Modelling business intelligence technologies framework for analyzing academic performance from learning management systems (LMS)

Abstract

Background: Learning analytics (LA) has been utilized to measure, collect, analyze, and report data regarding learners and their contexts, with the aim of understanding and optimizing the learning process. However, most universities having difficulties in identifying students’ academic performance and weaknesses in each subject throughout every semester. Methods: Therefore, to address this issue effectively, the integration of result in learning management systems (LMS) with business intelligence (BI) has been proposed. In this case study, power BI tools are used in Universiti Sultan Zainal Abidin (UniSZA) LMS platform known as knowledge and eLearning integrated platform (KeLIP) to analyze student performance. The three-layer business intelligence framework is applied, data source layer, data analytics layer and presentation layer. Results: The successful implementation of the integrated LA system with business intelligence tools yielded valuable insights into students’ academic performance, facilitating informed decision-making within the academic environment. Conclusions: In conclusion, this system will assist lecturers in guiding learners’ academic progress and provide them with da-ta-driven insights into their students’ performance each semester, enabling learners to enhance their academic achievements as well as their involvement in co-curricular activities. Furthermore, the integration of LA will contribute to optimizing the learning system, teaching methods, and educational management in this new era of education.