The Higher Education System in The Context of Innovative and Intellectual Development of Territories
Denys Krylov
D.Sc. in Economics, Assoc. Prof.,
Zaporizhia National University,
Zaporizhzhia, Ukraine.
Yuliia Hermash
PhD in Pedagogy, Senior Lecture,
National Technical University of Ukraine
Igor Sikorsky Kyiv Polytechnic Institute,
Kyiv, Ukraine.
Ihor Chobitok
PhD in Economocs, Senior Lecture,
Kharkiv, Ukraine.
Svitlana Nazarko
PhD in Economics, Assoc. Prof.,
Penitentiary Academy of Ukraine,
Chernihiv, Ukraine.
Rostyslav Pashov
PhD in Philosophy, Assoc. Prof.,
National Technical University of Ukraine
Igor Sikorsky Kyiv Polytechnic Institute,
Kyiv, Ukraine.
Abstract
Globalization trends prove the undeniable need for the development of territories on the intellectual and innovative basis, which in turn necessitates the need to pay more attention to the higher education system, which ensures the formation of intellectual potential and the innovative direction of the development of territories. The purpose is to develop methodological principles for evaluating the higher education system in the context of intellectual and innovative development of territories. Problems of the functioning of the higher education system in the context of ensuring intellectual and innovative development of territories are identified, namely: asymmetric spatial development of territories within the national economic system; effect of the legal regime of martial law; prevalence of practices of the command-administrative nature in the field of management and organization of educational activities both from the point of view of excessive bureaucratization of the system; formalized nature of the value perception of the higher education institution among the population; limited financial resources to ensure the proper level of material and technical base of domestic higher education institutions and sufficient level of material motivation of scientific and pedagogical workers; negative trends in the development of the socio -cultural environment. Separate indicators of the higher education system in terms of territories are analyzed, namely dynamics of the number of students in higher education institutions of Ukraine by region, number of higher education institutions and graduation of specialists by higher education institutions of Ukraine by region. The methodological approach to assessing the higher education system in the conditions of intellectual and innovative development of territories is proposed. It involves adhering to the principles of complexity and systematicity, as well as using the methodological apparatus of the taxonomic analysis to obtain comprehensive assessment, which involves constructing a system of descriptive indicators; qualitative analysis of the system of descriptive indicators; standardization of the values of constructing the observation matrix; construction of the “standard vector” , and on its basis calculating the value of the Euclidean distance; calculation of the integral indicator for assessing the state of the higher education system in the conditions of intellectual and innovative development. The proposed methodological approach was tested on the example of the functioning of the higher education system in the territories of Ukraine.
Keywords: Education, Higher Education Institutions, Higher Education System, Innovative Development, Intellectual Development, Region, Territory.
Introduction
Today, one of the key system-forming vectors to ensure progressive economic growth within the main levels of organization of economic systems remains the intellectual and innovative component of development, aimed at intensifying scientific and technical, personnel, investment, natural and ecological potential of both individual spatial formations and the national economy as a whole. The outlined trends in the dynamics of socio-economic development are explained by paradigmatic transformation of economic systems embodied in gradual formation of post-industrial forms of organization of economic relations, focused on the specific approaches to management and the use of the resource potential of economic systems, as well as general reprioritization of key resource components of development as such.
The fundamental driving forces that ensure actualization of the issues of innovative and intellectual development are dynamic processes of changing the structural indicators of the return of key resource components of economic systems. These processes manifest themselves in strengthening the role of intellectual potential (as an inexhaustible resource for generating managerial and technical, and technological solutions), innovations (as tools for optimizing business processes and implementing fundamentally new methods, means and forms of economic activity), information resources (as a multivariate category that can serve as a primary resource for making managerial decisions, a product, a communication tool, etc.), creative potential (as an integral component for achieving full realization of the individual potential of the human resource, based on the relevant psycho-emotional and moral-value aspects), inclusive environment (as an infrastructural aspect of ensuring physical opportunities for realizing the individual potential of all categories of the population), knowledge resources (as an objective basis for structural and analytical formalization, cognitive processing of information resources to achieve its functionality). It is worth noting that among the above-mentioned aspects of the implementation of intellectual and innovative development processes, a special place is occupied by the issue of building knowledge potential, which forms the basis for further implementation of intellectual and creative potential, using information resources, and generation of innovative products.
