IN THE ADVANCEMENT OF DIGITAL ECONOMY EVALUATING STUDENT SATISFACTION IN ACADEMIC-FINANCIAL INDEPENDENT HEIS: A CASE STUDY OF BUKHARA STATE UNIVERSITY Текст научной статьи по специальности «Экономика и бизнес»

IN THE ADVANCEMENT OF DIGITAL ECONOMY EVALUATING STUDENT SATISFACTION IN ACADEMIC-FINANCIAL INDEPENDENT HEIS: A CASE STUDY OF BUKHARA STATE UNIVERSITY

Yuldashev Feruz Isroil ugli

PhD researcher at Bukhara State University f.i.yuldashev@buxdu.uz

Abstract: This article presents advanced methodologies for evaluating and enhancing the quality of education in higher education institutions (HEIs). By integrating multiple dimensions such as educational efficiency, research productivity, student activity, and organizational efficiency, we propose enhanced formulas that incorporate interaction and higher-order terms. These complex indicators, including variables such as student performance, satisfaction, research output, and institutional support, provide a comprehensive framework for assessing HEI competitiveness. The educational efficiency formula, for instance, considers student-to-teacher ratios and academic capacity, while research efficiency accounts for publications and citations. The inclusion of interaction terms and non-linear effects captures the multifaceted nature of HEI performance. This approach allows for more nuanced insights, enabling HEIs to identify key areas for improvement and implement targeted strategies to enhance overall educational quality. The proposed methodology is exemplified through data from Bukhara State University, demonstrating its practical application and potential for widespread adoption.

Keywords: higher Education Institutions (HEIs), Educational Quality Management, Educational Efficiency, Research Productivity, Student Activity Efficiency, Organizational Efficiency, Interaction Terms, Higher-Order Terms, Student Satisfaction, Academic Performance, Research Output, Institutional Support, Competitiveness Indicators, Quality Enhancement, Bukhara State University

RAQAMLI IQTISODIYOTNI RIVOJLANTIRISH SHAROITLARIDA AKADEMIK-MOLIYAVIY MUSTAQIL OTMLAR TALABALARNING QONIQISH DARAJALARINI BAHOLASH: BUXORO DAVLAT

UNIVERSITETI MISOLIDA

Yuldashev Feruz Isroil o'g'li

Buxoro Davlat Universiteti tayanch doktoranti f. i.yuldashev@buxdu.uz

Annotatsiya: Ushbu maqolada oliy ta'lim muassasalarida (OTM) ta'lim sifatini baholash va oshirishning ilg'or metodologiyalari keltirilgan. Ta'lim samaradorligi, tadqiqot samaradorligi, talabalar faoliyati va tashkiliy samaradorlik kabi bir nechta o'lchovlarni birlashtirib, o'zaro ta'sir va yuqori darajadagi atamalarni o'z ichiga olgan kengaytirilgan formulalar taklif qilingan. Ushbu murakkab ko'rsatkichlar, jumladan talabalarning ta'lim olishi, ta'lim xizmatlaridan qoniqishi, tadqiqot natijalari va institutsional qo'llab-quvvatlash kabi o'zgaruvchilar, OTM raqobatbardoshligini baholash uchun keng qamrovli asos bo'lib xizmat qiladi. Masalan, ta'lim samaradorligi formulasi talaba-o'qituvchi nisbati va akademik salohiyatini hisobga oladi, tadqiqot samaradorligi esa nashrlar va iqtiboslarni hisobga oladi. O'zaro ta'sir atamalari va chiziqli bo'lmagan effektlarning kiritilishi OTM faoliyatining ko'p qirrali xususiyatini aks ettiradi. Ushbu yondashuv yanada nozik tushunchalari anglashga imkon beradi, bu esa OTMlar uchun takomillashtirishning asosiy yo'nalishlarini aniqlash va umumiy ta'lim sifatini oshirish uchun maqsadli strategiyalarni amalga oshirishga imkon beradi. Taklif etilayotgan metodologiya Buxoro Davlat universiteti ma'lumotlari orqali namuna bo'lib, uning amaliy qo'llanilishi va keng qo'llash imkoniyatlarini namoyish etadi.

