An ontology-based adaptive personalized e-learning system, assisted by software agents on cloud storage
TLDR
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.Abstract:
DL Query is used to extract information from content stored in the ontology.The Felder Silverman model is used to determine learning styles of learner's.JADE agents monitor learner's behavior to provide adaptive learning.Deployments on cloud enable scope for expanding the content stored on an ontology.The proposed system supports the vision of?Semantic web education learning (SWEL). 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.read more
Citations
More filters
Journal ArticleDOI
Review of ontology-based recommender systems in e-learning
Gina George,Anisha M. Lal +1 more
TL;DR: The comprehensive survey in this paper gives an overview of the research in progress using ontology to achieve personalization in recommender systems in the e-learning domain.
Journal ArticleDOI
Cloud Computing Adoption in Higher Education Institutions: A Systematic Review
TL;DR: This systematic literature review aims to analyze existing research on adopting and using CC in HEIs, review background research to develop a coherent taxonomy and provide a landscape for future research on CC inHEIs.
Journal ArticleDOI
On the way to learning style models integration
TL;DR: In this paper, the authors introduce a Learner's Characteristics Ontology based on creating interconnections between the different learning style model dimensions and learning styles with the relevant learner's characteristics, that helps instructors to improve and personalize the learning content; can recommend learning materials to learners according to their learning characteristics and preferences; and can provide both instructors and learners with extensive knowledge about how they can improve their teaching and learning abilities.
Journal ArticleDOI
A systematic review of ontology use in E-Learning recommender system
TL;DR: In this article , the authors examined the development and evaluation of ontology-based recommender systems and discussed technical ontology use and the recommendation process and found that the most popular recommendation item is the learning object.
Journal ArticleDOI
Semi-automatic terminology ontology learning based on topic modeling
TL;DR: In this paper, two topic modeling algorithms are explored, namely LSI and SVD and Mr.LDA for learning topic ontology and the objective is to determine the statistical relationship between document and terms to build a topic ontologies and ontology graph with minimum human intervention.
References
More filters
Journal ArticleDOI
Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility
TL;DR: This paper defines Cloud computing and provides the architecture for creating Clouds with market-oriented resource allocation by leveraging technologies such as Virtual Machines (VMs), and provides insights on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain Service Level Agreement (SLA) oriented resource allocation.
Learning and Teaching Styles in Engineering Education.
TL;DR: A self-scoring web-based instrument called the Index of Learning Styles that assesses preferences on four scales of the learning style model developed in the paper currently gets about 100,000 hits a year and has been translated into half a dozen languages.
Journal ArticleDOI
What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction
TL;DR: An integrated model with six dimensions of learners, instructors, courses, technology, design, and environment reveals critical factors affecting learners' perceived satisfaction and shows institutions how to improve learner satisfaction and further strengthen their e-Learning implementation.
Proceedings Article
METHONTOLOGY: From Ontological Art Towards Ontological Engineering
TL;DR: The goal of this paper is to clarify to readers interested in building ontologies from scratch, the activities they should perform and in which order, as well as the set of techniques to be used in each phase of the methodology.
Proceedings Article
Methodology for the Design and Evaluation of Ontologies
TL;DR: The goal of the TOVE (TOronto Virtual Enterprise) Enterprise Modelling project is to create the next generation Enterprise Model, a Common Sense Enterprise Model that has the ability to deduce answers to queries that require relatively shallow knowledge of the domain.