A grid-aware implementation for providing effective feedback to on-line learning groups

Constantly providing feedback to on-line learning teams is a challenging yet one of the latest and most attractive issues to influence learning experience in a positive manner. The possibility to enhance learning group's participation by means of providing appropriate feedback is rapidly gaining popularity due to its great impact on group performance and outcomes. Indeed, by storing parameters of interaction such as participation behaviour and giving constant feedback of these parameters to the group may influence group's motivation and emotional state resulting in an improvement of the collaboration. Furthermore, by feeding back to the group the results of tracking the interaction data may enhance the learners' and groups' problem solving abilities. In all cases, feedback implies constantly receiving information from the learners' actions stored in log files since the history information shown is continuously updated. Therefore, in order to provide learners with effective feedback, it is necessary to process large and considerably complex event log files from group activity in a constant manner, and thus it may require computational capacity beyond that of a single computer. To that end, in this paper we show how a Grid approach can considerably decrease the time of processing group activity log files and thus allow group learners to receive selected feedback 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.