(LUẬN văn THẠC sĩ) some factors influencing student satisfaction in e learning, a study of university students in ho chi minh city, viet nam

Introduction

Background

Education is essential for the development of a country, influencing its society, economy, and politics It is crucial for governments to prioritize education to foster growth and improve citizens' quality of life In today's world, lifelong learning and self-directed study are vital for personal and professional development E-learning has emerged as a key method to meet these educational needs In Vietnam, the State and Party are committed to creating a successful learning society, as highlighted in the eleventh Congress of the Communist Party of Vietnam (2011), which emphasizes promoting study encouragement, building a learning society, and expanding e-learning initiatives.

Vietnam's shift towards a market-oriented economy and its membership in the World Trade Organization (WTO) have created both opportunities and challenges for businesses The country now enjoys access to new markets for exports, imported raw materials, and enhanced international cooperation However, this openness also intensifies competition and enforces stricter business standards regarding product quality and safety A significant challenge for Vietnam is the lack of business management knowledge, compounded by the growing demand for updated skills and knowledge since the market liberalization Consequently, Vietnamese universities play a crucial role in supplying qualified business graduates to meet the needs of the labor market, actively working to fulfill the expectations of students and other stakeholders.

In Vietnam, the higher education system, established under the 2012 education laws, encompasses both undergraduate and postgraduate studies, with master's and doctoral degrees classified as postgraduate The structure includes universities, research institutions, and colleges, where universities can offer a wide range of programs from college to doctoral levels, while colleges are limited to lower-level undergraduate offerings Over the past 11 years, the higher education landscape has evolved significantly, marked by the establishment of new institutions and improvements in quality, with approximately 386 universities and colleges reported by the Ministry of Education and Training The advent of technology and the Internet has revolutionized access to education, enabling diverse online learning opportunities that enhance the educational experience This shift towards e-learning is seen as a transformative force in the education sector, driven by the demand for lifelong learning and budget constraints, compelling universities to adopt modern technologies to remain competitive in a globalized world.

Research problem

E-learning is making use of technology innovations and Internet to deliver information for education and training (Sun, Tsai, Finger, Chen, & Yeh, 2006) Thanks to the progress of information and communication technology development, it is impossible for people to deny the fact that e-learning is emerging as the paradigm of modern education As regards e-learning, it actually has some advantages, comprising liberating interactions between learners and instructors, or learners and learners, from limitations of time and space through the asynchronous and synchronous learning network model (Sun et al., 2006) It is obvious that the characteristics of e-learning fulfill the requirements for learning in a modern society However, some students feel unpleased and disappointed when experiencing e- learning at Vietnamese universities, including: University of Science Ho Chi Minh city, Ho Chi Minh city Open University, Hutech University, Ho Chi Minh city University of Technology, and University of Information Technology

Research on student satisfaction is essential for evaluating whether colleges and universities are achieving their educational goals A well-prepared graduate is the primary outcome of these institutions, and student satisfaction serves as a crucial indicator of success Numerous studies indicate that satisfied students are more inclined to put in greater effort compared to their dissatisfied peers (Bryant, 2006; Ozgungor, 2010) Consequently, satisfied students are more likely to engage actively in their studies, which includes attending classes regularly and participating more fully in their coursework.

Understanding the factors that affect the satisfaction of Vietnamese students is essential for both academics and university administrators This study aims to explore key elements influencing this satisfaction, specifically focusing on the roles of instructor quality, learner engagement, and technology integration in enhancing e-learner satisfaction among Vietnamese students.

Research plays a crucial role in education by providing universities with insights into the factors that influence e-learner satisfaction The findings help institutions enhance learner satisfaction and strengthen their e-learning initiatives Additionally, the study highlights the importance of integrating technological innovations in teaching and developing appropriate policies to improve instructors' teaching capabilities.

This study aims to identify the key factors influencing e-learners' satisfaction and assess the strength of each factor on student satisfaction with e-learning The primary objectives of this research are to determine the critical elements associated with e-learners' contentment and to evaluate their impact on overall satisfaction levels.

To examine the factors impacting student satisfaction in e-learning in interaction, learner attitude toward technology, technology quality, and internet quality

Ho Chi Minh City is one of the major business and education centers in Vietnam, so the empirical in this particular research is the e-learning in the context of

This study focuses on e-learning students from Ho Chi Minh City, specifically analyzing data collected from local universities The research primarily targets post-graduate and graduated students, excluding other types of university students from consideration.

The structure of the paper is divided into five key sections: it begins with an introduction to the study, followed by a literature review and hypothesis The methodology is then presented, leading to the research results Finally, the paper concludes with discussions, implications, limitations, and a summary of findings.

This chapter examines the current state of education in Vietnam and explores existing research on e-learning It ultimately identifies the research problem, outlines the objectives of the study, and highlights its significance.

Chapter 2 – Literature review and hypothesis

This chapter outlines the theoretical framework of the research by defining key concepts such as instructor capability, learner attitude towards computers, technology quality, internet quality, and learner satisfaction within the context of e-learning It also examines the relationships between these concepts as presented in existing literature, leading to the formulation of hypotheses for the study.

Chapter 3 outlines the establishment of measures and the survey process, comprising two key steps: qualitative research to refine the draft measurement scale and quantitative research design to test the hypotheses.

The findings of this research are showed in this chapter The results are exhibited corresponding to each step of the data analysis As a result, the research hypotheses are tested

Chapter 5 – Discussions, Implications, Conclusion, and Limitations

The final chapter of this study reviews the research findings, emphasizing their exploratory significance while relating them to real-world scenarios for practical implementation It acknowledges the limitations encountered, providing a foundation for future research directions In conclusion, it offers a comprehensive overview of e-learning, highlighting its broader implications.

Organization of the thesis

This paper is structured into five key sections: an introduction outlining the study, a literature review that presents the hypothesis, a methodology section detailing the research approach, followed by the presentation of research results, and concluding with discussions that encompass implications, limitations, and the overall conclusion.

This chapter examines the current state of education in Vietnam and explores existing research on e-learning It culminates in the identification of the research problem, along with the objectives and significance of this study.

Chapter 2 – Literature review and hypothesis

This chapter outlines the theoretical framework for the research by defining key concepts such as instructor capability, learner attitude towards computers, technology quality, internet quality, and learner satisfaction within the e-learning context It also explores the relationships among these concepts as discussed in existing literature, leading to the formulation of the research hypotheses.

Chapter 3 outlines the establishment of measures and the survey process, consisting of two key steps: qualitative research aimed at refining the draft measurement scale and quantitative research design to evaluate the hypotheses.

The findings of this research are showed in this chapter The results are exhibited corresponding to each step of the data analysis As a result, the research hypotheses are tested

Chapter 5 – Discussions, Implications, Conclusion, and Limitations

The final chapter of this study highlights the research findings, emphasizing their exploratory significance while relating them to real-world conditions for practical application It acknowledges the study's limitations to guide future research directions In conclusion, it offers a comprehensive overview of e-learning.

