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E-learning and online education have made great strides in the recent past.It has moved from a knowledge transfer model to a highly intellect, swift andinteractive proposition capable of advanced decision-making abilities. Twochallenges have been observed during the exploration of recent developments ine-learning. Firstly, to incorporate e-learning systems effectively in theevolving semantic web environment and secondly, to realize adaptivepersonalization according to the learner's changing behavior. Anontology-driven system has proposed to implement the Felder-Silverman learningstyle model in addition to the learning contents, to validate its integrationwith the semantic web environment. Software agents are employed to monitor thelearner's actual learning style and modify them accordingly. The learner'slearning style and their modifications are made within the proposed e-learningsystem. Cloud storage is used as the primary back-end in order to maintain theontology, databases and other required server resources. To verify the system,comparisons are made between the information presented and adaptive learningstyles of the learner along with actions of agents according to learners'behavior. Finally, various conclusions are drawn by exploring the learner'sbehavior in an adaptive environment for the proposed e-learning system.

An Ontology-based Adaptive Personalized E-learning System, Assisted by Software Agents on Cloud Storage