Xi Zhang
ABSTRACT
With the increasingly prevailing usage of Information and Communication technologies (ICT) in collaborative learning, students can cooperate with others online easily, in spite of the restriction of time and location. Social loafing, a common phenomenon in collaborative work, has negative effect on team performance, especially on the individual's knowledge sharing behavior. In recent years, there are also some researches pointing out that social loafing is a kind of hidden and unobservable behavior. In this study, we propose a research model based on the stimulus-organism-response (S-O-R) framework and build a hidden Markov model (HMM) to infer the student's unobservable social loafing state. We collect real world behavior data from an online collaborative course from Nov 11th 2016 to Dec 21th 2016.The dataset includes more than 1200 knowledge sharing records from 150 students on Slack. Our research is expected to contribute in both academic study and managerial implications on how to set up a collaborative team.
- Baloian, N., J.A. Pino, and U.H. Hoppe, Dealing with the Students' Attention Problem in Computer Supported Face-to-Face Lecturing. Journal of Educational Technology & Society, 2008. 11(2): p. 192--205.Google Scholar
- Bonacich, P. 1972. "Factoring and Weighting Approaches to Status Scores and Clique Identification," Journal of Mathematical Sociology (2), pp. 113--120. Google ScholarCross Ref
- Bououd, I., Rouis, S., & Boughzala, I. (2013). Social loafing impact on collaboration in 3d virtual worlds: an empirical study. Post-Print.Google Scholar
- Bukowitz, W. R., & Williams, R. L. (1999). The knowledge management field book. Upper Saddle River, N.J: Financial Times (FT) Press, Prentice HallGoogle Scholar
- Burt, R. S. 1992. Structural Holes: The Social Structure of Competition Cambridge, MA:Harvard University Press.Google ScholarCross Ref
- Chidambaram, L., and Tung, L.L. "Is Out of Sight, Out of Mind? An Empirical Study of Social Loafing in Technology-Supported Groups," Information Systems Research (16:2) 2005, pp 149--168. Google ScholarDigital Library
- Ding, W. 2003. A Study of Collaborative Scientific Discovery. Bell & Howell Information and Learning Company.Google Scholar
- Dissanayake, I., Zhang, J., & Gu, B. (2015, January). Virtual Team Performance in Crowdsourcing Contest: A Social Network Perspective. In System Sciences (HICSS),In the 48th Hawaii International Conference (pp. 4894--4897). IEEE. Google ScholarDigital Library
- Donovan, R. J. and J. R. Rossiter. 1982. Store atmosphere: an environmental psychology approach. Journal of Retailing, 58 (1), 34--57.Google Scholar
- Freeman, L. 1979. "Centrality in Social Networks: Conceptual Clarification," Social Networks (1), pp. 215--239.Google Scholar
- George, J. "Extrinsic and Intrinsic Origins of Perceived Social Loafing in Organizations," Academy of Management Journal (35:1) 1992, pp 191--202.Google Scholar
- Karau, S.J., and Williams, K.D. "Social Loafing: A Meta-Analytic Review and Theoretical Integration," Journal of Personality and Social Psychology (65:4) 1993, pp 681--706Google ScholarCross Ref
- Liden, R.C., Wayne, S.J., Jaworski, R.A., and Bennett, N. "Social Loafing: A Field Investigation," Journal of Management (30:2) 2004, pp 285--304.Google ScholarCross Ref
- Lin, B., Zagalsky, A., Storey, Margaret, Anne, & Serebrenik, A. (2016). Why Developers Are Slacking Off: Understanding How Software Teams Use Slack. ACM Conference on Computer Supported Cooperative Work and Social Computing Companion (pp.333--336). ACM Google ScholarDigital Library
- Lin, T.C., and Huang, C.C. "Understanding Social Loafing in Knowledge Contribution from the Perspective of Justice and Trust," Expert Systems with Applications (36:1) 2009, pp 6156--6163 Google ScholarDigital Library
- Marques, Cardoso, D. V., Zappalá, L., & Salvatore. (2008). Knowledge sharing networks and performance. Comportamento Organizational E Gesto, 14(2)161--192.Google Scholar
- Mehrabian, A. and J. A. Russell. 1974. An approach to environmental psychology. Cambridge, MA: MIT.Google Scholar
- iezon, S. L., & Donaldson, R. L. (2005). Online groups and social loafing: understanding student-group interactions. Online Journal of Distance Learning Administration, 8(4)Google Scholar
- Suleiman, J., and Watson, R.T. 2008. "Social Loafing in Technology-Supported Teams," Computer Supported Cooperative Work (CSCW) (17:4), pp. 291--309. Google ScholarDigital Library
- Tapscott, D., Grown up digital. 2009: New York: McGraw-Hill. 361.Google Scholar
- Voelpel, S.C. "David against Goliath? Group Size and Bystander Effects in Virtual Knowledge Sharing," Human Relations (61:2) 2008, pp 271--295.Google ScholarCross Ref
- Voyles, E. C., Bailey, S. F., & Durik, A. M. (2015). New Pieces of the Jigsaw Classroom: Increasing Accountability to Reduce Social Loafing in Student Group Projects. The New School Psychology Bulletin, 13(1), 11--20.Google Scholar
- Wasko, M.M., and Faraj, S. 2005. "Why Should I Share? Examining Social Capital and Knowledge Contribution in Electronic Networks of Practice," MIS Quarterly (29:1), pp. 35--37. Google ScholarDigital Library
- Zhi, W. H., Chang, T. T., Kankanhalli, A., Zhi, W. H., & Chang, T. T. (2010). The Impact of Individual Centrality and Helping on Knowledge Sharing: A Study of Fit. Sustainable It Collaboration Around the Globe. Americas Conference on Information Systems, Amcis 2010, Lima, Peru, August (pp.149).Google Scholar
Index Terms
- Inferring the Student Social Loafing State in Collaborative Learning with a Hidden Markov Model: A Case on Slack
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