Literature review and hypothesis

Elearning

E-learning represents the latest advancement in distance learning, characterized by the separation of instructors and learners across time and space (Raab, Ellis, & Abdon, 2002) Utilizing network technologies, e-learning facilitates the creation and delivery of educational content anytime and anywhere, effectively removing barriers related to time and location (Sun et al., 2006) This web-based system enables institutions to provide consistent education and training, update content as needed, and minimize travel expenses for learners (Burgess & Russell, 2003) Through tools like live streaming, electronic presentations, and interactive discussions via message boards and chat rooms, e-learning maximizes its potential to engage students Additionally, research from psychology and information systems has identified key factors influencing e-learning success, including the technology acceptance model (Ajzen).

& Fishbein, 1977; Davis, Bagozzi, & Warshaw, 1989; Oliver, 1980), and the expectation and confirmation model (Bhattacherjee, 2001; Lin, Wu, & Tsai, 2005;

E-learning offers numerous advantages, including the flexibility to choose when to engage with lessons and the independence from traditional time constraints imposed by instructors (Liaw, Huang, & Chen, 2007; Bouhnik & Marcus, 2006) Students can freely express their thoughts and ask questions without limitations, while also accessing course materials at their convenience This mode of learning allows for participation anytime and anywhere, facilitating asynchronous interactions that keep discussions focused and succinct Additionally, e-learning promotes group collaboration through electronic messaging, enabling shared conversations and teamwork It also introduces innovative educational approaches, making diverse learning strategies more accessible and economically feasible, while providing unique opportunities for learners to share their innovations with immediate support from electronic communities.

E-learning offers significant innovations over traditional learning methods by combining visual, audio, and interactive elements, making training more effective for diverse learners while reducing costs associated with printing, publishing, and distribution This mode of learning allows students to control their pace, bypass unnecessary instructions, and still achieve course objectives Additionally, e-learning minimizes expenses related to teacher salaries, classroom rentals, travel, and accommodation, leading to substantial cost savings Key benefits include access to high-quality faculty worldwide, a reduction in learning time by 40-60%, consistent content delivery aligned with school requirements, automated training program completion, and precise communication with learners Ultimately, e-learning enhances students' ability to balance work and education, enabling them to study anytime and anywhere, thus facilitating the completion of training programs alongside their professional commitments.

The rapid advancement of information technology and communications has led to a significant expansion of online training, offering learners opportunities for self-study and review Despite the growth in the educational system's quality and quantity, it still struggles to meet the diverse learning needs of the population In response, the Party has emphasized the importance of promoting both formal and non-formal education, advocating for a learning society that supports education for all (Tam, 2013) Consequently, the Education and Training Sector has devised strategies to enhance educational development, focusing on non-formal education as a means to mobilize community resources and create social learning opportunities for individuals of all ages and abilities This approach fosters lifelong learning tailored to individual circumstances and contributes to the overall quality of human knowledge (Tam, 2013) E-learning plays a crucial role in achieving these educational objectives.

As Vietnam integrates into the global economy by joining the WTO, its education system faces the challenge of equipping future citizens with the necessary skills and intelligence to thrive in an increasingly competitive environment E-learning has become a prevalent method of education worldwide, with nearly 90% of universities in Singapore and over 80% in the USA adopting this approach The rapid advancement of information technology in Vietnam has led to a significant increase in Internet users, transforming how people work, study, and entertain themselves Currently, Vietnamese learners can access e-learning programs through three primary channels: university courses, international programs introduced in Vietnam, and courses developed by companies.

The Vietnam Ministry of Education and Training has made significant strides in integrating information technology into education, enhancing online learning for managers, teachers, and students The establishment of the e-learning website (el.edu.net) facilitates access to technological resources, while the adoption of open-source software Moodle has enabled the development and management of an effective online learning system Additionally, the Ministry is utilizing globally recognized SCORM technology to advance information technology collaboration Efforts are underway to ensure compliance with SCORM file formats, such as Exe, Lectora, and Voilet, tailored to the country's needs The Ministry has also improved connectivity with a fiber optic cable linking 34 Mbps domestically and 2 Mbps internationally, supported by Viettel's high-quality NET packages for educational institutions, ensuring robust online educational access.

E-learning in Vietnam lags behind developed countries like Singapore and the USA, facing significant challenges such as low quality and quantity of resources, limited scope, and low participation rates among learners Additionally, there is a lack of necessary facilities and insufficient online interaction between teachers and students, leading to a reliance on cold guidance for responses Many universities prioritize rapid growth over maintaining training quality, resulting in inadequate teaching staff and methodologies Consequently, the true value of university quality in e-learning remains underappreciated, posing practical difficulties in the e-learning process.

As a consequence, many people doubt the quality of e-learning, and have e-learning dissatisfaction.

Student satisfaction

Student satisfaction, perception of quality, and self-confidence are fundamental concepts that are often taken for granted Despite their simplicity, numerous studies aim to clarify these ideas, create metrics for measurement, and explore their interrelationships and effects on other factors What appears to be straightforward can become complex when attempting to define and isolate these constructs.

Consumer satisfaction is defined as the positive evaluation of an individual's experiences and outcomes related to purchasing or using a product (Hunt, 1977) Tse and Wilton (1988) further elaborate that customer satisfaction involves the consumer's response to the perceived gap between their expectations and the actual performance of the product after use.

Student satisfaction in education reflects the positive evaluations students make regarding their experiences and outcomes (Oliver & DeSarbo, 1989) It is influenced by their overall experiences, as noted by Oliver (1980), and is interconnected with all aspects of campus life, highlighting that classroom experiences and academic choices impact overall satisfaction (Seymour, 1993) According to Parasuraman et al (1985, 1988), satisfaction arises when students' expectations are met or exceeded, while dissatisfaction occurs when there is a negative disparity between expected and perceived performance.

Student satisfaction is a short-term attitude shaped by individual educational experiences, while perceived quality is a broader perception influenced by objective information and institutional reputation For government officials and administrators, program quality is assessed through measurable outcomes such as retention rates, graduation timelines, enrollment trends, average starting salaries of graduates, the percentage of students pursuing further education, and professional exam passing rates.

Student satisfaction, as defined by Astin (1993), refers to the perceived value of educational experiences at a university Muilenburg and Berge (2005) highlight the significant differences in how students perceive their online learning experiences These perceptions play a crucial role in students' decisions to continue with their courses (Carr, 2000) and can significantly influence their overall satisfaction with online learning (Kenny, 2003) Therefore, in the context of this research, student satisfaction is understood as the perceived value of online experiences during e-learning.

Theoretical Background of student satisfaction model

In the online learning environment, several elements significantly influence student satisfaction Key factors identified by Bolliger and Martindale (2004) include the instructor, technology, and interactivity, along with communication among course participants and effective course management systems Liaw (2008) highlights the importance of students’ perceptions of task value, self-efficacy, social skills, system quality, and multimedia instruction Additionally, confidence in their ability to succeed in online learning is crucial for students (Bolliger & Wasilik, 2009) Ultimately, student satisfaction not only impacts performance but also plays a vital role in understanding faculty satisfaction.

(2009), the correlation between faculty satisfaction and student learning is quite high

Numerous researchers in psychology and information systems have identified key variables that influence student satisfaction The accompanying figures (2.3.1, 2.3.2, 2.3.3, and 2.3.4) present models that illustrate the factors affecting this important aspect of the educational experience.

