A New Ontology-Based Recommender System for Academic Guidance in Paramedical Studies

Abstract

This paper presents NurSHT-RS (Nursing Sciences and Health Techniques-Recommender System). The purpose is to help students choose study options within the paramedical education sector in Morocco. Recognizing the challenges students face due to insufficient knowledge about study specialties and the reliance on subjective advice, NurSHT-RS aims to address the risks of uninformed career decisions. The system leverages machine learning (ML) and ontology techniques to personalize recommendations based on students’ academic profiles, demographic data, and physical conditions, including disabilities. The system also incorporates NSHTOri-Onto (Nursing Sciences and Health Techniques Orientation-Ontology), a comprehensive ontology that semantically represents student profiles, paramedical specialties, and training institutions. This ontology not only supports accurate recommendations but also provides reusable and extensible knowledge frameworks for similar applications. NurSHT-RS stands out by offering students detailed and up-to-date information, including study modules, admission criteria, and career opportunities, to ensure informed decision-making. In addition, it could be used by educational advisors, Moroccan students, or foreign students wishing to continue their studies in Morocco.