INTRODUCTION TO RESEARCH
Urgency of the study
With the globalization of the market economy, education has transitioned from a non-commercial, non-profit activity to an "educational service" model Viewing students as customers emphasizes the importance of their feedback in enhancing training quality, enabling managers to make necessary adjustments Therefore, the evaluation of educational quality should be based on customer (student) satisfaction rather than solely on technical standards, quantity, or regulatory compliance.
In the field of education, evaluating service quality based on student feedback is increasingly essential This underscores the importance of understanding student satisfaction to improve teaching and learning experiences Therefore, our research focuses on analyzing student opinions at Skyline School to assess the quality of education provided The study aims to identify key factors influencing student satisfaction and enhance overall educational service quality.
Objectives of the study
- Research on the quality of training services of Skyline school
- Level of student satisfaction when studying at Skyline school
- Determining the factors affecting the satisfaction of the quality of training services of Skyline students
- Measuring the impact of factors on the quality of training services at Skyline
- Proposal to improve student satisfaction at Skyline
Research question
To address the research objective stated above, the study will answer and focus on the following questions:
- How satisfied are students with the quality of teaching and learning at Skyline?
- What is the most important factor affecting the quality of teaching and learning of students at Skyline?
- How to improve student satisfaction at Skyline?
Object and scope of the study
- Research object: The satisfaction of students about the quality of teaching and learning at Skyline school.
- Survey object: Students studying at Skyline school.
+ Space: Research conducted in Da Nang city at Skyline school
+ Time: The study was carried out from October 2022 to December 2022
Research Methods
The research was carried out through two methods: qualitative research and quantitative research
This study investigates the key factors influencing student satisfaction at Skyline by developing a comprehensive survey and evaluation scale grounded in existing research The research process begins with qualitative methods to identify the most relevant model components and measurement variables tailored to the specific educational context By establishing a validated assessment tool, the study aims to provide clear insights into the teaching and learning experiences that impact student satisfaction.
This study utilizes an online questionnaire survey to collect data from students, employing a quantitative research approach Samples were gathered through Google Forms and email distribution, ensuring efficient data collection The collected data is analyzed using SPSS 20.0 software, where reliability is tested with Cronbach's Alpha, and then exploratory factor analysis (EFA) is conducted to identify underlying factors These factors are subsequently used in regression analysis to evaluate the proposed research model and test hypotheses, ensuring comprehensive and data-driven insights.
Meaning of research
This article explores the theoretical and practical foundations of student satisfaction, focusing on evaluating the training quality at Skyline School It examines the key factors influencing student satisfaction and their impact on overall training quality Additionally, the study offers targeted recommendations for school improvements to enhance future educational experiences By conducting comprehensive student satisfaction research, Skyline School aims to meet students' needs, foster trust and loyalty, and encourage continued enrollment, ensuring sustained success and reputation.
The layout of the study
Chapter 1: Introduction to the research
Chapter 2: Theoretical foundations and research models
THEORETICAL BASIS AND RESEARCH MODEL
Customer satisfaction
According to Bachelet (1995), “customer satisfaction is an emotional response by customers to their experience with a product or service”.
Customer satisfaction is fundamentally linked to the perceived value and quality of products and services, reflecting how well they meet or exceed customer expectations Oliva, Oliver, and Bearden (1995) emphasize that the relationship between the value customers derive from products or services and previous offerings directly impacts their satisfaction levels Oliver (1997) describes customer satisfaction as the consumer’s response to the fulfillment of their desires Supporting this, Zeithaml and Bitner (2000) define customer satisfaction as a customer's evaluation of whether a product or service meets their specific wants and requirements Overall, customer satisfaction is an assessment used to measure how effectively a product or service fulfills customer needs.
According to Kotler (2001), customer satisfaction is the level of a person's sensory state resulting from a comparison of the results obtained from the consumption of a product/service and the customer's expectations.
According to Philip Kotler, customer satisfaction is the level of a person's sensory state resulting from comparing the results obtained from consuming a product/service with their own expectations .
Customer satisfaction is a crucial factor reflecting a customer's overall attitude towards a service provider It is defined as the emotional response experienced when there is a gap between customer expectations and the actual service received According to Hansemark and Albinsson (2004), satisfaction arises from fulfilling specific needs, goals, or desires, highlighting the importance of meeting or exceeding customer expectations to ensure positive perceptions and loyalty.
Customer satisfaction is a sense of pleasure or disappointment resulting from comparing the actual benefits of a product with customer expectations The level of satisfaction depends on whether the product's benefits meet or exceed what customers anticipated before making a purchase Understanding this relationship is essential for businesses aiming to enhance customer experience and loyalty.
Customer satisfaction is considered as a comparison between expectations before and after purchasing a product or service, there are 3 levels of satisfaction:
- If the results are less than expected, then the customer will feel dissatisfied.
- If the results are as expected, then the customer will feel satisfied.
- If the results received exceed the customer's expectations, then they will feel very satisfied with the service.
Quality of teaching and learning services
Discussing teaching quality involves evaluating the knowledge, skills, and attitudes that learners develop throughout the learning and training process High-quality education ensures that learners acquire meaningful competencies and positive attitudes, reflecting effective teaching methods Emphasizing learner outcomes highlights the importance of instructional effectiveness in fostering comprehensive growth Ultimately, quality teaching translates into improved learner performance and mastery of essential skills.
Teaching service quality is a multifaceted concept that varies based on different perspectives, including students, employers, staff, government agencies, and accrediting bodies Each group perceives quality through distinct lenses, such as compliance with standards, fulfillment of customer needs, or the achievement of institutional goals Green and Harvey (1993) identify five key aspects of quality teaching and learning: excellence, perfection, fitness for purpose, value for money, and transition between states Among these, “fitness for purpose” is widely adopted by quality assurance organizations in countries like the United States, the United Kingdom, and Southeast Asia, emphasizing the importance of meeting specific needs and objectives.
Factors affecting the quality of teaching and learning
There are many factors that affect the quality of teaching as well as the quality of learning such as curricula, teachers, facilities, input quality, etc.
The curriculum design is essential for establishing the structure and content that direct the outputs of a training program Effective curriculum design ensures that learning outcomes are closely aligned with course content, forming the basis for high-quality teaching Focusing on the connection between outcomes and courses is vital to meet the interests and needs of learners, ultimately enhancing the overall teaching quality.
