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Title: Increasing Learner Retention in a Simulated Learning Network using Indirect Social Interaction
Authors: Koper, Rob
Keywords: learning network
indirect social interaction
Issue Date: 15-Oct-2004
Abstract: A learning network is a network of persons who create, share, support and study learning resources ('units of learning') in a specific knowledge domain. Such networks may consist of a large number of alternative units of learning. One of the problems learners face in a learning network is to select the most suitable path through the units of learning in order to build the required competence in an effective and efficient way. This study explored the use of indirect social interaction to solve this problem. Units of learning that have been completed successfully by other comparable learners are presented to the learners as navigational support. A learning network is simulated in which learners search for, enrol in and study units of learning, subject to a variety of constraints: a) variable quality of the different units of learning, b) disturbance, i.e. interference by priorities other than learning and c) matching errors that occur when the entry requirements of the selected unit of learning do not align with the pre-knowledge of the learner. Two conditions are explored in the network: the selection of units of learning with and without indirect social interaction. It was found that indirect social interaction increases the proportion of learners who attain their required competence in the simulated learning network.
Description: Please refer to original publication: Koper, E.J.R. (2005). Increasing Learner Retention in a Simulated Learning Network Using Indirect Social Interaction. Journal of Artificial Societies and Social Simulation vol. 8, no. 2. Software is only stored to ensure later replication. Only the Linux version used in the experiments is stored. See to download software.
Appears in Collections:1. LN: Publications and Preprints
Keur der Wetenschap

Files in This Item:
File Description SizeFormat 
software.zipsimulation package8.4 MBzip (linux tar version)View/Open
LNmodel127-articleVersion.nlogosimulation code36.2 kBformat of sim programmeView/Open
preprint-LNsimulation.pdfpublication563.03 kBpdfView/Open

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