Implementing Continuous Quality Improvement (CQI) in Online Education: Leveraging Learning Analytics and Stakeholder Satisfaction Data

Ghazali, Al
Ali, Moh
Rusydi, Ibnu
Safrul , Safrul
Husein Prawironegoro, Alwy
Najmi Aulia, Neila

Jurnal Manajemen Pendidikan Islam
Vol. 11 No. 1 (2026): Transformative Islamic education management

The rapid expansion of online education necessitates robust Continuous Quality Improvement (CQI) frameworks that integrate both objective learning analytics and subjective stakeholder feedback. This study investigates the implementation of CQI in online education by examining the predictive role of learning analytics indicators engagement frequency, course completion rate, and assessment performance on student satisfaction, while incorporating stakeholder feedback as a complementary dimension. A quantitative correlational design was employed with 145 participants (120 students, 25 instructors) from a higher education institution in Indonesia. Learning analytics data were extracted from the Learning Management System, and satisfaction was measured using a validated questionnaire. Multiple regression analysis revealed that course completion rate was the strongest predictor of satisfaction (β = 0.41, p < 0.01), followed by engagement frequency (β = 0.34, p < 0.01) and assessment performance (β = 0.22, p < 0.05). The model explained 64% of the variance in satisfaction (R² = 0.64). These findings underscore the importance of integrating behavioral, performance-based, and perceptual data to strengthen CQI frameworks. The study contributes to bridging the gap between objective system-generated data and subjective stakeholder feedback, demonstrating how their integration can provide a comprehensive framework for quality enhancement. By confirming that satisfaction is influenced not only by academic achievement but also by behavioral engagement and persistence, the study highlights the need for multidimensional monitoring in online education. The results provide strong empirical evidence that institutions should adopt data-driven continuous improvement strategies incorporating both analytics and satisfaction measures. This integration supports early identification of learning challenges and enhances institutional capacity to refine instructional design, improve learner support, and ultimately strengthen the quality of online education.