The leading role in the building and expanding the knowledge potential of economic systems belongs primarily to the higher education system, which is designed to ensure multifaceted development of the individual potential of individuals both in terms of basic skills and abilities, and in the formation of holistic qualification competencies for conducting professional activities in terms of specific functional aspects and also in terms of moral, ethical and psychological qualities necessary for establishing communication interactions and making managerial decisions.
It should be emphasized separately that it is important to consider the spatial aspect of the functioning of the higher education system in the context of intellectual and innovative development, which consists in the need to ensure sustainable and effective functioning of relevant educational and scientific institutions in the context of their ability to organize training of specialists with appropriate level of professional competence, taking into account the specific territorial conditions and needs of the region in human resources and their knowledge potential.
The purpose of the study is to develop methodological principles for evaluating the higher education system in the context of intellectual and innovative development of territories.
To achieve the goal, the following tasks were solved:
Literature review
Articles of Wang Halving et al. (2025), Allam H. M. et al. (2025), Sheng Yaninq. (2025) are devoted to the methodology formation for the strategy of implementing content innovations in digital education in higher professional colleges using artificial intelligence, and to the study the AI impact on sustainable development of innovations and transformation of higher education. Within the framework of research of Ocen S. et al. (2025), Gao Y. (2025), Gutiérrez-Leefmans M. et al. (2025), the role of AI in the development of higher education institutions, its impact on the formation of innovation in learning models, assessment systems, and personalized learning was analyzed.
The authors Barqawi L. et al. (2024), Alejandra Colmenares Garzon et al. (2024), Nugraheni Anjar Sri Ciptorukmi et al. (2024) focused their research on enhancing innovation in higher education through artificial intelligence and intellectual property, and proposed the use of the business intelligence dashboard as a technological innovation for analyzing digital transformation in higher education. Ruixin Zhang (2024), Dangying Liu (2024), Danli Huang (2024) demonstrate the experience of the AI use in higher education, proving that the artificial intelligence technology contributes to model innovations in higher education management and student learning mechanisms.
Alam Ashraf et al. (2022), Chedrawi C. et al. (2019), Popelo O. et al. (2024) demonstrate the results of developing a business model, business strategy, and innovation in higher education, consider AI as a revolutionary innovation in higher education accreditation programs, and analyze global trends in university digitalization within the framework of the sustainable development concept. Kholiavko N. et al. (2023), Marhasova V. et al. (2023), Arefiev S. et al. (2022) analyze the path of a higher education institution to sustainable development, investigate the impact of digitalization on its innovative development, taking into account the challenges of war and pandemic. Djakona A. et al. (2021), Jakubek P. et al. (2023) consider the role of higher education in the information economy development, analyze managerial control in the system of ensuring economic security and innovative development.
However, taking into account the above-mentioned achievements of scientists, we can argue about the feasibility of conducting further research related to the higher education development in the context of innovative and intellectual development of territories.
Methodology
Within the framework of this study, it is proposed to use the methodological apparatus of the taxonomic analysis as a method to assess the state of the higher education system in the conditions of intellectual and innovative development of territories to ensure the complexity of the obtained results and possible quantitative formalization of the obtained effective assessment indicators. The substantive basis of the taxonomic analysis method is to calculate the quantitative level of the Euclidean distance between the analyzed objects of multidimensional space. Within the framework of the taxonomic analysis method, the dimension of this system is represented by a selected list of descriptive indicators of the studied objects. At the same time, the method allows you to freely vary the composition of the system of descriptive indicators, regardless of their dimension and typology, allowing you to form arrays of indicators that are heterogeneous in their economic nature without losing the properties of the assessment representativeness. The latter is achieved by carrying out a procedure for standardizing the values of the selected descriptive indicators, which ensures their comparability and quantitative uniformity, protecting against possible distortion of subsequent quantitative integral assessments. Thus, the involvement of the methodological apparatus of the taxonomic analysis opens up opportunities for the formation of the comprehensive evaluation system based on a wide range of descriptive indicators of the higher education system in the context of intellectual and innovative development of territories, calculating on its basis generalized integral assessments for each of the studied regional objects.