Kalit so'zlar: oliy ta 'lim muassasalari (OTM), ta 'lim sifatini boshqarish, ta 'lim samaradorligi, tadqiqot samaradorligi, talabalar faoliyati samaradorligi, tashkiliy samaradorlik, talabalarning qoniqishi, akademik ko'rsatkichlar, ilmiy natijalar, institutsional qo'llab-quvvatlash, raqobatbardoshlik ko'rsatkichlari, sifatni oshirish, Buxoro Davlat Universiteti

В РАМКАХ РАЗВИТИЯ ЦИФРОВОЙ ЭКОНОМИКИ ОЦЕНКА

УДОВЛЕТВОРЕННОСТИ СТУДЕНТОВ В АКАДЕМИЧЕСКИ-ФИНАНСОВЫХ НЕЗАВИСИМЫХ ВУЗАХ: НА ПРИМЕРЕ БУХАРСКОГО ГОСУДАРСТВЕННОГО УНИВЕРСИТЕТА

Юлдашев Феруз Исроилович

докторант Бухарского государственного университета f. i.yuldashev@buxdu.uz

Аннотация: В этой статье представлены передовые методики оценки и повышения качества образования в высших учебных заведениях (ВУЗАХ). Объединяя множество показателей, таких как эффективность образования, продуктивность научных исследований, активность студентов и эффективность организации, мы предлагаем усовершенствованные формулы, которые включают взаимодействие и термины более высокого порядка. Эти сложные показатели, включающие такие переменные, как успеваемость студентов,

удовлетворенность, результаты научных исследований и институциональная поддержка, обеспечивают комплексную основу для оценки конкурентоспособности вуза. Например, формула эффективности образования учитывает соотношение числа студентов и преподавателей и академические способности, в то время как эффективность научных исследований определяется публикациями и цитируемостью. Включение условий взаимодействия и нелинейных эффектов отражает многогранный характер деятельности вуза. Такой подход позволяет получить более детальную информацию, позволяя вузам определять ключевые области для улучшения и реализовывать целенаправленные стратегии для повышения общего качества образования. Предлагаемая методология проиллюстрирована данными Бухарского государственного университета, демонстрирующими ее практическое применение и потенциал для широкого внедрения.

Ключевые слова: высшие учебные заведения (ВУЗы), управление качеством образования, эффективность обучения, эффективность исследований, эффективность студенческой деятельности, организационная эффективность, удовлетворенность студентов, академическая успеваемость, научные результаты, институциональная поддержка, показатели конкурентоспособности, повышение качества, Бухарский государственный университет

INTRODUCTION

The integration of the digital economy into the evaluation of student satisfaction in academically and financially independent higher education institutions (HEIs) offers several significant advantages. These advantages stem from the enhanced capabilities provided by digital tools and technologies in collecting, analyzing, and interpreting data. Higher education plays a crucial role in the global economy and management. It is a key driver of economic growth, innovation, and competitiveness. Higher education institutions (HEIs) contribute to the development of human capital by equipping individuals with advanced knowledge and skills necessary for the labor market (Marginson, 2011). The knowledge and innovation generated by universities are essential for technological advancements and industrial development (Teixeira & Dill, 2011). Furthermore, HEIs are pivotal in fostering critical thinking, problem-solving abilities, and leadership skills, which are vital for effective management and governance. The landscape of higher education is continuously evolving, driven by globalization, technological advancements, and changing societal needs. As it can be seen in various social sectors in the form of growing emphasis on international collaboration, student mobility, and cross-border education (Knight, 2008), the integration of digital technologies in teaching, learning, and administration which is

transforming the educational experience (Sá & Serpa, 2020). Furthermore, the focus shifting towards continuous learning opportunities, catering to the needs of diverse learner populations is next social requirement that government should keep on motivating(Jarvis, 2008).

