A Holistic Approach to Academic Advising Through Fuzzy Logic, Semantic Web Technologies, and Expert Reasoning in Engineering Education

Higher Education Institutions (HEIs) face increasing demands for efficient, scalable, and personalized academic advising solutions. Traditional advising methods, often resource-intensive and inconsistent, struggle to accommodate diverse student needs. This paper introduces EDUC8EU, a knowledge-driven AI-powered academic advising system, leveraging a fuzzy expert system to provide adaptive and context-aware recommendations. The system integrates expert systems, fuzzy logic, and semantic web technologies to provide dynamic, personalized recommendations that align with students' academic interests, skill sets, and career aspirations. By leveraging external validated sources such as ESCO and O*NET, EDUC8EU performs real-time analysis to ensure alignment between academic pathways and industry requirements. Built on a modular, scalable architecture, EDUC8EU enables continuous adaptation through a selfevolving feedback loop, dynamically refining recommendations based on user interactions and emerging labor market trends. The system is grounded in well-established educational principles, incorporating methodologies that emphasize career alignment, personality-based reasoning, and self-exploration. An empirical evaluation within an engineering education setting demonstrated high levels of student satisfaction, increased decision-making confidence, and enhanced career alignment. This research contributes to the growing field of AI-powered academic advising, demonstrating its potential to support students in making well-informed, career-aligned decisions.