Practical implementation of the taxonomic analysis involves implementation of some computational and analytical stages, which includes the sequence of actions described below.
(1)
where: X is - observation matrix;
n – number of studied periods;
m – number of descriptive evaluation indicators;
x ij –value of descriptive indicator j in the ith period.
(2)
where: – value of the i -th descriptive indicator in the array j;
– average value of the i -th descriptive indicator in the array j;
– level of the standard deviation of the descriptive indicator i.
(3)
The constructed “standard vector” allows us to demonstrate at what standardized levels of descriptive assessment indicators the best state of the higher education system is achieved in the conditions of intellectual and innovative development of territories.
(3)
where is the Euclidean distance between and the values of the “standard vector”.
(4)
where - average deviation of the descriptive indicator from the “standard vector”.
(5)
where - value of the standard deviation of the indicator .
(6)
where - maximum deviation of descriptive indicators from the “standard vector” (using the “three sigma rule”).
(7)
where - intermediate indicator of the assessment of the state of the higher education system in the conditions of intellectual and innovative development of territories.
(8)
where - indicator of the assessment of the state of the higher education system in the conditions of intellectual and innovative development of territories.
The calculated values of the integrated indicator allow us to obtain comprehensive integral assessment of the state of the higher education system in each of the studied regions based on wide array of descriptive indicators, taking into account the influence of time characteristic, that is, and dynamics of their change within the studied period.
Results
Currently, the higher education system in the context of ensuring intellectual and innovative development of territories faces a number of systemic problems that significantly limit possibilities of territories to accelerate relevant processes of intensification of economic development. Among the mentioned problems, it is advisable to highlight the following:
Thus, the problems outlined above form a complex of systemic restrictions both to the development of higher education within individual territories and within the national economic system as a whole, reducing the latter's potential to ensure intellectual and innovative development. The presented problematic aspects find their practical expression in corresponding quantitative indicators of the functioning of the national higher education system. One of these indicators is the indicator of the number of students in higher education institutions by region, the dynamics of which is presented in Table. 1.
Table 1 – Dynamics of the number of students in higher education institutions of Ukraine by region (2019-2023)
|
Region/Year |
2019 |
2020 |
2021 |
2022 |
2023 |
|
Vinnytsia |
41359 |
39347 |
32807 |
34492 |
37898 |
|
Volyn |
24069 |
20678 |
19269 |
23054 |
28035 |
|
Dnipropetrovsk |
107995 |
82685 |
70298 |
78653 |
82444 |
|
Donetsk |
33390 |
27457 |
23932 |
– |
– |
|
Zhytomyr |
26913 |
22352 |
17577 |
18597 |
21454 |
|
Transcarpathian |
21589 |
20212 |
17394 |
21055 |
22493 |
|
Zaporizhzhia |
66188 |
49049 |
46044 |
44501 |
50540 |
|
Ivano-Frankivsk |
35323 |
32206 |
30184 |
38034 |
36610 |
|
Kiev |
24845 |
18798 |
15883 |
17507 |
20868 |
|
Kirovohrad |
13357 |
11626 |
10181 |
14614 |
17270 |
|
Luhansk |
20078 |
17856 |
13233 |
– |
– |
|
Lviv |
115700 |
95364 |
90385 |
97257 |
108968 |
|
Mykolaiv |
29440 |
26958 |
21437 |
21631 |
21561 |
|
Odessa |
95240 |
75060 |
67743 |
71332 |
75355 |
|
Poltava |
41936 |
34019 |
29895 |
35038 |
41174 |
|
Rivne |
30068 |
24290 |
18868 |
21032 |
26128 |
|
Sumy |
31031 |
18879 |
18073 |
19177 |
22979 |
|
Ternopil |
39546 |
28315 |
26982 |
31949 |
37971 |
|
Kharkiv |
165230 |
124215 |
122386 |
113495 |
119032 |
|
Kherson |
24801 |
20733 |
18579 |
– |
– |
|
Khmelnytskyi |
29927 |
25308 |
22252 |
25195 |
27109 |
|
Cherkassy |
36140 |
32422 |
28832 |
30132 |
32436 |
|
Chernivtsi |
26575 |
22329 |
18748 |
20577 |
20964 |
|
Chernihiv |
17684 |
12976 |
11917 |
12523 |
15941 |
|
Kyiv |
341282 |
258755 |
253770 |
263925 |
281428 |
Source: State Statistics Service of Ukraine (2023)
