Document Details

Document Type : Thesis 
Document Title :
LINKED-DATA FRAMEWORK FOR MUTUALLY ENRICHING TRADITIONAL AND OPEN EDUCATION BASED ON LABOR S COMPETENCIES
إطار البيانات المترابطة للإثراء المتبادل بين التعليم التقليدي و المفتوح بناء على مهارات العمل
 
Subject : Faculty of Computing and Information Technology 
Document Language : Arabic 
Abstract : Education highly appreciates values such as shareability, openness, reusability, and interoperability due to their profound impact on education's evolution. However, most educational organizations suffer from a lack of interoperability and from the heterogeneity within their internal schemas and with the external education organizations and movements. This hinders mutual benefits among educational organizations’ resources. One of such significant benefits is making mutual enrichment between the formal education organizations’ resources and open educational movements such as Open Courseware (OCW), Massive Open Online Courses (MOOCs), and Open Education Resources (OER). These benefits could lead to an important leap in education's evolution. For example, OCW, MOOCs, and OER support lifelong learning and give the chance to learn from the industry leaders, which provides a vital role to support renewed educational paradigms such as the competency-based education (CBE). Indeed, there is a favorable matching between education aspirations and LD (LD) abilities. Therefore, we investigated the potentials of LD to link formal education courses, open education courses, and competencies of labor to go toward CBE. Accordingly, traditional universities can take advantage of LD to design/refine their courses to be more oriented toward CBE and to be supported by open education materials. Based on that, this thesis provided a LD framework to enable making mutual enrichment between traditional and open courses based on the labor’s competencies. The framework provided an architecture that offers an outline for the educational organizations to produce their data as LD including the open educational resources, therefore gaining the main features of LD. Consequently, an innovative approach is provided that represents LD wrapper surrounding courses’ information. The approach offers sets of competencies lists that can be used as candidates for the courses’ topics. Accordingly, the CBC Model (Competency-Based Course Model) is developed to enable building competency-based courses according to the CBE courses’ fundamentals. The CBC Model made bridging with the open educational repositories to offer the required materials and bridging with the competencies of labor knowledge-base to enable accessing the real-world competencies. The EBL tool (Explorer-Builder-Linker tool) was built based on an algorithm that we created to offer multiple exploring and linking procedures beside a builder established based on the CBC Model attributes. The EBL tool proved the interoperability of the proposed framework by presenting the abilities of accessing and exploring both the materials and competencies from multiple sources and including them under common, clear, and well-documented concepts by using the CBC Model. The tool also showed the ability of reaching the deepest level of the competencies related to occupations’ knowledge and the related materials and their related courses. Finally, useful measures that give interesting indicators for the course designers are created based on the proposed framework components. The CBC Model was evaluated by several approaches to meet several dimensions. All dimensions were met by more than one approach or at least one approach, which boosts the trustworthiness of the model. Hence, the overall results showed that LD played a vital role in achieving the framework objectives in serving the education and particularly the CBE. 
Supervisor : Prof. Omaimah Bamasag 
Thesis Type : Doctorate Thesis 
Publishing Year : 1441 AH
2019 AD
 
Co-Supervisor : Prof. Maher Khemakhem 
Added Date : Wednesday, December 4, 2019 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
صفية محمد نحاسNahhas, Safieh MohammedResearcherDoctorate 

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