Learning Analytics for the Development of Adapted E-Assessment Workflow System

Learning analytics (LA) is a significant area of the enhanced learning technology that has been emerged during the last decade. In this paper, we present a Cloud Adapted Workflow e-Assessment System, called Cloud-AWAS. This system makes use of the learning analytics in order to turn learners into more effective and better learners. Hence, Cloud-AWAS could be seamlessly integrated into any learning management system. This system provides a generic e-assessment workflow which is adapted to learner's profiles. We have started by creating a learner profile ontology based on extraction data from e-assessment activities, file log and personal information. Then, we have defined three adaptation actions: Add Activity, Edit Activity, and Delete Activity, applied on the workflow assessment and using information extracted from learner profile ontology instances. Each action is applied according to a number of conditions. Finally, we present some results of the empirical evaluation of Cloud_AWAS. (C) 2016 Wiley Periodicals, Inc.