Analysis of Economic Motives in the Individual Choice of Educational Paths

The authors consider the economic motivations when individuals choose an educational path. This line of research is relevant from both, the point of view of science — research of economic behavior of an individual, and the point of view of practice — allows to increase efficiency of investments in a human capital. The authors have developed the economic and mathematical model of choice of optimum educational paths by individuals. The model is realized in the software and approved on real data on more than 5,5 thousand students. For the analysis of the importance of rational economic expectations when an educational path has to be chosen, the paths chosen by students is compared and the educational paths optimum from the point of view of economic rationality are calculated. The analysis of the results has showed that mainly, the choice of educational paths happens according to the economic motivations. On the considered selection, 66 % of prospective students have chosen an optimum path from the point of view of economic preferences. The most significant factor providing development of optimum educational paths is an expectation of higher income upon completion of education — 22 % of all educational paths, and a possibility of cost-cutting of educating or state-subsidized education — 12 %. In our opinion, one of the most important practical results of the research of optimum educational path is the need to consider expectations of students and prospective student when developing a state policy of investment in human capital

Приветствие от Уральского федерального университета

Original manuscript received April 13, 2020.Revised manuscript accepted June 13, 2020

Миграционные тренды российских ученых: региональный аспект

The quality of human capital is of key significance for the technological and economic development as a factor of competition for highly qualified personnel. Previously, the migration of scholars was described as a “brain drain”, but due to globalization and the development of communication tools, its characteristics expanded. Nowadays, additional relevant terms “brain circulation”, “brain exchange”, and “brain sharing” have appeared. Bibliometric analysis in this paper relies on the Scopus database to estimate the migration of scholars affiliated to the Ural Federal University. We present our algorithm for generating scientometric data. The research findings show that, in general, the regional tendencies follow, with some time lag, the Russian average, as well as the global trends of transition from the “brain drain” to the cooperative work. We identified similarities between the list of host countries and countries for cooperation. The key difference is that the region trend is featured by more positive figures in terms of “brain drain” than Russia on average. Practical significance of our paper refers to the application of generation algorithm as an independent tool for collecting scientometric data. The results of the study can be used by the public authorities when implementing socio-economic policy. © 2021, Terra Economicus. All Rights Reserved.Acknowledgment: The study is supported by the Russian Science Foundation, project № 19-78-00080

Modeling the Choice of an Optimal Educational Trajectory in the Conditions of Digital Transformation of the Economy

The processes of transformation of the modern economy taking place in recent decades encourage researchers to determine the place of higher education in general and of sets of educational programs in particular, in the new conditions of the educational services market. In the context of significant changes in the processes of market structures interaction, employers are forced to impose new requirements on university graduates, whose qualifications should be relevant to the current market. Since the university in this case is an intermediary between enterprises and skilled labor, its goal is to solve the shortage of personnel with a level of training that meets the new objectives of employers in the regional labor market. In these conditions, optimizing recruitment of students for the areas necessary for the market becomes relevant. To solve these problems, the following tools can be used: identifying value orientations and incentives for applicants in the process of choosing bachelor's degree programs, and admission of master's degree applicants who have shown an inclination for professional activity related to their undergraduate degree field. Thus, there is a need to study the applicants' educational trajectories in relation to their economic incentives, such as the amount of expected income after graduation. The method of this study combines an agent-based model with econometric modeling to determine the maximum expected salary after graduation. The first stage of modeling involves the use of an econometric model to adapt students' educational trajectories to their preferences. At the second stage of modeling, an agent-based model is used, which allows determining the behavior of students within the overall sample. To determine the probability of a student changing their educational trajectory, a fuzzy logical model was developed. Copyright © 2022 The Authors.Russian Science Foundation, RSF, (22-28-01010)The research work of Tarasyev A.A. is supported by a grant from the Russian Science Foundation, scientific research project No. 22-28-01010 “People’s Savings as a Basis for Safe Socio-Economic Development of Russian Regions: Analysis, Forecast and System of Measures for Localization and Neutralization of Threats”

Приоритеты в современной организации университетской науки в свете теории принципала-агента

