Open AccessModern technology for evaluating measures to optimize and improve the working of teacher and staff
Author(s) -
Светлана Веретехина,
S V Krapivka,
Olga L. Mnatsakanyan,
Olga Kireeva,
E. Yu. Romanova,
I Iu Galin,
Svetlana Pivneva
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1691/1/012197
Subject(s) - reputation , computer science , working time , performance indicator , markov chain , isolation (microbiology) , christian ministry , generalization , operations research , econometrics , industrial engineering , risk analysis (engineering) , management science , engineering , mathematics , work (physics) , machine learning , business , marketing , mechanical engineering , mathematical analysis , social science , microbiology and biotechnology , sociology , biology , philosophy , theology
The study was conducted using a natural science approach to assessing the working conditions of teachers and staff. Applied methods: system analysis, mathematical modeling, logical generalization of statistical data of a sociological survey. The introduction describes changes in the regulatory framework of the Ministry of labor of Russia. The requirements for the working conditions of the teaching staff during the period of self-isolation COVID-19 are described. Modern technology for evaluating measures to optimize and improve the working conditions of teachers and staff offers new calculation coefficients of criteria and indicators for evaluating the effectiveness of measures to optimize and improve working conditions. The effectiveness of measures is proposed to be evaluated by four groups of indicators: physical, social, economic, and reputational (reputation). For the resulting analysis of the effectiveness of measures, it is proposed to apply a "Generalized criterion". The generalized efficiency criterion is proposed to be calculated as a generalized Harrington desirability function. It is proposed to use regression methods, expert evaluation methods, and Bayesian methods to predict the effectiveness of the assessment. The simulation is performed using the Monte Carlo method, using Markov chains. The identified modern trends in achieving the University’s target indicators and indicators are described. Technologies that reduce time, labor, financial, and material costs are described. Overall satisfaction with the working conditions of teachers and staff was revealed. Modeling and forecasting were performed. New trends in achieving the University’s target indicators and indicators are identified and described. Ways to automate processes are suggested. A new motivational approach is described, which forms a new General vector of the University’s orientation. The practical significance of the research results is proved. In conclusion, the results of a sociological survey of teachers on satisfaction with working conditions are promised. The directions of development of the University that increase satisfaction with the working conditions of teachers and staff are identified.