The project-vector management method application in higher education quality assessment

Higher education system of Kazakhstan remains in transition, where preventive state regulation, fragmented evaluation procedures, and limited institutional autonomy still shape quality assurance practices. Existing assessment tools rely on isolated indicators and do not provide a systemic understanding of universities' progression toward desired quality levels. This study applies the project-vector management method as an analytical framework for modeling institutional trajectories in a multidimensional quality space. The research integrates secondary data from the Independent Agency for Quality Assurance in Education with a nationwide survey of 10,718 participants, including students, faculty, administrators, and employers, complemented by 19 expert interviews. The study was conducted in three stages: monitoring and classifying universities by achieved quality level; identifying systemic challenges through survey-based and interview-based SWOT analysis; and applying the project-vector method to calculate resistance coefficients and evaluate movement toward target quality indicators. The results demonstrate substantial variation in university performance across the five IQAA quality components. Survey findings highlight recurring problems such as limited infrastructure capacity, variability in teaching quality, insufficient internationalization opportunities, and inconsistent administrative procedures. SWOT analysis confirms that excessive preventive control, uneven resource allocation, and low levels of autonomy significantly increase systemic resistance. The project-vector calculations reveal that institutions with stronger resource bases and greater managerial flexibility show lower resistance coefficients and more stable trajectories toward the planned quality level. The study concludes that effective quality improvement requires shifting from control-oriented regulation toward data-driven, adaptive governance. The project-vector management method provides a transparent, diagnostic foundation for monitoring, interpreting, and supporting university development trajectories at both institutional and national levels.

1 Introduction

Project-vector management can be defined as the project assessment and management based on the vector model built as dependencies on different components. The main advantage of the method is its adaptability to changes in the project environment. In addition, it allows you to react quickly to every opportunity and challenge. The application of the vector models usually allows for high accuracy by considering many factors.

In the higher education context, a project is considered as the process, which includes planning and implementation of the tasks, thus increasing the efficiency of the university. Educational programs development and modernizing the technical infrastructure of the universities are common examples. The aim is to develop a higher education quality assessment system and further integrate it, considering international standards and the experience of modern analogous systems. Due to the global education quality evaluation complexity, which is attributed to very high diversity, the internal system at the state level can be considered. Creation of those systems is very significant not only for universities, but also for national economics and the community. Qualified fresh specialists are a valuable resource for every organization as their knowledge and experience, which are formed during the education process, increase the quality of the product or service. Therefore, the project-vector management method application in the higher education field during the creation of higher education monitoring systems is an urgent task. Detailed information on the technical components development for the project-vector management in the educational environment is described in Biloshchytskyi et al. (2018). The introduction of a quality monitoring system for higher education is an important process that requires a systematic approach and consideration of many aspects. The main features and aspects that should be taken into account when implementing such a system include:

- regulatory requirements and standards include both international and national standards, such as ISO 9004 on quality management (ISO 9004:2018, 2018) or the European Association for Quality Assurance in Higher Education (ENQA) standards (ENQA, 2023);

- attracting students, teachers, university administrators and employers through surveys and interviews;

- application of a process approach to the management and monitoring of the higher education institutions activities, continuous improvement of processes, development of plans and measures to improve the quality of higher education based on the obtained analysis;

- quality monitoring both at the state and at the university level;

- ensuring communication and developing a culture of quality among other things includes training and professional development of staff;

- development of university infrastructure at all levels to support the educational process.

This article evaluates the quality of higher education on the example of higher educational institutions of the Republic of Kazakhstan. It should be noted that the chosen country is currently reforming the higher education system. In addition, the supported by the Bologna Process and international accreditation of educational programs transition from the post-Soviet to the European system still in process. Moreover, the national legislative framework plays an important role, including the Law “On Education” and national educational standards. They define minimum requirements for the content of educational programs and qualification requirements. Kazakhstan also has national quality assurance agencies, such as the National Agency for Quality Assurance in Education (IQAA, n.d.). It is the main organization responsible for the accreditation of educational institutions and the assessment of the educational programs quality. In general, important steps have been taken to establish a system for monitoring the higher education quality. However, an important task is to establish the influence of the state regulation (preventive management) process, internal university monitoring and the educational programs accreditation process. The Kazakhstan higher education quality monitoring system is constantly developing with the consideration of international experience and national characteristics, which contributes to the competitiveness of educational services and the quality of specialists training. In this process, it is very important to create tools for effective higher education quality monitoring to provide recommendations to the institutions based on the analysis of quality change trajectories. One of the solutions is the application of project-vector management methodology, which in addition allows to analyze the problems in desired quality achievement. It also allows to compare the results among the country.

The practice study of the project-vector management methodology application in the educational sphere of developing countries undergoing transformational processes in higher education currently has high interest. An example of such a country is the Republic of Kazakhstan. Another important consequence of this area development could be the intensification of social communications and the development of society as a whole by improving the quality of higher education.

The purpose of the study is to develop and test the project-vector management method for assessing and improving the quality of higher education in universities, using the Republic of Kazakhstan as a case study.For the implementation the following tasks were set:

1. To monitor and evaluate the current level of quality of higher education institutions and to classify universities according to the achieved quality level.

2. To identify key problems in the quality assurance system of higher education through surveys and interviews with stakeholders, and based on the obtained results, to construct a SWOT analysis to determine strengths, weaknesses, opportunities, and threats.

3. To apply the project-vector management method to analyze the trajectory of each university toward achieving the desired quality level, including the calculation of resistance coefficients, in order to formulate recommendations for improving the quality of education.

It should be noted that previous studies on the education quality monitoring did not use this methodology and were mainly based on comparative analysis, as, for example, in Anafinova (2020).

2 Literature review

The national system of higher education in the Republic of Kazakhstan development and reforming problem has been the subject of research by scientists since the 1990s and continues to this day. The Republic of Kazakhstan joined the Bolon Process in 2003. In the early 1990s, the education system maintained a centralized regime with features inherited from the Soviet Union. The Ministry of Education played a central role in ensuring the quality of the higher education system. Gradually, the education system began to move from centralization to decentralization. In the new conditions, the main mechanism for ensuring the quality of higher education has become the implementation of the accreditation procedure for educational programs. This function has been transferred to independent agencies. Since about 15% of the territory of the Republic of Kazakhstan is geographically located on the European continent, the education system is increasingly approaching the European quality assessment system. Universities carry out international accreditation of educational programs, open English-language educational programs.

In Stensaker (2008), the growing discussion about quality management was called the “trend” of management. Quality is also becoming an agenda for external parties, such as government agencies and the business sector, not just universities. In Gulden et al. (2020), it is argued that the organization's ability and willingness to change directly affect the organization's management system. The study of institutionalism and its elements can help determine the organizational structures of universities and their response to the external environment. In Sluijsmans et al. (2015), quality assurance is considered as measures taken to determine the guaranteed quality of education. Quality assurance requires a comprehensive, integrative approach, since it involves a comprehensive assessment of the program's results, reflecting both the philosophy of the educational program and the complexity of the results (Jessop et al., 2012). Continuous improvement and quality assurance of evaluation requires “a transition from quality control (with an emphasis on accountability) to greater autonomy based on the experience and knowledge of stakeholders (Bendermacher et al., 2017). In studies Kleijnen et al. (2013) and Abad-Segura et al. (2020), quality is considered as a transformation, a process of change that increases the importance of students through their learning experience, which emphasizes the possibility of developing and improving students' competencies. Institutional quality management has become the most important issue in quality assurance and part of educational organization responsibility. Nowadays, universities face the challenges of providing high-quality services and maintaining competitiveness in national and international markets. Thus, quality assurance is considered as a “procedure” to maintain the required properties and characteristics of educational services as they are provided. It is important for an educational institution to know the cost-effectiveness of quality management processes.

The work Manarbek et al. (2019) argues that quality management tools, concept development and many management issues remain open and to make an objective decision in quality management, it is necessary to supplement and revise the factors of quality assessment, control and monitoring. In Sluijsmans et al. (2015), it was shown that an effective approach to improving external and internal quality is a self-assessment report, which can lead to improvement of specific points and increased awareness of quality assessment.

The education quality strategy ensures a qualitative process of continuous improvement. A single macro system integrated into the university system includes such components as the quality of the results of the educational system, the quality of the educational system and process, the quality of educational services and conditions. In Sarbu et al. (2009), when forming the process of managing the quality of education, it was suggested to consider and use modern management, control and monitoring tools. In Galkute et al. (2014), quality was identified as a central tool for the transformation of universities. To ensure quality in the context of sustainable development, the approach of “matching the goal” and continuous transformation in the context of achieving sustainable development is proposed. Based on the analysis of internal quality systems in the work Galkute et al. (2014), they concluded that the key role is played by “literate, open to change, inventive, ethically stable leaders of tomorrow and for this a deep transformation of universities is necessary.” In Mishin (2005), five important points that should be considered in the process of implementing quality assurance, such as guidelines, policies, goals, management mechanism and activities were identified. These five factors are considered as a source in the implementation of quality improvement.

