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Developing a computational model to understand the contributions of social learning modes to task coordination in teams

Published online by Cambridge University Press:  15 January 2013

Vishal Singh ,
Andy Dong  and
John S. Gero
Vishal Singh*
Affiliation:
Department of Civil and Structural Engineering, Aalto University, Espoo, Finland
Andy Dong
Affiliation:
Faculty of Engineering and Information Technology, University of Sydney, Sydney, Australia
John S. Gero
Affiliation:
Krasnow Institute of Advanced Study, George Mason University, Fairfax, Virginia, USA
*
Reprint requests to: Vishal Singh, Department of Civil and Structural Engineering, Aalto University, Espoo 0076, Finland. E-mail: vishal.singh@aalto.fi
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Abstract

This paper reports on a computational model developed to study the effects of various modes of social learning on task coordination in teams through the mapping of distributed team competence, a significant aspect of efficient teamwork. The computational model emphasizes and operationalizes distinct modes of social learning, differentiated in terms of socialization opportunities. Simulation results demonstrate that computational models based on fundamental principles of social learning provide a robust approach to study task coordination in teams and can be used to explore ways to organize opportunities for social learning depending upon member retention, team structure, and the complexity of the design task.

Keywords

Member RetentionSocial LearningTeam StructureTransactive Memory
Type
Regular Articles
Information
AI EDAM , Volume 27 , Issue 1 , February 2013 , pp. 3 - 17
Copyright
Copyright © Cambridge University Press 2013

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