Figure 2.3.1 Partial model of student satisfaction and retention (Oscar, Ali, &

The model presented by Oscar, Ali, & Erdener (2005) emphasizes the connections between faculty, advising staff, and classes, allowing researchers to assess how these critical factors shape students' experiences at universities and influence their overall satisfaction By examining this unique set of variables, the model aims to elucidate aspects of the college experience within higher education institutions that contribute to student satisfaction.

Figure 2.3.2 A conceptual model of user’ satisfaction, behavioral intention, and effectiveness toward e-learning ( Liaw, 2008)

Liaw (2008) presents a conceptual model that examines the relationships between learner satisfaction, behavioral intention, and e-learning effectiveness This model illustrates how learners' characteristics influence their perceived satisfaction and perceived usefulness of e-learning products Additionally, environmental factors also play a role in shaping these perceptions Importantly, the model indicates that higher perceived satisfaction and perceived usefulness lead to a positive impact on learners' intention to engage with e-learning platforms.

Learners’ characteristics, such as self- efficacy, self- directedness, etc

Environmental factors, such as multimedia instruction, system quality, synchronous, and/or asynchronous interaction, etc

Behavioral intention of using e- learning

Figure 2.3.3: Research model ( Eom, Ashill, and Wen, 2006)

Figure 2.3.3 highlights the key factors influencing e-learning outcomes and student satisfaction in university online education The researchers aim to explore the critical elements that shape students' perceived learning experiences and satisfaction with e-learning systems The model includes various factors such as student self-motivation, learning styles, instructor expertise and facilitation, feedback from instructors, interaction levels, and course structure.

Figure 2.3.4 Dimensions and antecedents of perceived e-learner satisfaction (Sun et al., 2006)

According to Sun et al (2006), Figure 2.3.4 presents a comprehensive model summarizing the key factors influencing e-learning activities and learner satisfaction This model encompasses six critical dimensions: student, instructor, course, technology, design, and environment, which collectively include thirteen specific factors Notably, the learner dimension focuses on aspects such as learner attitude toward computers.

- Learner perceived interaction with others

E-learner satisfaction is influenced by various factors, including computer anxiety and learner Internet self-efficacy Key elements in the instructor dimension include the timeliness of instructor responses and their attitude toward e-learning In the course dimension, the flexibility and quality of e-learning courses play a significant role The technology dimension encompasses technology and Internet quality, while the design dimension highlights perceived usefulness and ease of use Finally, the environmental dimension focuses on assessment diversity and learners' perceived interaction with others These factors have been explored in previous research studies.

Factors influencing the student satisfaction with e-learn

This study leverages established theories and models to examine online student satisfaction at universities in Vietnam, focusing on three key dimensions: instructor capability, learner attitude, and technology By aligning with the research objectives and the current educational landscape, the study aims to provide valuable insights into enhancing the online learning experience for students.

Research on instructor capability highlights its multidimensional nature, with various perspectives emphasizing different components For instance, Braskamp and Ory (1994) identify six key elements: course organization and planning, clarity and communication skills, instructor-student interaction, course difficulty and workload, grading and examinations, and student self-learning Similarly, Marks (2000) outlines five components, including course organization, workload expectations, grading fairness, and instructor-student rapport Ginns et al (2007) further contribute to this discourse by proposing five components based on student perceptions of teaching quality, which encompass effective teaching, clear goals and standards, appropriate assessment, manageable workload, and essential skills.

Research indicates that increased interaction among learners enhances e-learning satisfaction (Arbaugh, 2000) In virtual learning environments, meaningful interactions between students and instructors are crucial for addressing challenges and fostering academic progress Electronic interactions can significantly boost learning outcomes (Piccoli et al., 2001), and there are three primary types of interactions in e-learning: student-teacher, student-content, and student-student (Moore, 1989) Notably, the relationship between instructors and students is vital; a lack of interaction can lead to distractions and hinder concentration on course materials (Isaacs et al., 1995) E-learning demands greater focus than traditional face-to-face learning due to its flexible nature (Kydd & Ferry, 1994) This study defines learners' interaction as their perception of the engagement level between students and instructors.

This study emphasizes three key components of instructor capability: teaching capability, course organization, and instructor-student interaction Teaching capability encompasses the instructor's knowledge, investment in the course, clarity, and communication skills Course organization pertains to the overall structure of the course, while instructor-student interaction involves opportunities for students to engage with the instructor and participate in discussions, ask questions, and express ideas According to Biggs (1999), instructor capability plays a crucial role in enhancing teaching and learning, as it aids students in grasping course materials and understanding the value of their education High evaluations of instructor capability lead to increased student interest and satisfaction in the course, resulting in greater effort and time dedicated to their studies (Nguyen & Nguyen, 2010).

H1a Teaching capability will have a positive impact on student satisfaction with e-learning in Vietnam

H1b Course organization will have a positive impact on student satisfaction with e-learning in Vietnam

H1c Instructor-student interaction will have a positive impact on student satisfaction with e-learning in Vietnam

It is impossible for researchers to deny the important role of learner attitude towards tehnology, such as computers or IT, in e-learning satisfaction (Sun et al.,

Learner attitude refers to students' perceptions of participating in e-learning activities through computer usage Specifically, students rely heavily on information technology as essential tools for their online education In this context, instructors share their materials online, requiring learners to utilize various technologies or internet-connected devices to access these resources A positive attitude towards technology correlates with higher satisfaction and effectiveness in e-learning environments.

Cole, 1983) There is no doubt that the positive attitude of students toward technology or computers lead to the increase in the chances of successful learning for themselves

Negative attitudes can diminish learners' interest in their studies, highlighting the importance of learners' perceptions of technology and computers in achieving learning satisfaction This leads to the formulation of Hypothesis 2, which aims to test this assumption.

H2 Learner attitude towards technology will positively influence student satisfaction with e-learning in Vietnam

Research indicates that the quality of technology and the Internet plays a crucial role in student satisfaction with e-learning (Sun et al., 2006) User-friendly software tools that require minimal effort, such as easy-to-learn features and intuitive interfaces, enhance the learning experience Consequently, when learners encounter fewer barriers to adoption, their satisfaction increases (Sun et al., 2006) Thus, improved quality and reliability in information technology lead to more effective student learning outcomes (Piccoli et al.).

In e-learning, the quality of technology and the Internet significantly impact student learning outcomes Essential tools such as video conferencing facilitate discussions and enhance the learning experience Technology quality refers to learners' perceptions of the IT tools used, including microphones, earphones, and electronic blackboards Similarly, Internet quality is defined by the network performance as perceived by learners, with both factors—technology reliability and network transmission speed—playing crucial roles in effective e-learning environments.

H3a Technology quality will positively influence student satisfaction with e- learning in Vietnam

H3b Internet quality will positively influence student satisfaction with e- learning in Vietnam

This study presents a research model that identifies key factors influencing student satisfaction with e-learning in Vietnam, based on the frameworks established by various researchers, including Oscar, Ali, & Erdener (2005) and Sun et al (2006) The assessment encompasses three dimensions: instructor capability, learner attitude toward technology, and technology quality Within the instructor dimension, critical factors include course organization, teaching effectiveness, and student-instructor interaction The learner dimension focuses on the learner's attitude toward technology, while the technology dimension evaluates technology quality and Internet quality The comprehensive framework developed in this study is illustrated in Figure 2.5.1.