The works Kerimkulova and Kuzhabekova (2017), Hartley et al. (2016), and Yelibay et al. (2022) describe the problems that have arisen in the process of reforming the higher education system in Kazakhstan. The identification of these problems, among other things, involves conducting qualitative surveys of stakeholders, students, employers and everyone who is directly or indirectly involved in the educational process or may affect the quality of educational services. In particular, the work Manarbek and Kondybayeva (2022) describes the mechanisms of using the ServQual measurement tool to determine the quality of services provided in the field of higher education from the point of view of students. The survey was conducted at al-Farabi Kazakh National University among 322 students. The results of this study can help higher education managers improve the quality of administrative services in order to meet students' expectations. However, the sample size was small, and it would be worthwhile to create questionnaires for other target groups of the university in order to more fully characterize the quality of educational services provided.

Currently, a triple system for assessing the quality of higher education has been formed, including preventive management (state regulation), accreditation procedures and internal university control. The paper Bokayev et al. (2022) analyzes new forms of quality management in higher education after the 2018 reform aimed at expanding the academic and administrative autonomy of universities (Zhospary, 2021). To assess the establishment and development of the institute of accreditation, a retrospective analysis of legislative acts, program and strategic documents was conducted. Based on the study of statistical data from government agencies and an expert survey conducted among senior management, faculty and staff of Kazakhstani universities their perception of the existing quality assurance system of higher education was assessed. The survey results indicate a moderately positive attitude of university representatives toward both the process of preventive state management and the process of independent accreditation. The obtained results were compared with the information of the Bureau of National Statistics (Stat.Gov, 2024). Nevertheless, there is a need to study the issues of university autonomy, the effectiveness of the system of preventive management and its impact on the quality of higher education.

Stakeholder surveys on the quality of higher education have also been conducted at other universities. In particular, the results of the survey were studied in Cardoso et al. (2013), considering gender, type of higher education institution and educational experience. A total of 962 responses were received from teachers of the Portuguese State higher education system. The data were processed using descriptive statistics, hypothesis testing and analysis of variance. The conclusion is that scientists generally support most of the goals of quality assessment, as well as the main characteristics of the new quality assessment and accreditation system. In (Stat.Gov), only the opinions of university professors were analyzed, so it would be advisable to expand the target groups to include students, teachers and the university administration. This is necessary to study the issue of ensuring the quality of education from different points of view.

The issue of accreditation of educational programs in higher educational institutions was discussed in Haakstad (2001). The general conclusion is that accreditation is an important mechanism for the functioning of the higher education quality system, if it is based on a flexible but enhanced approach to auditing. Accordingly, the education system of the Republic of Kazakhstan operates within the framework of the system of independent accreditation of educational programs, which improves the quality of educational services provided.

Another component of the quality system of higher education is internal university monitoring. The main criteria for assessing the quality of higher education are the quality of personnel, the quality of content, the quality of the student body, the quality of infrastructure and ensuring international relations. For the higher education quality assessment ensuring it is necessary to analyze a large set of factors that directly or indirectly affect the teaching, the work of the teaching staff and researchers, the international relations of the university, etc. All these components together form the educational environment of the university, which is transformed over time, increasing the quality of educational services provided. One of the methods of monitoring is conducting surveys among participants in the educational process.

According to the Global Knowledge Index (data for 2020) Kazakhstan took the 62nd place out of 138 countries with an indicator of 46.2 with a global average of 46.7 (Global Knowledge Index, 2020). In 2022, this figure dropped to 43.5 with a global average of 46.5. As a result, Kazakhstan took 78th place out of 132 countries (Global Knowledge Index, 2022). The worst rating was observed in the field of research, development and innovation. Average results were obtained in the fields of higher education, economics, information and communication technologies, technical and vocational education and training. Preuniversity education received the highest rating.

The problems of the higher education quality in Kazakhstan are based on several factors. Here are the main ones (Omirbayev et al., 2023):

- lack of autonomy of universities. Until 2018, the higher education system was under strict government regulation, losing flexibility in the face of global competition. As a result, there has been a rapid aging of educational content, outdated educational programs and limited opportunities for universities to offer students a variety of educational trajectories;

- insufficient financing, given the low solvency of the population. For a long time, the cost of government grants remained unchanged. This has led to low salaries for teachers and the aging of the material and technical base of universities;

- creation of a large number of higher education institutions that do not meet the qualification requirements.

These and other problems reduce the competitiveness and effectiveness of higher education, which, in turn, affects the development of society. To solve these problems, it is necessary to take comprehensive measures considering global trends and best practices, as well as strengthen the interaction of the state, universities, employers and society.

The analysis of scientific papers has shown that there are different approaches to the concept of “quality”: as a process, as a procedure and as a result. A combined approach to the definition of the concept of “quality” is also revealed, in which it (“quality”) is considered as a set of various components. Despite various attempts to formulate new theories and apply existing ones, researchers have yet to develop an updated theory of quality.

According to the analysis, main factors defining the “quality” are international reputation, high-quality research activity, the research nature of students, new subjects and courses and effective management (Omirbayev et al., 2023). It should be noted that quality management systems in higher education are gradually evolving from an emphasis on external control mechanisms, such as accreditation and ranking, toward strengthening the focus on internal mechanisms of quality assurance and the development of a quality culture within universities (Berkat, 2026). In study Miranda (2025), it is indicated that an important element of ensuring the quality of higher education is the consideration of three dimensions: input parameters, processes, and outcomes. Thus, to ensure the quality of higher education, it is important to take into account the emphasis on input parameters (state preventive regulation), processes (accreditation and internal monitoring), and outcomes (education quality indicators within the university). In all these areas, numerous difficulties can be observed that slow down the processes of ensuring the quality of higher education.

In particular, study Kristoffersen (2025) described a collective thematic investigation that included document analysis and semi-structured interviews with four quality assurance agencies. The results of the study revealed numerous interdependencies with stakeholders that must be managed for quality assurance agencies to ensure the quality of educational outcomes. Overall, all studies in this field emphasize the integration of internal quality assurance cycles with external accreditation requirements. Study Pham et al. (2022) described examples of indicators and procedures for using assessment results to implement changes in university programs. As a result, a framework (Purpose-People-Process) can be formed for internal quality assurance, which establishes a link between institutional monitoring processes and the responsibilities of university staff (Krooi et al., 2024). The features of the influence of external accreditation frameworks on the design of internal monitoring are described in study Carvalho et al. (2022). All this creates opportunities for the implementation of an effective internal quality assurance system in higher education and for efficient operational performance. At the same time, it is important to rationally select key quality indicators that should be incorporated into the university's quality assurance policy. The approaches to the formation of such indicators, including performance, learning outcomes, and quality culture, as described in study Brika et al. (2021), make it possible to establish a strong connection between the university's quality assurance policy, key indicators, and internal quality assurance cycles, taking into account the Plan-Do-Check-Act (PDCA) principle. Nevertheless, studies Mufanti et al. (2024) and Loukkola et al. (2020) indicate that the system of quality assurance indicators in universities requires improvement. Study (Loukkola et al. 2020) found that there is currently a critical lack of reliable indicators that measure learning outcomes at the practical level. Main disadvantage of the analyzed publications is the absence of the systematic approach for assessment. The evaluation results are mainly based on comparative analysis. Based on the results of monitoring the quality of education the objectives of this study include the classification of universities according to the achieved level of quality. Another important task is to formulate recommendations for improving the quality of education based on surveys and interviews of various target categories of participants in the educational process. A deep understanding of the components that affect the quality of higher education will allow to apply the method of project-vector management (Biloshchytskyi et al., 2018), calculate the coefficients of resistance of universities to the appropriate level of quality and assess resource availability. This will make recommendations for universities regarding the possible adjustment of the trajectory in the direction of ensuring an appropriate level of quality of higher education formulation possible. The literature review shows the need for an analysis of the higher education quality considering diverse approaches to understanding the quality. It is also an urgent task to conduct surveys for detailed screening of quality assurance problems at universities. There is also a necessity to study the application of the education quality management method, in particular the project vector method, to achieve the desired quality of education. This is necessary because traditional approaches do not allow for a comprehensive assessment of the dynamics and multifactor nature of the quality improvement process. They do not take into account the interconnections between different aspects of university activities and do not provide practical guidelines for resource allocation or management decisions. In particular, approaches such as the Balanced Scorecard or ServQual provide only a descriptive snapshot of the quality status at a given point in time, whereas the project-vector management method is a management tool capable of forecasting development trajectories and modeling improvements.

Thus, the analysis revealed that an important direction capable of linking the input parameters, processes, and outcomes of quality assurance, as well as formulating perspectives and providing recommendations for the further development of the university, is the application of the project-vector management method in a new context with comprehensive data and stakeholder integration.

