An Ontology-based Adaptive Personalized E-learning System, Assisted by Software Agents on Cloud Storage
Monika Rani, Riju Nayak, O.P. Vyas

TL;DR
This paper presents an ontology-based, adaptive e-learning system utilizing software agents and cloud storage to personalize learning experiences based on learner behavior and styles.
Contribution
It introduces an integrated ontology-driven framework with software agents for real-time personalization in e-learning, leveraging cloud storage for scalability.
Findings
Effective adaptation to learner styles demonstrated
Software agents successfully monitor and modify learning paths
System shows improved engagement through personalization
Abstract
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 and interactive proposition capable of advanced decision-making abilities. Two challenges have been observed during the exploration of recent developments in e-learning. Firstly, to incorporate e-learning systems effectively in the evolving semantic web environment and secondly, to realize adaptive personalization according to the learner's changing behavior. An ontology-driven system has proposed to implement the Felder-Silverman learning style model in addition to the learning contents, to validate its integration with the semantic web environment. Software agents are employed to monitor the learner's actual learning style and modify them accordingly. The learner's learning style and their modifications are made within the proposed…
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Taxonomy
TopicsLearning Styles and Cognitive Differences · Online Learning and Analytics · Open Education and E-Learning