Figure 2.5.1: Factors of e-learner satisfaction model

Methodology

Research process

The first step in the study was to define the research problem, which set the foundation for the investigation Following this, a literature review was conducted to identify relevant concepts related to student satisfaction with e-learning, which informed the development of the research model and hypotheses Subsequently, the research design was established to outline data sources, data collection methods, measurement scales, sampling design, and data analysis techniques A draft questionnaire was created based on measurement scales from previous studies and translated into Vietnamese, after which it was revised by the researcher’s supervisor to correct any errors before the research commenced.

The research was conducted in two phases: a preliminary phase and an official phase The preliminary phase involved qualitative research through a focus group to refine measurement scales, alongside a quantitative pilot survey to evaluate the reliability of these scales Following this, the official phase utilized the finalized questionnaire in a quantitative main survey to gather data for analysis, ensuring reliability based on the results obtained Figure 3.3.1 illustrates the entire research process.

Data needs and data resources

Delete low item- total correlation items (< 0.3)

Preliminarily qualitative research

To ensure accurate responses from students, it is essential for them to fully understand the questionnaire, which was developed in both English and Vietnamese (see Appendix A) This research, consisting of a pilot study and a main survey, was conducted in Ho Chi Minh City, a key hub for business and education in Vietnam While many constructs are established in existing literature, it is vital to confirm their relevance to this study by exploring the impact of instructor capability, learner attitudes towards computers, and technology dimensions on student satisfaction The pilot study included qualitative research through in-depth interviews with six master's students from the University of Economics Ho Chi Minh City (UEH) (see Appendix D) to evaluate the content of the measures.

In addition, the pilot quantitative survey with participation of sixty learners was undertaken at universities in Ho Chi Minh city.

Sampling design

The appropriate sample size for research is influenced by factors such as reliability expectations and data analysis methods According to Hair et al (1998), a minimum sample size of 100 to 150 elements is recommended, while Bollen (1989) suggests at least five elements per estimated parameter For regression analysis, Harris (1985) proposed a formula indicating that the sample size should be at least 104 plus the number of independent variables In the context of Exploratory Factor Analysis (EFA), Hair et al (1998) recommend a minimum of 50 elements, ideally 100, with at least five elements per parameter In this study, a survey was conducted with approximately 300 university students using electronic tools and paper-and-pencil methods, with data collected through questionnaires serving as primary data, supplemented by secondary data from related articles, business journals, and online resources.

Measurement

The study identifies 27 key items related to instructor capability, learner attitude, technology dimension, and learner satisfaction, all of which will be assessed using a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) Additionally, the research will employ the Statistical Package for the Social Sciences (SPSS) for statistical analysis.

Quantitative Research

The research commenced by assessing the current state of e-learning issues in Ho Chi Minh City, Vietnam, which laid the groundwork for identifying the research purpose Following this, a literature review was conducted to explore the factors influencing student satisfaction in e-learning, providing a theoretical foundation for the study Subsequently, the research framework was developed, utilizing both mail and paper surveys as the primary research methods.

The development of questionnaires for both mail and paper surveys will be guided by literature reviews and consultations with experienced academics to ensure validity and reliability Subsequently, quantitative data will be gathered through self-administered questionnaires distributed via mail and paper surveys The research process will conclude with the formulation of conclusions and recommendations based on the collected data.

The research commenced in August 2013, focusing on identifying the research dilemma and objectives After developing and refining questionnaires through pilot testing and expert consultations, they were distributed to respondents in Ho Chi Minh City in September 2013, with data collection concluding two months later The analysis of the collected data took place in December 2013, and the interpretation of results was completed in February 2014 The entire research process concluded by the end of March 2014 with the final report writing.

Data analysis

The data analysis process involved several key steps Initially, a descriptive analysis was conducted to gather demographic information about the respondents Following this, Cronbach’s Alpha coefficients were utilized to assess reliability Exploratory Factor Analysis (EFA) was then performed to identify relationships between various items and constructs After EFA, a multi-collinearity test was carried out to check for any existing correlations among predictors Regression analyses were subsequently conducted to explore the relationships between the predictors and the dependent variables in the study Hypothesis testing was also an essential part of the research, allowing the researchers to determine the validity of their proposed hypotheses Finally, the implications of the analysis results were discussed, along with relevant recommendations.

Research Results

Data statistical analysis

By performing surveys via electronic tools or mails, and papers, there were total 600 questionnaires collected from students at universities in Ho Chi Minh City

A total of 301 questionnaires were either incomplete or poorly filled out, leaving 299 usable responses for analysis Among these, 75 questionnaires were collected through email, while 224 were submitted on paper Most respondents reported having experience with e-learning.

According to the gender table of appendix C, in the 299 respondents, there were 167 females, equivalent to 55.9% In comparison with females, males were lower, accounting for 44.1%

The majority of respondents, 69.9% (209 individuals), fall within the 22-35 age range, as detailed in the age table (see appendix C) In contrast, those aged 36-45 represent a smaller segment at 30.1% (90 individuals) Notably, there were no respondents over the age of 45.

Following the education table 3 in the appendix C, most of the people surveyed were bachelors and masters, making up 42.1% (126 persons) and 57.9%

The descriptive statistics evaluating the questionnaire variables of the respondents are presented in Tables 4.1.1 and 4 (see Appendix C) The framework comprised 27 items, including 12 related to instructor capability, 5 to learner attitude, 6 to technology dimension, and 4 to learner satisfaction As indicated in Table 4-1-1, the mean scores reflected a strong positive perception of the research items, with scores exceeding 3.00 on a five-point Likert scale, except for the learner attitude construct Additionally, the standard deviation values were generally acceptable, suggesting minimal variability among the responses.

Cronbach’s Alpha coefficient of reliability test

The Cronbach’s Alpha coefficient of reliability test was applied for each scale in this research model According to Nguyen (2012), Nancy, Karen, and George

(2005), Hoang, and Chu (2008), Cronbach’s Alpha reliability coefficient belongs from 0.7 to 0.8 is acceptable in the research

In the Item-total Statistics table, the Corrected Item – Total Correlation is crucial for evaluating item quality According to Nancy et al (2005), a correlation of 40 or higher indicates that the item is likely well correlated with other items, making it a valuable part of the summated rating scale Conversely, items with lower correlations may not align well psychometrically, and those with negative or very low correlations (below 30) should be scrutinized for potential wording issues or conceptual misalignment, prompting consideration for modification or removal.

The results of Cronbach’s Alpha coefficient and Corrected Item-Total Correlation for each scale are detailed in tables 4.2.1 to 4.2.8 In table 4.2.1, the Cronbach’s Alpha for instructor capability (IC) was deemed acceptable, with a value of 893, which falls within the acceptable range of 0.7 to 0.8 Additionally, table 4.2.2 indicates that most items demonstrated acceptable item-total correlations, exceeding the threshold of 0.3.

