Prospects for the training development of qualified personnel in the agricultural education system: a case study from Tashkent State Agrarian University, Uzbekistan

. Development, implementation, and achievement of the desired results of Uzbekistan's stable progress and development of reforms are directly related to the professional personnel who organize these processes and their knowledge of innovative management. Because the correct determination of the directions of the reforms and the results to be achieved requires such qualities as high knowledge, potential, and professional skills from the specialist personnel. In addition, it is important to properly organize personnel management in every enterprise and organization in every field, direction, and place the most qualified personnel with the necessary knowledge and potential in every job. An important aspect of econometric analysis is that it is an analysis based on the assessment of the effects of factors that have an indirect, but not direct, effect on the change in the outcome variable. That is, in our analysis, if we define the indicator of employment of graduates as a result, the factors that indirectly influence its change are the scientific potential of teachers, the degree to which the institution where the graduate is trained is compatible with practice, the level of scientific research in the educational institution, education in harmony with international experiences. Factors such as have an indirect effect. In this article, medium-term forecast indicators of the level of employment of graduates in the training of agricultural educational institutions in the period of 2022-2027 have been developed. Also, the main directions of introduction of market mechanisms in effective management of agrarian education system are highlighted in the article.


Introduction
The introduction of new technologies in the educational system of the developed countries of the world and the special attention paid to the potential of personnel, in order to meet the demand for personnel in the fields, the integration of education, innovation and the connection of practices with production are widely established [1][2][3].
The fact that the development of the new century is directly related to the development of science, and the increasing demand for personnel shows that each field needs young, capable professionals in their field [4].
In order to ensure the integration of science and production in the agricultural sector, to introduce modern information and digital technologies into the educational process, to improve the system of training of personnel with sufficient knowledge and skills in advanced foreign experience and agro-technologies, taking into account the prospects for the development of regions consistent implementation of the tasks defined in the decision of the Cabinet of Ministers of the Republic of Uzbekistan No. 788 of December 15, 2020 "On approval of the strategy of innovative development of the agricultural education system until 2030" dated July PQ-4795 bringing agriculture to the industrial level and highly qualified training in the field is one of the main tasks of today [5].
Currently, structural changes and updates are taking place in every direction around the world, along with the emergence of new professions and specialties, the demand for some professions and specialties is disappearing [6].
The most important priority and the ultimate goal of the higher education system of Uzbekistan is to train and deliver high-potential specialists who have perfectly mastered modern knowledge in specialties that meet the requirements of the time. Our research is also dedicated to this direction and is aimed at improving the management mechanisms of personnel training in the agricultural education system.
We know that there is a lot of innovation and change in the agrarian sector and it is the need of the hour. Because, in the agrarian sector, food and products that meet most of the primary needs of the society are created [7]. The objective need to improve the management mechanisms of personnel training in the agrarian education system is that now the population is constantly increasing, while their food and other primary needs are also increasing, but the land resources that produce such products are limited. If the level of profitability in the use of land resources remains in the current state, one day it will be impossible to satisfy the basic needs of man. That is why increasing the efficiency of land use and increasing profitability is the demand of the times. This is achieved by training qualified, modern, well-educated personnel, training specialists in the required fields, and effective organization of personnel management.

