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Quantitative methods for assessing the level of competence for quality management systems of education

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Authors


Doctor of Physical and Mathematical Sciences, Professor, Head of Department of Applied Mathematics and Computer Science
Russia, Saratov Institute of Social and Economic RG Plekhanov
[email protected]


PhD, Associate Professor of Applied Mathematics and Informatics
Russia, Saratov Social and Economic Institute REU them. Plekhanov
[email protected]


PhD student, Department of Applied Mathematics and Computer Science
Russia, Saratov Social and Economic Institute REU them. Plekhanov
[email protected]

Abstract

The paper studies the process of assessing the quality of education in higher education. The concept of educational quality which is considered from the point of view of all interested parties in the form of indicators sets and which structure included the additional indicators connected with an external assessment from employers, graduates and all society. The Rasch model for educational quality assessment is modernized by introduction of the additional parameters characterizing tests non-standard and their practical importance. That allowed using model for forecasting of probability of manifestation of separate components of competence. The author shows aggregate indicators to measure the level of aggregate formed competencies. The results can be used to assess the quality of the educational process in the transition to the new educational standards. Assessed error of actual measurements. The results can be used in the Quality Management System of Education on going to new educational standards.

Keywords

educational process, competence, assessment of the quality of education, quality management system of education

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This work was supported by RFBR grant 14-06-00339.

Suggested citation

Gusjatnikov Viktor Nikolaevich , Bezrukov Aleksej Iosifovich , Kajukova Inna Viktorovna
Quantitative methods for assessing the level of competence for quality management systems of education// Modern Management Technology. ISSN 2226-9339. – #3 (51). Art. # 5105. Date issued: . Available at: https://sovman.ru/en/article/5105/

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