Cronbach's Alpha Based on Standardized Items N of Items

Scale Mean if Item Deleted

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

The Cronbach's Alpha for learner attitude toward computers (LA) in Table 4.2.3 was deemed acceptable at 0.846, exceeding the threshold of 0.7 Additionally, Table 4.2.4 indicated that the item-total correlations were significant, with values greater than 0.3.

Cronbach’s Alpha of technology (TE) in the table 4.2.5 was satisfied because its value (equals 782) was above 0.7 In table 4.2.6, apart from Technology Quality

Most item-total correlations were above 0.3, indicating their acceptance, except for Technology Quality 01, which had a correlation of 0.284 This lower correlation suggests that this item is unacceptable and may be removed from the scale.

The results indicate that Cronbach’s Alpha for learner satisfaction (LS) is a strong 829, exceeding the acceptable threshold of 0.7 Additionally, the item-total correlations presented in table 4.2.8 demonstrate satisfactory values, all surpassing 0.3.

Exploratory Factor Analysis ( EFA) result

The Kaiser-Meyer-Olkin (KMO) measure is a crucial statistic for assessing the suitability of data for factor analysis, with a recommended value exceeding 0.7, as noted by Nguyen (2012) and supported by Nancy et al (2005) and Hoang and Chu (2008) A KMO value below 0.5 indicates that the data may not be adequate for this type of analysis.

(2012) provided the following rules of KMO, including: excellent (KMO>= 0.9), good (KMO>= 0.8), acceptable (KMO>= 0.7), questionable (KMO>= 0.6), poor

The Bartlett test is essential for determining the suitability of variables for factor analysis, as it indicates a strong correlation among them (Nancy et al., 2005) A significant (Sig) value of less than 0.05 in the Bartlett test further supports its importance in research analysis (Nancy et al., 2005).

In research analysis, it is crucial to examine the Total Variance Explained table, as it details how variance is allocated among various factors (Nancy et al., 2005) The eigenvalue, which quantifies explained variance, should be highlighted, particularly when its value exceeds 1.0 According to Nancy et al (2005), an eigenvalue below 1.0 indicates that the factor contributes less information than a single item, rendering it unimportant for analysis (p.82).

When analyzing data, it is essential to examine the factor loadings in the Rotated Factor Matrix table According to Nguyen (2012), a factor loading of 0.707 or higher is considered useful, while in practical research, a loading of 0.50 or above is deemed acceptable Items with the highest factor loadings are associated with their respective factors, and any items that do not meet these criteria should be excluded from the construct.

Table 4.3.1: KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .882 Bartlett's Test of Sphericity Approx Chi-Square 4.284E3 df 351

The analysis indicated a KMO value of 0.882, surpassing the acceptable threshold of 0.7, which confirms its validity Additionally, the significance value was 0.000, further supporting the reliability of the results.

Loadings Rotation Sums of Squared Loadings

Extraction Method: Principal Component Analysis.

This study utilized Exploratory Factor Analysis (EFA) with Principal Axis Factoring and Promax rotation to evaluate the underlying structure of a 27-item questionnaire Six factors were identified, reflecting four dimensions: instructor capability, learner attitude, and technology The analysis revealed acceptable factors with Eigenvalues of 9.082, 3.132, 1.830, 1.464, 1.133, and 1.037, all exceeding one The factors accounted for cumulative variances of 33.638%, 45.240%, 52.016%, 57.438%, 61.633%, and 65.476%, respectively Notably, 22 items demonstrated loadings greater than 0.5, and the Total Variance Extracted was 65.476%, indicating robust explanatory power The results confirmed that learner satisfaction was influenced by three independent variables, with no alterations in the constructs' items The research demonstrated convergent validity, and the EFA model was deemed appropriate The scree plot further illustrated a decline in Eigenvalues after the first four components, reinforcing the findings.

Independence of residual

The Durbin – Waston test is a number that tests for autocorrelation in the residuals from a statistical regression analysis (Nancy et al., 2005) The value between

The Durbin-Watson statistic ranges from 0 to 4, with values above 2 indicating negative autocorrelation and values below 2 indicating positive autocorrelation In Table 4.1.1, the Durbin-Watson value is 1.682, which is less than 2.0, confirming the presence of positive autocorrelation in the sample.

Std Error of the Estimate Durbin-Watson

1 740 a 548 538 2.46124 1.682 a Predictors: (Constant), IQ, LA, TC, IN, TQ, CO b Dependent Variable: LS

4.5 Test of normality of residual and homoscedasticity

Homoscedasticity, as defined by Berry and Feldman (1985) and Tabachnick and Fidell (1996), refers to the condition where the variance of errors remains consistent across all levels of the independent variables In contrast, heteroscedasticity occurs when the variance of errors varies at different levels of the independent variables.

The research assessed the normality of residuals and homoskedasticity As illustrated in Appendix B, Chart 1 displays the Regression Standardized Residual, while Chart 2 presents the Normal P-P plot of the Regression Standardized Residual.

2) indicated that the residuals were normally distributed, the residual was relatively uncorrelated with the linear combination of predictors, and the variances of the residuals were constant Regression standardized predicted values in the chart 3 of Appendix B were distributed randomly The data therefore met the assumptions

To ensure accurate results regarding the correlations among predictor variables, researchers must test for multicollinearity A Variance Inflation Factor (VIF) greater than 10 indicates potential multicollinearity issues (Nguyen, 2011) In Table 4.6.1, the VIFs for six independent variables—learner attitude towards technology (LA), teaching capability (TC), course organization (CO), instructor-student interaction (IN), technology quality (TQ), and internet quality (IQ)—are presented, highlighting the importance of assessing these factors in research.

The analysis revealed that the values 1.078, 2.191, 2.711, 1.782, 1.997, and 1.953 were all lower than 10, indicating the absence of multicollinearity among the predictor variables This confirms that there was no multicollinearity present between the independent variables in the study.

4.7 No significant outliers or influential points

Case Number Std Residual LS Predicted Value Residual

B Std Error Beta Tolerance VIF

Casewise Diagnostics helps the studiers find the unvalued data in the analysis The data is not outlier when its Standardized Residual belongs the range of between -

3 and +3 (Nancy et al., 2005) According to table 4.7.1, the Standardized Residual of the case number 299 was 3.386, above +3 Therefore, this means that the case number

299 was outlier, and the researcher could consider to delete or to review it

Model Sum of Squares df Mean Square F Sig

Total 3910.970 298 a Predictors: (Constant), IQ, LA, TC, IN, TQ, CO b Dependent Variable: LS

The model summary table (Table 4.4.1) indicates that the multiple coefficient (R) is 54.8%, with an R-squared value of 548 The Adjusted R-squared is 538, demonstrating that 53.8% of the variability in LS can be predicted by the combined effects of IQ, LA, TC, IN, TQ, and CO.

The Anova table (Table 4.8.1) revealed a significant F-value of 58.936, indicating that the predictors effectively forecasted LS Furthermore, the p-value (Sig.) was below 0.05, supporting the conclusion that the model significantly enhances the understanding of student satisfaction in e-learning.