Teaching quality is fundamentally determined by a combination of factors, with teachers playing a crucial role Research consistently demonstrates that effective teaching depends on a teacher’s pedagogical skills, professional qualifications, practical experience, and classroom architecture Enhancing these elements is essential for improving overall educational outcomes.
Advancements in science and technology, particularly information technology, significantly enhance support services that meet learners' needs and improve overall quality of life Effective curriculum design, modern facilities, and up-to-date teaching equipment are crucial for elevating the quality of education and ensuring school excellence To prepare students for real-world demands, easy access to advanced technologies within training institutions and schools is essential.
The quality of education is fundamentally influenced by the entire educational journey, starting from kindergarten through high school, as well as the social environment and family support While university training adds value, poor foundational input limits the overall quality of output Among various factors affecting teaching quality, the role of the teaching staff is paramount, as it directly impacts both the effectiveness of education and student satisfaction Investing in qualified and dedicated teachers is essential to enhance learning outcomes and ensure a positive academic experience.
Theories of the study
2.4.1 SERVQUAL model ( Parasuraman et al., 1988)
Since its publication by Parasuraman et al (1985), the SERVQUAL scale has sparked ongoing debates regarding the most effective methods to measure service quality Over the past two decades, numerous researchers have tested and validated the effectiveness of the SERVQUAL model Today, it is recognized as a comprehensive and precise tool for assessing service quality, notably through its introduction of the innovative 5-gap model, which provides a detailed framework for identifying and improving service performance.
Figure 2 1 SERVQUAL model ( Parasuraman et al., 1988)
(Source: Nguyen Dinh Tho et al (2003) )
Gap 1: The perceived gap between customer expectations and customer expectations.
Gap 2: The perceived gap between customer expectations and service quality standards.
Gap 3: Gap between service quality standards and actual services provided to customers.
Gap 4: Gap between actual service standards provided and information provided to customers.
Gap 5: Gap between perceived service and expected quality when customers consume the service
Based on this model, Parasuraman et al introduced the SERVQUAL scale with 10 components: (1) Reliability, (2) Responsiveness, (3) Service capacity, (4) Approach, (5) Courtesy, (6) Communication, (7) Credibility, (8) Safety, (9) Understanding of customers,
Reliability: The ability to perform a service as promised and exactly, always on time, in the same style and without error the first time.
- Responsiveness: Refers to the willingness, enthusiasm, and desire of service staff to meet customer requirements.
- Service capacity (Competence): speaking about the qualifications, capacity, practice and professionalism of the staff performing the service.
- Access: refers to creating favorable and easy conditions for customers to access services.
- Courtesy: related to welcoming, respectful and friendly to customers
- Communication: refers to the ability to communicate, convey information to customers.
- Credibility: related to creating trust in customers, making customers trust the organization.
- Security: refers to ensuring the safety of customers, making customers trust the organization.
Understanding the customer: showing the ability to understand customers, care and understand their needs through understanding customers' wishes and requirements about services.
- Tangible: refers to tangible elements that make an impression on customers such as costumes, equipment, documents, and facilities of the service.
The SERVQUAL scale, introduced by Parasuraman et al (1988), is a comprehensive tool designed to measure service perception across five key dimensions: Reliability, Assurance, Tangibles, Empathy, and Responsiveness While the original service quality measurement encompasses nearly all aspects of service delivery, its complexity posed challenges in assessment To address this, the SERVQUAL scale was re-calibrated to provide a more precise and manageable way to evaluate service quality effectively.
- Reliability: represents the ability to perform a service appropriately and on time
- Assurance: aims to build customer trust through professionalism, courtesy, respect for customers, ability to communicate and an attitude of caring to do what is best for customers.
- Tangibility: the appearance of facilities, equipment, staff uniforms, items and materials used for communication.
- Empathy: refers to the service style of employees through caring, paying attention to customers, wholeheartedly understanding customer needs and creating a sense of peace and safety for customers .
- Responsiveness: showing enthusiasm to help customers and quickly fix problems when something goes wrong or unexpected situations arise.
The SERVQUAL scale with the above 5 components includes 44 observed variables
The study utilizes 22 observed variables to assess customer expectations for the service, alongside another 22 observed variables to evaluate the customer's perception of the service performance This comprehensive approach allows for a detailed comparison between what customers anticipate and their actual experiences Analyzing these variables provides valuable insights into service quality gaps and helps organizations enhance customer satisfaction Understanding both expectations and perceptions is essential for delivering improved service performance and achieving higher customer loyalty.
On the basis of Parasuraman's SERVQUAL model, Cronin and Taylor (1992) have overcome and released the SERVPERF (Service quality) model, a variant of SERVQUAL According to the SERVPERF model:
The SERVPERF scale consists of 22 observed variables that measure customer perceptions across five core factors Unlike the SERVQUAL model, which assesses both expectations and perceptions, SERVPERF focuses solely on customer feelings and experiences These five fundamental components provide a comprehensive evaluation of service performance, emphasizing actual performance over expectations This streamlined approach enhances the accuracy and reliability of measuring customer satisfaction.
- Tangibility factors: expressed through appearance, service staff's clothing, equipment serving the service.
- Reliability: refers to the ability to perform the right service and on time the first time.
- Responsiveness: expressing the desire and willingness of employees to provide services to customers.
- Assurance: showing the qualities of employees that will create trust for customers: professionalism, courtesy, respect for customers.
- Empathy: showing care for each individual customer After many applied testing studies, SERVPERF is recognized as a scale with theoretical as well as practical value.
Figure 2 2 Cronin and Taylor's SERVPERF model 1992
Related research works
In fact, there are many studies on student satisfaction about the quality of teaching and learning of schools Some of the prominent studies include:
Pham Thi Lien's research on "Training Service Quality and Student Satisfaction at the University of Economics, Vietnam National University, Hanoi" highlights that students' satisfaction is most strongly influenced by the training program The study, which surveyed 160 students, emphasizes that high-quality teachers and effective teaching methods significantly contribute to positive student perceptions Overall, the findings indicate that the university's teaching staff and program quality are highly appreciated by students, underlining the importance of robust training services in enhancing student satisfaction.
