Document Details

Document Type : Thesis 
Document Title :
Extracting and Investing Knowledge in Academic Student Counseling Processes: Developing an Expert System at King AbdulAziz University
استخلاص واستثمار المعرفة في عمليات الإرشاد الطلابي الأكاديمي: تطوير نظام خبير في جامعة الملك عبد العزيز
 
Subject : Faculty of Arts and Humanities 
Document Language : Arabic 
Abstract : Expert systems techniques work on consulting and contributing to decision-making at all times and places by programming / extracting knowledge and including it in the system. This research aims to improve academic advising at King Abdulaziz University by exploring the role of knowledge extraction in expert systems and developing tool support, which the researcher refers to as ( (Murshede). The proposed expert system offers guidance based on the expertise and experience of subject matter experts and specialists in order to populate a knowledge base and reap the benefits of machine learning techniques. The study also examined the foundations and phases of expert system development in educational institutions. The research was conducted at the College of Computing and Information Technology at King Abdulaziz University in Jeddah, and the system was designed using the Waterfall Model. This easy-to-implement methodology serves both technical and non-technical beneficiaries and is simple to manage and monitor. The proposed expert system was presented to an expert focus group as one of the study's information-gathering methods. Several advisory services were discussed, including intelligent placement for students in the preparatory year, elective courses via intelligent counseling registration, and a smart chatbot program for auto-responding to inquiries in the context of academic advising. Then, using the usability test methodology, the system was evaluated by a sample of students from the male and female campuses. Also, a sample of academic advisors from the male and female campuses evaluated the system using the expert review methodology. The study revealed that the sample's satisfaction with the expert system was (94.9%) among students and (96.5%) among academic advisors. Among the main results were: (1) the validity of the knowledge base contributes to the success of expert systems and the ability to make decisions based on their recommendations; (2) extraction of specialized tacit knowledge contributes significantly to the success of expert systems. Experts contribute to the advancement of any field, mainly if they are employed and benefit from expert system techniques that simulate human thought when making recommendations. According to the academic advisors, the proposed system also reduces the burden. It saves time and effort in academic advising, with (100%) approval rate among the sample population. Among the study's recommendations is adopting a proposal for an expert system that would enhance academic advising at the university and with external parties. Keywords: Academic Advising, Academic counseling, Expert Systems, Knowledge Extraction, Chatbot, Machine Learning 
Supervisor : Prof. Faten Saeed Ba-Mufleh 
Thesis Type : Doctorate Thesis 
Publishing Year : 1445 AH
2023 AD 
Added Date : Tuesday, November 28, 2023 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
شهد أحمد عبد الغفارAbdulgaffar, Shahad AhmedResearcherDoctorate 

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 49562.pdf pdf 

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