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

arXiv: https://arxiv.org/abs/1709.01492 · HTML: https://mlsanity.com/paper/1709.01492/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Aug 2017.

## Built on by (most cited first, 5 of 5)

- [DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware](https://mlsanity.com/paper/2207.00083/) (2022)
- [A Survey of Demonstration Learning](https://mlsanity.com/paper/2303.11191/) (2023)
- [Subgoal-Based Explanations for Unreliable Intelligent Decision Support Systems](https://mlsanity.com/paper/2201.04204/) (2022)
- [Amorphous Fortress: Observing Emergent Behavior in Multi-Agent FSMs](https://mlsanity.com/paper/2306.13169/) (2023)
- [Reorganizing Educational Institutional Domain using Faceted Ontological Principles](https://mlsanity.com/paper/2306.10300/) (2023)

## Abstract (arXiv)

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 e-learning system. Cloud storage is used as the primary back-end in order to maintain the ontology, databases and other required server resources. To verify the system, comparisons are made between the information presented and adaptive learning styles of the learner along with actions of agents according to learners' behavior. Finally, various conclusions are drawn by exploring the learner's behavior in an adaptive environment for the proposed e-learning system.