Tran Huu Ai (2016) examined the relationship between training quality and student satisfaction at Van Hien University’s Faculty of Economics The study surveyed 289 students to assess key factors influencing educational quality, including facilities, school reliability, lecturers, training programs, and the educational environment Results indicated that four factors—facilities, lecturers, training programs, and the educational environment—positively impact students’ perceptions, while school reliability was found to have no significant effect and was thus excluded from the final analysis.
Vasiliki.GV and colleagues conducted a study assessing the quality of training services at the National University of Greece through surveying 469 students across five key factors: academic perspective, facilities, training programs, staff, and translation support services The study revealed that the academic perspective significantly influences student satisfaction, indicating that students highly value the university’s academic approach and educational facilities These findings highlight the importance of academic quality in shaping positive student experiences and overall satisfaction.
Mustafa & Chiang's study highlights that educational quality is influenced by key factors such as teacher performance (ability and attitude), course content (documents and duration), and the overall knowledge gained Their analysis of 485 surveys revealed that teacher ability, teacher attitude, learning materials, and course content significantly impact educational quality Additionally, students with lower GPAs perceived improvements in course content when taught by skilled teachers, while high-GPA students believed that quality of education improved mainly with better course content These findings underscore the importance of both instructor qualities and course materials in enhancing educational outcomes.
Proposed research model and research hypothesis
Facilities such as study rooms, teaching and learning equipment, library resources, and reliable internet connectivity are essential for maintaining high-quality educational services Well-equipped facilities play a crucial role in enhancing the learning experience and ensuring effective education delivery According to industry standards, investing in quality facilities and teaching resources significantly improves student satisfaction and learning outcomes.
According to Do Hong Sam (2016), educational facilities play a crucial role in enabling learners to fully utilize their cognitive abilities, enhance practical skills, and develop self-training and study habits These physical environments serve both as tools for practice and as objects for perception, thereby improving the scientific understanding of knowledge Overall, well-designed educational spaces are essential components of a comprehensive teaching and learning process that fosters holistic development.
H1: When the quality of facilities is rated high or low by students, the satisfaction level is high or low, respectively.
Effective community development training (CTDT) is demonstrated through the establishment of clear standards that meet societal needs Teaching quality plays a crucial role in shaping service excellence in education, with course content serving as a fundamental component of effective instruction (Hill, 1995) Well-designed training programs are key to enhancing students' cognitive development and overall learning outcomes (Athiyaman, 1997) According to LeBlanc and Nguyen (1997), the relevance of curriculum and course content ensures alignment with educational objectives and directly influences the success of learning programs for students.
H2: When the training program is rated high or low by students, the satisfaction level is high or low, respectively
Qualified teachers with strong English and communication skills play a vital role in education, serving as both managers and leaders in the classroom As Le Duc Quang & Nguyen Thi Hong Yen (2016) emphasize, teachers are one of the pillars of the school, directly influencing teaching and learning activities Ngo Xuan Thanh (2012) highlights that teachers are a decisive factor and a direct reflection of educational quality A skilled teacher not only helps students achieve better academic results during their school years but also positively impacts their future success.
H3: If the teaching staff is rated high or low by the students, the satisfaction level is high or low, respectively
Empathy in schools involves understanding students' feelings, thoughts, and concerns, providing essential support for their beliefs and well-being Schools should offer timely assistance when students face learning difficulties, fostering an environment that encourages the development of excellent students Sharing positivity and creating a comfortable, engaging, and enjoyable learning atmosphere motivates students and strengthens relationships built on respect, mutual understanding, and collaborative learning between teachers and students.
H4: If sympathy is rated high or low by students, the satisfaction level is high or low, respectively
Environmental factors in education play a crucial role in shaping human personality and fostering student development A well-designed educational environment motivates students to become more active and creative, enhancing their learning experience Creating a safe, healthy, and engaging educational setting is essential for supporting student growth, offering meaningful social activities, and cultivating a positive educational culture An ideal educational environment is also one that is free from negative influences, ensuring students can learn and thrive in a secure and inspiring atmosphere.
H5: If the educational environment is rated high or low by students, the satisfaction level is high or low, respectively
This study explores various research models related to service quality, with a particular focus on teaching and learning environments We propose a comprehensive research model to assess student satisfaction at Skyline School, emphasizing key factors such as facilities, training programs, teachers, staff, and the overall educational environment Our model aims to highlight the importance of these elements in enhancing student experiences, ensuring high-quality teaching and learning services.
Figure 2 3 Proposed research model(Source: As suggested by the author)
RESEARCH DESIGN
Research process
Research Methods
The primary goal of qualitative research is to calibrate measurement scales and develop effective questionnaires During this phase, non-probability sampling is employed, selecting participants based on specific characteristics relevant to the study, such as students at Skyline School The insights gained from qualitative research serve as a foundation for designing the formal survey questionnaire used in subsequent quantitative analysis Following scale calibration, the questionnaire is refined and adjusted thoroughly, incorporating feedback from students to ensure accuracy and relevance, with scale ratings typically ranging from 1 to [specified range].
5 with the level of significance from "totally dissatisfied", "dissatisfied", "no opinion",
"satisfied" and "completely satisfied" with the statements in the Table of questions.
This study investigates student satisfaction with the quality of teaching and learning at Skyline through a comprehensive survey Utilizing quantitative research methods, data were collected via online questionnaires designed based on qualitative research insights The sampling scope aimed to clearly define the concept and key components of student satisfaction, providing valuable insights into the educational experience at Skyline.
The study employs a random sampling method to select participants, ensuring an unbiased and representative sample All students at Skyline School are eligible to participate in the survey, provided they give their informed consent This approach enhances the reliability and generalizability of the survey results.
The data collection was conducted through online questionnaires, which included a brief overview of the study to inform participants The survey was distributed via Gmail, with a link to a Google Form sent directly to respondents Participants were kindly requested to complete the survey thoughtfully, ensuring the accuracy and reliability of the collected data.
Methods of data analysis: Processing data collected from survey results on IBMSPSS Statistics 20 data processing program.
Research scale development
Using an established analytical framework, a comprehensive questionnaire was developed and refined to ensure accuracy and relevance Once finalized, the survey will be conducted to gather valuable insights The questionnaire primarily employs a 5-point Likert scale to measure key factors influencing students' satisfaction with the quality of teaching and learning at Skyline School This approach helps identify critical areas for improvement, enhancing the overall educational experience for students.
