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Joint interactions in large online knowledge communities: The A3C framework

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Abstract

Social interaction is crucial for understanding individual and collective processes in knowledge communities. We describe how technology has changed the way people interact in large communities. Building on this description, we propose a framework that distinguishes four types of joint interactions in online knowledge communities: Attendance, Coordination, Cooperation, and Collaboration (A3C framework). These four types of interactions vary depending on the extent to which community members share their goals, processes, and outcomes. Attendance, the weakest form of joint interaction, is characterized by individualistic orientations; people may belong to a community but are still driven by individualistic goals, work as individuals, and produce outcomes for personal benefits. Coordination, a stronger form of interaction, is characterized by interdependence among community members; members still act largely as individuals, but their goals, processes, and outcomes are now interdependent or contingent on other community members. Cooperation is characterized by shared goals and outcomes, but the process of achieving the goal is not fully shared; members coordinate their activities and may also engage in some joint processes but work individually for most of the time. Collaboration is characterized by sharing in all of the dimensions involved; people share the processes, as well as the goals and outcomes of their work. These four types of joint interactions are not mutually exclusive, but instead build on each other. We discuss how the A3C framework may serve as a guide for future research and can support design efforts in online knowledge communities.

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References

  • Ahn, Y. Y., Bagrow, J. P., & Lehmann, S. (2010). Link communities reveal multiscale complexity in networks. Nature, 466, 761–764.

    Article  Google Scholar 

  • Anthony, D., Smith, S. W., & Williamson, T. (2009). Reputation and reliability in collective goods the case of the online encyclopedia Wikipedia. Rationality and Society, 21(3), 283–306.

    Article  Google Scholar 

  • Bakhtin, M. (1981). The dialogic imagination: Four essays. Austin: University of Texas Press.

    Google Scholar 

  • Barron, B., Martin, C. K., Mertl, V., & Yassine, M. (2016). Citizen science: Connecting to nature through networks. In U. Cress, J. Moskaliuk, & H. Jeong (Eds.), Mass collaboration and education (pp. 257–284). Cham: Springer International.

    Chapter  Google Scholar 

  • Beaudoin, M. F. (2002). Learning or lurking? Tracking the “invisible” online student. Internet and Higher Education, 5(2), 147–155.

    Article  Google Scholar 

  • Bientzle, M., Steffen, W., Jeong, H., Cress, U., & Kimmerle, J. (2017). Text chatting in collaborative writing: Its role in coordinating activities, Proceedings of the 12th International Conference on Computer Supported Collaborative Learning (pp. 771–772). Philadelphia: International Society of the Learning Sciences.

    Google Scholar 

  • Butler, B., Sproull, L., Kiesler, S., & Kraut, R. (2013). Community effort in online groups: who does the work and why? In S. P. Weisband (Ed.), Leadership at a distance: Research in technologically-supported work (pp. 171–193). New York: Erlbaum.

    Google Scholar 

  • Chi, M. T. H., Roy, M., & Hausmann, R. G. (2008). Observing tutorial dialogues collaboratively: Insights about human tutoring effectiveness from vicarious learning. Cognitive Science, 32, 301–341.

    Article  Google Scholar 

  • Cress, U., & Kimmerle, J. (2008). A systemic and cognitive view on collaborative knowledge building with wikis. International Journal of Computer-Supported Collaborative Learning, 3(2), 105–122.

    Article  Google Scholar 

  • Cress, U., Stahl, G., Ludvigsen, S., & Law, N. (2015). The core features of CSCL: Social situation, collaborative knowledge processes and their design. International Journal of Computer-Supported Collaborative Learning, 10(2), 109–116.

    Google Scholar 

  • Cress, U., Jeong, H., & Moskaliuk, J. (2016). Mass collaboration as an emerging paradigm for education? Theories, cases, and research methods. In U. Cress, J. Moskaliuk, & H. Jeong (Eds.), Mass collaboration and education (pp. 3–27). Cham: Springer International.

    Chapter  Google Scholar 

  • Dehler, J., Bodemer, D., Buder, J., & Hesse, F. W. (2011). Guiding knowledge communication in CSCL via group knowledge awareness. Computers in Human Behavior, 27(3), 1068–1078.

