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 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.

Integration and Open Access System Based on Semantic Technologies

“…On the other hand, and taking into account that the university has the dual responsibility of teaching and research, as already mentioned, another line of research and improvement would be that the system designed could also contribute to the more academic facet. An analysis of the contribution of the semantic web to educational systems is shown in (Hu, 2022). The paper shows different examples of how the semantic web helps educational systems to respond to the needs of their users.…”

A Novel Cuckoo Search-Based Optimized Deep CNN Model for Phishing Attack Detection in IoT Environment

“…A Dropout layer (1-10) is included to randomly deactivate certain neurons during training to avoid overfitting and improve the model's generalisation. The two classes (like "Nor-mal" and "Phishing") are represented by the two output units in the last fully linked layer, Linear (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11). It features 258 customizable settings.…”

“…Technological advancements have driven application products towards intelligence, convenience, low power consumption, large connectivity, and wide coverage [1,4,5]. Additionally, there has been a focus on improving IoT intrusion detection systems (IDS) using artificial intelligence (AI) techniques, particularly machine learning (ML) algorithms [6,7,8]. Researchers have reviewed and compared various ML algorithms and techniques using different datasets to en-hance the efficiency of IoT IDSs [6,9,10].…”

An Open-Ended Web Knowledge Retrieval Framework for the Household Domain With Explanation and Learning Through Argumentation

“…It is a very interesting method to allow an individual (i.e., machine or human) to learn new knowledge, because it resembles a commonsense reasoning procedure which is closer to the human way of thinking. This method is applied in schools (Berland & McNeill, 2010;Von Aufschnaiter et al, 2008;Pratiwi et al, 2019;Akhdinirwanto et al, 2020;Hu et al, 2022;Fiorini, 2020), to allow students to argue and learn through argumentation by accepting other students' arguments, if they cannot defend their position. In most cases the need of a supervisor, a teacher in most cases, which will check the rationality of arguments is mandatory.…”