To conduct the survey, participants are instructed to submit their responses via a Google Form link provided by the team, which will be shared with Skyline students through Gmail The questionnaire utilizes a nominal scale to gather information on key variables such as gender, training level, and class.
The scale is composed of 26 observed variables, encompassing six key factors Factor 1, Facilities, includes 4 observed variables that assess the availability and quality of infrastructural resources Factor 2, Training Program, consists of 6 observed variables measuring the effectiveness and comprehensiveness of professional development initiatives Factor 3, Teachers, comprises 4 observed variables evaluating teacher qualifications and performance Factor 4, Sympathy, includes 4 observed variables that gauge the level of emotional support and understanding provided Factor 5, Educational Environment, involves 4 observed variables related to the overall learning atmosphere Lastly, the dependent variable is represented by 4 observed variables that reflect the overall educational outcomes Incorporating these factors enhances the reliability of the scale for assessing educational quality and effectiveness.
Observable variables Variable code Infrastructure
Are the equipment in the classroom safe enough? CSVC1
Classrooms are spacious and airy CSVC2
Computer room, computer equipment to meet the learning needs of students
The rooms have enough light to study CSVC4
A study plan that ensures knowledge for students CTDT1
The forms of examination and evaluation are consistent with the program's objectives
Valid assessment test results CTDT3 Are supplemental learning materials relevant to the curriculum? CTDT4 Prestigious and high quality training program CTDT5
The training program has a reasonable ratio of theory and practice
Teachers are enthusiastic in teaching DNGV1
Teachers receive feedback and respond promptly to students' questions
The teacher has a clear and easy to understand method of communication
Teachers have extensive knowledge of the subjects DNGV4
Teachers care and share students' difficulties in learning SCT1
The school has timely support for students SCT2
There are extra-curricular sessions for students to approach practice
The school organizes fundraising and sharing sessions with difficult circumstances inside and outside the school
Educational culture is healthy, useful and interesting MTGD2 The school organizes propaganda sessions to prevent social evils MTGD3 The school has specific and strict measures for violations MTGD4
Are you satisfied with the quality of teachers at Skyline? HL1 Are you satisfied to study at Skyline school? HL2
You choose to study at Skyline school because of the good quality of teaching and learning
Does the training program meet your individual expectations? HL4
Table 3 -1Proposed research model scale
All questions in the survey are mandatory, ensuring respondents cannot submit their responses without answering each one, which guarantees complete data collection The collected survey data is then downloaded, imported into an Excel file for initial organization, and subsequently exported to SPSS for detailed statistical analysis This process enhances data accuracy and facilitates efficient data management.
Research sample
A formal study was conducted with a randomly selected sample of 150 students out of a total of 210 students The survey was carried out over a two-week period, from November 9 to November 23, ensuring timely data collection and relevance for research purposes.
Data processing methods
The data was processed using the IBM SPSS data processing program.
The reliability of the scale is assessed by the method through Cronbach's Alpha coefficient Criteria for evaluating the scale according to Nunnally and Burnstein (1994) and Nguyen Dinh Tho (2011):
- Significance level of Cronbach's Alpha coefficient: 0.6 ≤ α ≤ 0.95 (acceptable); α from 0.7 to 0.9 is good; if α > 0.95, there is a phenomenon of duplication in the variables, so it is not acceptable.
The variable-total correlation coefficient should be greater than 0.3 to ensure meaningful relationships within the scale This coefficient measures the correlation between a single variable and the mean scores of other variables on the same scale, indicating how well the variable aligns with the overall construct A higher variable-total correlation coefficient signifies a stronger relationship with other variables in the group Conversely, variables with a total correlation coefficient below 0.3 are deemed irrelevant or "garbage" and should be removed from the scale to improve its reliability and validity.
Factor analysis is a statistical method employed to reduce a large number of variables into a smaller, more meaningful set of key variables, enhancing the efficiency of the study This technique helps identify underlying relationships among variables, making it easier to interpret complex data By applying factor analysis, researchers can uncover latent factors that explain the observed correlations, leading to more insightful and focused analysis This method is essential for data simplification and uncovering hidden patterns in research.
In factor analysis, the following five conditions must be satisfied:
- (1) KMO coefficient ≥ 0.5 and the significance level of Bartlett test ≤ 0.05(According to Hoang Trong and Chu Nguyen Mong Ngoc 2008)
- (2) Factor Loading ≥ 0.5 to generate convergent values (According to Hair and Anderson 1998)
- (3) The scale is accepted when the total variance extracted 50%
- (4) Eigenvalue coefficient > 1 (According to Hair and Anderson 1998) The number of factors was determined based on an index representing the portion of variation explained by each factor.
- (5) The factor loading factor difference of an observed variable between factors must be ≥ 0.3 to create a discriminant value between factors (Jabnoun and Al-Tamimi 2003).
After testing condition (1) of factor analysis, proceed to determine the number of factors through the condition that (3) is the extracted variance ≥ 50% and (4) is Eigenvalue
To ensure the validity of the model, it is essential to test the convergence value according to condition (2) and the discriminant value based on condition (5) of the scales These steps help adjust the model for subsequent regression analysis, ultimately confirming that the factor analysis results meet both convergent and discriminant validity criteria The mean number of factors used is determined after conducting Cronbach’s Alpha and exploratory factor analysis, with the factor value being the average (mean) of the variables (items) within each identified factor, as outlined by Nguyen Dinh Tho et al (2011).
When the Pearson correlation coefficient indicates a linear relationship between independent and dependent variables, a multiple linear regression model can be used to analyze their causal connection This approach involves designating one variable as the dependent variable and the other as the independent variable, allowing for a clear understanding of how changes in the independent variable influence the dependent variable (Hoang Trong & Chu Nguyen Mong Ngoc, 2008).
- Check the fit of the model
- Check the significance of the regression coefficients
- Evaluate the fit of multiple linear regression model by coefficient R 2 and adjusted coefficient R 2
To ensure the reliability of the final regression model, essential assumptions of linear regression are tested These include verifying the independence of residuals through Durbin-Watson statistics and assessing multicollinearity using the Variance Inflation Factor (VIF) Confirming these assumptions helps establish the accuracy and validity of the regression analysis.