Materials and methods
From this point of view, "how much is the need for personnel trained in the agrarian education system now?", "are they getting jobs after completing their education?" through such questions, the current state of personnel training in the agrarian education system is evaluated, existing shortcomings are identified and analyzed. Based on the results obtained from the analysis, development directions and strategies are determined.
One of the important research methods is econometric modeling. Below, we will perform econometric modeling analyzes on our research topic based on the information of Tashkent State Agrarian University. As we mentioned above, the effective and optimal organization of personnel management in agricultural educational institutions is directly evaluated by the indicator of employment of graduates. The employment of graduates is directly influenced by their level of education, potential, knowledge of foreign languages, mastery rates and many other factors.
The basis of econometric modeling is based on correlational and regression analysis. In correlational analysis, the influence of factors on the change of the resulting sign is evaluated. In regression analysis, models showing the effect of factors on the resulting sign are built, and it is checked by econometric tests, the optimal and most accurate model is determined, and forecasting is carried out through the model [8,9].
In our research, we determine the employment level of TDAU graduates of different years (in percent) as a result indicator, and its change depends on the scientific potential of professors and teachers (in percent), the number of articles published by OTM in prestigious journals (pieces), the number of subjects taught in a foreign language (pieces), abroad We hypothesize that the number of professors (persons) who have advanced training or internships and others will have an indirect effect.
First, let's look at the descriptive statistics of the data in Table 1. Here is what the conditional variables in Table 1 represent [10]: BD -employment rate of graduates (%); IS -scientific potential (%); MS -number of articles published in international prestigious journals; CTF -number of specialized subjects conducted in foreign languages; XS -number of professors and teachers who have advanced their qualifications or completed internships abroad; RT -level of introduction of digital technologies to the educational process (%); AT -level of provision of educational literature (%); AS -number of qualified specialists involved in the educational process from the main employing organizations. Based on the correlation matrix, we select the indicators we need for modeling. In this case, we will define the BD indicator as a symbol of performance in our analysis. The correlation coefficient is an important indicator of how much a factor affects the change of another factor, and it varies between -1 and 1. If the indicator is between 0 and 1, the factor sign is positive for the resulting sign change, and if it is between -1 and 0, the factor sign represents the opposite effect on the resulting sign change. The closer the correlation coefficient is to 1 or -1, the stronger the relationship. In order to continue the analysis, we need to choose factors with a correlation coefficient higher than 0.7 or lower than -0.7, because in this case, it means that the factors have a strong influence on the resulting sign.
We describe it in a model built on a linear function. That is, the general formula is as follows [11]:
An important indicator of the applicability of models in time series is the test for the absence of autocorrelation. It is called the Darbin-Watson statistic. In our example, the interval between the absence of autocorrelation is between 1.58 and 2.42. So only our models 3, 4 and 5 do not have autocorrelation and are valid for application. Summarizing all the criteria, the optimal model with the largest R-squared value, the smallest standard error, and the smallest mean square deviation is model 3, and model 4 also meets these criteria. For the next step of our analysis, we chose to use model 3. We describe the optimal model as follows [11]: (2) Where: BDtemployment rate of graduates in the period t (%); ISt-1scientific potential of the period t-1 (%); RTt-2the level of introduction of digital technologies to the educational process in the period t-2 (%); еunaccounted factor.
The value of the Fisher-Snedekor F-criterion in the model is less than 0.01, so the model is statistically valid. The statistical significance of the obtained independent variables (ISt-1 and RTt-2) was confirmed to be less than 0.01 and statistically significant when tested by Student's t-test. Therefore, this model is suitable for use in inductive analysis.

