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

Authors

  • Bibigul Koshoeva

    Department of Automatic Control, I. Razzakov Kyrgyz State Technical University, Bishkek, Kyrgyz Republic

  • Bekzhan Torobekov

    Department of Organization of Transportation and Transport Management, I. Razzakov Kyrgyz State Technical University, Bishkek, Kyrgyz Republic

  • Asel Abdyldaeva

    Digital Innovation Academy, Bishkek, Kyrgyz Republic

  • Rima Osmonova

    Department of Information Systems in Economics, I. Razzakov Kyrgyz State Technical University, Bishkek, Kyrgyz Republic

  • Nurlanbek Tashpolotov

    School of Information Technology, Washington University of Science and Technology, Alexandria, USA

How to Cite

Koshoeva, B., Torobekov, B. ., Abdyldaeva, A. ., Osmonova, R. ., & Tashpolotov, N. . (2025). Development of Models, Methods, and Algorithms for An Auto-Mated Rating System in Professional Education. International Journal of Basic and Applied Sciences, 14(SI-3), 20-33. https://doi.org/10.14419/83h3xh17

Received date: May 8, 2025

Accepted date: July 2, 2025

Published date: August 15, 2025

DOI:

https://doi.org/10.14419/83h3xh17

Keywords:

Assessment Efficiency; Data Analysis; Indicator Normalisation; Information Processing; Quality of Education

Abstract

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.

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How to Cite

Koshoeva, B., Torobekov, B. ., Abdyldaeva, A. ., Osmonova, R. ., & Tashpolotov, N. . (2025). Development of Models, Methods, and Algorithms for An Auto-Mated Rating System in Professional Education. International Journal of Basic and Applied Sciences, 14(SI-3), 20-33. https://doi.org/10.14419/83h3xh17

Received date: May 8, 2025

Accepted date: July 2, 2025

Published date: August 15, 2025