Based on the above dynamics of the number of students in higher education institutions of Ukraine during 2019-2021, a steady downward trend is observed. The highest levels of reduction in the number of students were recorded in 2020 in Kyiv from 341,282 people to 258,755 people, which is 24.1%, Dnipropetrovsk region (reduction by 25,310 people, or 30.1%); Kharkiv region (reduction by 41,015 people, or 24.8%), Lviv region (reduction by 20,336 people, or 17.6%). These processes are explained by negative impact of the coronavirus pandemic, which led to a significant change in approaches to organizing the educational process, complicating access to traditional forms of educational activity, reducing the population and corresponding volume of solvent demand for educational services. At the same time, during 2022-2023, there is a partial recovery in the number of students in higher education institutions, in particular, the highest levels of the growth rate are observed among the following regions: Transcarpathian region (21.0%), Ivano-Frankivsk region (26.0%), Volyn region (19.6%), and Ternopil region (18.4%). The outlined trend is a direct result of the beginning of the full-scale invasion and the effect of the legal regime of martial law, which caused the migration outflow of the population, to regions remote from the line of hostilities, as well as the specific features of the regulatory and legal nature that are in force under the martial law regime. A further reduction in the number of students in higher education institutions during the specified period was observed among front-line regions, including Kharkiv region (-7.3%) and Zaporizhzhia region (-3.4%).
It is worth noting that an important aspect of ensuring functioning of the higher education system is available appropriate infrastructure and relevant parameters of their effectiveness , which is why we propose to consider the indicators of the number of higher education institutions and the volume of graduates of qualified specialists in 2023 (Fig. 1).
Figure 1 – Number of higher education institutions and graduates of higher education institutions of Ukraine by region (2023)
Source: State Statistics Service of Ukraine (2023)
Based on the data presented in Fig. 1, it can be stated that the highest concentration of higher education institutions in 2023 is observed in Kyiv (83 units), Kharkiv region (30 units), Dnipropetrovsk region (29 units), Lviv region (21 units) and Odessa region (21 units). Analyzing the absolute values of the indicator of the graduation of specialists by higher education institutions, the highest levels are recorded in Kyiv (101,454 people), Kharkiv (44,880 people), Lviv (40,619 people) and Odessa regions (30,422 people).
However, examining this issue from the perspective of estimates based on relative values, in particular, student graduation per 1 higher education institution among the regions of Ukraine, the highest levels are demonstrated by Ternopil region (2611.5 persons/unit of higher education institution), Chernivtsi region (2474.7 persons/unit of higher education institution), Poltava region (2111.1 persons/unit of higher education institution) and Lviv region (1934.2 persons/unit of higher education institution). This situation is explained by available large higher education institutions with the “national” status, which accumulate a significant number of applicants.
It should be noted that the study of the functioning of the higher education system in the conditions of intellectual and innovative development of the territory is a complex issue with the presence of a wide range of influential factors, both systemic and situational, directly affecting the indicators of the efficiency of the higher education system and corresponding effectiveness in the context of accelerating intellectual and innovative development. That is why, assessing the state of the higher education system in the conditions of intellectual and innovative development of territories requires going beyond traditional methods of statistical analysis and requires the formation of more representative forms of organizing a comprehensive assessment process based on the tools of economic and mathematical analysis.
Based on the above-presented sequence of implementation of the taxonomic analysis within the framework of the study of the state of the higher education system in the context of intellectual and innovative development of territories, one of the key stages is the construction of a system of descriptive indicators. Taking into account the need to adhere to the principles of complexity and systematicity, within the framework of this study it is proposed to expand the applied plane of the analysis in relation to selected analytical indicators. This need is explained by the inexpedient isolated consideration of indicators that characterize exclusively the state and dynamics of the higher education development, since the issues of intellectual and innovative development also cover the issue of the effective knowledge potential generated by higher education institutions in the context of the functioning of the regional economic system as a whole. That is why, by constructing a matrix of observations of the initial values of descriptive indicators, it is proposed to rely on the following analytical aspects:
Thus, the constructed model for assessing the state of the higher education system in the context of intellectual and innovative development of regions includes 15 descriptive indicators; the research period is 2019-2023.