RESEARCH RESULTS
Description of the study sample
This study assessed students' satisfaction with the quality of teaching and learning at Skyline School through a combination of qualitative and quantitative research methods A total of 150 surveys were randomly selected from an initial pool of 210 responses, ensuring representative data Using SPSS software for data analysis, the research provided valuable insights into students' perceptions of instructional effectiveness and overall learning experiences at the school.
The purpose of descriptive analysis is to present respondents' personal information and ensure that the results align with the central research question Additionally, it was used to confirm that respondents consistently agreed with all subsequent responses in the satisfaction measure, providing valuable insights into overall participant perceptions.
This study aims to identify the key factors influencing student satisfaction with the quality of teaching and learning at Skyline School Data was collected through an online survey using Google Forms, reflecting students' genuine perceptions The high participation rate demonstrates students' enthusiasm and genuine interest in sharing their opinions The assessment results accurately represent students' overall satisfaction levels, providing valuable insights into the factors affecting their educational experience at Skyline School.
Education level Primary school 34 22.7 junior high school
Table 4 -2Sample statistics by sex and training level
(Source: Analysis from survey results on SPSS)
What class are you currently in?
Table 4 -3 Sample statistics by class (Source: Analysis from survey results on SPSS)
The survey included 150 respondents, with 50.67% of participants identifying as male and 49.33% as female, ensuring a balanced and representative sample This demographic distribution enhances the reliability and accuracy of the research findings.
Figure 4 5Gender chart(Source: Analysis from survey results on SPSS)
4.1.2 Survey results on training level
According to the survey, individuals with upper secondary education constitute the largest group, representing 41.33% (62 people) The lowest proportion is among those with primary education, accounting for 22.67% (34 people), while the lower secondary education group makes up 36% (54 people) These findings highlight the distribution of education levels within the surveyed population.
Figure 4 6 Graph of training level (Source: Analysis from survey results on SPSS)
According to the research results, the class with the highest percentage is grade 11 with 16% (24 people), the class with the lowest percentage is grade 2 with 0.7% (1 person).
The distribution of samples across classes is uneven, with grades 5, 7, 8, 10, and 12 having over 10% of the total samples, indicating higher representation in these categories In contrast, classes 3, 4, 6, and 9 each account for less than 10% of the samples, reflecting lower sample percentages Notably, no samples were selected from class 1, highlighting its absence in the dataset This uneven distribution has significant implications for model training and performance in classifying different grades.
Figure 4 7 Class chart(Source: Analysis from survey results on SPSS)
Evaluation of scale reliability
4.2.1 Evaluation of the scale by the reliability coefficient Cronbach's Alpha
The scale will initially be analyzed using SPSS software with Cronbach's Alpha reliability coefficient to assess its internal consistency Variables with an item-total correlation below 0.3 will be removed to ensure the reliability of the scale The scale will be considered suitable for further analysis once its Cronbach's alpha reaches 0.6 or higher, in line with standard reliability thresholds (Nunnally & Burnstein, 1994).
Average of the scale if variable type
Variance of the scale if variable type
Coefficient of correlation of total variables
Cronbach's Alpha if variable type
Table 4 -4 Table of results of reliability analysis of the Facility factor
(Source: Analysis from survey results on SPSS)
The "Facilities" scale demonstrates excellent reliability with a Cronbach's Alpha coefficient of 0.835, indicating strong internal consistency above the acceptable threshold of 0.6 Additionally, all individual variables show correlation coefficients greater than 0.3 with the total scale score, supporting their relevance Consequently, all scale variables will be retained for further analysis, including subsequent factor analysis, ensuring comprehensive evaluation of the construct.
Scale “Training program”: Cronbach Alpha = 0.888
Average of the scale if variable type
Variance of the scale if variable type
Coefficient of correlation of total variables
Cronbach's Alpha if variable type
Table 4 -5 The table of results of the reliability analysis of the factor Training program
(Source: Analysis from survey results on SPSS)
The Cronbach's Alpha coefficient for the "Training Program" scale is 0.888, indicating excellent reliability since it exceeds the threshold of 0.6 Additionally, all observed variables within the scale have correlation coefficients greater than 0.3, confirming their relevance Consequently, all scale variables are retained for the subsequent factor analysis, ensuring comprehensive and reliable measurement of the training program construct.
Scale “Teacher team”: Cronbach Alpha = 0.847
Average of the scale if variable type
Variance of the scale if variable type
Coefficient of correlation of total variables
Cronbach'sAlpha if variable type
Table 4 -6 Table of results of analyzing the reliability of the factor Teachers team
(Source: Analysis from survey results on SPSS)
The Cronbach's Alpha coefficient for the "Teachers" scale is 0.847, indicating high reliability greater than the acceptable threshold of 0.6 All observed variables within the scale demonstrate correlation coefficients exceeding 0.3, confirming their relevance Consequently, all variables are retained for subsequent factor analysis, ensuring comprehensive and accurate assessment of the construct.
Average of the scale if variable type
Variance of the scale if variable type
Coefficient of correlation of total variables
Cronbach's Alpha if variable type
Table 4 -7 Reliability analysis table of the factor Sympathy
(Source: Analysis from survey results on SPSS)
The "Sympathy" scale demonstrates a high level of reliability, evidenced by a Cronbach's Alpha coefficient of 0.797, which exceeds the acceptable threshold of 0.6 All individual variables within the scale show correlation coefficients greater than 0.3 with the total score, indicating their relevance and consistency Consequently, all scale variables are retained for further analysis and will be used in subsequent factor analysis to explore underlying dimensions.
Scale “Educational environment”: Cronbach Alpha = 0.845
Average of the scale if variable type
Variance of the scale if variable type
Coefficient of correlation of total variables
Cronbach's Alpha if variable type
Table 4 -8 Table of results of the reliability analysis of the educational environment factor
(Source: Analysis from survey results on SPSS)
The "Educational Environment" scale demonstrates excellent reliability, with a Cronbach's Alpha coefficient of 0.845, exceeding the acceptable threshold of 0.6 Additionally, all observed variables show correlation coefficients greater than 0.3 with the total scale, indicating their appropriateness for inclusion Consequently, all variables are retained and will be utilized in future factor analysis to ensure comprehensive assessment of the educational environment.