3 Materials and methods

Assessment of the higher education provision quality is one of the key aspects of effective management of the university and the higher education system as a whole. The choice of quality assessment methods and the interpretation of quality assessment results affect various aspects of the activities of higher education institutions and form the basis for determining the quality of educational services provided. Within the framework of this project, it was planned to analyze possible problems arising in the quality assurance system of higher education in the country and provide recommendations on how to solve them.

The study consists of three stages. At the first stage, it is necessary to monitor the quality of higher education in higher educational institutions of the Republic of Kazakhstan and classify universities by quality level. At the second stage, it is necessary to assess the position of universities within each constructed classroom and formulate recommendations for improving the quality level based on SWOT analysis. It can be done based on the results of surveys and interviews on quality assurance issues at universities. At the third stage, it is necessary to apply the method of project-vector management to analyze the trajectory and evaluate. The project-vector management method was chosen to develop a systematic approach to evaluating and improving the effectiveness of universities, which is lacking in current practice. The higher education system in many countries faces the need to ensure continuous quality improvement in a measurable form. The project-vector management method provides the tools for this purpose by combining assessment with managerial actions. In addition, it aligns well with the multifaceted nature of quality assurance in education, which involves various stakeholder groups such as university administrators, faculty members, and students.

3.1 Terms and concepts

As the analysis of the literature shows, there are many interpretations of the concept of ensuring the higher education quality (Omirbayev et al., 2023):

(1) quality assurance as a process of formation and maintenance of the required properties and characteristics of educational services in higher educational institutions;

(2) quality assurance as a procedure for maintaining the required properties and characteristics of educational services in the form of which they are provided in higher educational institutions;

(3) ensuring the quality of higher education as a result of the formation of the required properties and characteristics of educational services in higher educational institutions;

(4) a combined approach to defining the concept of “quality” in a broad sense.

The concept of quality assessment of higher education includes processes and methods aimed at determining the degree of compliance of educational programs and institutions with established standards and requirements. Quality assessment includes the processes of accreditation, certification or licensing, monitoring of educational results, feedback from students and employers, comparative analysis or the formation of ratings. These processes are aimed at ensuring a high level of education, improving educational processes and achieving better results for students and society as a whole.

3.2 The project-vector management method for trajectory analysis and higher educational institutions resistance coefficients evaluation

It is known fact that higher education institutions operate within their educational environment. The management of each institution strives to achieve quality indicators that would enhance the reputation of the university. With the growing reputation of the institution, interest from future students is growing, scientific activity is intensifying, accelerating the movement of the institution to achieve the desired level of quality. Quality management is one of the key aspects of the project-vector management methodology, which is primarily applied to project management, as described in Biloshchytskyi et al. (2018). However, this concept can be effectively used to measure the state of a higher education institution and its path to the desired level of quality.

Let the accreditation agency set the direction of the higher education institution to achieve the required quality. Therefore,

$\begin{array}{l}{P}_i(t)=(x_1^i(t),x_2^i(t),\dots ,x_p^i(t))\end{array}$

where p is the number of criteria for evaluating the university's activities at a given time is the actual vector of the university's movement toward the desired quality indicator.

The movement in the project-vector space is due to the implementation of measures aimed at improving the quality of higher education.

Also, the planned vector can be given as:

$\begin{array}{l}{\widehat{P}}_i(t)=({\widehat{x}}_1^i(t),{\widehat{x}}_2^i(t),\dots ,{\widehat{x}}_p^i(t))\end{array}$

where ${\widehat{P}}_i(t)$ is the planned vector of the university's movement toward the desired quality indicator at time t.

Targets can be set by an accreditation agency or an organization responsible for the quality of higher education.

Therefore, the first differences in all components between the planned and actual vectors is calculated first. As a result, a management vector that will determine the trajectory of the university will have the following form:

$\begin{array}{l}{\tilde{P}}_i(t)=({\widehat{x}}_1^i(t)-x_1^i(t),{\widehat{x}}_2^i(t)-x_2^i(t),\dots ,{\widehat{x}}_p^i(t)-x_p^i(t))\end{array}$

where ${\tilde{P}}_i(t)$ is the administrative vector of the university's movement toward the desired quality indicator at time t.

Achieving the desired level of quality for each indicator of a higher educational institution in the project-vector space may require a different amount of resources. Let N = {N₁, N₂, …, N_p} represent the directions of movement that form the basis of the design vector space. The resistance to movement, which prevents the achievement of an appropriate level of quality of higher education according to the indicator, will be calculated using the following formula:

$\begin{array}{l}{O}_j^i(t)={\alpha }_j^i\left(\frac{\partial ({\widehat{x}}_j^i(t)-x_j^i(t))}{\partial t}\right),j=\overline{1,p},\end{array}$

where $O_j^i(t)$ is the movement resistance for the indicator N_j of higher education institutions U_i,$i=\overline{1,k}$, $j=\overline{1,p}$, $\frac{\partial ({\widehat{x}}_j^i(t)-x_j^i(t))}{\partial t}$ is the speed of movement; ${\alpha }_j^i$ is coefficient of movement resistance.

In general, the coefficient of resistance to movement ${\alpha }_j^i$ can depend, for example, on the level of infrastructure of a higher educational institution. If this level is satisfactory, then the coefficient ${\alpha }_j^i$ takes small values. If the level of infrastructure is unsatisfactory, then the coefficient ${\alpha }_j^i$ takes large values, thus increasing the overall resistance to movement $O_j^i(t)$. Resources needed to move in direction N_j, $j=\overline{1,p}$ are defined as follows:

$\begin{array}{l}{R}_j^i(t)=S·O_j^i(t),\end{array}$

where $R_j^i(t)$ represents the resources needed to counter the resistance $O_j^i(t)$ and overcome the distance S to achieve the desired level of higher education quality at the university.

It should be noted that the primary problem that may arise on the university's path to achieve the desired higher education quality is the growth of resistance to the movement $O_j^i(t)$. The increase in resistance is due to an increase in the coefficient ${\alpha }_j^i$. As a result of the increased resistance, planning is needed, which can be carried out taking into account the internal reserves of the university and additional allocation of resources $R_j^i(t)$. Additional allocation of reserves to overcome resistance is impossible in the case of low autonomy of the university. At the same time, e upper limits of the components of the motion vector L_j are planned and established by the state through preventive control, i.e. ${\widehat{x}}_j^i(t)\ge L_j$,$j=\overline{1,p}$. The rigidity of these restrictions determines the calculation of quality indicators at the university. For example, there may be a restriction that the number of teachers with a Doctor of Philosophy (PhD) degree should be more than 50% of the total number of teachers. According to the system of criteria for accreditation of higher educational institutions of Kazakhstan, there are five such criteria (IQAA, n.d.).

Thus, considering the project-vector management methodology concept it is established that the influence of preventive control occurs at the level of setting restrictions on the vector components values, which determine the direction of movement of universities to the desired higher education quality level. An accreditation agency at the second level of quality assessment influences goal setting. Intra-university control is implemented at the level of resource redistribution. Effective redistribution is influenced by a sufficient level of autonomy of universities. Additionally, the resistance to the movement of the university is influenced by the availability of resource and logistical support or infrastructure, determined by the value of the coefficient. As can be seen, all components of the higher education quality assessment system are interconnected and ensure the progressive movement of the university toward achieving the appropriate level of quality.

3.3 Project-vector method application for the higher education quality assessment in institutions of the Republic of Kazakhstan

The methodology of the institutional rating conducted annually by the Independent Agency for Quality Assurance in Education is taken as the basis for monitoring the higher education quality in universities of the Republic of Kazakhstan (IQAA, n.d.). This methodology includes five components:

1. The academic resources quality assessment in universities. This component reflects the academic activities of universities. Universities provide the agency with the initial data, which are verified by various methods. Some of the information is requested by IQAA from sources unrelated to universities.

2. Expert assessment of the university's activities quality. The expert pool is determined by the Agency.

3. Evaluation of the university's activities based on a sociological survey of employers and government agencies.

4. Evaluation of the university's activities based on a sociological survey of students. The results of the survey determine the reputation of the university “through the eyes of students”.

5. Assessment of the university's activities based on a sociological survey of graduates. The results of the survey determine the reputation of the university, especially in terms of the level of professional training and employment results, according to graduates.

According to the IQAA methodology (IQAA, n.d.), the integral assessment of the university is calculated as a weighted sum of five components. Let U = {U₁, U₂, …, U_k} is higher education institutions set, each of which has certain quality indicators calculated according to the definition of the accreditation body. The integral score is then calculated using the following formula:

$\begin{array}{l}{\Phi }^i(t)={\displaystyle \sum _{j=1}^5}{\beta }_j{E}_j^i(t),\end{array}$

where Φⁱ(t) is integral score of U_i university, $i=\overline{1,k}$ at time t; k is number of higher educational institutions. $E_1^i(t)$ is assessment of the academic resources quality of the university U_i at time t. $E_2^i(t)$ is expert assessment of the quality of the U_i university's activities at time t. $E_3^i(t)$ is assessment of the university's activities U_i at time t based on a sociological survey of employers and authorities. $E_4^i(t)$ is the assessment of the university's activities U_i based on a sociological survey of students at a given time t. $E_5^i(t)$ is the assessment of the U_i university's activities H and based on a sociological survey of graduates at the time of t. Weight coefficients β_j they are determined by the evaluation system and with the condition that $\sum _{j=1}^5{\beta }_j=1$. In the IQAA methodology (IQAA, n.d.), the weight coefficients have the following values:β₁ = 0.8, β₂ = β₃ = β₄ = β₅ = 0.05.