    Article  Google Scholar 

  • Dennen, V. P. (2008). Pedagogical lurking: Student engagement in non-posting discussion behavior. Computers in Human Behavior, 24(4), 1624–1633.

    Article  Google Scholar 

  • Dillenbourg, P. (1999). What do you mean by “collaborative learning”? In P. Dillenbourg (Ed.), Collaborative learning: Cognitive and computational approaches (Vol. 1, pp. 1–15). Oxford: Elsevier.

    Google Scholar 

  • Doan, A., Ramakrishnan, R., & Halevy, A. Y. (2010). Mass collaboration systems on the World-Wide Web. Communications of the ACM, 54, 86–96.

    Article  Google Scholar 

  • Eberle, J., Stegmann, K., & Fischer, F. (2014). Legitimate peripheral participation in communities of practice: Participation support structures for newcomers in faculty student councils. The Journal of the Learning Sciences, 23(2), 216–244.

    Article  Google Scholar 

  • Elliott, M. (2016). Stigmergic collaboration: A framework for understanding and designing mass collaboration. In U. Cress, J. Moskaliuk, & H. Jeong (Eds.), Mass collaboration and education (pp. 65–84). Cham: Springer International.

    Chapter  Google Scholar 

  • Fischer, G. (2001). Communities of Interest: Learning through the interaction of multiple knowledge systems. In S. Bjornestad, R. Moe, A. Morch, & A. Opdahl (Eds.), Proceedings of the 24th IRIS Conference (pp. 1–14). Bergen: Department of Information Science.

    Google Scholar 

  • Fischer, G. (2016). Exploring, understanding, and designing innovative socio-technical environments for fostering and supporting mass collaboration. In U. Cress, J. Moskaliuk, & H. Jeong (Eds.), Mass collaboration and education (pp. 43–63). Cham: Springer International.

    Chapter  Google Scholar 

  • Hakkarainen, K. (2009). A knowledge-practice perspective on technology-mediated learning. International Journal of Computer-Supported Collaborative Learning, 4, 213–231.

    Article  Google Scholar 

  • Heylighen, F. (2016). Stigmergy as a universal coordination mechanism I : Definition and components. Cognitive Systems Research, 38, 4–13.

    Article  Google Scholar 

  • Janssen, J., & Bodemer, D. (2013). Coordinated computer-supported collaborative learning: Awareness and awareness tools. Educational Psychologist, 48, 40–55.

    Article  Google Scholar 

  • Järvelä, S., Kirschner, P. A., Hadwin, A., Järvenoja, H., Malmberg, J., Miller, M., & Laru, J. (2016). Socially shared regulation of learning in CSCL: Understanding and prompting individual- and group-level shared regulatory activities. International Journal of Computer-Supported Collaborative Learning, 11, 263–280.

    Article  Google Scholar 

  • Jeong, H., & Chi, M. H. (2007). Knowledge convergence and collaborative learning. Instructional Science, 35, 287–315.

    Article  Google Scholar 

  • Jeong, H., & Hmelo-Silver, C. E. (2016). Seven affordances of computer-supported collaborative learning: How to support collaborative learning? How can technologies help? Educational Psychologist, 51, 247–265.

    Article  Google Scholar 

  • Jirschitzka, J., Kimmerle, J., Halatchliyski, I., Hancke, J., Meurers, D., & Cress, U. (2017). A productive clash of perspectives? The interplay between articles’ and authors’ perspectives and their impact on Wikipedia edits in a controversial domain. PloS One, 12, e0178985. doi:10.1371/journal.pone.0178985.

    Article  Google Scholar 

  • Kimmerle, J., Thiel, A., Gerbing, K.-K., Bientzle, M., Halatchliyski, I., & Cress, U. (2013). Knowledge construction in an outsider community: Extending the communities of practice concept. Computers in Human Behavior, 29, 1078–1090.

    Article  Google Scholar 

  • Kimmerle, J., Moskaliuk, J., Oeberst, A., & Cress, U. (2015). Learning and collective knowledge construction with social media: A process-oriented perspective. Educational Psychologist, 50, 120–137.

