Development of Models, Methods, and Algorithms for An Auto-Mated Rating System in Professional Education

This study aims to develop tools for constructing an automated rating system to objectively assess vocational education quality in the Kyrgyz Republic. It led to the creation of a conceptual model for an automated rating system, identification of key evaluation criteria, and development of a framework for component interaction. Methods for automated data collection were developed, including database integration via a software interface, electronic questionnaires, and web scraping. Processes for data cleaning, normalisation, and weighting were established to prepare information for analysis. Algorithms were implemented to integrate quantitative and qualitative indicators in assessing educational institutions' performance. The conceptual model reflects the specific features of vocational education and the regional environment. Key methods include data cleaning, normalisation, assigning weights to criteria, and analysing institutional effectiveness. Algorithms for automated data collection via software interfaces and web scraping ensure access to up-to-date information from educational portals. Prohierarchycessing algorithms, such as data cleaning and normalisation, ensure high-quality data preparation. Quality assessment algorithms, based on hierar-chy analysis and efficiency evaluation methods, objectively incorporate qualitative and quantitative indicators like teaching quality, student performance, scientific publications, and material resources.