Unlike the IQAA, n.d. assessment methodology, according to the design vector methodology, the university assessment is represented as a point in a multidimensional space (in this case, a five-dimensional one) (see Figure 1). Taking into account statistical data on the assessment of the quality of higher education in universities, it is possible to trace the trajectory of the university in this space. The goal of any higher education institution is to achieve the appropriate maximum level of quality.

Figure 1

Figure 1. The concept of the projector-vector method.

Figure 1 shows the concept of the design vector method. The real trajectory of the university's movement in the five-dimensional space of higher education quality assessment is shown. This trajectory can be built as a result of monitoring. Under the influence of the vector of administrative influence, the trajectory is adjusted. When calculating the magnitude of the vector of administrative impact, it is important to take into account the resistance of the environment in which the movement takes place.

After calculating the grades of higher education institutions or the higher education quality provided at these universities, it is possible to classify universities according to the level of maximum quality achievement. Those universities that are in the first class (where the quality is the highest) will be exemplary, and other universities belonging to different classes will adjust their trajectories to be included in the first class in the next period.

3.4 Screening and interviews on quality assurance issues at universities

Surveys were conducted among students, teachers, university administration and employers of all higher educational institutions of the Republic of Kazakhstan to achieve the purpose of the study. Additionally, interviews were conducted with experts in the higher education field to identify the main problems hindering the improvement of the higher education quality assurance system. On the basis of project-vector management, the theoretical justification of the interrelationships between the components of triple management, as well as the influence of restrictions imposed by preventive management on the speed, at which the university achieves the required level of quality of higher education, is determined.

3.4.1 Permission to reuse and copyright

Students, teachers, administrative staff and employers participate in the effective functioning of the higher education quality assurance system in institutions. Therefore, the sample for the survey was formed on the basis of these four categories (detailed in Table 1). The sample type is typical, the sample is stratified. The heterogeneous population was divided into typological groups according to significant characteristics and a sample was made from each group. The age range of the participants is from 20 to 49 years old, among them 48% of men and 52% of women. Participants from all regions of the Republic of Kazakhstan were selected for the survey.

Table 1

Table 1. Participants target groups in the survey on the higher education quality system.

One of the target groups of the study are students (target group I) enrolled in bachelor's and master's degree programs at higher educational institutions of the Republic of Kazakhstan. Students who took part in the survey are enrolled in bachelor's degree and enter universities in the 2020–2021 academic year (32.7%), 2021–2022 academic year (26.4%) and 2022–2023 academic year (16.1%). The masters, who took part in the survey, enrolled in the university in the 2021–2022 academic year (12.3%) and in the 2021–2023 academic year (12.5%). The survey was conducted from May 20 to June 27, 2023. The students, who took part in the survey, studied philology, psychology, sociology, history, law, economics, politics, as well as information and communication technologies, international relations, art, journalism.

Another target group of survey participants was the teaching staff (target group II), including assistants, associate professors and professors. All participants are affiliated with higher educational institutions of the Republic of Kazakhstan and work in these institutions on a permanent basis. The target group of administrative staff (target group III) included representatives of the university management and employees of various departments: planning and finance, international relations, academic affairs and others. The target group of employers (target group IV) included directors and managers of companies employing graduates of higher educational institutions of the Republic of Kazakhstan, who are familiar with the work of graduates and their level of knowledge.

In addition, for a deeper study of the survey results, a separate interview was conducted in September 2023 among three categories: five independent experts, six university staff and eight employers, including nine women and 10 men aged 31–56 years. The selection of experts was based on their extensive experience in the field of higher education quality assurance. The group of experts included representatives of national accreditation agencies, university administrators, and policy experts in higher education. It should be noted that the sample of 19 individuals is relatively small. Nevertheless, the study prioritized ensuring diversity of perspectives by covering different regions and types of institutions, while selecting only highly qualified experts whose conclusions are significant, reliable, and relevant.

3.4.2 Tools

The questionnaires were created to conduct the survey. They are the main tool for collecting information on the higher education provision quality. The survey was conducted anonymously, which allowed the participants of the target group to freely answer the questions posed.

The questionnaire for the target group was divided into several categories: the university admission process, the university infrastructure and the educational process. A five-point scale was used for the evaluation. Respondents were asked to rate each item on a scale from 1 to 5, where 1 indicated the lowest (negative) rating and 5 indicated the highest (positive) rating. Specifically, for statements related to quality or level of agreement, 1 corresponded to “strongly disagree” (or very low quality), 5 to “strongly agree” (or very high quality), and 3 represented a neutral or moderate position. For example, when a respondent indicates that “the average score of the quality assurance system was 3.5,” it should be understood that this value is above the neutral level, reflecting a somewhat positive assessment (“satisfactory”), since the context of the scale is clearly defined. The first category was asked the following questions: “Did you go through career guidance at school?”, “What influenced your choice of university to study?”, “What influenced your choice of educational program to study?”, “How do you assess the process of admission to university?”, “What was difficult for you when have equal admission and training conditions been created for people of different social groups, has inclusivity been ensured, etc.?

The following questions were asked to the second category: “How satisfied are you with the infrastructure of your university?”, “Evaluate the quality of the infrastructure on a five-point scale”, “Do you think that the infrastructure of your university meets the requirements, rules and standards of work for people with special needs?”.

The third category was asked the following questions: “Please rate the listed areas of activity of your university on a five-point scale.”, “What is the relevance of the content of the disciplines you study?”, “Please rate the quality of classes on a five-point scale according to the specified parameters”, “How would you rate the level of qualifications on a five-point scale to the faculty of the university conducting your classes?”, “How satisfied are you with the work and communication of your faculty?”, “Do students have access to international libraries and scientific literature portals?”, “Are there conditions at the university for academic mobility of students abroad?”, “Have you participated in academic mobility programs?”

The survey for target group II includes the following categories: the level of resource provision and the quality of content.

The first category was asked the following questions: “Indicate how satisfied are you with the university's infrastructure?”, “Indicate whether the university has enough classrooms for comfortable learning?”, “Do you consider the availability of a number of educational and scientific literature is the university (including electronic media) enough for students and teachers?”, “Evaluate the quality of medical facilities located at the university?”, “Are you satisfied with the quality of the table at the university?”, “Evaluate the quality of infrastructure on a five-point scale”, “Does the university's infrastructure comply with all the rules and standards for people with special needs?”

In the second category, the following questions were asked: “Do you think that students receive modern knowledge and skills?”, “Assess the level of training of applicants”, “Are you satisfied with the functional responsibilities and tasks?”

The survey of administrative and managerial personnel includes the following questions: “How do you assess the qualification requirements for educational activities of universities?”, “Do you think that the quality assurance system has improved/the quality of education has improved in your university based on the results of recent inspections (state control/preventive control) of an authorized state body in in the field of education and science?”

The questionnaire for employers included the following questions: “Assess your satisfaction with the quality of training of young specialists (university graduates) when applying for a job”, “What criteria for training young specialists do you consider the most important?”, “Do you think that employers should participate in the development of educational programs at universities?”, “Ready does your organization provide/send its specialists to train and train students either on the territory of the university or in your organization?”

For the interview, the questions were formulated in three main blocks:

- understanding the key concepts of the higher education quality assurance system;

- assessment of the existing quality assurance system (control and accreditation);

- recommendations for improving the quality assurance system of higher education.

3.4.3 Procedure

The survey was conducted in all universities of Kazakhstan within the framework of the educational project Astana IT University (Republic of Kazakhstan) (see the section financing). The studies involving humans were approved by The Committee on Research Ethics, Astana IT University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.The survey was conducted online, which ensured the requirement of anonymity. A link to the online questionnaire was provided to the participants of task force I–III via corporate email. This ensured that responses were given directly by participants from the relevant target groups. Repeated responses were not possible because the link sent by corporate email allowed only one response. The questionnaire was sent to the participants of group IV by personal e-mail. The questionnaire was available to the public from May 20 to June 27, 2023. In September 2023, interviews were conducted with experts in the field of higher education. The questions for the questionnaire and the interview were chosen in order to reveal and highlight the problems of ensuring the necessary quality of higher education in universities, as well as to explore possible ways to solve these problems. After this period, an analysis of the results was carried out and assessments of quality assurance of higher education in universities of the Republic of Kazakhstan were established. The results obtained are important for reforming the higher education sector, bringing it to international standards, etc.