Bukhara State University (BukhSU) as one of the prominent higher education institutions in Uzbekistan is also recognized with actively participation in national and international level competition for supporting educational reforms. Recently, BukhSU was among the 40 higher education institutions in Uzbekistan granted autonomy by the government. This move towards autonomy is part of a broader strategy aimed at improving the quality of higher education, fostering innovation, and enhancing institutional accountability and governance.

LITERATURE REVIEW

The digital economy, characterized by the pervasive use of digital technologies and the internet, has significantly transformed higher education. According to Brynjolfsson and McAfee (2014), digital technologies enhance educational processes by improving access to information, fostering interactive learning environments, and enabling data-driven decision-making. The digital economy's tools, such as big data analytics, cloud computing, and mobile technologies, provide new opportunities for evaluating and enhancing student satisfaction (Manyika et al., 2011). The concept of autonomy in higher education is well-documented in a lot of academic literature. According to Altbach and Knight (2007), university autonomy refers to the degree of self-governance necessary for effective decision-making regarding academic, financial, and administrative matters. Autonomy allows institutions to innovate, respond to changing educational demands, and improve their competitive standing (Neave, 2012). This autonomy encompasses various dimensions, including academic freedom, financial independence, and administrative self-governance (Berdahl, 1990). Autonomy is associated with enhanced institutional performance, increased efficiency, and greater responsiveness to student and labor market needs (Shattock, 2010). A study by Estermann and Nokkala (2009) found that autonomous universities are better positioned to foster academic excellence and innovation. Furthermore, autonomy can lead to improved governance structures, as institutions gain the flexibility to tailor their management practices to their unique contexts (Fielden, 2008). While the benefits of autonomy are substantial, the transition process is not without challenges. Universities must develop robust governance frameworks and ensure accountability mechanisms are in place (Salmi, 2009). The shift to autonomy also requires a cultural change within institutions, as faculty and administrators adapt to new roles and responsibilities (Marginson & Considine, 2000). Additionally, there is a need for adequate funding and resources to support the transition and sustain autonomous operations (Clark, 1998). In

Uzbekistan, the move towards university autonomy is part of broader educational reforms aimed at modernizing the higher education sector. These reforms are designed to align the country's educational standards with international best practices and improve the overall quality of higher education (Ministry of Higher and Secondary Specialized Education of the Republic of Uzbekistan, 2020). The autonomy granted to institutions like BukhSU is expected to empower them to innovate, enhance educational quality, and better meet the needs of students and society. Such legislative framework as "On measures to provide financial independence to state higher education institutions", "On approval of the procedure for financing from the state budget of the republic of Uzbekistan for the training of personnel on the basis of a state order (state grant) in state institutions of higher education for which financial independence has been granted" and "On additional measures to ensure academic and organizational and managerial independence of state higher education institutions" are considered main documents supporting this transition that are crucial to supply the completion of the process.

METHODOLOGY

Digital tools facilitate efficient and accurate data collection from a large number of students across various faculties and departments. Online surveys, feedback forms, and digital assessments can be easily distributed and collected, ensuring higher response rates and reducing the time and resources required for data collection. Advanced data analytics tools can process this data quickly, providing real-time insights and enabling more nuanced analysis of student satisfaction. A survey was conducted among students from various faculties at BukhSU to gather their perceptions of different aspects of their educational experience. The survey included questions on overall satisfaction with the educational process, the relevance of course content, teacher knowledge, classroom suitability, and the availability of educational resources. The survey data were collected and analyzed using SPSS to identify correlations between different factors affecting educational quality.