According to the table 4.6.1, it is clear that teaching capability (TC) (with ò 104, t= 1.784, sig = 075 > 5%) had a positive effect on learner satisfaction in e- learning In other words, H1a was unsupported

In the table 4.6.1, course organization (CO); including ò= 154, t= 2.382, and sig = 018 < 5%; had a positive effect on learner satisfaction in e-learning Hence, H1b was supported

Obviously, instructor-student interaction (IN) (with ò= 098, t= 1.865, sig .063 > 5%) had a positive effect on learner satisfaction in e-learning in the table 4.6.1

The analysis of learner attitude towards technology revealed a lack of positive correlation with learner satisfaction, indicated by values of ò= 033, t= 798, and a significance level of sig = 425, which exceeds the 5% threshold Consequently, the second hypothesis was not supported.

In the test, H3a and H3b were finally considered According to the Coefficients table, the p-values of technology quality (TQ) and internet quality (IQ)

The study found a statistically significant relationship between Transformational Engagement (TE), which encompasses both Transformational Quotient (TQ) and Intelligence Quotient (IQ), and Life Satisfaction (LS) The beta values indicated a positive influence of TE on LS, with TQ at 202 and IQ at 346, thereby supporting both hypothesis 3a and hypothesis 3b.

A regression analysis revealed that instructor capability (IC) and technology dimension (TE) significantly influence learner satisfaction (LS) in e-learning environments Key factors such as course organization (CO), technology quality (TQ), and internet quality (IQ) within IC and TE play a crucial role in enhancing LS, particularly in Vietnam Conversely, learner attitude (LA) was found to have a minimal effect on overall learner satisfaction when considering all predictors.

The analysis revealed that LS exhibited the strongest positive correlation with IQ, indicated by a beta weight of 0.346 and a p-value of 0.000, which is significant at the 5% level Additionally, a robust positive relationship was found between LS and TQ, with a beta weight of 0.202 and a p-value of 0.000, further supporting this connection The correlation between LS and CO was also notably positive, demonstrated by a beta weight of 0.154 and a p-value of 0.018, both of which are significant In contrast, LA showed no statistically significant relationship with LS, as evidenced by a beta weight of 0.033 and a p-value of 0.425, exceeding the 5% threshold.

LA, TC ( including ò =.104 and p=.075 > 5%), IN (ò =.098 and p=.063 > 5%) did not have statistically positive relations to LS In general, TQ, IQ and CO were the significant predictors of LS

Table 4.9.1: Results of the Testing Hypotheses

Research questions: The questions asked whether learner satisfaction impacted by instructor capability, learner attitutde and technology during the transaction on the internet

H2 Learner attitude towards computers will positively influence student satisfaction with e-learning in Vietnam

This research re-evaluated the factors influencing student satisfaction with e-learning at universities in Vietnam, identifying key elements such as instructor capability—which encompasses teaching effectiveness, course organization, and student-instructor interaction—and the technology dimension, which includes the quality of technology used in the learning process.

Internet quality) The strength of each factor on the e-learner satisfaction also is predicted, and presented in the below figure 4.9.2

Figure 4.9.2 The final research model

Multicollinearity test

To ensure accurate results regarding the correlations among predictor variables, researchers must conduct a multicollinearity test A Variance Inflation Factor (VIF) exceeding 10 indicates potential multicollinearity issues (Nguyen, 2011) In Table 4.6.1, it is evident that the VIFs for six independent variables—learner attitude towards technology (LA), teaching capability (TC), course organization (CO), instructor-student interaction (IN), technology quality (TQ), and internet quality (IQ)—are presented.

The results of the analysis revealed variance inflation factor (VIF) values of 1.078, 2.191, 2.711, 1.782, 1.997, and 1.953, all of which were below the threshold of 10 This indicates that multicollinearity among the predictor variables was not present, confirming that the independent variables in the study were not highly correlated.

No significant outliers or influential points

Case Number Std Residual LS Predicted Value Residual

B Std Error Beta Tolerance VIF

Casewise Diagnostics helps the studiers find the unvalued data in the analysis The data is not outlier when its Standardized Residual belongs the range of between -

3 and +3 (Nancy et al., 2005) According to table 4.7.1, the Standardized Residual of the case number 299 was 3.386, above +3 Therefore, this means that the case number

299 was outlier, and the researcher could consider to delete or to review it.

Hypotheses Testing

Model Sum of Squares df Mean Square F Sig

Total 3910.970 298 a Predictors: (Constant), IQ, LA, TC, IN, TQ, CO b Dependent Variable: LS

The model summary table (Table 4.4.1) indicates that the multiple coefficient (R) is 54.8% (R² = 548), with an Adjusted R Square of 538 This reflects that 53.8% of the variability in LS can be predicted by the combined effects of IQ, LA, TC, IN, TQ, and CO.

The Anova table (Table 4.8.1) revealed a significant F-value of 58.936, indicating that the combination of predictors effectively predicted learning satisfaction (LS) Additionally, the p-value was less than 0.05, confirming the model's strong capability in assessing student satisfaction in e-learning environments.

According to the table 4.6.1, it is clear that teaching capability (TC) (with ò 104, t= 1.784, sig = 075 > 5%) had a positive effect on learner satisfaction in e- learning In other words, H1a was unsupported

In the table 4.6.1, course organization (CO); including ò= 154, t= 2.382, and sig = 018 < 5%; had a positive effect on learner satisfaction in e-learning Hence, H1b was supported

Obviously, instructor-student interaction (IN) (with ò= 098, t= 1.865, sig .063 > 5%) had a positive effect on learner satisfaction in e-learning in the table 4.6.1

The analysis of learner attitude towards technology revealed a value of ò = 033, t = 798, and a significance level of sig = 425, indicating that learner attitude does not have a positive relationship with learner satisfaction Consequently, the second hypothesis was not supported.

In the test, H3a and H3b were finally considered According to the Coefficients table, the p-values of technology quality (TQ) and internet quality (IQ)

The study found a statistically significant relationship between Teacher Effectiveness (TE), which encompasses Teacher Quality (TQ) and Instructional Quality (IQ), and Learning Satisfaction (LS) The beta values indicated that TQ and IQ had positive influences on LS, with values of 202 and 346, respectively Thus, both hypothesis 3a and hypothesis 3b were supported, confirming the positive impact of TE on LS.

Summary of the Results

A regression analysis revealed that instructor capability (IC) and technology dimension (TE) significantly influence learner satisfaction (LS) in e-learning environments Specifically, factors such as course organization (CO), technology quality (TQ), and internet quality (IQ) under IC and TE play a crucial role in enhancing LS in Vietnam Conversely, learner attitude (LA) was found to have a lesser impact on overall learner satisfaction compared to other predictors.

The analysis revealed that LS exhibited the strongest positive correlation with IQ, indicated by a beta weight of 0.346 and a p-value of 0.000, which is statistically significant Additionally, LS also demonstrated a strong positive relationship with TQ, with a beta weight of 0.202 and a p-value of 0.000 Furthermore, the correlation between LS and CO was notably strong, as shown by a beta weight of 0.154 and a p-value of 0.018 In contrast, LA showed no statistically significant positive relationship with LS, evidenced by a beta weight of 0.033 and a p-value of 0.425.

