EDUC8EU: A Transformative Hybrid Academic Advising Approach with Intelligent Microservices, Fuzzy Logic and Semantic Web Technologies

Abstract

Students navigating Higher Education Institutions (HEIs) encounter complex decisions and procedures. HEIs are increasingly turning to online academic advising systems to enhance services, reduce costs, and streamline processes. This paper introduces EDUC8EU, an innovative hybrid software infrastructure empowered by microservices architecture, leveraging Artificial Intelligence (AI), fuzzy reasoning, and ontological tools to provide reliable recommendations for students' subsequent learning steps. The system employs fuzzy logic to determine students' interest level for a specific academic choice, semantic web technologies to model the knowledge and experience of academic advisors, and incorporates matching mechanisms with external validated sources to perform skill gap analysis and gain insights into other crucial factors such as prerequisites, required knowledge, and essential abilities. As students progress through their academic journey, the proposed system dynamically adapts, continuously updating its knowledge base through a self-evolving feedback process within the microservices architecture. The integration of foundational principles, encompassing the alignment of individual preferences, personality traits, and the encouragement of self-exploration, forms the conceptual backbone of the hybrid infrastructure. The paper provides in-depth insights into the modeling artifacts of the proposed approach and delineates the architecture of the implemented prototype system, highlighting its various components and functionalities.