Implementation of Business Intelligence Technologies of Course Learning Outcomes based on Multidimensional Model Approaches

Abstract

Business Intelligence (BI) technologies offer intuitive insights and advanced analytical capabilities by transforming raw data from integrated sources into actionable knowledge. In the context of higher education, where institutions face heightened competition, dwindling public funding, and increased accountability, BI serves as a pivotal tool for data-driven decision-making. This paper addresses the problem of optimizing Course Learning Outcomes (CLOs) by implementing BI technologies. Our objectives are to integrate CLO data into a multidimensional model, apply BI tools for CLO analysis, and evaluate how BI can enhance CLO performance in higher education institutions (HEIs). We propose the Intelligence Course Learning Outcomes Platform (ICLOP) as a solution, utilizing BI technologies to generate efficient student data and performance metrics. The case study involving students from Universiti Sultan Zainal Abidin (UniSZA), Malaysia, demonstrates that BI can significantly improve enrolment management, resource allocation, and student success. The findings conclude that BI tools provide an effective means to enhance CLOs, offering a robust framework for improving educational outcomes and institutional efficiency, highlighting the transformative potential of BI in the academic sector.