Intelligent Blockchain for Managing Micro-credentials (IBMM)

Abstract

Recently, blockchain technology or distributed ledger technology (DLT) has been used in a wide range of fields as a way to preserve records and information in a distributed and trusted manner. Blockchain technology has revolutionized higher education, particularly in the area of micro-credentials. The incorporation of micro-credentials in higher education has the potential to change traditional education and learning process. A number of micro-credentials can be accumulated for credit toward a specific academic degree. Validating micro-credentials is a time-consuming and cumbersome process, but blockchain technology enables students’ micro-credentials to be validated easily and quickly. The immutability, decentralization, security, and transparency of blockchain technology make it a suitable technology for addressing the significant challenges associated with micro-credential provenance and data sharing in a secure manner. Several existing micro-credential platforms that use blockchain technology to efficiently and securely manage students’ micro-credentials and academic accomplishments have been discussed in the literature. However, none of these existing platforms offer a comprehensive solution that can securely store, manage, and share micro-credentials with stakeholders in a privacy-preserving manner, nor are they able to provide personalized recommendations on students’ majors and action plans. In this thesis, we propose an intelligent blockchain for managing micro-credentials (IBMM) framework as a holistic platform for higher education students to manage their micro-credentials. A systematic literature review (SLR) was carried out to identify the shortcomings of the existing scientific studies in the micro-credential management area and to identify the research questions and solutions. By employing the SLR process, 15 relevant studies were identified and systematically reviewed which highlighted a number of research gaps. None of the existing studies propose a method that ensures the anonymity of students’ identities on the blockchain when exchanging micro-credentials. Moreover, no intelligent techniques are used to recommend suitable majors for students and assist them in selecting the best action plan. This thesis examines the use of privacy-preserving and AI methods to address these research gaps. Blockchain and AI techniques are integrated into the IBMM framework to undertake the following tasks: • verify and store micro-credentials on the blockchain ledger to ensure the immutability and security of data. • preserve the privacy of students’ identities while sharing their micro-credentials with HEIs. • recommend the most appropriate academic majors for students based on their micro-credentials. • choose the most optimal action plan for students from multiple options based on several criteria. In this thesis, research questions and objectives are identified, and an end-to-end solution is proposed to address the research issues.