LA, TC ( including ò =.104 and p=.075 > 5%), IN (ò =.098 and p=.063 > 5%) did not have statistically positive relations to LS In general, TQ, IQ and CO were the significant predictors of LS

Table 4.9.1: Results of the Testing Hypotheses

Research questions: The questions asked whether learner satisfaction impacted by instructor capability, learner attitutde and technology during the transaction on the internet

H2 Learner attitude towards computers will positively influence student satisfaction with e-learning in Vietnam

This research redefined the factors influencing student satisfaction with e-learning at universities in Vietnam, highlighting the importance of instructor capability—encompassing teaching skills, course organization, and student-instructor interaction—as well as the technology dimension, which includes technology quality.

Internet quality) The strength of each factor on the e-learner satisfaction also is predicted, and presented in the below figure 4.9.2

Figure 4.9.2 The final research model

Discussion, Implications, Limitation, and Conclusion

Discussion

This study investigated the factors influencing student satisfaction with e-learning in Vietnam, utilizing SPSS software for data analysis from a sample of 299 university students in Ho Chi Minh City The research identified three key dimensions affecting e-learner satisfaction: instructor capability, learner attitude, and technology The findings revealed that 53.8% of the variance in e-learner satisfaction could be attributed to these dimensions, with instructor capability and technology being the most significant predictors This contradicts previous studies, as a positive relationship between technology and student satisfaction was established The predictive model for learner satisfaction can be represented as LS = IC*ò1 + LA*ò2 + TE*ò3, where LS denotes e-learner satisfaction, IC represents instructor capability, and TE signifies the technology dimension, with ò1, ò2, and ò3 as empirically determined Beta weights Overall, instructor capability and technology are crucial factors that positively influence learner satisfaction in e-learning environments.

Implications and suggestions

This study enhances our understanding of the impact of instructor capability on learner satisfaction in Vietnam, revealing that effective course organization significantly boosts e-learner satisfaction These findings align with previous research by Smeets (2005) and Piccoli et al., emphasizing the importance of structured courses in online learning environments.

Instructors play a crucial role in the quality of education, particularly in e-learning environments, where their capability significantly impacts student satisfaction and learning performance Research indicates that while teaching factors account for only 18% of learning variance in developed countries, the interaction between students and instructors is essential for fostering a sense of personalization and overcoming feelings of remoteness Effective course organization, which includes course design, teaching materials, and flexibility, is also vital for enhancing student satisfaction in online learning Unlike traditional classroom settings, e-learning offers the advantage of flexibility, allowing students, especially those in continuing education, to effectively balance their professional and personal commitments.

As Vietnam transitions from a centrally planned to a market-oriented economy, the demand for a qualified labor force is surging, prompting universities to significantly increase the number of e-learning students This shift is facilitated by technological innovations and the Internet, which enhance access to higher education However, the rapid growth of e-learning reveals a shortage of capable online instructors in Vietnamese universities, impacting e-learner satisfaction This study highlights the critical role of instructor capability in ensuring a positive online learning experience To address this, instructors should focus on effective online course organization, foster student-instructor interaction, and enhance their teaching skills University administrators are encouraged to implement strategic recruitment and training programs to elevate teaching quality Additionally, proper course scheduling, well-structured discussions, and comprehensive course materials are essential for improving e-learner satisfaction, alongside robust instructional expertise and technical support.

A review of education and training in computer and Internet use reveals that, despite some inconsistencies with previous research, there remains no significant correlation between student satisfaction and attitudes toward technology In many countries, university students are mandated to complete technology courses to enhance their digital literacy, indicating that technology illiteracy is no longer an issue among college students As attitudes toward technology have evolved, it is clear that e-learning students must engage with technology extensively, which can lead to increased satisfaction To further boost user satisfaction and enhance e-learning effectiveness, Vietnamese universities should focus on improving students' knowledge of computers and related technologies By fostering a deeper understanding of technological innovations, a more positive student attitude is likely to develop.

Vietnam, in fact, although having approaches to computers and technology innovations, university students have incompletely applies them for their own study

To enhance students' proficiency in technology and e-learning, Vietnamese universities should integrate qualified computer and technology courses into their curriculums Mandatory participation in these courses will enable students to effectively utilize technology in their e-learning experiences, fostering a positive attitude towards computers and technology Furthermore, promoting the use of technological innovations in e-learning will boost student satisfaction and engagement, ultimately enriching the overall learning experience in Vietnamese higher education.

This study highlights the critical role of technology in enhancing e-learner satisfaction, despite some discrepancies with previous research findings The technology dimension significantly impacts e-learning satisfaction, as observed through student interactions and current technological applications While developed countries benefit from advanced e-learning technologies, developing nations, including Vietnam, often lack the necessary infrastructure to support effective online education Poor technology, characterized by slow response times and frequent issues, discourages learners and hinders the adoption of e-learning innovations To improve e-learning satisfaction, Vietnamese universities must invest in advanced technology, including high-speed networks and up-to-date software and hardware Furthermore, building a skilled workforce to manage these technologies is essential for maintaining quality online education.

To enhance student satisfaction in online courses at Vietnamese universities, it is essential to maintain a high-speed internet connection and advanced technology Additionally, universities should explore opportunities for financial support from the government, funds, and organizations to effectively upgrade their technological infrastructure.

Conclusion

Online e-learning has emerged as a viable alternative to traditional education, particularly benefiting non-traditional students who balance work and study As universities globally adopt e-learning, the complexity of the learning environment increases due to reliance on the Internet This research identifies key factors influencing e-learner satisfaction, based on a study that achieved a 49.83% response rate with 299 valid questionnaires A stepwise multiple regression analysis revealed that course organization, technology quality, and Internet quality are critical to learners' perceived satisfaction in Vietnamese universities The study found that six factors—teaching capability, course organization, learner attitude towards technology, technology quality, and Internet quality—account for 65.476% of the variance in learner satisfaction An integrated model, refined through Principle Axis Factoring with Promax methods, enhances understanding of e-learner satisfaction and offers practical tools to improve online education in Vietnam This model not only deepens insights into satisfaction predictors but also supports the advancement of e-learning initiatives.

This study acknowledges several limitations that can guide future research Firstly, the model was tested solely on business students from a few universities in Ho Chi Minh City, suggesting the need for broader testing across various universities in different cities and provinces, such as Can Tho and Hanoi, to improve the generalizability of the findings Secondly, the model focused on only three factors— instructor capability, learner attitude towards computers, and technology dimension—affecting e-learner satisfaction, while other factors like assessment diversity, perceived usefulness, and perceived ease of use should also be explored in future studies Additionally, researchers have proposed that learning performance and student scores could serve as dependent variables influencing learner satisfaction in e-learning, indicating that the current study may not be comprehensive due to constraints in cost, time, and resources Conducting extensive research in Vietnam often requires significant investment and time for data collection and analysis Lastly, while this study employed stepwise multiple regression analysis, alternative statistical methods, such as SEM (e.g., LISREL, EQS, PLS) or neural networks, could provide further insights into the relationships between variables.