Due to the methodological apparatus of the taxonomic analysis based on the formed initial array of descriptive indicators of the state of the higher education system in the conditions of intellectual and innovative development of territories, the following intermediate indicators were obtained, which are presented in Table 2.
Table 2 – Intermediate indicators of the calculation of the integral indicator of the state of the higher education system in the conditions of intellectual and innovative development of territories
|
Region/Year |
2019 |
2020 |
2021 |
2022 |
2023 |
|||||
|
d i0 |
c i * |
d i0 |
c i * |
d i0 |
c i * |
d i0 |
c i * |
d i0 |
c i * |
|
|
Vinnytsia |
19,646 |
0.770 |
19,620 |
0.779 |
19,736 |
0.774 |
19,824 |
0.786 |
19,281 |
0.663 |
|
Volyn |
20,294 |
0.796 |
20,450 |
0.811 |
20,424 |
0.801 |
20,360 |
0.807 |
19,925 |
0.686 |
|
Dnipropetrovsk |
17,854 |
0.700 |
17,972 |
0.713 |
18,163 |
0.712 |
18,049 |
0.716 |
17,079 |
0.588 |
|
Donetsk |
20,787 |
0.815 |
20,764 |
0.824 |
20,854 |
0.818 |
- |
- |
- |
- |
|
Zhytomyr |
20,330 |
0.797 |
20,433 |
0.811 |
20,587 |
0.807 |
20,759 |
0.823 |
20,353 |
0.700 |
|
Transcarpathian |
20,296 |
0.796 |
20,371 |
0.808 |
20,479 |
0.803 |
20,556 |
0.815 |
20,211 |
0.695 |
|
Zaporizhzhia |
19,228 |
0.754 |
19,416 |
0.770 |
19,478 |
0.764 |
20,133 |
0.798 |
21,277 |
0.732 |
|
Ivano-Frankivsk |
20,068 |
0.787 |
19,958 |
0.792 |
20,030 |
0.785 |
19,818 |
0.786 |
19,736 |
0.679 |
|
Kiev |
19,680 |
0.772 |
19,930 |
0.791 |
19,921 |
0.781 |
20,238 |
0.802 |
18,944 |
0.652 |
|
Kirovohrad |
20,600 |
0.808 |
20,694 |
0.821 |
20,705 |
0.812 |
20,581 |
0.816 |
20,303 |
0.699 |
|
Luhansk |
20,615 |
0.808 |
20,606 |
0.818 |
20,748 |
0.813 |
- |
- |
- |
- |
|
Lviv |
17,021 |
0.667 |
17,486 |
0.694 |
17,582 |
0.689 |
17,451 |
0.692 |
15,640 |
0.538 |
|
Mykolaiv |
20,101 |
0.788 |
20,212 |
0.802 |
20,301 |
0.796 |
20,639 |
0.818 |
20,358 |
0.701 |
|
Odesa |
17,779 |
0.697 |
18,129 |
0.719 |
18,262 |
0.716 |
18,742 |
0.743 |
17,917 |
0.617 |
|
Poltava |
19,641 |
0.770 |
19,639 |
0.779 |
19,836 |
0.778 |
19,861 |
0.787 |
19,132 |
0.658 |
|
Rivne |
20,346 |
0.798 |
20,408 |
0.810 |
20,460 |
0.802 |
20,546 |
0.815 |
20,185 |
0.695 |
|
Sumy |
20,238 |
0.793 |
20,436 |
0.811 |
20,501 |
0.804 |
20,789 |
0.824 |
20,318 |
0.699 |
|
Ternopil |
19,869 |
0.779 |
20,163 |
0.800 |
20,260 |
0.794 |
20,190 |
0.800 |
19,771 |
0.680 |
|
Kharkiv |
15,847 |
0.621 |
16,142 |
0.641 |
16,333 |
0.640 |
17,449 |
0.692 |
16,751 |
0.576 |
|
Kherson |
20,235 |
0.793 |
20,354 |
0.808 |
20,406 |
0.800 |
- |
- |
- |
- |
|
Khmelnytskyi |
20,053 |
0.786 |
20,004 |
0.794 |
20,138 |
0.789 |
20,143 |
0.799 |
19,728 |
0.679 |
|
Cherkasy |
19,892 |
0.780 |
19,943 |
0.791 |
20,052 |
0.786 |
20,070 |
0.796 |
19,699 |
0.678 |
|
Chernivtsi |
20,400 |
0.800 |
20,533 |
0.815 |
20,724 |
0.812 |
20,665 |
0.819 |
20,495 |
0.705 |
|
Chernihiv |
20,572 |
0.807 |
20,692 |
0.821 |
20,709 |
0.812 |
21,070 |
0.835 |
20,756 |
0.714 |
|
Kyiv |
11,029 |
0.432 |
11,821 |
0,469 |
11,351 |
0,445 |
12,248 |
0,486 |
4,249 |
0,146 |
|
M(di0) |
19,2969356 |
19,44706486 |
19,52161464 |
19,55361522 |
18,73220044 |
|||||
|
σ0 |
2,070063519 |
1,918043702 |
1,995238004 |
1,890060734 |
3,443191791 |
|||||
|
d0 |
