Monitoring Educational Quality through Digital Analytics: An Innovative Approach in the Azerbaijani Education System

Abstract

In the contemporary educational landscape, improving mechanisms for monitoring educational quality remains a key priority, and digital analytics offers significant opportunities to accelerate this process through data-driven decision-making. This article provides a comprehensive analysis of the application of digital analytics technologies in monitoring educational quality and examines their innovative potential. By leveraging large-scale data, digital analytics enables the real-time collection, processing, and visualization of information, allowing educational institutions to assess student achievement, teacher performance, and the overall effectiveness of the teaching–learning process in a more objective, systematic, and timely manner.

The primary aim of the article is to analyze the current state of educational quality monitoring and evaluation through digital analytics within the Azerbaijani education system, to propose innovative implementation models, and to identify the advantages of this approach in comparison with traditional monitoring methods. The study also explores the use of real-time data processing, the tracking of individualized learning trajectories, and the role of data-driven decision-making in shaping educational policy.

The scientific and practical significance of the research lies in its contribution to the integration of innovative analytical practices into the national education strategy, providing a solid theoretical and methodological foundation for future applications. The proposed conceptual framework supports the transition of the Azerbaijani education system toward a more flexible, transparent, and data-driven governance model, while enhancing institutional effectiveness and accountability. Methodologically, the study adopts a mixed-methods approach, combining quantitative and qualitative techniques, including statistical data analysis, content analysis, and expert interviews.

The findings indicate that digital analytics creates new opportunities for strengthening data-driven decision-making in education, designing personalized learning trajectories, and continuously improving educational quality. Moreover, this approach facilitates the early identification of learning gaps and disparities in academic achievement, thereby enhancing quality assurance mechanisms and enabling timely intervention.