ANALYSIS OF NON-ACADEMIC ASPECTS INFLUENCING STUDENT SATISFACTION
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STATEMENT ABOUT THE INDEPENDENT CHARACTER OF THE MASTER THESIS 4
INTRODUCTION 6
Chapter 1. Student satisfaction overview 8
1.1 Problem statement 8
1.1.1 Company description 8
1.1.2 Current student satisfaction assessment methods and their shortcomings 9
1.2 Theoretical background and literature overview 10
1.2.1 Customer satisfaction overview 10
1.2.2 Student satisfaction overview 12
1.2.3 Ways of measuring students KPI 14
1.2.4 Approaches to measuring student satisfaction 16
1.3 Research goal and objectives 22
1.3.1 Managerial problem 22
1.3.2 Research goal 22
1.3.3 Research tasks 22
1.3.4 Expected results 23
1.3.5 Practical application 23
1.3.6 Limitations on research 23
Summary 24
Chapter 2. Methodology 26
2.1 Procedure of Structural equation modeling 26
2.1.1 Preliminary stage: Confirmatory and Exploratory Factor Analysis 28
2.1.2 Modeling stage: Structural Equation Modeling 29
2.2 Metrics for measuring model quality 30
2.2.1 Chi2 (2X) indices 30
2.2.2 Adaptive fitness index (CFI) 30
2.2.3 GFI fitness index 31
2.2.4 Root Mean Square Error of Approximation index (RMSEA) 31
2.2.5 Metrics for measuring survey quality (Cronbach’s alpha) 31
Summary 33
Chapter 3 Exploring factors and research results 34
3.1 Identifying groups of key factors 34
3.2 Creating a questionnaire 35
3.3 Research hypotheses 38
3.4 Data collection 39
3.5 Evaluation of reliability and validity of questionnaire components 42
3.6 Results of Structural Equation Modeling 47
3.7 Recommendations and further development 51
Summary 52
CONCLUSION 53
REFERENCES 55
ANNEX 60
INTRODUCTION 6
Chapter 1. Student satisfaction overview 8
1.1 Problem statement 8
1.1.1 Company description 8
1.1.2 Current student satisfaction assessment methods and their shortcomings 9
1.2 Theoretical background and literature overview 10
1.2.1 Customer satisfaction overview 10
1.2.2 Student satisfaction overview 12
1.2.3 Ways of measuring students KPI 14
1.2.4 Approaches to measuring student satisfaction 16
1.3 Research goal and objectives 22
1.3.1 Managerial problem 22
1.3.2 Research goal 22
1.3.3 Research tasks 22
1.3.4 Expected results 23
1.3.5 Practical application 23
1.3.6 Limitations on research 23
Summary 24
Chapter 2. Methodology 26
2.1 Procedure of Structural equation modeling 26
2.1.1 Preliminary stage: Confirmatory and Exploratory Factor Analysis 28
2.1.2 Modeling stage: Structural Equation Modeling 29
2.2 Metrics for measuring model quality 30
2.2.1 Chi2 (2X) indices 30
2.2.2 Adaptive fitness index (CFI) 30
2.2.3 GFI fitness index 31
2.2.4 Root Mean Square Error of Approximation index (RMSEA) 31
2.2.5 Metrics for measuring survey quality (Cronbach’s alpha) 31
Summary 33
Chapter 3 Exploring factors and research results 34
3.1 Identifying groups of key factors 34
3.2 Creating a questionnaire 35
3.3 Research hypotheses 38
3.4 Data collection 39
3.5 Evaluation of reliability and validity of questionnaire components 42
3.6 Results of Structural Equation Modeling 47
3.7 Recommendations and further development 51
Summary 52
CONCLUSION 53
REFERENCES 55
ANNEX 60
The number of higher education institutions is increasing every year. Every year, new educational programmes appear, and there is therefore increasing competition not only between applicants, but also between universities. Universities have a constant need to improve their campuses and research centers because applicants are becoming more finicky in their choices. Universities spend millions each year to advertise and attract the most talented students. However, the best advertising is likely to be only feedback from university students.
For this reason, in order to maintain their competitiveness, universities need to monitor student satisfaction, for which many aspects of the learning process are important. With the increasing complexity of the education system comes the need for more sophisticated models that allow for non-obvious conclusions and detailed analysis of the findings.
Universities want to retain their students, and assessing their satisfaction can help identify areas that need improvement and address them accordingly. This can help prevent students from dropping out or transferring to other institutions. Along with this student satisfaction is closely linked to a university's reputation. If students are happy with their experience, they are more likely to recommend the institution to others, which can lead to increased enrollment and a positive reputation. Assessing student satisfaction can help universities identify areas where they need to improve the quality of education they offer. This can include things like curriculum, teaching methods, and resources.