Average of the scale if variable type
Variance of the scale if variable type
Coefficient of correlation of total variables
Cronbach's Alpha if variable type
Table 4 -9 Table of results of reliability analysis of factor Satisfaction
The "Satisfaction" scale demonstrated a Cronbach's Alpha coefficient of 0.793, indicating high reliability beyond the acceptable threshold of 0.6 Additionally, all observed variables showed correlation coefficients greater than 0.3 with the total scale score, confirming their relevance Consequently, all variables are retained for subsequent factor analysis, ensuring comprehensive and accurate measurement of satisfaction.
Conclusion: After testing Cronbach's Alpha, no observed variables were removed when included in EFA exploratory factor analysis The final reliability test of each group of variables is as follows:
Factor Number of original observed variables
Table 4 -10 Table of results of reliability analysis of independent and dependent factors
(Source: Analysis from survey results on SPSS)
4.2.2.1 EFA analysis for the independent variable
The Cronbach's Alpha results indicate that five factors comprising 22 observed variables reliably measure the quality of teaching and learning Consequently, these variables are subjected to further evaluation through Exploratory Factor Analysis (EFA) to ensure their validity and robustness.
KMO coefficient (Kaiser - Meyer - Olkin) .902
Bartlett's test of the scale
.000Table 4 -11 KMO and Bartlett test table of independent variables
(Source: Analysis from survey results on SPSS)
The test results indicate a KMO coefficient of 0.902, confirming that the data meet the necessary condition of 0.5 ≤ KMO ≤ 1, which demonstrates that the observed variables are sufficiently correlated for factor analysis Additionally, Bartlett's test yields a value of 996.995 with a significance level of Sig = 0.000, well below 0.05, indicating that factor analysis is appropriate and the data are suitable for this statistical method.
The EFA results reveal the extraction of four meaningful factors, all meeting evaluation criteria Each factor has an eigenvalue greater than 1, indicating their significance Observed variables exhibit satisfactory factor loadings above 0.5, confirming the robustness of the factors Additionally, the total variance explained by these factors is 75.641%, which exceeds the minimum requirement of 50%, demonstrating a strong and reliable factor structure.
Table 4 -12 Factor rotation matrix (Source: Analysis from survey results on SPSS)
In our analysis, we identified 10 observed variables with factor loadings below 0.5, including CTDT2, CTDT4, CTDT6, MTGD3, DNGV1, DNGV3, SCT1, SCT2, SCT3, and SCT4, leading us to remove these from the model After refining the model, the rotation matrix revealed that 12 remaining observed variables clustered into four coherent factors, each with factor loadings of 0.5 or higher These factors were clearly grouped and assigned specific names, ensuring a robust and reliable factor structure for subsequent analysis.
- Factor one: Pooled with the average command Compute Variable CSVC = MEAN (CSVC1, CSVC2, CSVC3, CSVC4) and named Facilities, denoted CSVC.
- Second factor: Pooled by the average command Compute Variable CTDT = MEAN (CTDT1, CTDT3, CTDT5) and named Training Program, denoted CTDT.
- Third factor: Pooled with the average command Compute Variable DNGV = MEAN (DNGV2, DNGV4) and named Team of Teachers, denoted by DNGV.
- Fourth factor: Pooled with the average command Compute Variable MTGD= MEAN (MTGD1, MTGD2, MTGD4) and named Educational Environment, denoted MTGD.
The research model and hypotheses were refined based on Cronbach's Alpha reliability analysis and Exploratory Factor Analysis (EFA), revealing four key factors that influence student satisfaction with teaching and learning quality Although the initial measurement included five variables and five factors, the factor analysis indicated a reduction to four primary factors impacting student satisfaction, ensuring a more accurate and reliable understanding of the contributing elements.
22 to 12 variables, it did not change the properties of each factor Therefore, the research model and hypotheses are changed compared to the original.
4.2.2.2 EFA analysis for dependent variable (Satisfaction)
The Student Satisfaction Scale comprises four observed variables, providing a comprehensive measure of student satisfaction Reliability analysis using Cronbach's Alpha coefficient confirms the scale's consistency, supported by exploratory factor analysis results The survey table presents these findings, demonstrating the scale's validity and reliability in capturing student perceptions effectively.
KMO coefficient (Kaiser - Meyer - Olkin) .774
Bartlett's test of the scale
Table 4 -13 KMO and Bartlett test table of dependent variables
(Source: Analysis from survey results on SPSS)
The KMO coefficient of 0.774 indicates that the sampling is adequate for factor analysis, as it falls within the acceptable range of 0.5 to 1, demonstrating sufficient correlation among observed variables Bartlett's test results, with a value of 174.642 and a significance level of 0.000, confirm that the data is suitable for factor analysis, ensuring the variables are significantly correlated for meaningful exploratory factor analysis (EFA).
The EFA results reveal that four factors were successfully extracted, meeting all evaluation criteria Each factor has an eigenvalue greater than 1, indicating their significance The observed variables demonstrate satisfactory factor loadings, all exceeding 0.5, which confirms strong associations with their respective factors Additionally, the total variance explained by these factors is 61.711%, exceeding the minimum threshold of 50%, thus ensuring the adequacy of the factor solution.
Table 4 -14 Result of factor rotation matrix Satisfaction
(Source: Analysis from survey results on SPSS)
Correlation and regression analysis
The correlation analysis focuses on student satisfaction with the quality of teaching and learning at Skyline School (HL), examining how it is influenced by key factors such as Facilities (CSVC), Training Program Creation (CTDT), Teaching Staff (DNGV), Empathy (SCT), and Educational Environment (MTGD) Additionally, this analysis explores the relationships among the independent variables themselves, as understanding these correlations is crucial for accurate regression analysis and interpreting how each factor impacts student satisfaction By identifying these key relationships, the study provides valuable insights into improving educational quality at Skyline School.
A Sig value greater than 0.05 indicates that there is no significant linear correlation between the variable pairs, while a Sig value less than 0.05 suggests a significant linear relationship Additionally, examining the Pearson Correlation coefficient reveals the strength of the correlation; a value above 0.4 reflects a strong positive correlation between the variables, with the strength diminishing as the value decreases.
