Knowledgebase Ontology Driven Model for Student Development Through Swot Analysis

Abstract

Traditional educational systems often rely on rigid, siloed databases that do not capture the multifaceted nature of student development. This limits the ability of institutions to provide personalized support and informed guidance. To address this challenge, this paper proposes a knowledge-based, ontology-driven framework for the holistic development of students. The model integrates diverse dimensions—including academic performance, personal background, extracurricular involvement, cultural context, behavioral patterns, and SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis—into a unified semantic structure. By leveraging technologies such as RDF, OWL, and SPARQL, the system constructs a dynamic knowledge graph that enables intelligent querying, semantic reasoning, and real-time data analysis. The inclusion of SWOT data enhances the ability to uncover latent potential and identify areas for targeted intervention. Unlike conventional systems, this approach supports context-aware decision-making and adaptive learning strategies. Experimental results demonstrate the effectiveness in identifying critical patterns—such as the relationship between financial status and academic performance, behavioral insights, and self-directed learning tendencies—ultimately promoting more effective educational planning and student development.