The article focuses on the current state of the balance of interests in the field of organizing research activities in Russian universities. The theoretical framework of the research is the theory of the principal-agent, from the position of which the research management system is considered through the relationship between actors who have different degrees of awareness and potentially act in different interests. The purpose of the study is to compare the problems in the field of organizing funding, digitalization and scientific cooperation, which were the most important for agents, with those strategic decisions that took place at the level of the principal after extensive expert discussions. The following sources were used: 1) the results of the largest expert project implemented at the initiative of the Ministry of Science and Higher Education of the Russian Federation; 2) the results of a sociological study conducted at the Ural Federal University, where scientists and employees involved in the organization of scientific research were interviewed. A limitation of the study was the difficulty of comparing the results of the qualitative analysis made by the principal and the quantitative assessments given by the agents. In this connection, an emphasis in the interpretation of the results was made not so much on the specific quantitative assessments of the agents as on the comparison of the priorities of the problems expressed by the agents and the solutions generated by the principal. The results of the analysis showed that most of the priority tasks for agents in the field of organizing financing, digitalization, scientific cooperation were reflected in the decisions of the principal. The gaps stem from the lack of solutions aimed at intensifying research work in terms of monitoring the current scientific thematic agenda, and the importance of increasing the weight of this criterion when evaluating scientific projects. There are two ways to reduce the identified gaps: 1) inclusion of the support for the development of aggregators that allow scientists to quickly obtain the most relevant results with growing volumes of data into the list of tasks facing the principal; 2) development of modern analytical information and digital mechanisms for assessing the prospects of topics, which creates conditions for their compliance with the dynamic global research agenda. © 2021 Moscow Polytechnic University. All rights reserved

Priorities in the Modern Organization of University Science in the Light of the Principal-Agent Theory

The article focuses on the current state of the balance of interests in the field of organizing research activities in Russian universities. The theoretical framework of the research is the theory of the principal-agent, from the position of which the research management system is considered through the relationship between actors who have different degrees of awareness and potentially actin different interests. The purpose of the study is to compare the problems in the field of organizing funding, digitalization and scientific cooperation, which were the most important for agents, with those strategic decisions that took place at the level of the principal after extensive expert discussions. The following sources were used: 1) the results of the largest expert project implemented at the initiative of the Ministry of Science and Higher Education of the Russian Federation; 2) the results of a sociological study conducted at the Ural Federal University, where scientists and employees involved in the organization of scientific research were interviewed. A limitation of the study was the difficulty of comparing the results of the qualitative analysis made by the principal and the quantitative assessments given by the agents. In this connection, an emphasis in the interpretation of the results was made not so much on the specific quantitative assessments of the agents as on the comparison of the priorities of the problems expressed by the agents and the solutions generated by the principal. The results of the analysis showed that most of the priority tasks for agents in the field of organizing financing, digitalization, scientific cooperation were reflected in the decisions of the principal. The gaps stem from the lack of solutions aimed at intensifying research work in terms of monitoring the current scientific thematic agenda, and the importance of increasing the weight of this criterion when evaluating scientific projects. There are two ways to reduce the identified gaps: 1) inclusion of the support for the development of aggregators that allow scientists to quickly obtain the most relevant results with growing volumes of data into the list of tasks facing the principal; 2) development of modern analytical information and digital mechanisms for assessing the prospects of topics, which creates conditions for their compliance with the dynamic global research agenda

Chinese students’ motivation to adopt distance learning of the Russian language

Introduction. Currently, restrictions related to the coronavirus pandemic have not yet been fully lifted in the People's Republic of China and students studying in Russia periodically switch to distance learning. The purpose of the article is to study the specifics of students' motivation to use distance technologies for teaching the Russian language using internationally recognized methods of measurement and statistical data analysis. Materials and Methods. The Instructional Materials Motivation Survey (IMMS) measuring materials for studying the specifics of the educational motivation of students of the Ural Federal University (hereinafter referred to as UrFU) from the PRC for the use of distance technologies for teaching the Russian language were created for the Attention-Relevance-Confidence-Satisfaction (ARCS) structural model. We studied the relationship between the personal data of students (gender, age, year of study, educational program, additional language training and the results of measuring educational motivation (IMMS) for the use of distance technologies for teaching the Russian language and its structural components: attention (ATT), relevance (REL), Confidence (CON), Satisfaction (SAT).The study involved 673 UrFU students from the PRC, who had experience of long-term distance learning under restrictions due to the coronavirus pandemic. Statistical processing of the measurement results was carried out using the structural equation modeling method Structural Equation Modeling (SEM). A confirmatory and exploratory factorial analysis of the obtained results was carried out using the SPSS software tool, including the AMOS module. Results. The developed IMMS questionnaire was validated by confirmatory factor analysis of IMMS measurement results using the AMOS module of the SPSS software tool. The method of exploratory factor analysis revealed statistically significant relationships between the indicators of students' educational motivation for using distance technologies for teaching the Russian language (IMMS) and its structural components with the personal data of the respondents. The gender of the student and the presence of parallel additional language training were found to have the strongest influence on learning motivation (girls are more motivated than boys). The gender of the student and the presence of parallel additional language training (regression coefficient r = 0.61) have the strongest influence on the structural component of learning motivation relevance (REL). Conclusion. The results of the study showed a high level of motivation for distance learning of the Russian language among UrFU students from China which is due to the effective design of educational materials. It is shown that when developing motivating teaching materials for distance learning, it is necessary to take into account the gender composition of trainees and the availability of parallel additional training in the subject. © 2023 LLC Ecological Help. All rights reserved