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

Hu, B, Gaurav, A, Choi, C and Almomani, A (2022) Evaluation and Comparative Analysis of Semantic Web-Based Strategies for Enhancing Educational System Development. International Journal on Semantic Web and Information Systems, 18 (1). pp. 1-14. ISSN 1552-6283

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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 and the system. As a consequence, we may say that 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, we 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.

Affiliation: Skyline University College
SUC Author(s): Almomani, A ORCID: https://orcid.org/0000-0002-8808-6114
All Author(s): Hu, B, Gaurav, A, Choi, C and Almomani, A
Item Type: Article
Uncontrolled Keywords: Artificial Intelligence, Big Data, E-Learning, Machine Learning, Ontology
Subjects: B Information Technology > BM Artificial Intelligence
Divisions: Skyline University College > School of IT
Depositing User: Mr Veeramani Rasu
Date Deposited: 25 May 2022 12:47
Last Modified: 25 May 2022 12:47
URI: https://research.skylineuniversity.ac.ae/id/eprint/233
Publisher URL: https://doi.org/10.4018/IJSWIS.302895
Publisher OA policy: https://v2.sherpa.ac.uk/id/publication/17961
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