학술논문

Designing Ontology for Massive Open Online Courses using Protégé
Document Type
Conference
Source
2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2020 8th International Conference on. :403-406 Jun, 2020
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Engineering Profession
Ontologies
Semantic Web
Electronic learning
Data mining
Semantics
Information technology
Adaptivity
Dropout Rate
E-Learning
Knowledge Discovery
MOOC
Ontology
Smart Learning
Software Agents
Language
Abstract
Aimed at the problem of dropout in massive open online courses, this research work addresses the challenges and attributes of attrition. It investigates various factors to increase the effectiveness and efficiency in mooc platforms. The issue is not only interaction with the instructor but the necessity to create a social environment. The semantic web is an elongation of the present web that facilitates the meaning of information rather than syntax of the distinct vocabularies to the people and computers. The fundamental technique of semantic web mining is ontology. We have proposed semantic web mining by designing ontology for mooc platforms that can allow different mooc platforms to interact and create social environment for their users.