Let us describe in more detail how the sample of respondents was formed. To ensure the representativeness of the empirical study, a cluster sampling approach was applied, covering all administrative regions of the Republic of Kazakhstan. Within each cluster, a simple random sampling without replacement was conducted among four stakeholder groups of the higher education system: students, academic staff, administrative and management personnel, and employers. The sample size was determined using the formula described by Krejcie and Morgan (1970) for a known population at a 95% confidence level and a margin of error of 5%. The calculations were performed under the assumption of maximum variability (p = q = 0.5), which corresponds to a conservative approach when no prior data on the distribution of characteristics are available. The total sample size was 10,718 individuals, including 7,595 students, 2,502 academic staff members, 292 administrative and management personnel, and 329 employers. The standardized questionnaire survey method was used for data collection, ensuring the comparability of results across different respondent groups. The questionnaires included both closed (dichotomous, scale-based, and multiple-choice) and open-ended questions.

To ensure the reliability of the results, the internal consistency coefficient α by Cronbach (1951) was calculated, with α ε (0.78, 0.89) for different thematic sections, which indicates high reliability of the instrument. The validity of the questionnaires was confirmed through expert evaluation of the content of the questions and their correspondence to the research objectives.

The obtained empirical data were processed using MS Excel software. Inferential statistics were applied for the analysis of relationships between categorical variables, one-way analysis of variance (ANOVA) was used to compare mean values among respondent groups, and correlation analysis was conducted to identify relationships between the level of satisfaction, the quality of the educational process, and infrastructure. The interpretation of the results was carried out considering the level of statistical significance (p < 0.05) and the contextual relevance of the identified trends. This approach ensured a comprehensive evaluation of the collected data, verification of their reliability, and the possibility of reproducing the results in further studies.

4 Results

4.1 The results of the analysis of the higher education quality in the Republic of Kazakhstan

As indicated in Section 3, at the first stage we obtained official annual assessments of universities based on five key criteria of education quality. Using these data, we conducted our own analysis to rank and classify universities according to their quality level, identifying groups of institutions with consistently high quality indicators and those with unstable or lower results. As a result of the analysis of the IQAA rating (IQAA, n.d.), data on 13 leading universities of the Republic of Kazakhstan for the period from 2020 to 2023 were selected. These universities train specialists in various fields of knowledge. The monitoring results are presented in Table 2. All the universities for which the grades were calculated and ranked according to the maximum number of points. Based on the calculated scores, the trajectories of the universities' movement toward ensuring the appropriate level of quality according to the project-vector method were constructed (see Figure 2).

Table 2

Table 2. Rating for universities of the Republic of Kazakhstan.

Figure 2

Figure 2. Trajectories of higher education institutions to ensure an appropriate quality level.

The trajectories of higher educational institutions were studied in a five-dimensional space. Analyzing the trajectories of movement, two main classes of universities can be distinguished. The first class, with the highest quality indicators, includes Al-Farabi Kazakh National University, Satbayev University and KIMEP University. These universities are characterized by consistently high scores according to all criteria. Therefore, for other universities, these universities can be considered reference for achieving the appropriate level of quality of higher education. In addition, during the international rankings analysis, in particular QS World University Rankings, it is worth noting the high positions of these universities, which are constantly improving (see Table 2). If a university holds a high position in the QS ranking, this generally corresponds to a high quality of higher education at that university.

The second class includes the rest of the universities. In these institutions, in 2021 and 2022, there was a decrease in quality indicators compared to 2020, and in 2023 there was an increase. This decrease may be due to objective reasons, such as the COVID-19 pandemic and a change in the form of education for higher education applicants.

As a result of the analysis, the necessity of using methods of higher education quality management, in particular project-vector management, has been established. For a more detailed study of the features of the implementation of this method, a screening of the higher education quality in institutions of the Republic of Kazakhstan was conducted.

In 2023, a massive online survey of students, teachers, administrative and managerial staff and employers of the Republic of Kazakhstan was conducted to identify problems in the field of higher education quality assurance. Let's look at the survey results for each target group.

According to the results of the first target group survey, 76% of respondents stated that they received vocational guidance at school. Career guidance at school is an integral part of the university admission process as it provides data on the preferences, inclinations and opportunities of students and helps to build a flexible system of interaction between universities and institutions of additional and vocational education. The distribution of answers to this question considering the profile of the educational program is shown in Table 3. An analysis of the profile of the respondents' educational program indicates that students in pedagogical areas were less likely to receive vocational guidance at school (13.0%).

Table 3

Table 3. Distribution of answers to the question “Did you have a professional orientation at school?” taking into account the profile of the educational program.

When choosing a higher education institution, respondents most often relied on the recommendations of friends and relatives (25.9%), and also considered the location of the institution (22.5%). A significant part of the respondents also considered the location of the institution (17.6%) (see Figure 3). Students primarily focused on the high probability of employment (35%) and the prestige of their future profession (27.8%) as the factors for an educational program choice (see Figure 4). Interestingly, men mostly based their choice of university on lower tuition fees (43%) and teaching staff (38%), while women were influenced by the choice of parents (67%) and the number of grants available at the university (66%).

Figure 3

Figure 3. Distribution of answers to the question “What influenced your choice of higher education institution to study?”.

Figure 4

Figure 4. Answers distribution to the question “What influenced your choice of an educational program of study?”.

The first category was asked the following questions: “Indicate how satisfied you are with the infrastructure of the university?” The survey results indicate that the university admission process as a whole does not cause problems. In general, 59.8% of respondents noted that the admission process was simple and understandable, 32.9% replied that it was generally good, but had some difficulties, 3.7% considered it bad and difficult, and 2.9% found it difficult to answer. The most difficult stages were testing or exams and choosing a university (see Figure 5). Most respondents believe that admission creates equal opportunities for different groups of people. To the question “Are there equal conditions for admission and education for people of different social groups, which is inclusivity ensured?” 55.6% of respondents answered “Yes,” 25.7% answered “Rather yes,” 6.9% answered “Rather no,” 8.8% answered “No,” and 3.0% found it difficult to answer.

Figure 5

Figure 5. Distribution of answers to the question “What was difficult for you when applying?”.

Study Omirbayev et al. (2023) analyzed the influence of architectural and planning solutions in the design of university campuses on the effectiveness of educational and scientific processes. The focus group was universities, in which the premises are organized considering the interests of intra-university groups. It was revealed that this factor stimulates students to actively acquire knowledge, and scientists and teachers to generate and distribute the knowledge. The survey results show that students are generally satisfied with the infrastructure of their university. 44.8% were completely satisfied, 31.0% were rather satisfied, 9.8% were rather dissatisfied, 4.8% were completely dissatisfied and 4.0% were difficult to answer. The greatest satisfaction was noted regarding the availability of the library and the university grounds. The least satisfaction is with the functioning of Wi-Fi, etc. (see Figure 6). One of the main components of a high-quality university infrastructure is its accessibility for people with special needs. When asked whether the university's infrastructure complies with the rules and standards for people with special needs 38.2% of respondents answered “Yes,” 29.3% answered “Rather yes,” 13.5% answered “Rather no” and 5.6% answered “No.”

Figure 6

Figure 6. Answers distribution to the question “Evaluate the quality of infrastructure on a five-point scale?”.

The educational process is a procedure in which a student or listener learns a certain set of disciplines, acquiring certain knowledge and skills necessary in life. The organization of this process requires consideration of several factors and conditions. According to the survey, students are less satisfied with the opportunity to choose a teacher, desired course or subject, as well as with the consideration and processing of student complaints (see Figure 7). Speaking about the knowledge gained, in the combined answers “Yes” and “Rather yes than no,” 72.5% of respondents believe that the disciplines they study may be useful in the future. The relevance of knowledge is generally appreciated. To the question “What is the degree of relevance of the content of the disciplines you study?” 34.7% of the answers are in the range from 71 to 90%, 27.9%—in the range from 91 to 100%, 14.8%—in the range from 50 to 70%, and 4.9%—in the range from 0 to 50%. Regarding the quality of classes, students express the greatest dissatisfaction with the audience and the format of classes (see Figure 8).

Figure 7

Figure 7. Answers distribution to the question “Please rate the following areas of activity of your university on a five-point scale?”.

Figure 8

Figure 8. Distribution of responses to the question “Please rate the quality of classes on a five-point scale according to specified parameters?”.

As for the assessment of teachers' professional qualities, in all categories the majority of students give positive evaluations (4–5 points), which range from 61.1% to 66.8%. The highest scores are observed for “Knowledge of the subject, mastery of educational material” (66.8%), “Demanding requirements for the knowledge and skills of students” (66.7%), and “Interaction with students during classes, contact with students” (65.1%). At the same time, from 19.1% to 24.9% of respondents rate these qualities negatively (1–3 points), with the greatest share of critical assessments related to “Knowledge of modern technologies and teaching methods” (24.9%). Around 14% of students in each category did not give an answer. The detailed distribution of students' evaluations of teachers' qualities is presented in Figure 9.