Based on a significance level of 0.05 and a sample size of 150 data points, the author found a Sig value of 0.00, indicating a statistically significant linear correlation between the variables The study reveals that all variables are strongly correlated, with correlation coefficients exceeding 0.4 Consequently, the author concludes that the independent variable has a meaningful linear relationship with the dependent variable, supporting the presence of a significant correlation.
CSVC CTDT DNGV MTGD HL
Table 4 -15 Correlation matrix between factors (Source: Analysis from survey results on SPSS)
The study reveals that the independent variables are strongly correlated with the dependent variables, with correlation coefficients ranging from 0.618 to 0.904, all of which are statistically significant Additionally, the correlations among the independent variables themselves are notably strong, measured between 0.531 and 0.904 These findings confirm that using regression analysis in this context is appropriate and reliable for understanding the relationships between variables.
The model summary table shows that R adjusted by 0,894 means that 4 independent 2 variables MTGD, CSVC, DNGV, CTDT can explain 89.4% of the change of dependent variable HL (student satisfaction) born).
Paradigm CHEAP R 2 R Correction 2 Estimated error
1 947 a 896 894 24943 a Independent variables: (Constant), MTGD, CSVC, DNGV, CTDT
Table 4 -16 Model summary (Source: Analysis from survey results on SPSS)
The analysis of variance reveals a high F-test value of 313.705 with a significance level of 0.000, which is less than the threshold of 0.05 This indicates that the linear regression model reliably fits the data and that the included variables are statistically significant, confirming the model's validity.
Total 87.092 149 a Dependent variable: HL b Independent Variables: (Constant), MTGD, CSVC, DNGV, CTDT
Table 4 -17 Analysis of Variance ANOVA (Source: Analysis from survey results on SPSS) aradigm Unnormalized coefficients
Table 4 -18 Statistical analysis of regression coefficients (Source: Analysis from survey results on SPSS)
If Sig < 0.05, it is concluded that the independent variable has an impact on the dependent variable.
Most Sig values are less than 0.000, indicating strong statistical significance compared to the standard 0.05, except for MTGD which has a Sig value of 0.399 Specifically, CSVC, CTDT, and DNGV have Sig values of 0.000, 0.000, and 0.016 respectively, all below the 0.05 threshold, confirming their significant influence This suggests that these independent variables have a statistically significant effect on the dependent variable, and the results are valid except when applied in an educational setting.
A Variance Inflation Factor (VIF) greater than 2 indicates potential multicollinearity issues, which are undesirable in regression analysis When VIF exceeds 10, there is definite evidence of multicollinearity, compromising the model's reliability Conversely, a VIF below 2 suggests that multicollinearity is not present, ensuring more stable and interpretable regression results (Bach Khoa MBA Group, 2021).
In this paper, there exists a variance exaggeration factor VIF > 2, which shows the phenomenon of multicollinearity.
Multicollinearity occurs when independent variables are highly correlated, which can distort regression analysis results In our study, despite the p-value (Sig.) of the independent variable MTGD being greater than 0.05, multicollinearity persists, affecting the model's accuracy Consequently, the hypothesis suggesting that the educational environment influences student satisfaction with teaching quality at Skyline School was removed due to the adverse impact of multicollinearity on the analysis.
Based on regression analysis, three key factors significantly influence student satisfaction with teaching and learning quality at Skyline School: facilities quality, training program, and teaching staff Among these, the training program has the most substantial impact, with a high regression coefficient of 0.683, indicating its critical role in enhancing student satisfaction Conversely, facilities quality and teaching staff also contribute to student satisfaction but to a lesser extent.
“Teachers” with The regression coefficient is 0.089 The results of the regression are presented in mathematical form as follows:
H1: When the quality of facilities is rated high or low by students, the satisfaction level is high or low, respectively.
H2: When the training program is rated high or low by students, the satisfaction level is high or low, respectively
H3: If the teaching staff is rated high or low by the students, the satisfaction level is high or low, respectively
H4: If sympathy is rated high or low by students, the satisfaction level is high or low, respectively
H5: If the educational environment is rated high or low by students, the satisfaction level is high or low, respectively
Table 4 -19 Table of results for testing hypotheses (Source: Analysis from survey results on SPSS)
The analysis indicates that hypotheses H1, H2, and H3 are supported, demonstrating that facilities and training programs positively influence the quality of teaching and learning, thereby increasing student satisfaction Conversely, hypotheses H4 and H5 are not supported, as factors such as empathy and the educational environment do not significantly impact student satisfaction, suggesting these elements have no direct effect on students' perceptions of teaching quality.
The analysis confirms that the theoretical model aligns well with the research data and supports the hypotheses (H1, H2, H3) Student satisfaction is most significantly influenced by the training program (Beta = 0.683), followed by Facilities (Beta = 0.325), while the Team of Teachers has a lesser impact (Beta = 0.089) The Educational Environment shows a negative relationship (Beta = -0.035), indicating no significant link to student satisfaction, possibly because Skyline's high-quality education and effective teaching methods lead students to value the overall educational environment regardless of satisfaction levels Additionally, limited sample analysis may have affected the results.
Check the difference
To test the difference in Student Satisfaction about the quality of teaching and learning at Skyline, T-test analysis and ANOVA test were performed.
To test the difference in student satisfaction by gender, perform T-test analysis (Independent samples T-test).
Sex WOMEN Medium Statistical error
Table 4 -20Descriptive Statistics Satisfaction by Gender
(Source: Analysis from survey results on SPSS)
The test results give Sig results = 0.031 < 0.05, so the variance between the 2 groups of men and women is different In the section assuming equal variance there is Sig = 0.366
> 0.05, so it is concluded that there is no statistically significant difference in satisfaction level by gender.
Levene's test t-test for Equality of Means
What is the standa rd deviat ion differ ence?
Do not assume equal variances
Table 4 -21 Results of the satisfaction test by gender (Source: Analysis from survey results on SPSS)
4.4.2 Testing for differences in training levels
To test the difference in student satisfaction by sex, perform ANOVA (One-Way ANOVA) test.
Levene Stats df1 df2 Sig.
