Evaluation and Comparative Analysis of Semantic Web-Based Strategies for Enhancing Educational System Development

Abstract

Educators have been calling for reform for a decade. Recent technical breakthroughs have led to various improvements in the semantic web-based education system. After last year's COVID-19 outbreak, development quickened. Many countries and educational systems now concentrate on providing students with online education, which differs greatly from traditional classroom education. Online education allows students to learn at their own pace. As a consequence, education has become more dynamic. In the educational system, this changing nature makes user demands difficult to identify. Many instructors suggest using machine learning, artificial intelligence, or ontology to improve traditional teaching methods. Due to the lack of survey studies examining and comparing all of the researcher's semantic web-based teaching methodologies, the authors decided to conduct this survey. This paper's goal is to analyse all available possibilities for semantic web-based education systems that enable new researchers to develop their knowledge.