Figure 9

Figure 9. Answers distribution to the question: “How would you rate the level of qualification of university teachers who teach your classes on a five-point scale?”.

Students positively assess the work and communication of their department: 40.6% are completely satisfied, 30.5% are rather satisfied, 7.2% are rather dissatisfied and 3.1% are completely dissatisfied. To the question “Do students have access to international libraries and portals of scientific literature?” 53.8% answered “Yes,” 23.2%—“I find it difficult to answer,” 9%—“No.” At the same time, 46.9% of respondents believe that the university has created conditions for the possibility of academic mobility abroad, 21.5% answered “Rather yes than no,” 7.2% answered “Rather no than yes,” and 2.9% answered “No.” In addition, 28.9% of students participated in academic mobility programs.

Monitoring the effectiveness of teachers' activities is a necessary condition for the full functioning of the university's infrastructure. Along with the survey of students, a survey of target group II: the teaching staff was conducted. The survey results show that 37.2% of teachers are completely satisfied with the university's infrastructure, 39.4% are “Rather satisfied,” 12.6% are “Rather dissatisfied” and 5.3% are “Completely dissatisfied.” In addition, 51% of teachers indicated that, in general, there are enough classrooms for classes, 23.7% answered “More than enough classrooms,” 20.2% answered “Fewer classrooms than necessary,” and 4.6% answered “Critically few class-rooms.”

The survey of employers (target group IV) included the question: “Assess your satisfaction with the quality of training of young professionals (university graduates) when applying for a job,” to which 57.1% answered “Fully satisfied,” 22.8% “Rather satisfied,” 11.9% “Partially satisfied,” 4.0% are “Rather dissatisfied” and 0.9% are “Completely dissatisfied.” The most important criteria for training young professionals are considered by the employers to be “Practical skills and understanding of how to do work” (48.9%), “Readiness to learn” (19.7%) and “Theoretical knowledge” (14.6%). To the question “Do you think employers should participate in the development of educational programs at universities?” The majority of respondents (81.2%) answered “Yes, they should.” To the question “Is your organization ready to provide/allocate its specialists for the education and training of students both at the university and on the territory of your organization?” the majority (86.6%) also answered “Yes.”

The results of the analysis show that there are problems in certain components of the higher education quality. For a more detailed analysis of these components and the formation of recommendations for their elimination, an expert method can be used and a SWOT analysis conducted.

4.2 The results of the expert survey and SWOT analysis

As already mentioned in Section 3, at the beginning of 2023, an interview was conducted in three categories. The survey was formed of three blocks: a discussion of the basic concepts of the system and, with the exception of cases where there are grounds, assessments that include the lack of data on the resolution, recommendations for improving the systems.

For the analysis of the collected empirical survey data, descriptive and inferential statistical methods were applied, which made it possible to identify patterns in the perception of higher education quality among different stakeholder groups. The calculations were performed using Microsoft Excel software.

Descriptive statistics showed that the overall level of student satisfaction with the quality of the educational process is quite high. The mean score was 4.12 with a standard deviation of 0.84 and a 95% confidence interval within the range (4.09, 4.15). This indicates the stability of the obtained results (p < 0.05). The academic staff demonstrated slightly lower satisfaction levels regarding the infrastructure. The mean score in this group was 3.87 with a standard deviation of 0.91 and a 95% confidence interval within the range (3.82, 3.92) at p < 0.05. The administrative and management personnel evaluated this aspect at an average level of 3.95, with a standard deviation of 0.76 and a 95% confidence interval within the range (3.88, 4.02) at p < 0.05. Among employers, the average level of overall satisfaction with the preparedness of graduates was 3.76, with a standard deviation of 0.88, which is also statistically significant at p < 0.05. The proportion of positive responses among students who consider the acquired knowledge relevant was 76%, and among employers satisfied with the training level of young specialists was 79.9%. All these ratios are statistically significant. The Shapiro–Wilk normality test (Shapiro and Wilk, 1965) confirmed the absence of deviations (p > 0.05), which provides grounds for applying parametric analysis methods.

To test the hypotheses regarding the interdependence of variables, the χ² criterion was used. The analysis revealed a statistically significant relationship between students' field of study and their level of satisfaction with the admission process, χ² = 45.27, p < 0.05 with 15 degrees of freedom. A similar relationship was found between respondents' gender and the determining factors for choosing a university, χ² = 62.14, p < 0.05 with 10 degrees of freedom. A dependence was also observed between the respondent's position and the evaluation of infrastructure quality, χ² = 33.85, p < 0.05 with 8 degrees of freedom. Thus, socio-demographic characteristics have a significant impact on the assessment of the quality of the educational environment.

The one-way analysis of variance (ANOVA) confirmed the existence of statistically significant differences among the four respondent groups in terms of the overall satisfaction index with the higher education system. The value of the Fisher statistic was 8.92, with 3 degrees of freedom for the factor and 10,714 degrees of freedom for the residuals, at p < 0.05, and an effect size of 0.013. Accordingly, the examined factor explains ~1.3% of the total variance in the dependent variable, indicating a very small effect. The highest mean scores were observed among students (4.12), while slightly lower scores were reported by academic staff (3.87), administrative personnel (3.95), and employers (3.76). Tukey's range test showed that the most pronounced difference was observed between students and employers, which is logically explained by the difference in their perspectives and evaluation criteria of education quality.

The correlation analysis using Pearson's r coefficient made it possible to determine the degree of interrelation between individual satisfaction indicators. A moderate positive correlation was found between satisfaction with infrastructure and the quality of the educational process (r = 0.62; p < 0.05), as well as a strong relationship between the quality of teaching and the level of satisfaction with the work of the department (r = 0.74; p < 0.05). At the same time, a moderate level of correlation was observed between students' involvement in extracurricular activities and the overall assessment of the university (r = 0.49; p < 0.05), as well as between the evaluation of institutional leadership and the overall level of satisfaction with management processes (r = 0.58; p < 0.05). These interrelations confirm that the quality of material and technical resources, organizational culture, and human capital of universities have a direct impact on the perception of the quality of the educational process.

In summary, it can be stated that the results of descriptive and inferential statistics confirm the high internal consistency of the obtained data, and all identified relationships are statistically significant at the p < 0.05 level.

To date, in the Republic of Kazakhstan, there are three main tools for quality control and quality assessment in the quality assurance system of higher education:

- preventive control based on risk criteria;

- independent assessment of accreditation;

- the system of internal catering in universities.

The development of these tools influenced the inclusion of the Republic of Kazakhstan in the Bologna process and the expansion of academic freedom of universities. According to the majority of respondents gathered during the interview, the higher education system has a sufficient legislative framework for the functioning of universities and the use of academic freedom. However, during the interview, opinions were expressed that universities are still reluctant to take on this responsibility, which leads to the creation of new additional instructions and rules for them. People from the target group noted that preventive management is a barrier to academic freedom development due to its focus on education quality management. The document was prepared and includes risk criteria. A large number of consequent accreditations creates a big gap in the concept of the real education process and quality criteria. Due to the low number of doctors of science, the quality of the teaching staff is not improving. Another problem is related to living conditions, including the salary, which is better in the big cities like Astana and Almaty. Therefore, the educational institutions meet the problem of the low-quality staff in universities of small cities. However, there are experts who, on the contrary, support the system of profile control, since this approach sets the framework within which the activities of universities should be carried out. It is indicated that at the institutional level, preventive control is more important in order to see the compliance of the laboratory base, the ratio of the quality of teachers' work. And at the level of the educational program, accreditation is required, but with the involvement of experts who correspond to the educational program. However, it was noted that there is disagreement between the committees on educational activities, which causes problems in educational activities. Regarding the adopted legislative acts, university staff noted that such laws and regulations are adopted without discussion. That is, even if a working group is created, its work is carried out formally. Therefore, the system needs to be reformed. Conducting examinations and questioning different target groups of participants in the educational process will give a vision of the movement of these changes in the right direction.

Thus, during the interview, the majority of respondents noted the restrictive function of preventive control in the implementation of academic freedom, the autonomy of universities, the lack of discussion of adopted legislative acts, the inexpediency of some indicators of risk criteria in a rapidly developing economy.

On the issue of accreditation, many experts noted that today in the Republic of Kazakhstan there is a good experience in the development of the institute of accreditation and the legislative framework. The formation and development of the institute of accreditation was positively noted among the respondents, however, there is a lack of interference with the activities of the agencies themselves, established and recognized in the territory of Kazakhstan. Thus, many employers stressed that it is necessary to introduce a system of independent assessment of the quality of education with the involvement of experts from other countries. This will allow for objective assessments and comparisons with international standards, which can help identify the strengths and weaknesses of the education system. In the accreditation procedure, an important aspect is independence and objectivity, which are achieved through the involvement of independent experts, including employers and students. During the interview, many respondents noted the importance of this issue and the low activity of these individuals in the accreditation procedure. Often, the credit agencies themselves include such persons right before accreditation, without conducting appropriate training and explanations. Therefore, there is a low activity and lack of experience of these stakeholders in the accreditation process. At the same time, respondents noted that during various inspections and accreditation procedures, universities prepare reports, documents containing many different statistical data. However, most often, this data is not processed and is not used in decision-making. This problem is more related to the functioning of the internal quality assurance system in universities. To date, it has been legislatively approved to create such a system and universities, that are successful and are formally forming them. But the respondents note that, in general, the quality policy at universities is more formal and is not related to the university's development strategy (Morey, 2004).