Results and discussion
The mean of the graduate employment rate (BD) was 88.5 percent, almost the same as the median, with a minimum of 84.3 percent and a maximum of 93.5 percent. The standard deviation is 2.93, which is very small. The average of the scientific potential (IS) of university professors was 48.1%, the minimum was 46.2%, and the maximum was 66.1%. The standard deviation index (8.26) is slightly higher. The average number of articles published by university employees in international journals was 144.3, minimum 18 and maximum 384. The standard deviation is 151.2, which is very high. The level of availability of educational literature (AT) averaged 80 percent, varying from 72 percent to 100 percent. The number of specialized subjects conducted in foreign languages (CTF) has increased from 2 to 30. The number of professors and teachers who have advanced their qualifications or completed internships abroad has also increased from 2 to 82. The level of implementation of digital technologies in the educational process (RT) also improved, increasing from 72 percent to 90 percent.
The number of qualified specialists involved in the educational process from the main employer organizations has changed from a minimum of 31 to a maximum of 75. In fact, we determine whether the factors are related to the employment rate of graduates (BD) and how strong the connection is through the correlation coefficient (Table 2).  It can be seen from Table 2 that the correlation coefficients of all the factors obtained in the analysis with the level of employment are higher than 0.7 (the data of the first row of Table 2), from which the conclusion is that all the factors obtained in the analysis have a correct, strong connection with the level of employment of graduates.
At the next stage of the research, we will build econometric models of the influence of factors on the change of graduate employment rate (BD) using the least squares method and select the most appropriate model.
We perform calculations in the software package and get the results. In the modeling process, we analyze the impact of previous years' indicators on the level of employment in our example, such as scientific potential, the level of introduction of digital technologies, and the level of availability of literature, because the level of employment is known after graduation, but the education was received in previous years, from this point of view it is necessary to include the indicators of the factor variables in the previous years in the model.
We place the results of the models created as a result of the analysis in the ANOVA table (Table 3) Table 3 provides a description of the five optimal models. In the table, t are the values of the variables in the current year, and t-1 and t-2 are the values of the variables one and two years ago, respectively. It can be seen that the coefficients in front of the independent variables in all models are correctly connected according to the correlation coefficient. The reliability of all 5 mentioned models is at the highest level (statistically significant at the 1% level of significance), ISt-1 at the t-1 period in model 1 is statistically significant at the 5% level of significance, the remaining variables are statistically significant at the 1% level of significance. RTt-1 and ATt-1 in period t-1 in model 2 are statistically significant at the 5% significance level, and the remaining variables are statistically significant at the 1% significance level. All variables in models 3 and 4 are statistically significant at the 1% significance level. RTt-2 at period t-2 in model 5 is statistically significant at the 5% significance level, and the remaining variables are statistically significant at the 1% significance level. The R-squared value, which indicates how well the model represents the actual situation, is higher than 98 percent in all models. The value of the mean squared deviation is equal to 2.599 in models 3, 4, 5, and 2.745 in models 1 and 2. The standard error is 0.2624 in model 3, which is the smallest, and 0.309 in model 1, which is the largest.
The coefficient of determination (R-squared) of the developed equation is equal to 0.992, and 99.2 percent of the employment rate of graduates can be explained through the created model. According to the correlation coefficient, the independent variables of the model are correctly related.
The coefficient in front of ISt-1 (0.0741237) -when other factors remain unchanged, a 1% increase (decrease) in scientific potential in period t-1 leads to an increase (decrease) in the employment level of graduates in period t by 0.074%. The coefficient in front of RTt-2 (0.321783) is the level of introduction of digital technologies to the educational process in the period t-2, other factors remaining unchanged. A 1 percent increase (decrease) in graduations in period t means an increase (decrease) in the employment rate of 0.322 percent.
At the next stage of research, we will make forecasts of indicators for 2022-2027 through the regression equation (formula 2) obtained in modeling. For this purpose, we will initially make forecasts of the factor variables obtained in the model for 2022-2027 and forecasts of the level of employment based on the model based on these forecast data (Table 4).
It can be seen from Table 4 that in the forecasts, the indicator of scientific potential and the level of introduction of digital technologies into the educational process will have a tendency to increase. This will have a positive effect on increasing the employment rate of graduates in the future. According to our model, the indicator of the level of introduction of digital technologies to the educational process in year t-2 and the indicator of the scientific potential of professors and teachers in year t-1 are evaluated according to the impact on the employment level of graduates in year t. From this point of view, in 2022-2027, the level of scientific potential will increase from 68.1% to 78.1%, and the level of introduction of digital technologies into the educational process will increase from 62.2% to 63.0%, and the employment rate of graduates will increase from 92.8% to 94.4%. increase was predicted.
The most optimal solution is to gradually improve the quality indicators of agricultural education during the years of development of the educational process and radical reform of the sector. In the future, it will be necessary to fully study the impact of several factors on the training of personnel in the agricultural education system and to control the state support of the sector. As a result of the research, the factors influencing the management mechanisms of the agricultural educational institutions operating in Uzbekistan were analyzed, and it was shown that their prospective development requires a full study of the opportunities necessary for personnel training and the implementation of the necessary directions. Therefore, the implementation of large-scale reforms in the education system, the implementation of fundamental reforms in the agriculture of Uzbekistan, as well as the establishment of many private higher educational institutions and branches of foreign universities require the training of competitive personnel on the basis of market mechanisms in the agricultural education system. In this process, agrarian educational institutions are necessary to maintain their position as a leading source of personnel for the agricultural sector. Introduction of market mechanisms in institutions operating in the agrarian education system, which make a great contribution to the development of agriculture, have sufficient conditions to be recognized as modern educational institutions. In particular, Tashkent State Agrarian University is one of the largest and leading higher educational institutions in the field of agriculture of the Republic of Uzbekistan. It is necessary to prepare the university and its technical institutes for transformation within the framework of the state policy on the transfer of state universities to self-management and self-financing, which in turn requires a complete revision of the existing approaches and practices in its management, priorities for the introduction of market mechanisms in the training of qualified personnel, and the implementation requires the development of an increase mechanism (Table 5). This, in turn, is important for every educational institution to prepare mature specialists in today's constantly changing era.
On the basis of these priorities and expected results, in the process of effective management of the agrarian education system, it is the urgent task of today to consistently introduce it to higher, secondary special and professional educational institutions, to effectively use modern digital technologies, to conduct personnel training and staff management using innovative management methods. Therefore, an environment of free competition is formed in the labor market, and this process serves as an important factor in the sustainable development of the economy and the further development of the agrarian sector. Raising the content of higher education to a new level in terms of quality, sustainable development of the social sphere and economic sectors will be achieved. 2 Optimization of undergraduate education and master's specializations Qualified personnel with new specialties, competitive in the labor market, are trained.

