To assess and continuously improve the quality of education, the university has implemented a centralized information management system. Through this system, all key indicators of the educational process are regularly collected and analyzed. The collected data include:
Student statistics: the number of admitted, enrolled, and graduated students, as well as dropout rates;
Faculty profile: data on academic degrees and titles, professional development activities, and age distribution;
Learning outcomes: average grades by course, credit accumulation indicators, and examination results;
Student satisfaction level: results and analysis of end-of-semester surveys;
Graduate monitoring: employment status, employer feedback, and the level of graduates’ professional relevance.
This data collection system supports evidence-based decision-making in managing the educational process, improving academic programs, and enhancing quality assurance.
The data collected at the university are processed using statistical and qualitative analysis methods and are applied to improve the educational process and increase management effectiveness. The results of these analyses are used in the following areas:
Updating academic programs: making decisions to revise and adapt curricula based on labor market demands and student performance indicators;
Optimizing student support services: improving the effectiveness of academic, psychological, financial, and career guidance services;
Faculty professional development planning: organizing professional development courses and optimizing teaching workloads;
Strategic development planning: developing and updating the university’s annual and five-year strategic development plans.
The analysis results are presented annually in the form of reports to faculty councils and the university council. This process ensures transparency and strengthens an evidence-based approach to decision-making.
At the university, processes of data collection, processing, and storage are carried out using modern technologies and specialized platforms. Data are generated through the following main tools:
Higher education management information system: centralized storage and management of core personal, academic, and administrative data on students and faculty;
Learning Management System (LMS): online monitoring of the teaching and learning process by course, recording assignments and test results, and analyzing student activity;
Electronic survey platforms: regular collection of feedback from students, graduates, and employers and inclusion of this data in qualitative analysis;
Electronic library databases: monitoring research activities, publications, and bibliographic indicators.
These technologies enable accurate, timely, and systematic data collection and support effective monitoring of educational quality.
At the university, relevant analyzed data are shared with stakeholders in a transparent and systematic manner. This process is carried out in strict compliance with the principles of openness, as well as requirements for confidentiality and personal data protection.
Internal stakeholders: students, faculty members, and university leadership receive information through the university intranet, email notifications, and regular meetings;
External stakeholders: accreditation agencies, partner universities, and employers are provided with information through official reports, the university website, statistical booklets, and press releases;
Ensuring confidentiality: all processes strictly comply with current legislation on personal data protection and the university’s internal regulations.
This mechanism ensures transparency of university activities, strengthens effective cooperation with stakeholders, and enhances the reliability of educational quality monitoring.
The university’s information management system is regularly updated in line with modern requirements and user needs. This process aims to improve system efficiency and further enhance the quality of education.
Implementation of KPIs: developing and monitoring key performance indicators (KPIs) of the university based on collected data;
User training: organizing regular training sessions and workshops for faculty members, staff, and students on the effective use of information systems.
This approach ensures the relevance of the information management system, improves quality monitoring processes, and supports strategic management with accurate and reliable data.