Based on the results of the SWOT analysis of the interview responses and these recommendations, as well as on the results of the questionnaire, it is possible to determine the advantages and disadvantages of the current system of quality assurance of higher education in the Republic of Kazakhstan (Figure 10).

Figure 10

Figure 10. SWOT analysis based on the results of a survey of four target groups and interviews with experts in the field of higher education.

Therefore, it is necessary to note such recommendations for improving the system of higher education and ensuring its quality, which were given during the interview and based on the results of the survey of four target groups:

- it is necessary to finalize the state policy, explain to the participants of the educational process what the quality assurance system is, accreditation, and then special attention will be paid to it;

- it is necessary that the focus be shifted from control to ensuring the quality of education and trust in those bodies involved in monitoring;

– it is important that transparent methods for calculating quality indicators (qualification requirements) be published;

- the concept of “quality” would be conceptually defined by the state, and each university would develop its own quality criteria for itself and this would not be dictated from above, then each university could be creative in its activities;

- it is necessary to increase the financing of higher education.

To realize the strengths and avoid threats, while introducing opportunities, considering weaknesses, the method of project-vector management can be applied for assessing higher education quality.

It should be noted that the strengths and weaknesses were identified primarily based on internal feedback from stakeholders (survey responses and interview comments regarding positive and problematic aspects of university operations). At the same time, the opportunities and threats were identified based on external factors discussed by experts, as well as trends noted in national education reports. The results obtained from the SWOT analysis are of great importance for ensuring university quality management, and each conclusion has a well-grounded explanation. For example, “a well-equipped library and a modern collection of literature” was included among the strengths, as it provides resource support for the educational process and contributes to improving the quality of education. The statement “low quality of Wi-Fi coverage” was included among the weaknesses, as it hinders the development of digital learning and research, which is critically important for modern higher education. The statement “participation in academic mobility programs” represents an opportunity, as it promotes integration into the global educational space, while “demographic growth amid the aging of academic staff” constitutes a threat, since the overall demand for education is increasing, whereas the human resource potential may decline. Thus, each element of the conducted SWOT analysis affects the achievement of the main goal: improving the quality of higher education. The analysis was carried out with consideration of recognized systemic problems to ensure the validity of the obtained results.

Based on the results of the survey and interviews, a cross-validation was conducted to determine whether the problems identified by experts coincided with those reported by survey participants. We found a significant level of consistency (for example, both data sources highlighted university autonomy and funding as critical issues), which increases the credibility of our results.

4.3 The project-vector management method application for the motion trajectory analysis and the universities resistance to movement coefficient assessment

The project-vector management method provides the possibility of adjusting the higher education trajectory in the direction of achieving an appropriate quality level. These adjustments can only be made by higher education skill management. But there is monitoring data and open data on the available resources of each university, by which recommendations can be made for this adjustment. The formulas for calculating resource consumption (5)-(6) to estimate the resistance coefficients can be used to create those recommendations. The budget of higher education is considered as resources. For example, the amounts received by universities for student tuition. According to the data Forbes.kz (Forbes, 2022a,b,c), the largest amount of funds under this article was received by the AEO “Nazarbayev University” (see Table 4).

Table 4

Table 4. Amounts received by universities for student tuition, million USD.

Under certain assumptions $d_j^i(t)=\frac{\partial ({\widehat{x}}_j^i(t)-x_j^i(t))}{\partial t}$ can be roughly calculated as a divided difference $\frac{\Delta x_j^i}{\Delta t}$, Δt is a period of time, for example 1 year, a $\Delta x_j^i$ is the increase in the j assessment criterion for the university and for the corresponding period of time.

For example, the resistance coefficients can be calculated using the example of Auezov South Kazakhstan State University in the period of 2021–2023 years. Using the formula of divided differences, we get an approximate value d₁(t) = −0.03, d₂(t) = 0.105, d₃(t) = 0.07, d₄(t) = 0.045, d₅(t) = 0.065. Total budget Auezov South Kazakhstan State University during this period reaches to 8.7 million USD. Let the distribution of funds as resources to ensure overcoming resistance to movement occur with coefficients β₁ = 0.8, β₂ = β₃ = β₄ = β₅ = 0.05. Then the resistance coefficients can be found from formulas (5) and (6): α₁ = 232, α₂ = 4.1, α₃ = 6.2, α₄ = 9.6, α₅ = 6.7. These values can be used to build an administrative management vector for 2024. Similarly, resistance coefficients can be found for other institutions of higher education.

It is possible to more rationally allocate limited resources without losing the quality of higher education provision by calculating the coefficients of higher education institutions resistance. Based on the concept of design vector control (Figure 1), it is possible to form impact vectors based on these calculations to achieve the desired quality level by the institution of higher education.

5 Discussion

The methodology for calculating the grades of higher education institutions (IQAA, n.d.) by 2019 considered three criteria. Therefore, in the study Anafinova (2020), higher education institutions of the Republic of Kazakhstan were analyzed using this methodology. Starting in 2020, this methodology was improved and began to consider five criteria that determine the quality of higher education at universities. In this study, an improved methodology for calculating university grades was chosen as the basis and the quality of higher education was monitored based on it. According to the monitoring results, all analyzed institutions of higher education were divided into two classes. The first class includes universities with consistently high-quality education. The second class includes universities where the quality level is unstable and may decrease under the influence of unfavorable factors, for example, the COVID-19 pandemic. The distribution into classes is necessary to identify reference universities in which the quality level is consistently high. In the context of the project-vector management method, the indicators of first-class universities can determine the planned growth indicators of the quality level trajectory for second-class universities. Estimates of the coefficients of resistance to the movement of universities to the planned quality level were calculated to determine the allocation of resources for the formation of the administrative influence vector.

A questionnaire for four target groups and interviews with experts in the field of higher education were conducted to form recommendations on improving the quality. According to the results of which a SWOT analysis was conducted, which allowed to identify the opportunities and threats to the activities of higher education institutions. According to the results of the survey, it can be noted that the quality assurance level of higher education in the Republic of Kazakhstan is satisfactory. Based on the results of the survey of four target groups, a SWOT analysis was conducted. The strengths include: active career guidance, a simple and understandable university admission process, ensuring equal conditions for university admission, a well-formed library and a fund of modern literature, accessibility of university management and relevance of the disciplines taught, a sufficient number of classrooms for teachers and good training of applicants. Weaknesses include: poor provision of Wi-Fi connectivity at universities, poor quality of medical facilities and technical equipment at universities, a difficult university admission process in terms of testing, poor quality of university infrastructure for people with special needs, lack of university autonomy and bureaucracy, low quality of university infrastructure for people with special needs, lack of university autonomy and bureaucracy, low financing of the higher education system Opportunities are the participation of students in academic mobility programs, participation of students in the collegial management bodies of the university and employers in the creation of educational programs. Threats are a significant demographic growth of the population and along with this an increase in the average age of teachers, low motivation for applicants to universities in the Republic of Kazakhstan and the rapid aging of the material and technical base of universities.

Thus, based on the results of the survey and interviews, the concept of project-vector management is confirmed. In particular, it is a preventive management that sets too strict restrictions on the components of the university's movement vector toward the planned quality indicator. This leads to a slowdown in movement due to an increase in resistance. The accreditation agency influences goal setting, and internal university control is implemented at the resource allocation level. Effective redistribution is influenced in turn by a sufficient level of higher education institutions autonomy. Moreover, the resistance to the movement of the university is influenced by the availability of a resource for material-technical support or infrastructure. Accordingly, all components of the higher education quality system within the project-vector methodology framework are closely related and violation of one of the indicators entails significant changes in the movement of the university until the appropriate higher education quality level is achieved. For example, insufficient resource provision and outdated infrastructure may be associated with the establishment of too strict restrictions at the preventive management level and vice versa.

This study presents the first systematic implementation of the project-vector approach to the assessment of higher education quality based on a national dataset (Kazakhstani universities), marking a transition from conceptual preliminary research to full-scale empirical application. In particular, the five-criteria IQAA model was integrated with the project-vector approach, meaning that universities were represented in a multidimensional space with the tracking of their trajectories toward the target quality level. The study also introduced quantitative resistance coefficients for parameters that hinder movement toward defined vector goals. The combination of a large-scale survey of four stakeholder groups (students, faculty, administrative staff, and employers) and expert interviews, followed by a structured SWOT analysis, made it possible to validate the proposed approach. The theoretical assumptions of the model are consistent with empirical observations, indicating that low institutional autonomy, excessive formalism, and resource deficits determine a slower dynamic of improvement.