3
Establishing a "Media-center" in order to provide electronic information sources for distance and dual education Through modern forms of education in the agricultural sector, effective cooperation between employers and higher education institutions is established.

4
Complete digitization of educational literature in the information-resource center and creation of a Virtual agroinformation-resource network A unified agro-information database will be created for learners and producers to acquire new knowledge.

5
Organization of training and internships of qualified leaders and pedagogues in the agrarian education system in prestigious higher and scientific educational organizations with a rating of TOP-1000 Professional skills of leaders and pedagogues will be improved and they will have the opportunity to use foreign technologies in education.

6
Establish a system of training on modern personnel management processes (recruitment, selection, talent management, talent pool) In the future, a reserve of leading personnel will be formed and talented young people will be directed to science.

7
Improving the "Feedback" system in order to improve the quality of education An opportunity will be created to solve problems between students and teaching staff. Focusing on increasing the effectiveness of spiritual, educational and educational activities and improving environmental literacy Implementation of the tasks set within the five initiatives and implementation of the priority tasks of the transition to a green economy will be ensured.

10
Active involvement and cooperation of employer organizations in the process of training highly qualified specialists for the labor market In the organization of the educational process, employees with high qualifications are involved in the employing organizations and the integration of science production is ensured.

11
Ensuring financial independence and stability of educational institutions, strengthening material and technical support, attracting investments With the help of various methods of providing educational services, the material and technical base of HEIs will be strengthened and vacant buildings and facilities in HEIs will be used effectively.

12
Digitization (in the QR system) of normative-methodical documents of pedagogical staff and distribution according to the automatic management system It is possible to prevent various problematic situations in the distribution of the load intended for the academic year, to facilitate the downloading of created literature and training manuals. In the modern agrarian education system, management mechanisms of personnel training will be improved and an opportunity to ensure environmental protection will be created.
14 Conduct research that covers the development of business and operational efficiency in agriculture During the transition to the digital economy, it is possible to implement scientific research, projects, and start-ups on current topics.

15
Strengthening the position of HEIs in national and international rankings In the course of the globalization of educational services, the possibility of attracting foreign and local applicants to OTM, the possibility of cooperation with foreign higher and scientific educational organizations will increase.
Based on the above, in the future, it is necessary to pay attention to the following main tasks in the development of agricultural education, training of mature personnel for the agricultural sector and economic sectors: • pedagogical and methodological coordination of activities of educational institutions operating in the higher education system for the agricultural sector, organization of special departments for monitoring training and employment in the structures of agrarian educational institutions and their branches; • introduction of retraining courses for management personnel in order to modernize management methods affecting the activities of agrarian educational institutions and solving problems of cooperation; • organization of provision of additional professional activities in the course of acquiring knowledge and skills on the basis of modern technologies in addition to professional activities; • announcement of contests by employer organizations throughout the year for highly qualified personnel with the necessary knowledge and skills in educational institutions. Resolving the issues of qualification improvement, retraining and salary provision of personnel accepted for work based on the results of the competition; • independent determination of payment contract amounts, taking into account the fact that they are financially independent in agrarian educational institutions, effective establishment of a dual education system; • minimum of their total value as part of the investment projects being implemented in the agricultural sector • to envisage an educational component of up to 2%, centralizing these funds to study advanced foreign experience of pedagogues, to modernize the material and technical base, to purposefully create new generation textbooks; • to create the necessary motivations for attracting part of the higher education staff to secondary special education due to the change in the ratio of professors to the number of students, as defined in the concept of the development of higher education in 2020-2030, due to the acceptance of their number in connection with the introduction of the modular credit system of education.

Conclusions
In conclusion, in the future, in the development of personnel training in the agrarian education system, educational institutions will improve the scientific potential, if modern digital technologies are introduced into the educational process, it will certainly show its results in a short period of time, ensure the employment of graduates and prepare them as specialists who meet the requirements of the labor market. Also, as a result of forming a healthy competitive environment among educational institutions, taking into account the priority directions of market mechanisms, providing the agricultural sector with qualified personnel will be achieved.