The outbreak of the Covid-19 pandemic has significantly impacted various sectors of society, including the field of Education and Training. In the pre-Covid era, online learning was primarily used as a supplementary tool for students to reinforce their knowledge through individual and group assignments, quizzes, and tests to assess their understanding after classroom sessions. However, with the emergence and widespread development of the Covid-19 pandemic, online learning has become the primary mode of education, occupying all of the students‘ study time. As the Covid-19 pandemic progressed, online learning required a high level of collaboration between educators and students to ensure effective learning. Even after the end of the pandemic, online learning has become more prevalent and can be offered alongside traditional classroom-based courses. Therefore, analyzing and evaluating the factors that influence students‘ satisfaction with online learning is essential. The results of this study will provide insights to enhance the satisfaction of students at the Faculty of Finance and Banking at Van Lang University, especially when engaging in online learning.
Previous research studies have laid the foundation for identifying the factors influencing student satisfaction with online learning. According to Philip Kotler (2000), satisfaction depends on expectations and outcomes. Chen (2007) defined the quality of university education, including curriculum, quality of lecturers, facilities, student characteristics, administrative management, and interactive systems. Various studies by researchers such as Mahmoud Maqableh and Mohammad Alia (2021), Pei-Chen Sun (2008), Vu Thuy Hang and Nguyen Manh Tuan (2013), Dang Thi Thuy Hien (2020), Phan Thi Ngoc Thanh (2020), Nguyen Thi Ngoc Diep and Doan Thi Hong Nga (2021) have identified factors affecting student satisfaction and barriers to online learning. These factors may include technology, time management, student attitudes, instructor attitudes, course design, user interface, learning community, content personalization, internet connectivity, responsiveness, reliability, among others.
The research methodology employed in this study involved analyzing the impact of five representative factors on student satisfaction at the Faculty of Finance and Banking at Van Lang University during the Covid-19 period. The study utilized quantitative methods and the SPSS 26 software for analysis. The five factors in the regression model included information, course content; teaching methods; assessment methods; technology support; and support for related issues during the learning process.
The linear multiple regression model proposed was as follows:
SHL = β0 + β1X1 + β2X2 + β3X3 + β4X4 + β5*X5 + ei
Where:
SHL: student satisfaction at the Faculty of Finance and Banking when learning online during the Covid-19 period.
βk: regression equation coefficients, ei is the residual.
X1: Group of factors 1, including variables related to information and course content.
X2: Group of factors 2, including variables related to teaching methods.
X3: Group of factors 3, including variables related to assessment methods.
X4: Group of factors 4, including variables related to technology support during online learning.
X5: Group of factors 5, including variables related to support for various issues during online learning.
The study collected primary data through a survey using Google Forms, with a Likert scale questionnaire sent to students from various cohorts at the Faculty of Finance and Banking from December 2021 to May 2022. The survey yielded 149 valid responses out of 151 distributed, comprising 29 observed variables of the five independent variables and three observed variables of the dependent variable, meeting the required sample size for analysis.
The results of the statistical analysis showed that the average values of the observed variables were above 4 (ranging from 4.00 to 4.48 on a 5-point scale) with standard deviations ranging from 0.65 to 0.94. The highest average value was in the group of observed variables related to teaching methods and assessment methods.
The factor analysis of the independent variables revealed three factors extracted from 29 observed variables. These factors were redefined as content, implementation, and support. The content factor included reference materials; teaching methods; students acquiring skills during online learning; encouragement of students to study and research; appropriate assessment content; appropriate assessment methods; appropriate feedback on assessment results. The implementation factor included students receiving necessary information; course content meeting objectives; allocation of theoretical content, practical exercises, and assignments; fair and reasonable assessment; guidance and support for online software; students being able to use multiple devices for online learning. The support factor included students‘ reasonable resolution of related requirements during online learning; students receiving timely information through various channels; the university’s technology platform meeting teaching and learning needs online.
The factor analysis of the dependent variables revealed one factor extracted from three observed variables. This factor represented student satisfaction, and all three observed variables were retained in the model.
The final regression model after adjustments included three independent variables and one dependent variable in the form:
SHL = β0 + β1Content + β2Implementation + β3*Support + ei
The correlation analysis of the variables showed that all variables had a significance level of 0.000 and a high reliability (99%), indicating a strong positive correlation between the dependent variable and the independent variables. The correlation between the independent variables was also positive and highly correlated.
The model’s goodness-of-fit evaluation showed an adjusted R2 value of 75.6%, indicating that 75.6% of the variation in student satisfaction with the quality of service during online learning in the Covid-19 period was explained by the linear relationship of the independent variables.
Subsequently, the model was tested for the hypothesis β1 = β2 = β3 = 0.
Therefore, the study concluded that course content and related support during the learning process are the two factors that significantly impact the satisfaction of students at the Faculty of Finance and Banking at Van Lang University with the quality of service when engaging in online learning during the Covid-19 period.
In conclusion, the research model developed with five factors influencing student satisfaction with online learning during the Covid-19 period identified content and support as the key factors affecting student satisfaction. Among these factors, content had a stronger impact on student satisfaction compared to support.
Overall, this study provides valuable insights for the Faculty of Finance and Banking at Van Lang University to enhance the quality of online learning and improve student satisfaction in the post-Covid era.
References:
- Dang Thi Thuy Hien et al. (2020). Barriers to online learning for students at the Faculty of Tourism – Hue University. Journal of Science, Hue University: Economics and Development, Volume 129, Issue 5C.
- Phan Thi Ngoc Thanh, Nguyen Ngoc Thong, Nguyen Thi Phuong Thao (2020). Student perceptions of fully online learning during the Covid-19 pandemic. Journal of Science, Ho Chi Minh City Open University, 15(4), 18-28.
- Nguyen Thi Ngoc Diep, Doan Thi Hong Nga (2021). Evaluating student satisfaction with the quality of university education services through E-learning in the context of Covid-19 at Lac Hong University. Education Journal, Issue 493, Part 1.
- Vu Thuy Hang, Nguyen Manh Tuan (2013). Integrating factors affecting learner satisfaction into the E-learning system: A case study at the University of Economics – Law. Journal of Science, Ho Chi Minh City University of Education, 53, 24-46.
- Chen, C., Sok, P., & Sok, K. (2007). Benchmarking potential factors leading to education quality: A study of Cambodian higher education. Quality Assurance in Education, 15(2).
- Mahmoud Maqableh, Mohammad Alia (2021). Evaluation online learning of undergraduate students under lockdown amidst Covid-19 Pandemic: The online learning experience and students’ satisfaction. Children and Youth Services Review, 128, 106160.
- Pei-Chen Sun, Ray J. Tsai, Glenn Finger, Yueh-Yang Chen, Dowming Yeh (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183-1202.
- Philip Kotler (2000). Marketing Management. USA: Prentice Hall.
In conclusion, the study provides valuable insights into the factors influencing student satisfaction with online learning at the Faculty of Finance and Banking at Van Lang University during the Covid-19 period. The findings highlight the importance of course content and support in enhancing student satisfaction with the quality of online education. This research serves as a foundation for improving online learning experiences and student satisfaction in the post-pandemic era.