A Cloud Computing for the Learner’s Usage Tracks Analysis

In the context of distance learning, the assessment of the learner teaching activity becomes difficult due to the lack of feedback to the tutor. The analysis of the learner usage tracks generated by learning tools during training sessions is a way for supervising and monitoring the distant learners. In this paper, the authors present the definition of a collaborative and cooperative platform, exploited through the cloud, for analyzing learner’s tracks and managing indicators in educational scenarios. This paper describes the architecture and the design proposed for the platform, then it evocates the related security aspect. Finally, a test scenario is described to demonstrate the platform functionalities.

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University of Sioux Falls