25,50712616 |
25,20119596 |
25,50732865 |
25,22379742 |
29,06177581 |
|||||
Source: compiled by the author based on calculations
Based on the obtained intermediate indicators of the state of the higher education system in the conditions of intellectual and innovative development of the territories, the corresponding integral indicator was calculated. The dynamics of the integral indicator of the state of the higher education system in the conditions of intellectual and innovative development of the regions of Ukraine during 2019-2023 is presented in Table 3.
Table 3 – Dynamics of the integral indicator of the state of the higher education system in the conditions of intellectual and innovative development of regions (2019-2023)
|
Region |
Year |
Absolute deviation |
|||||||
|
2019 |
2020 |
2021 |
2022 |
2023 |
2020 to 2019 |
2021 to 2020 |
2022 to 2021 |
2023 to 2022 |
|
|
Vinnytsia |
23.0% |
22.1% |
22.6% |
21.4% |
33.7% |
-0.8% |
0.5% |
-1.2% |
12.2% |
|
Volyn |
20.4% |
18.9% |
19.9% |
19.3% |
31.4% |
-1.6% |
1.1% |
-0.6% |
12.2% |
|
Dnipropetrovsk |
30.0% |
28.7% |
28.8% |
28.4% |
41.2% |
-1.3% |
0.1% |
-0.3% |
12.8% |
|
Donetsk |
18.5% |
17.6% |
18.2% |
- |
- |
-0.9% |
0.6% |
- |
- |
|
Zhytomyr |
20.3% |
18.9% |
19.3% |
17.7% |
30.0% |
-1.4% |
0.4% |
-1.6% |
12.3% |
|
Transcarpathian |
20.4% |
19.2% |
19.7% |
18.5% |
30.5% |
-1.3% |
0.5% |
-1.2% |
11.9% |
|
Zaporizhzhia |
24.6% |
23.0% |
23.6% |
20.2% |
26.8% |
-1.7% |
0.7% |
-3.5% |
6.6% |
|
Ivano-Frankivsk |
21.3% |
20.8% |
21.5% |
21.4% |
32.1% |
-0.5% |
0.7% |
0.0% |
10.7% |
|
Kiev |
22.8% |
20.9% |
21.9% |
19.8% |
34.8% |
-1.9% |
1.0% |
-2.1% |
15.1% |
|
Kirovohrad |
19.2% |
17.9% |
18.8% |
18.4% |
30.1% |
-1.4% |
0.9% |
-0.4% |
11.7% |
|
Luhansk |
19.2% |
18.2% |
18.7% |
- |
- |
-0.9% |
0.4% |
- |
- |
|
Lviv |
33.3% |
30.6% |
31.1% |
30.8% |
46.2% |
-2.7% |
0.5% |
-0.3% |
15.4% |
|
Mykolaiv |
21.2% |
19.8% |
20.4% |
18.2% |
29.9% |
-1.4% |
0.6% |
-2.2% |
11.8% |
|
Odesa |
30.3% |
28.1% |
28.4% |
25.7% |
38.3% |
-2.2% |
0.3% |
-2.7% |
12.7% |
|
Poltava |
23.0% |
22.1% |
22.2% |
21.3% |
34.2% |
-0.9% |
0.2% |
-1.0% |
12.9% |
|
Rivne |
20.2% |
19.0% |
19.8% |
18.5% |
30.5% |
-1.2% |
0.8% |
-1.2% |
12.0% |
|
Sumy |
20.7% |
18.9% |
19.6% |
17.6% |
30.1% |
-1.7% |
0.7% |
-2.0% |
12.5% |
|
Ternopil |
22.1% |
20.0% |
20.6% |
20.0% |
32.0% |
-2.1% |
0.6% |
-0.6% |
12.0% |
|
Kharkiv |
37.9% |
35.9% |
36.0% |
30.8% |
42.4% |
-1.9% |
0.0% |
-5.1% |
11.5% |
|
Kherson |
20.7% |
19.2% |
20.0% |
- |
- |
-1.4% |
0.8% |
- |
- |
|
Khmelnytskyi |
21.4% |
20.6% |
21.1% |
20.1% |
32.1% |
-0.8% |
0.4% |
-0.9% |
12.0% |
|
Cherkasy |
22.0% |
20.9% |
21.4% |
20.4% |
32.2% |
-1.1% |
0.5% |
-1.0% |
11.8% |
|
Chernivtsi |
20.0% |
18.5% |
18.8% |
18.1% |
29.5% |
-1.5% |
0.2% |
-0.7% |
11.4% |
|
Chernihiv |
19.3% |
17.9% |
18.8% |
16.5% |
28.6% |
-1.5% |
0.9% |
-2.3% |
12.1% |
|
Kyiv |
56.8% |
53.1% |
55.5% |
51.4% |
85.4% |
-3.7% |
2.4% |
-4.1% |
33.9% |
Source: compiled by the author based on calculations
A graphic visualization of the distribution of regions of Ukraine by the state of the higher education system in the conditions of intellectual and innovative development of the territories is presented in Fig. 2.