Table 4 -22Test of uniformity of variance (Source: Analysis from survey results on SPSS)
The Homogeneity of Variances test results indicate a Sig value of 0.637, which is greater than the 0.05 significance level, suggesting that there is no significant difference in student satisfaction variances across different training levels Therefore, the data meet the assumptions required for ANOVA analysis, and the results of the ANOVA can be confidently interpreted.
Table 4 -23 Comparative results of student satisfaction by training level ANOVA
(Source: Analysis from survey results on SPSS)According to ANOVA analysis results, Sig results = 0.855 > 0.05, so there is no statistically significant difference in student satisfaction by training level.
Chương 5 CONCLUSIONS AND SUGGESTIONS IMPLIED GOVERNANCE
In the context of ongoing integration and development, customers increasingly focus on services and products that meet their high expectations, emphasizing the importance of investing in knowledge and facilities that satisfy their needs To ensure customer satisfaction with teaching and learning quality, it is essential to address internal factors influencing performance With fierce competition among schools seeking to attract students, families tend to choose institutions that excel in training quality, provide a safe and healthy living environment, and offer tangible benefits Therefore, understanding student satisfaction and the factors that affect it—such as teaching quality, safety, and overall experience—is crucial for Skyline School to enhance its educational offerings and meet the evolving expectations of its students and parents.
This study explores students' satisfaction with the quality of teaching and learning at Skyline School, building a research model based on previous studies and theoretical foundations The research employs descriptive statistics, reliability analysis, factor analysis, correlation analysis, and regression analysis to identify key factors influencing student satisfaction The findings reveal that various factors positively impact student satisfaction, with the "Training Program" emerging as the most influential factor Based on these results, Skyline School can implement targeted adjustments to enhance training quality and better meet the diverse needs of students, ultimately improving overall satisfaction.
Research indicates that three main factors influence student satisfaction with teaching and learning quality at Skyline, ranked by impact: training programs (Beta = 0.683), facilities (Beta = 0.325), and teaching staff (Beta = 0.089) To enhance student satisfaction, it is crucial to prioritize strengthening and refining training program regulations, processes, and content, followed by upgrading campus facilities, and finally improving the professional qualifications of teaching staff Focusing on these areas will lead to higher educational quality and greater student satisfaction.
Research indicates that the quality of training programs significantly impacts student satisfaction To enhance student experience, Skyline School must focus on continuously updating and improving its training and study programs to meet evolving student needs Implementing regular evaluations through professional inspection teams ensures the training processes align with the curriculum, thereby boosting overall student satisfaction.
Research indicates that “Facilities” is the second most influential factor affecting student satisfaction with teaching and learning quality Schools should prioritize building, upgrading, and maintaining classrooms with proper lighting and comfortable environments to enhance student learning experiences Additionally, updating reference materials, books, and newspapers is essential to meet students’ evolving educational needs; currently, the school library lacks recent and diverse resources, limiting students’ access to useful information To improve computer facilities, schools need to invest in additional computers and ensure the rooms are well-lit and spacious, ideally situated in open areas to minimize negative distractions and support effective learning.
Although teachers have the least influence compared to other factors on student satisfaction with teaching and learning, their enthusiasm and teaching methods significantly impact student outcomes Schools should focus on supporting teachers who lack enthusiasm to enhance overall student satisfaction Teachers’ passionate and engaging teaching styles improve students’ understanding and enjoyment of learning Furthermore, teachers must possess extensive subject knowledge beyond the curriculum to introduce students to new, engaging topics, making learning more interesting and facilitating better knowledge absorption.
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Van Hien University, pp number 3, pp 118-128, 2016.
[2] ND Tho, "Scientific research methods in business," Labor and Social Publishing
[3] CNMN Hoang Trong, "Analyzing research data with SPSS," Hong Duc Publishing
[4] PT Lien, "Training service quality and student satisfaction at University of Economics, Hanoi National University," Science Journal of Vietnam National University, Hanoi, pp.
[5] NTDs v VMS Dao Duy Huan, "Research Methods in Business," Can Tho Publishing
We are students from Vietnam Korea University of Information and Communication Technology conducting research on student satisfaction with the quality of teaching and learning at Skyline We kindly ask you to take a moment to complete the survey below, which is an essential part of our study Rest assured, all participant information will be kept confidential and used solely for research purposes Thank you for your valuable support.
We are very grateful to you!
What level of training are you currently studying at? *
Primary school junior high school high school
What class are you currently in? *
Please check the corresponding box showing your satisfaction with the criteria A 5- point rating scale is used in which: “1- Completely dissatisfied, 2- Not satisfied, 3- No opinion, 4- Satisfied, 5- Completely satisfied.”
1 Are the equipment in the classroom safe enough?
2 Classrooms are spacious and airy
3 Computer room, computer equipment to meet the learning needs of students
4 The rooms have enough light to study
1 A study plan that ensures knowledge for students
2 The forms of examination and evaluation are consistent with the program's objectives
4 Are supplemental learning materials relevant to the curriculum?
5 Prestigious and high quality training program
6 The training program has a reasonable ratio of theory and practice
1 Teachers are enthusiastic in teaching
2 Teachers receive feedback and respond promptly to students' questions
3 clear and easy to understand method of communication
4 Teachers have extensive knowledge of the subjects
1 Teachers care and share students' difficulties in learning
2 The school has timely support for students
3 There are extra-curricular sessions for students to approach practice
4 The school organizes fundraising and sharing sessions with difficult circumstances inside and outside the school
2 Educational culture is healthy, useful and interesting
3 The school organizes propaganda sessions to prevent social evils
4 The school has specific and strict measures for violations
1 Are you satisfied with the quality of teachers at Skyline?
2 Are you satisfied to study at Skyline school?
3 You choose to study at Skyline school because of the good quality of teaching and learning
4 Does the training program meet your individual expectations?
APPENDIX 2: CRONBACH'S ALPHA ANALYSIS RESULTS
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Scale Variance if Item Deleted
Cronbach'sAlpha ifItemDeleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
ANNEX 3: RESULTS OF FACTOR ANALYSIS OF EFA
KMO and Bartlett's TestKaiser-Meyer-Olkin Measure of Sampling Adequacy .902Bartlett's Test of Sphericity Approx Chi-Square 996,995
ANNEX 4: RESULTS OF correlative analysis
CSVC CTDT DNGV MTGD HL