Also, universities want their students to succeed, and assessing their satisfaction can help identify factors that contribute to their success. This can include things like access to support services, opportunities for internships and networking, and overall satisfaction with their academic experience. Assessing student satisfaction is a way for universities to hold themselves accountable for providing a high-quality educational experience. It shows that they are committed to meeting the needs of their students and are willing to make changes to improve their experience.
The main goal of this study is to identify factors that could influence non-academic student satisfaction. This direction was chosen based on the fact that the fastest changes that a university can make are often not related to the academic process. The curriculum is approved for several years ahead, but the university has the opportunity to quickly influence other aspects of student life.
The first chapter examines the main shortcomings of the current approach, including the time it takes to complete the survey and its complexity in identifying influencing factors. As a result of the literature analysis, factors were identified that were later used as a basis for the survey in chapter 3. The factors considered in other researchers' studies often include factors directly related to the learning process, such as lecture quality and teacher qualifications, and are not related to, for example, convenience of classrooms, sports sections, or laboratories. The study showed that Structural equation modeling is most commonly used for assessing student satisfaction, and sometimes this method is used to search for factors that later become the basis for building neural networks.
The second chapter discusses the methodology of using structural equation modeling. Structural equation modeling is a statistical technique used to analyze complex relationships between multiple variables. It is a method of constructing and testing models that explain the relationships among different variables. SEM can be used to analyze both observed and latent variables, and it allows researchers to test hypotheses about causal relationships between variables. SEM can also be used to estimate the strength and direction of these relationships, as well as to identify potential sources of measurement error or bias in the data. Overall, SEM is a powerful tool for understanding complex systems and relationships between different factors.
In the third chapter, based on interviews conducted with several undergraduate students and literature from chapter 1, the main factors that could influence student satisfaction with their non-academic life were identified. After data collection, one factor related to dormitories had to be excluded due to insufficient data. The remaining model included factors such as University’s atmosphere, Professional development opportunities, University’s support, Extracurricular activities, Canteen, vending machines, Career Center, Study office, International office, IT resources, Classrooms / places of individual studies, Appearance of buildings/territory. It was hypothesized that these factors affect non-academic student satisfaction, which in turn affects overall satisfaction, which in turn affects loyalty. In the result of the research, it was found that only 5 out of 11 factors were significant. These factors were University’s atmosphere, Professional development opportunities, Career Center, Study office, and International office. It was also revealed that these factors indirectly influence loyalty through non-academic and overall student satisfaction.
For this reason, in order to maintain their competitiveness, universities need to monitor student satisfaction, for which many aspects of the learning process are important. With the increasing complexity of the education system comes the need for more sophisticated models that allow for non-obvious conclusions and detailed analysis of the findings.
Universities want to retain their students, and assessing their satisfaction can help identify areas that need improvement and address them accordingly. This can help prevent students from dropping out or transferring to other institutions. Along with this student satisfaction is closely linked to a university's reputation. If students are happy with their experience, they are more likely to recommend the institution to others, which can lead to increased enrollment and a positive reputation. Assessing student satisfaction can help universities identify areas where they need to improve the quality of education they offer. This can include things like curriculum, teaching methods, and resources.
Also, universities want their students to succeed, and assessing their satisfaction can help identify factors that contribute to their success. This can include things like access to support services, opportunities for internships and networking, and overall satisfaction with their academic experience. Assessing student satisfaction is a way for universities to hold themselves accountable for providing a high-quality educational experience. It shows that they are committed to meeting the needs of their students and are willing to make changes to improve their experience.
The main goal of this study is to identify factors that could influence non-academic student satisfaction. This direction was chosen based on the fact that the fastest changes that a university can make are often not related to the academic process. The curriculum is approved for several years ahead, but the university has the opportunity to quickly influence other aspects of student life.
The first chapter examines the main shortcomings of the current approach, including the time it takes to complete the survey and its complexity in identifying influencing factors. As a result of the literature analysis, factors were identified that were later used as a basis for the survey in chapter 3. The factors considered in other researchers' studies often include factors directly related to the learning process, such as lecture quality and teacher qualifications, and are not related to, for example, convenience of classrooms, sports sections, or laboratories. The study showed that Structural equation modeling is most commonly used for assessing student satisfaction, and sometimes this method is used to search for factors that later become the basis for building neural networks.
The second chapter discusses the methodology of using structural equation modeling. Structural equation modeling is a statistical technique used to analyze complex relationships between multiple variables. It is a method of constructing and testing models that explain the relationships among different variables. SEM can be used to analyze both observed and latent variables, and it allows researchers to test hypotheses about causal relationships between variables. SEM can also be used to estimate the strength and direction of these relationships, as well as to identify potential sources of measurement error or bias in the data. Overall, SEM is a powerful tool for understanding complex systems and relationships between different factors.