RESULTS AND DISCUSSION

This study focuses on evaluating student satisfaction and the quality of educational services at BukhSU following its transition to autonomy. By analyzing student perceptions and feedback, this research aims to provide insights into the effectiveness of the autonomy model in enhancing higher education quality. The study uses survey data collected from students across various faculties to assess their satisfaction with different aspects of their educational experience, including course content, teacher knowledge, classroom suitability, and resource availability. Overall, 2383 respondents participated in the survey from 8 faculties and they answered 10 questions in likert scale answering system. In the Figure 1, the composition of

respondents by faculty is described in percentages according to which, students who actively participated in the survey mainly (46%) correspond to the share of foreign languages and history and law faculties.

faculties1

Based on the data of Figure 2, it can be said that most of the respondents who have an excellent assessment of the quality of the classes to be organized, come to the Faculty of philology (58%), foreign languages (55%) and physics and mathematics (52%). The faculties of Economics and tourism (16%), agronomy and biotechnology (11%) and Information Technology (10), on the other hand, cover the respondents with the highest average assessment of the quality of the classes.

It is not for nothing that the practice of organizing high-level classes at the university is effectively organized. In the current situation, the university operates 69 doctors of Sciences and professors, as well as 287 candidates of Sciences (PhD) and pedagogical employees with the title of Associate Professor (including 8 who have successfully carried out scientific work Protection in the world's prestigious Top-1000 list of universities). The scientific capacity index was 24.2% in 2020, while it reached 32.1% by 2023.

1 Designed by the Author

□ Bad ■Poor □ Mediocre BGood ■Excellent

Picture 2. Percentage of Student Competition results in faculty cross section2

The survey included questions on overall satisfaction with the educational process, the relevance of course content, teacher knowledge, classroom suitability, and the availability of educational resources. To facilitate the analysis and presentation of the results, the questions were coded numerically as Q1 to Q10.

The coding of the questions is as follows:

1. How satisfied are you with the educational process at your university?

2. Are there students in your group who do not regularly attend classes but still get ratings and advance from course to course?

3. How well does the content of the courses match your field and future career goals?

4. Evaluate the knowledge of teachers in their respective subjects.

5. Are the size and comfort of the classrooms suitable for effective learning?

6. Evaluate the availability and quality of educational resources (libraries, laboratories, online materials).

7. Are sufficient and clear instructions provided before exams?

8. Is student feedback considered in the organization of exams?

2 Designed by the Author

9. How well do the exam questions cover the curriculum?

10. Do the teaching methods used in the educational process encourage critical thinking and reflection?

Based on the correlation matrix (Table 1), we can draw several conclusions about the relationships between different aspects of the educational experience at the higher education institution. Here are some key observations:

Table 1

Correlation analysis of the survey results3

1 2 3 4 5 6 7 8 9 10

Pears. Cor 1 -099** ,258** ,191** ,126** ,192** ,065** ,103** -,073** -0,012

1 Sig. (2- tailed) 0 0 0 0 0 0,002 0 0 0,556

N 2383 2383 2383 2383 2383 2383 2383 2383 2383 2383

Pears. Cor -,099** 1 -,067** -,165** -,081** -,132** -,042* -0,021 ,156** -0,006

2 Sig. (2-tailed) 0 0,001 0 0 0 0,038 0,305 0 0,775

N 2383 2383 2383 2383 2383 2383 2383 2383 2383 2383

Pears. Cor ,258** -,067** 1 ,145** 0,037 ,127** ,106** ,147** -0,016 -0,002

3 Sig. (2-tailed) 0 0,001 0 0,072 0 0 0 0,421 0,923

N 2383 2383 2383 2383 2383 2383 2383 2383 2383 2383

Pears. Cor ,191** -,165** ,145** 1 ,201** ,268** ,092** -0,04 -,271** ,144**

4 Sig. (2-tailed) 0 0 0 0 0 0 0,05 0 0

N 2383 2383 2383 2383 2383 2383 2383 2383 2383 2383

Pears. Cor ,126** -,081** 0,037 ,201** 1 ,242** 0,03 0,027 -,146** ,041*

5 Sig. (2-tailed) 0 0 0,072 0 0 0,14 0,188 0 0,045

N 2383 2383 2383 2383 2383 2383 2383 2383 2383 2383

Pears. Cor ,192** -,132** ,127** ,268** ,242** 1 ,053** 0,014 -,187** 0,014

6 Sig. (2-tailed) 0 0 0 0 0 0,01 0,484 0 0,487

N 2383 2383 2383 2383 2383 2383 2383 2383 2383 2383

Pears. Cor ,065** -,042* ,106** ,092** 0,03 ,053** 1 ,109** -0,022 0,007

7 Sig. (2-tailed) 0,002 0,038 0 0 0,14 0,01 0 0,286 0,736

N 2383 2383 2383 2383 2383 2383 2383 2383 2383 2383

Pears. Cor ,103** -0,021 ,147** -0,04 0,027 0,014 ,109** 1 ,121** 157**

8 Sig. (2-tailed) 0 0,305 0 0,05 0,188 0,484 0 0 0

N 2383 2383 2383 2383 2383 2383 2383 2383 2383 2383

Pears. Cor -,073** ,156** -0,016 -,271** -,146** -,187** -0,022 ,121** 1 -,155**

9 Sig. (2-tailed) 0 0 0,421 0 0 0 0,286 0 0

N 2383 2383 2383 2383 2383 2383 2383 2383 2383 2383

Pears. Cor -0,012 -0,006 -0,002 ,144** ,041* 0,014 0,007 -,157** -,155** 1

10 Sig. (2-tailed) 0,556 0,775 0,923 0 0,045 0,487 0,736 0 0

N 2383 2383 2383 2383 2383 2383 2383 2383 2383 2383

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

3 Compiled by the Author using SPSS

1. Overall Satisfaction with Educational Process (Q3):

• Q3 and Q5: There is a significant positive correlation (r=0.258r=0.258, p<0.01p<0.01) between overall satisfaction and the relevance of course content. This suggests that students who find the course content relevant to their future careers are more likely to be satisfied with the educational process.

• Q3 and Q6: A significant positive correlation (r=0.191r=0.191, p<0.01p<0.01) exists between satisfaction and the perceived knowledge of teachers, indicating that knowledgeable teachers contribute to overall satisfaction.

• Q3 and Q8: There is a significant positive correlation (r=0.192r=0.192, p<0.01p<0.01) between satisfaction and the availability/quality of educational resources, highlighting the importance of resources in student satisfaction.

2. Presence of Non-Performing Students (Q4):

• Q4 and Q6: A significant negative correlation (r=-0.165r=-0.165, p<0.01p<0.01) suggests that the presence of non-performing students is associated with a lower perception of teachers' knowledge.

• Q4 and Q8: A significant negative correlation (r=-0.132r=-0.132, p<0.01p<0.01) between non-performing students and the availability/quality of educational resources implies that non-performing students might be linked to poorer perceived resource quality.

3. Relevance of Course Content (Q5):

• Q5 and Q6: There is a significant positive correlation (r=0.145r=0.145, p<0.01p<0.01) between the relevance of course content and the perceived knowledge of teachers. Relevant course content seems to align with better teacher knowledge.

• Q5 and Q8: A significant positive correlation (r=0.127r=0.127, p<0.01p<0.01) between course content relevance and resource quality, suggesting that good resources are associated with relevant course content.

4. Teachers' Knowledge (Q6):

• Q6 and Q7: A significant positive correlation (r=0.201r=0.201, p<0.01p<0.01) between teachers' knowledge and the suitability of classrooms indicates that appropriate classrooms contribute to better perceptions of teacher knowledge.

• Q6 and Q8: A significant positive correlation (r=0.268r=0.268, p<0.01p<0.01) between teachers' knowledge and the quality of educational resources shows the importance of resources for teaching effectiveness.

5. Classroom Suitability (Q7):

• Q7 and Q8: A significant positive correlation (r=0.242r=0.242, p<0.01p<0.01) indicates that suitable classrooms are associated with better educational resources.