Figure 2 – Cartogram of regions of Ukraine by the state of the higher education system in the context of intellectual and innovative development (2023)
Source: author's development
Conclusions
The scientific novelty of the study lies in the substantiation of the methodological principles of assessing the higher education system in the conditions of intellectual and innovative development of territories, which involves adhering to the principles of complexity and systematicity, as well as using the methodological apparatus of taxonomic analysis to obtain the complexity of the assessment, which involves constructing a system of descriptive indicators; qualitative analysis of the system of descriptive indicators; standardization of the values of constructing the observation matrix; construction of a “standard vector” and, based on it, calculating the value of the Euclidean distance; calculation of the integral indicator of assessing the state of the higher education system in the conditions of intellectual and innovative development.
The proposed methodological approach to assessing the higher education system in the context of intellectual and innovative development of territories using the example of regions of Ukraine was tested. Based on the results obtained, it can be stated that during 2019-2022, there was a significant deterioration in the state of higher education in the context of intellectual and innovative development of regions of Ukraine, which is explained by the direct effect of the factors of the coronavirus pandemic and the effect of the legal regime of martial law. The highest levels of decline in the integral indicator were recorded in Kharkiv region (from 37.9% in 2019 to 30.8% in 2022), Zaporizhzhia region (from 24.6% to 20.2%) and Kyiv city ( from 56.8% to 51.4%). However, during 2023, there is a gradual improvement in the functioning of the higher education system in the territories, which is due to the adaptation of the regions to the legal regime of martial law, at the same time, there is a slowed-down recovery dynamics among the front-line regions, and on the contrary, an accelerated recovery among the regions remote from the lines of hostilities. In general, it is worth noting the presence of significant disparities in the level of the functioning of the higher education system in the conditions of intellectual and innovative development of the territories, in particular, the highest levels are characteristic of Kiev, Lviv, Kharkiv, Dnipropetrovsk and Odessa regions, the lowest - Zaporizhzhia, Chernivtsi, Mykolaiv and Chernihiv regions.
The proposed methodological approach to evaluating the higher education system in the context of intellectual and innovative development of territories and the obtained test results have practical significance and can be used by higher education institutions, state, regional and local authorities to ensure more effective work of the higher education sector and increase its impact on ensuring intellectual and innovative development of territories.
Further research is required on the issues related to increasing the efficiency of higher education activities to ensure the intellectual and innovative development of regions.
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