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Teaching capability The instructor appears to be knowledgeable about the course materials

The instructor explains the course materials clearly and understandably

The instructor carefully prepares the course materials

The course objectives and contents are clearly introduced

The online course is systematically organized

I fully apprehend the objectives and requirements of the online course

The instructor makes clear the requirements of the course on the Internet

The instructor stimulates online and class discussion

I often discuss with the instructor about the course matters on the Internet

I often discuss with my classmates about the matters of course on the Internet

The instructor encourages students to ask questions via information technology (IT) devices

The instructor encourages students to express new ideas and opinions through IT devices

Learner attitudes towards technology often reflect a belief that working with computers is complex and requires technical skills, with some thinking that programming knowledge is essential and that technology is primarily suited for younger individuals However, many recognize that technology can enhance productivity in the workplace In contrast, the quality of information technologies used in e-learning is generally perceived as user-friendly, offering a variety of useful functions, good flexibility, and easy accessibility.

Internet quality I feel satisfied with the speed of the Internet

I feel that it is easy to go on-line

& Yeh (2006) E-learner satisfaction I am satisfied with my decision to take this course via the

If I had an opportunity to take another course via the Internet, I would gladly do so

I feel that this course served my needs well

I will take as many courses via the Internet as I can

STUDENT SURVEY FORM (PHIẾU KHẢO SÁT Ý KIẾN SINH VIÊN)

Participation in this anonymous and voluntary study allows you to withdraw at any time This research focuses on your perceptions of E-learning, which involves utilizing technological innovations like mobile phones, laptops, iPads, and computers, along with the Internet for educational purposes The study is part of a master's thesis titled “Some Factors Influencing Student Satisfaction with E-learning.” It aims to provide empirical insights into the factors affecting student satisfaction and offers strategic recommendations for the development of E-learning in Vietnam We appreciate your cooperation in selecting the appropriate answers Thank you!

Filter questions (Câu hỏi bắt buộc)

Have you participated in any academic courses that integrate internet and technological innovations, such as mobile phones, laptops, iPads, and computers? Engaging in such courses can enhance your learning experience by leveraging modern technology.

Yes ( Có): => Continue (Tiếp tục trả lời)

No ( Không): => Stop ( Dừng tại đây)

The following statements evaluate your perceptions of online learning For each statement, please select and circle the number that reflects your level of agreement or disagreement using the provided scale.

Teaching capability ( Khả năng giảng dạy)

1/ The instructor appears to be knowledgeable about the course materials (Giáo viên có kiến thức chuyên sâu về môn học)……… … 1 2 3 4 5

2/ The instructor explains the course materials clearly and understandably (Người hướng dẫn giải thích các tài liệu học tập rõ ràng và dễ hiểu)……… 1 2 3 4 5

3/The instructor carefully prepares the course materials (Người hướng dẫn chuẩn bị các tài liệu học tập một cách cẩn thận)……… ……… 1 2 3 4 5

Online course organization ( Tổ chức khóa học trực tuyến)

4/ The course objectives and contents are clearly introduced (Các mục tiêu và nội dung khóa học được giới thiệu rõ ràng)………… ……….…….1 2 3 4 5

5/ The online course is systematically organized (Các khóa học trực tuyến được tổ chức có hệ thống )……… ……… 1 2 3 4 5

6/ I fully apprehend the objectives and requirements of the online course (Tôi hoàn toàn bắt được các mục tiêu và yêu cầu của khóa học trực tuyến )…… … 1 2 3 4 5

7/ The instructor makes clear the requirements of the course on the Internet (Người dạy làm rõ các yêu cầu của khóa học trên Internet )……… 1 2 3 4 5

Instructor-student interaction (Tương tác giữa giáo viên và người học)

8/ The instructor stimulates online and class discussion (Người hướng dẫn khuyến khích thảo luận trên mạng và ở lớp )……… ……… 5 4 3 2 1

9/ I often discuss with the instructor about the course matters on the Internet ( Tôi thường thảo luận với giáo viên về các vấn đề của khóa học trên mạng)……5 4 3 2 1

10/ I often discuss with my classmates about the course matters on the Internet (Tôi thường thảo luận với bạn cùng lớp của tôi về các vấn đề trong khóa học trên mạng Internet)……… 5 4 3 2 1

11/ The instructor encourages students to ask questions via information technology (IT) devices (Giảng viên khuyến khích sinh viên đặt câu hỏi thông qua các thiết bị công nghệ thông tin ( CNTT) )……….……….….5 4 3 2 1

12/ The instructor encourages students to express new ideas and opinions through IT devices (Giảng viên khuyến khích sinh viên thể hiện những ý tưởng mới và ý kiến thông qua các thiết bị CNTT) ……… ….5 4 3 2 1

Learner attitude toward technology (Thái độ của người học đối với máy tính)

13/ I believe that working with technology is very difficult (Tôi tin rằng làm việc

14/ I believe that working with technology is very complicated (Tôi tin rằng làm việc với máy tính là rất phức tạp )………1 2 3 4 5

15/ I believe that working with technology requires technical ability (Tôi tin rằng làm việc với máy tính đòi hỏi có kỹ thuật )………1 2 3 4 5

16/ I believe that working with technology can be done only if one knows a programming language (Tôi tin rằng làm việc với máy tính có thể được thực hiện chỉ nếu ai biết ngôn ngữ lập trình)……… 1 2 3 4 5

17/ I believe that working with technology is for young people only (Tôi tin rằng làm việc với máy tính là chỉ dành cho những người trẻ tuổi)………… ………1 2 3 4 5

Technology quality (Chất lượng công nghệ)

18/ I feel the information technologies used in e-learning are very easy to use (Tôi cảm thấy công nghệ thông tin được sử dụng trong học tập điện tử là rất dễ sử dụng)……… 5 4 3 2 1

19/ I feel the information technologies used in e-learning have many useful functions (Tôi cảm thấy công nghệ thông tin được sử dụng trong học tập trực tuyến có nhiều chức năng hữu ích )……… ……….5 4 3 2 1

20/ I feel the information technologies used in e-learning have good flexibility (Tôi cảm thấy công nghệ thông tin được sử dụng trong học tập điện tử có tính linh hoạt)………5 4 3 2 1

21/ I feel the information technologies used in e-learning are easy to obtain (Tôi cảm thấy công nghệ thông tin được sử dụng trong học tập điện tử là dễ dàng để có được)……….……… 5 4 3 2 1

Internet quality ( Chất lượng internet)

22/ I feel satisfied with the speed of the Internet (Tôi cảm thấy hài lòng với tốc độ của Internet )……….………5 4 3 2 1

23/ I feel that it is easy to go on-line (Tôi cảm thấy rằng nó rất dễ dàng để lên mạng)……… 5 4 3 2 1

E-learner satisfaction (Sự hài lòng của người học)

Tiêu đề	Some Factors Influencing Student Satisfaction in E-Learning, A Study of University Students in Ho Chi Minh City, Viet Nam
Tác giả	Nguyen Huu Quy
Người hướng dẫn	Dr. Nguyen Dong Phong
Trường học	University of Economics Ho Chi Minh City
Chuyên ngành	Master of Business
Thể loại	thesis
Năm xuất bản	2014
Thành phố	Ho Chi Minh City

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