Designing A Unified Student Information and Learning Analytics System for Omani Higher Education

This study proposes a conceptual framework for designing a Unified Student Information and Learning Analytics System (SIS-LA) tailored for higher education institutions in Oman. The framework addresses the current fragmentation of academic, administrative, and learning systems that limit data sharing and hinder institutional efficiency. By integrating these components into a single interoperable platform, the SIS-LA supports data-driven decision-making, personalized learning, and effective academic planning. The system design applies System Analysis and Design (SAD) and Database Management System (DBMS) methodologies to ensure robust data management and interoperability. It incorporates artificial intelligence, ontology-based data modeling, and standardized application programming interfaces (APIs) to enable real-time reporting, predictive analytics, and early identification of at-risk students. Ethical data governance and compliance with Oman’s Personal Data Protection Law are central to the framework, ensuring privacy and cultural alignment. The proposed model is benchmarked against international learning analytics frameworks to assess adaptability to Oman’s educational and regulatory context. Findings suggest that the unified, ontology-driven approach enhances institutional adaptability, strengthens data governance, and supports Oman’s digital transformation goals. The SIS-LA framework provides a foundation for future implementation and contributes to achieving the objectives of Oman Vision 2040 in advancing higher education innovation.

Student Information System Learning Analytics Artificial Intelligence in Education Higher Education in Oman Data Integration

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