The project-vector model assumes that excessively rigid preventive management (that is, strict state requirements) acts as a resistance vector, which can slow a university's progress toward quality improvement goals if not compensated by sufficient resources or autonomy. Our empirical results indeed revealed evidence of this phenomenon: many respondents and experts identified bureaucratic regulations and the lack of autonomy as the main obstacles in the system, and we classified them as key weaknesses and threats in the SWOT analysis. According to the model, these factors correspond to an increase in the strength of the “resistance” vector that hinders development. Similarly, insufficient funding and outdated infrastructure, which were frequently mentioned during the surveys and interviews, are interpreted by the model as elevated resistance coefficients caused by resource deficits. These identified issues precisely correspond to the factors that the model defines as resistance amplifiers. Strict accreditation criteria and state control (preventive management) without sufficient autonomy lead to a slowdown in improvement. This dynamic is confirmed by our data, as universities with higher levels of bureaucracy or lower autonomy showed stagnation in quality rankings. Similarly, where funding (the resource factor) was limited, progress was hindered, which is consistent with the model's assumption of high resistance caused by a lack of resources.

The results obtained indicate the need to reform the quality assurance system of higher education in terms of creating transparent accreditation mechanisms, adjusting criteria for preventive management and reviewing the status of other higher education quality assurance system components according to the project-vector management concept.

It should be noted that many of the problems and dynamic patterns identified in this study are not unique to Kazakhstan. For example, the tension between state regulatory control and university autonomy in quality assurance systems is a common theme in higher education worldwide, as noted in the study by Miranda (2025). Similarly, issues related to insufficient funding, outdated infrastructure, and the need to engage stakeholders in quality assurance processes are observed in many countries, particularly those developing or reforming their higher education systems. The identification of such threats as “outdated infrastructure” or “low motivation of teaching staff” may also be relevant for other countries with similar socio-economic conditions. Accordingly, the solutions proposed in this study (for example, increasing investment in infrastructure, implementing reforms to strengthen autonomy, and enhancing staff motivation) may be applicable beyond our specific case.

In the case of international application, the project-vector management method would require adaptation of quality criteria and survey instruments to the local context, as well as more frequent data collection (if possible) to more accurately track trajectories. Nevertheless, the project-vector model is capable of operating with any set of quantitatively measurable indicators. Despite the need for adaptation, the fundamental advantage of the method, providing a systematic quantitative tool for quality management, remains valid in any educational environment.

The limitation of this study is determined by the fact that the methodology described in (IQAA, n.d.) was used as a basis for monitoring the higher education quality at universities in the Republic of Kazakhstan. This technique allows to calculate the higher education quality assessments at universities once a year. And for the more correct application of the design vector control method, it is necessary that estimates are calculated more often, at least once a quarter or month. Another limitation is that the monitoring and application of the design vector control method was carried out for higher education in the Republic of Kazakhstan. Also, questions during the survey and interviews related to ensuring the quality of higher education in the Republic of Kazakhstan. If these approaches are used to analyze the quality of higher education in other countries, it is possible to significantly adjust the course of research and adapt questions during questionnaires and interviews.

Among the disadvantages of the study, it should be noted that interviews with experts in the higher education field were conducted among 19 people. More experts should have been involved. In addition, the disadvantage is that the data on the resources of the Republic of Kazakhstan universities are partially open. Moreover, the quality assessments of higher education are calculated only for a certain number of universities. In particular, for young higher education institutions with a significant amount of funding, according to the assessment described in (glavnyiy; Studencheskaya; Dohodnyiy), quality assessments have not been considered. Such universities include Nazarbayev University and Astana IT University. In the future, it is planned to develop research in the direction of creating information systems for assessing the quality of higher education in the Republic of Kazakhstan. At the same time, access will be provided for more data required for the application of the design vector control method. Another future direction is to test the project-vector management model in higher education systems of other countries. An additional promising area of research is to study how the development of an internal quality culture within universities can reduce resistance and improve development trajectories. This would make it possible to combine the described quantitative approach with the socio-behavioral aspects of change management. In particular, it would be useful to investigate how leadership, staff motivation, or student participation in decision-making affect the effectiveness of the quality assurance system. Another promising direction is the creation of international comparisons based on the project-vector approach. If several countries apply the model, it will be possible to compare their “resistance coefficients” among universities in different states to identify systemic factors that some countries address more effectively than others. This opens the way for the development of international policy based on comparative data.

6 Conclusions

To accomplish the first task, the universities were classified into two categories based on their quality of performance: universities with consistently high quality and universities with unstable quality. The universities in the first category can be used as benchmarks for the institutions in the second category.

To accomplish the second task, the main problems identified during the study (in particular, insufficient university autonomy, limited funding, outdated infrastructure, etc.) were summarized, and potential directions for improvement were determined based on the results of the SWOT analysis and stakeholder surveys. In addition, the positive aspects (strengths) that can serve as a foundation for further improvement of the system were identified.

To accomplish the third task, the concept of project-vector management was applied to the collected data, which made it possible to construct the trajectories of universities and calculate their resistance coefficients. This made it possible to determine that some universities experience high resistance in certain criteria (such as research performance or infrastructure) and to provide recommendations to university management on reducing this resistance through appropriate resource reallocation. Thus, the conclusion demonstrates the implementation of the third objective of the study, namely the practical application of the project-vector management method for analytical evaluation, trajectory modeling, and the formulation of recommendations for improving university quality.

The paper analyzes the main problems of ensuring the higher education quality in the Republic of Kazakhstan. The project-vector management methodology concept was taken as a basis, which describes the university movement toward achieving the desired quality level. Initially, higher education quality monitoring was carried out in Kazakhstani institutions and the distribution of universities into classes according to the quality level was carried out. Subsequently, questionnaires and interviews were conducted to ensure the education quality at universities. The survey was conducted among four target groups (students, academic staff, administrative staff, employers) among all universities in Kazakhstan. Based on the results of the survey, a SWOT analysis was conducted, which determined the main directions for the possible reformation of the higher education system and improvement of its functioning in the Republic of Kazakhstan. The main problems identified by the experts are the lack of competence and expert level of accreditation and preventive management experts at universities, as well as a formal approach to testing and quality management, thus, after quality management, there are no actions that would improve the situation in higher education. As a result of imperfections in the process of implementing preventive management in universities, the gap in understanding the higher education quality and the real provision of the educational process in the universities activities is growing. That is, a formal approach to monitoring educational activities does not entail sufficient improvement. Locally, at the university level, the survey results were attributed to poor Wi-Fi connectivity, poor quality of medical facilities and technical equipment at universities, a difficult admission process, and poor quality of university infrastructure for people with special needs. In addition, there is a lack of autonomy of universities and low funding of the higher education system.

From the project-vector management point of view in the Kazakh higher education system, preventive management sets limits on the components of the movement vector, accreditation procedures are responsible for goal setting, and intra-university control establishes the possibilities of redistributing resources to overcome the external environment resistance. If the resistance is small, then the movement speed of the university before reaching the appropriate quality is greater. The resistance coefficient is also established, which, for example, is determined by the availability of infrastructure at the university and material and technical support. All components of the higher education quality system within the framework of the project-vector methodology are closely related and violation of one of the indicators entails significant changes in the movement of the university to achieve the appropriate higher education quality level.

Based on the analysis results, it can be concluded that too strict restrictions on the components of the university's motion vector (preventive management) increase resistance to movement and in combination with insufficient funding and infrared structural support (coefficient of resistance) and insufficient level of autonomy of universities, which determines the possibility of resource influence on reducing resistance, leads to a delay is the continuation of the university's movement toward achieving the desired level of higher education quality. Therefore, approximate resistance coefficients were calculated to assess why some higher education institutions are moving faster to the desired level of quality, while others are moving slower. Based on the results, recommendations were made to the higher education institutions management to adjust the movement trajectories.

The obtained results of the analysis of the higher education quality in Kazakhstan will allow at the legislative level and at the university level to consider threats and disadvantages in the quality assurance systems implementation. This will increase the students knowledge level, improve infrastructure, intensify scientific work and raise the rating of higher educational institutions in Kazakhstan. The obtained results demonstrate that the project-vector management method is an effective and informative tool for assessing the quality of higher education, as it makes it possible to diagnose systemic problems and identify pathways for improvement using the example of universities in Kazakhstan.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Ethics statement

The studies involving humans were approved by the Committee on Research Ethics, Astana IT University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

AM: Conceptualization, Data curation, Supervision, Writing – review & editing. SO: Conceptualization, Project administration, Writing – review & editing. OK: Formal analysis, Methodology, Writing – original draft. AB: Conceptualization, Project administration, Writing – review & editing. YA: Data curation, Formal analysis, Methodology, Writing – review & editing. SB: Formal analysis, Writing – review & editing. IK: Writing – review & editing. AI: Writing – review & editing, Validation.

Funding

The author(s) declare that no financial support was received for the research and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Gen AI was used in the creation of this manuscript.

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