6. Information Before Exams (Q10):

• Q10 and Q11: A significant positive correlation (r=0.109r=0.109, p<0.01p<0.01) between information before exams and the inclusion of student input in exam setup highlights the importance of communication and transparency.

7. Exam Coverage of Syllabus (Q12):

• Q12 and Q11: A significant positive correlation (r=0.121r=0.121, p<0.01p<0.01) between the comprehensiveness of exam questions and student input in exam setup emphasizes the need for student involvement in the exam process.

8. Critical Thinking Promotion (Q14):

• Q14 and Q6: A significant positive correlation (r=0.144r=0.144, p<0.01p<0.01) between critical thinking promotion and teachers' knowledge indicates that knowledgeable teachers foster critical thinking.

• Q14 and Q11: A significant negative correlation (r=-0.157r=-0.157, p<0.01p<0.01) suggests that there might be an inverse relationship between critical thinking promotion and student input in exam setup, which may require further investigation.

Overall, the analysis indicates that various factors, such as the relevance of course content, teacher knowledge, classroom suitability, and the availability of resources, significantly influence student satisfaction and the perceived quality of education. Effective communication and student involvement in the exam process also play crucial roles in the educational experience. Addressing these areas could enhance the overall quality of higher education services.

The findings of this study provide significant insights into the evaluation of student satisfaction in an academically and financially independent higher education institution (HEI) such as Bukhara State University (BukhSU). By leveraging digital economy tools, this research highlights the advantages and challenges associated with utilizing digital technologies to enhance the evaluation process.

The integration of digital tools in assessing student satisfaction has several implications for autonomous HEIs. First, digital tools enable more efficient and comprehensive data collection and analysis. The ability to gather large volumes of data quickly and accurately allows institutions to gain a deeper understanding of student needs and preferences. This aligns with findings from Watson et al. (2010) and Johnson et al. (2014), who emphasize the benefits of digital data collection in educational settings.

Real-time feedback mechanisms facilitated by digital platforms allow for immediate identification and resolution of issues. This continuous improvement cycle is crucial for maintaining high levels of student satisfaction. Robinson and Hullinger (2008) support this by noting the importance of real-time data in implementing timely

interventions. BukhSU can leverage these capabilities to promptly address student concerns, thereby enhancing the overall educational experience.

CONCLUSION

This study aimed to evaluate student satisfaction and the quality of educational services at Bukhara State University (BukhSU) following its transition to autonomy. The survey, which included questions coded as Q1 to Q10, provided valuable insights into various aspects of the educational experience at BukhSU.

The findings indicate that students generally express satisfaction with the educational process, particularly emphasizing the relevance of course content and the knowledge of their teachers. The availability of resources and classroom suitability also play significant roles in shaping student perceptions of educational quality. However, the correlation analysis revealed that these relationships, while statistically significant, are moderate rather than strong. This suggests that multiple factors influence student satisfaction and educational quality, highlighting the complexity of the educational environment.

The transition to autonomy appears to have positively impacted BukhSU, empowering the institution to innovate and better meet the needs of its students. The autonomy model provides greater flexibility and accountability, which are crucial for improving educational outcomes. The experiences of BukhSU can serve as a valuable case study for other higher education institutions in Uzbekistan and the broader Central Asian region undergoing similar transitions.

Despite the positive findings, there are areas that require further attention. Ensuring consistent quality across all faculties and continuously improving resource availability and classroom conditions are essential for maintaining high standards of education. Additionally, addressing the challenges of funding, quality assurance, and expanding access and equity will be critical for sustaining the benefits of autonomy.

Overall, this study underscores the importance of relevant course content, knowledgeable teachers, suitable classrooms, and adequate resources in enhancing student satisfaction at autonomous universities. The moderate correlations highlight the need for a holistic approach to educational quality, taking into account the interplay of various factors. As BukhSU continues to develop as an autonomous institution, it can serve as a model for others, demonstrating the potential of autonomy to enhance higher education quality in Uzbekistan and beyond.

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