    Article  Google Scholar 

  • Kittur, A., & Kraut, R. E. (2008). Harnessing the wisdom of crowds in Wikipedia: Quality through coordination. In: Proceedings of the 2008 ACM conference on Computer supported cooperative work (pp. 37–46). ACM.

  • Lakhani, K., & von Hippel, E. (2003). How open source software works: “Free” user-to-user assistance. Research Policy, 6(32), 923–943.

    Article  Google Scholar 

  • Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Ludvigsen, S. (2016). CSCL: Connecting the social, emotional and cognitive dimensions. International Journal of Computer-Supported Collaborative Learning, 11, 115–121.

    Article  Google Scholar 

  • Ludvigsen, S., Stahl, G., Law, N., & Cress, U. (2015). Collaboration and the formation of new knowledge artifacts. International Journal of Computer-Supported Collaborative Learning, 10, 1–6.

    Article  Google Scholar 

  • Matschke, C., Moskaliuk, J., & Cress, U. (2012). Knowledge exchange using Web 2.0 technologies in NGOs. Journal of Knowledge Management, 16, 159–176.

    Article  Google Scholar 

  • Oeberst, A., Halatchliyski, I., Kimmerle, J., & Cress, U. (2014). Knowledge construction in Wikipedia: A systemic-constructivist analysis. The Journal of the Learning Sciences, 23, 149–176.

    Article  Google Scholar 

  • Orr, J. E. (1990). Sharing knowledge, celebrating identity: War stories and community memory among service technicians. In D. S. Middelton & D. Edwards (Eds.), Collective remembering: Memory in society (pp. 169–181). London: Sage.

    Google Scholar 

  • Paavola, S., & Hakkarainen, K. (2005). The knowledge creation metaphor–An emergent epistemological approach to learning. Science & Education, 14, 535–557.

    Article  Google Scholar 

  • Paavola, S., & Hakkarainen, K. (2014). Trialogical approach for knowledge creation. In S. C. Tan, H. J. So, & J. Yeo (Eds.), Knowledge creation in education (pp. 53–73). Singapore: Springer.

    Google Scholar 

  • Paavola, S., Lipponen, L., & Hakkarainen, K. (2004). Modeling innovative knowledge communities: A knowledge-creation approach to learning. Review of Educational Research, 74, 557–576.

    Article  Google Scholar 

  • Preece, J., Nonnecke, B., & Andrews, D. (2004). The top five reasons for lurking: Improving community experiences for everyone. Computers in Human Behavior, 20(2), 201–223.

    Article  Google Scholar 

  • Ren, Y., Kraut, R., & Kiesler, S. (2007). Applying common identity and bond theory to design of online communities. Organization Studies, 28(3), 377–408.

    Article  Google Scholar 

  • Resnick, M. (2012). Mother's Day, Warrior Cats, and Digital Fluency: Stories from the Scratch online community. In Proceedings of the Constructionism 2012 Conference: Theory, practice and impact (pp. 52–58).

  • Roque, R., Rusk, N., & Resnick, M. (2016). Supporting diverse and creative collaboration in the Scratch online community. In U. Cress, J. Moskaliuk, & H. Jeong (Eds.), Mass collaboration and education (pp. 241–256). Cham: Springer International.

    Chapter  Google Scholar 

  • Rummel, N., & Spada, H. (2005). Learning to collaborate: An instructional approach to promoting collaborative problem solving in computer-mediated settings. The Journal of the Learning Sciences, 14(2), 201–241.

    Article  Google Scholar 

  • Sacks, H., Schegloff, E., & Jefferson, G. (1974). A simplest systematics for the organization of turn-taking in conversation. Language, 50(4), 696–735.

    Article  Google Scholar 

  • Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. In B. Smith (Ed.), Liberal education in a knowledge society (pp. 67–98). Peru, IL: Open Court.

    Google Scholar 

  • Scardamalia, M., & Bereiter, C. (1994). Computer support for knowledge-building communities. The Journal of the Learning Sciences, 3(3), 265–283.

