<![CDATA[This study examines data-driven and artificial intelligence (AI)–based learning management as a strategic approach to supporting Outcome-Based Education (OBE) in higher education. The main problem addressed is the limited ability of conventional learning management practices to systematically monitor, evaluate, and improve student learning outcomes in alignment with OBE principles. The purpose of this research is to analyze how the integration of data analytics and AI can enhance planning, implementation, monitoring, and evaluation of learning processes to ensure the achievement of intended learning outcomes. This study employs a qualitative descriptive approach through literature review and analysis of relevant models and practices of data-driven learning management and AI applications in higher education. The findings indicate that data-driven learning management supported by AI enables more accurate measurement of student performance, personalized learning pathways, early identification of learning difficulties, and evidence-based decision-making for continuous improvement. Furthermore, AI-based systems contribute to adaptive feedback, predictive analytics, and automated assessment, which strengthen the alignment between learning activities, assessment, and expected outcomes. The study concludes that the adoption of data-driven and AI-enabled learning management plays a significant role in reinforcing the effectiveness and sustainability of Outcome-Based Education in higher education institutions.]]>
Copyrights © 2026