In the third chapter, based on interviews conducted with several undergraduate students and literature from chapter 1, the main factors that could influence student satisfaction with their non-academic life were identified. After data collection, one factor related to dormitories had to be excluded due to insufficient data. The remaining model included factors such as University’s atmosphere, Professional development opportunities, University’s support, Extracurricular activities, Canteen, vending machines, Career Center, Study office, International office, IT resources, Classrooms / places of individual studies, Appearance of buildings/territory. It was hypothesized that these factors affect non-academic student satisfaction, which in turn affects overall satisfaction, which in turn affects loyalty. In the result of the research, it was found that only 5 out of 11 factors were significant. These factors were University’s atmosphere, Professional development opportunities, Career Center, Study office, and International office. It was also revealed that these factors indirectly influence loyalty through non-academic and overall student satisfaction.
Each year, there is a rise in the number of higher education institutions and new educational programs, leading to increased competition among universities and applicants. Universities must constantly improve their facilities and research centers to attract the most talented students, spending millions on advertising. However, the best form of advertising is positive feedback from current students. To remain competitive, universities must monitor student satisfaction, considering various aspects of the learning process. A more complex education system requires sophisticated models for detailed analysis of findings.
As a result of the literature review, it was found that the most popular way to study the topic of student satisfaction is Structural Equation Analysis. Data obtained from a survey, which was based on interviews with students, were used to build the model. The questionnaire included a total of 51 questions, 7 of which were general questions (gender, age, employment status, happiness level, etc.) and 44 questions related to variables for assessing satisfaction, which were used to construct the model.
As a result of the analysis the opportunity for professional development was found to be the most significant factor, followed by the international office, university atmosphere, career center, and study office. Table 10 presents the coefficients of influence of each factor on extracurricular satisfaction and the most frequent score that was given when assessing student satisfaction. Since a Likert scale was used in the study, the values in the above table denote the following. 5 - Very good, 4 - Good, 3 - Neither good nor bad, 2 - Bad, 1 - Very bad.
As can be seen, the majority of students rate the non-academic work of the university at a good level. The atmosphere at the university is the most well rated and is in 3rd place in importance with a score of 5. With a score of 4, the opportunity for professional development is ranked 1 st in importance. The international office is ranked 2nd with a score of 3.
Considering the results, it can be said that attention needs to be paid to the international exchange office and professional development opportunities in order to increase student satisfaction. Changes in these areas should raise student satisfaction more than, for example, changes in the study office and career centre.
The resulting non-academic satisfaction has an impact on overall satisfaction, which in turn affects loyalty. However, it is important to note that only a limited group of factors were considered in this study. Therefore, it may not accurately reflect the impact of extracurricular activities on overall satisfaction or the factors that contribute to loyalty beyond overall satisfaction.
To create a more precise model that can accurately evaluate the impact of a specific factor on overall student satisfaction, a comprehensive list of factors that could potentially affect it must be compiled. However, data collection and analysis for this model may be complex, as the amount of required data should be four times greater than the number of observed variables. Therefore, selecting factors based on the principle of quantity over quality is not advisable. Instead, only essential and relevant factors with a significant influence should be included in further refining the model.
As a result of the literature review, it was found that the most popular way to study the topic of student satisfaction is Structural Equation Analysis. Data obtained from a survey, which was based on interviews with students, were used to build the model. The questionnaire included a total of 51 questions, 7 of which were general questions (gender, age, employment status, happiness level, etc.) and 44 questions related to variables for assessing satisfaction, which were used to construct the model.
As a result of the analysis the opportunity for professional development was found to be the most significant factor, followed by the international office, university atmosphere, career center, and study office. Table 10 presents the coefficients of influence of each factor on extracurricular satisfaction and the most frequent score that was given when assessing student satisfaction. Since a Likert scale was used in the study, the values in the above table denote the following. 5 - Very good, 4 - Good, 3 - Neither good nor bad, 2 - Bad, 1 - Very bad.
As can be seen, the majority of students rate the non-academic work of the university at a good level. The atmosphere at the university is the most well rated and is in 3rd place in importance with a score of 5. With a score of 4, the opportunity for professional development is ranked 1 st in importance. The international office is ranked 2nd with a score of 3.
Considering the results, it can be said that attention needs to be paid to the international exchange office and professional development opportunities in order to increase student satisfaction. Changes in these areas should raise student satisfaction more than, for example, changes in the study office and career centre.
The resulting non-academic satisfaction has an impact on overall satisfaction, which in turn affects loyalty. However, it is important to note that only a limited group of factors were considered in this study. Therefore, it may not accurately reflect the impact of extracurricular activities on overall satisfaction or the factors that contribute to loyalty beyond overall satisfaction.
To create a more precise model that can accurately evaluate the impact of a specific factor on overall student satisfaction, a comprehensive list of factors that could potentially affect it must be compiled. However, data collection and analysis for this model may be complex, as the amount of required data should be four times greater than the number of observed variables. Therefore, selecting factors based on the principle of quantity over quality is not advisable. Instead, only essential and relevant factors with a significant influence should be included in further refining the model.
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