    Article  Google Scholar 

  • Scardamalia, M., Bereiter, C., & Drucker, A. P. (2003). Knowledge building. In: Encyclopedia of education (Vol. 2, pp. 1370–1373).

  • Schoor, C., Narciss, S., & Körndle, H. (2015). Regulation during cooperative and collaborative learning: A theory-based review of terms and concepts. Educational Psychologist, 50(2), 97–119.

    Article  Google Scholar 

  • Sfard, A. (1998). On two metaphors of learning and the dangers of choosing just one. Educational Researcher, 27(2), 4–13.

    Article  Google Scholar 

  • Shirky, C. (2010). Cognitive surplus: Creativity and generosity in a connected age. London: Penguin Books.

    Google Scholar 

  • Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2.

  • Slavin, R. E. (1990). Cooperative learning: Theory, research, and practice. Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  • Stahl, G. (2006). Group cognition: Computer support for building collaborative knowledge. Cambridge: MIT Press.

    Google Scholar 

  • Steiner, I. D. (1972). Group processes and productivity. New York: Academic Press.

    Google Scholar 

  • Tajfel, H., & Turner, J. C. (1986). The social identity theory of intergroup behavior. In S. Worchel (Ed.), Psychology of intergroup relations (pp. 7–24). Chicago: Nelson-Hall.

    Google Scholar 

  • Trausan-Matu, S. (2009). The polyphonic model of hybrid and collaborative learning. In Handbook of research on hybrid learning models: Advanced tools, technologies, and applications (pp. 466–486). Hershey: Information Science Reference.

    Google Scholar 

  • Viégas, F. B., Wattenberg, M., Kriss, J., & Ham, F. Van. (2007). Talk before you type: Coordination in Wikipedia. In: Hawaii International Conference on System Science (pp. 78–87).

  • Weinberger, A., & Fischer, F. (2006). A framework to analyze argumentative knowledge construction in computer-supported collaborative learning. Computers & Education, 46(1), 71–95.

    Article  Google Scholar 

  • Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Wenger, E. (2000). Communities of practice and social learning systems. Organization, 7(2), 225–246.

    Article  Google Scholar 

  • Yeager, C., Hurley-Dasgupta, B., & Bliss, C. A. (2013). CMOOCs and global learning: An authentic alternative. Journal of Asynchronous Learning Networks, 17(2), 133–147.

    Google Scholar 

  • Zhang, J., Scardamalia, M., Reeve, R., & Messina, R. (2009). Designs for collective cognitive responsibility in knowledge-building communities. The Journal of the Learning Sciences, 18(1), 7–44.

    Article  Google Scholar 

  • Zhang, J., Hong, H.-Y., Scardamalia, M., Teo, C. L., & Morley, E. a. (2011). Sustaining knowledge building as a principle-based innovation at an elementary school. The Journal of the Learning Sciences, 20(2), 262–307.

    Article  Google Scholar 

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Acknowledgements

This work was funded in part by the National Research Foundation of Korea (NRF-2012R1A1A3015115). This work originated when the first author spent her sabbatical in Tuebingen, Germany. She is grateful for the support from Leibniz-Institut fuer Wissensmedien (Knowledge Media Research Center), the hosting institution, as well as Hallym University, her home institution (HRF-201408-004). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies. The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Department of Psychology, Hallym University, Hallymdaehak-gil 1, Chuncheon, Gangwon-do, 200-702, South Korea

    Heisawn Jeong

  2. Leibniz-Institut fuer Wissensmedien, Tuebingen, Germany

    Ulrike Cress, Johannes Moskaliuk & Joachim Kimmerle

  3. University of Tuebingen, Tuebingen, Germany

    Ulrike Cress & Joachim Kimmerle

  4. International School of Management, Frankfurt, Germany

    Johannes Moskaliuk

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  1. Heisawn Jeong
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Correspondence to Heisawn Jeong.

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Jeong, H., Cress, U., Moskaliuk, J. et al. Joint interactions in large online knowledge communities: The A3C framework. Intern. J. Comput.-Support. Collab. Learn 12, 133–151 (2017). https://doi.org/10.1007/s11412-017-9256-8

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