Alexandria Engineering Journal (Mar 2025)
Increasing the degree of acceptability for chatbots in technical support systems for educational sector by using ML and semantic web
Abstract
Work on digital transformation is one of the main features of the fourth economic revolution, which tends to benefit from technology in various aspects of life. The Machine Learning (ML), Semantic Learning (SL), and Deep learning (DL) and dealing with robots are the most prominent features and widespread aspects. This study focuses on taking advantage of Chatbot through SL to provide a wide-knowledge and multi-tasking communication environment by using chat-applications to find typical answers commensurate with customers' questions and reach with them to detail and appropriate answer stage, as well as providing various types of files such as audio, images, video, and documents. After the spread of the Corona pandemic and the transition of education from face-to-face to distance education approach, a number of algorithms were developed that deal with the method of Chatbot to answer the cognitive required aspects to assist the instructors and students what are the necessary features to maximize benefit from the distance education style. Thus, the shifting to digital educational approach represented a major challenge, especially in communities that depend their groups on physical education and their schools do not have any infrastructure for distance education. Therefore, these groups need more technical support to clearly and quickly understand how they can use technology. The experience of King Abdulaziz University (KAU) offers multiple solutions to support instructors and students to fill the shortage of transformation and take advantage of Chatbot to increase the opportunity for ML and SL to develop the technical support operations in professional manner. The number of KAU members is 100,000 users who should be helped and develop through Chatbot solution based to understating the main concept from the clients and providing supporting materials including documents, images, audio and video files to beneficiaries from various sources and supporting databases before reaching the human technical team, that has a good effect on participants and learning services. This study presents the infrastructure and algorithms implemented in Chatbot services, and what are the implications for the emergence of the service.
