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Conference Papers Year : 2007

Supporting Effective and Useful Web-based Distance Learning


Learners interacting in a Web-based distance learning environment produce a variety of information elements during their participation; these information elements usually have a complex structure and semantics, which makes it rather difficult to find out the behavioral attitudes and profiles of the users involved. User modelling in on-line distance learning is an important research field focusing on two important aspects: describing and predicting students' actions and intentions as well as adapting the learning process to students' features, habits, interests, preferences, and so on. This work provides an approach that can be used to greatly stimulate and improve the learning experience by tracking the students' intentions and helping them reconduct their actions that could evolve accordingly as the learning process moves forward. In this context, user modelling implies a constant processing and analysis of user interaction data during long-term learning activities, which produces large and considerably complex information. In this paper we show how a Grid approach can considerably decrease the time of processing log data. Our prototype is based on the master-worker paradigm and is implemented using a peer-to-peer platform called Juxtacat running on the Planetlab nodes. The results of our study show the feasibility of using Grid middleware to speed and scale up the processing of log data and thus achieve an efficient and dynamic user modelling in on-line distance learning.
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Dates and versions

hal-00190818 , version 1 (23-11-2007)


  • HAL Id : hal-00190818 , version 1


Santi Caballé, Thanasis Daradoumis, Fatos Xhafa, Joan Esteve. Supporting Effective and Useful Web-based Distance Learning. Third International Conference on Web Information Systems and Technologies (WEBIST 2007), 2007, Spain. pp.536-539. ⟨hal-00190818⟩


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