An Enabling Framework for Master-Worker Applications on the Computational Grid
HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing
Online Collaborative Learning: Theory and Practice
Online Collaborative Learning: Theory and Practice
Towards a generic platform for developing CSCL applications using Grid infrastructure
CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid
Expert Systems with Applications: An International Journal
WISE'06 Proceedings of the 7th international conference on Web Information Systems
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A Providing collaborative learning applications the possibility to offer continuous awareness to on-line collaborative learning teams is a challenging issue since it is essential to keep participants informed of both what is happening and what happened in the learning group. Moreover, awareness is the basis to enhance collaboration and improve the individual and group performance since it allows to track and assess the collaborative learning process more objectively and to model students' behavior more efficiently. In order to provide students and tutors with effective awareness, we consider the collaborative actions registered in log files. It is necessary to process large and considerably complex event log files in a constant manner, and thus it may requires processing capacity beyond that of a single computer. In this paper we show how a Grid approach can considerably decrease the time of processing group activity log files and thus allow students and tutors to be aware of what is going on in the group activity even in real time. Our approach is based on the master-worker paradigm and is implemented using Globus technology running on the Planetlab platform. To test our application, we used event log files from the Basic Support for Collaborative Work (BSCW) system.