Abstract
While collaborative learning has long been believed to hold a great value for organizations and classrooms, Modeling this learning in small, short-term project teams is a challenge. This paper describes the development of an agent-based modeling approach that can assist in understanding the collaborative learning of such project teams. A key aspect of the presented approach is our distinction between knowledge and skills required for the achievement of project goals. Both of these forms of intelligence need to be learned in the project context, but the rate of their expansion or enhancement may proceed differently, depending on the personality makeup of the team and the mechanism employed for team assembly. Based on reports from the theoretical and empirical literature, we derive a multi-agent computational model that characterizes how knowledge and skills may be learned among team members with varying personality attributes. Also, Group formation in virtual learning environments is either done voluntary or with the support from the system. In this connection, we studied two types of group formation mechanisms and the role of each mechanism in the collaborative learning and performance of teams.
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Farhangian, M., Purvis, M., Purvis, M., Savarimuthu, T.B.R. (2015). The Effects of Temperament and Team Formation Mechanism on Collaborative Learning of Knowledge and Skill in Short-Term Projects. In: Koch, F., Guttmann, C., Busquets, D. (eds) Advances in Social Computing and Multiagent Systems. MFSC 2015. Communications in Computer and Information Science, vol 541. Springer, Cham. https://doi.org/10.1007/978-3-319-24804-2_4
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DOI: https://doi.org/10.1007/978-3-319-24804-2_4
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