & C. Kieran, Research issues in the learning and teaching of algebra (pp. 167--194). Hillsdale, NJ: Erlbaum.Google ScholarGoogle Scholar
  13. Kerr, N. L., & Tindale, R. S. (2004). Group performance and decision making. Annu. Rev. Psychol., 55, 623--655.Google ScholarGoogle ScholarCross RefCross Ref
  14. Kirschner, P. A. (2002). Cognitiv load theory: Implications of cognitive load theory on the design of learning. Learning and instruction, 12(1), 1--10.Google ScholarGoogle Scholar
  15. Landis, J. R., Koch, G. G. The measurement of observer agreement for categorical data. Biometrics 33 (1977), 159--174.Google ScholarGoogle Scholar
  16. Letsky, M., & Warner, N. (2008). Macrocognition in teams. In M. Letsky, N. Warner, S. Fiore & C. Smith (Eds.), Macrocognition in Teams: Theories and Methodologies. Hampshire: Ashgate Publishing Limited.Google ScholarGoogle Scholar
  17. Norman, D. A. (1990). Four (more) issues for cognitive science. Department of Cognitive Science, University of California, San Diego.Google ScholarGoogle Scholar
  18. Marshall, P., Hornecker, E., Morris, R., Dalton, N. S., & Rogers, Y. (2008, October). When the fingers do the talking: A study of group participation with varying constraints to a tabletop interface. In Horizontal Interactive Human Computer Systems, 2008. TABLETOP 2008. 3rd IEEE International Workshop on (pp. 33--40). IEEE.Google ScholarGoogle Scholar
  19. Schafer, W.A., Ganoe, C.H. & Carroll, J.M. Supporting community emergency management through a geocollaboration software infrastructure. Computer- Supported Cooperative Work: The Journal of Collaborative Computing, 16 (2007), 501--537. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Schraw, G., Crippen, K. J., & Hartley, K. (2006). Promoting self-regulation in science education: Metacognition as part of a broader perspective on learning. Research in Science Education, 36(1--2), 111--139.Google ScholarGoogle Scholar
  21. Shimoda, T., White, B., Borge, M., & Frederiksen, J. (2013). Designing for science learning and collaborative discourse. In Proceedings of the 12th International Conference on Interaction Design and Children (pp. 247--256). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Stahl, G. (2006). Knowledge negotiation online. In G. Stahl (Ed.), Group Cognition (pp. 177--189). Cambridge. MA: MIT Press.Google ScholarGoogle ScholarCross RefCross Ref
  23. Stahl, G., Koschmann, T., & Suthers, D. (2006). Computer-supported collaborative learning: An historical perspective. In R. K. Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 409--426). Cambridge, UK: Cambridge University Press.Google ScholarGoogle Scholar
  24. Stasser, G., & Titus, W. (1985). Pooling of unshared information in group decision making: Biased information sampling during discussion. Journal of personality and social psychology, 48(6), 1467.Google ScholarGoogle ScholarCross RefCross Ref
  25. Sweller, J. (1994). Cognitive load theory, learning difficulty, and instructional design. Learning and instruction, 4(4), 295--312.Google ScholarGoogle Scholar
  26. Van Merrienboer, J. J., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational psychology review, 17(2), 147--177.Google ScholarGoogle Scholar
  27. Warner, N., Burkman, L., & Biron, C. H. Special operations reconnaissance (SOR) scenario: Intelligence analysis and mission planning, No. NAWCADPAX/TM-2008/184, 2008.Google ScholarGoogle Scholar
  28. West, G. P. Collective Cognition: When Entrepreneurial Teams, Not Individuals, Make Decisions. Entrepreneurship Theory and Practice, 31,1 (2007), 77-- 102.Google ScholarGoogle Scholar
  29. White, B. Y., & Frederiksen, J. R. (1998). Inquiry, modeling, and metacognition: Making science accessible to all students. Cognition and instruction, 16(1), 3--118.Google ScholarGoogle Scholar
  30. Woolley, A., Chabris, C., Pentland, A., Hashmi, M., & Malone, T. Evidence for a collective intelligence factor in the performance of human groups. Science, 330, 6004 (2010), 686--688.Google ScholarGoogle Scholar

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        cover image ACM Conferences
        GROUP '14: Proceedings of the 2014 ACM International Conference on Supporting Group Work
        November 2014
        340 pages
        ISBN:9781450330435
        DOI:10.1145/2660398

        Copyright © 2014 ACM

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        Publication History

        • Published: 9 November 2014

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        GROUP '14 Paper Acceptance Rate27of90submissions,30%Overall Acceptance Rate103of311submissions,33%

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