Factors Affecting Students’ Perceived Outcomes and Satisfaction in Virtual Classrooms

Authors

  • Xiem Thuy Cao National Economics University, Hanoi, Vietnam
  • The Doan Truong National Economics University, Hanoi, Vietnam

DOI:

https://doi.org/10.52296/vje.2022.167

How to Cite

Cao, X. T., & Truong, T. D. (2022). Factors Affecting Students’ Perceived Outcomes and Satisfaction in Virtual Classrooms. Vietnam Journal of Education, 6(2), 161–171. https://doi.org/10.52296/vje.2022.167

Abstract

The sudden switch from the traditional face-to-face classroom to a synchronous virtual classroom has been a challenge to universities’ lecturers and students. This study aims to determine factors affecting students’ perceived learning outcomes and satisfaction in the virtual mode of education. The structural equation model-based PLS technology is applied to analyze the relationships between the five factors and perceived learning outcomes and satisfaction of students who participated in online courses at three state universities in Hanoi. The study found four factors that significantly affected the students’ perceived outcomes: assessment, infrastructure, interaction, and self-motivation. Three factors that influence student satisfaction are infrastructure, interaction, and lecturer knowledge and facilitation. The survey was conducted virtually at an unfavorable time so the majority of survey respondents were first-year students, which might result in biased estimates. The research findings suggest that universities should provide more technological supports for both teachers and students, re-module subjects, ensure more realistic, justified, and unbiased assessment, stimulate teachers to interact with students respectfully and flexibly, take self-motivation in consideration in course design, and provide financial support in various forms for students. The research findings contribute to a comprehensive assessment of the effectiveness of online teaching and learning in the inevitable context of the COVID-19 pandemic.

Downloads

Download data is not yet available.

References

Alavi, M., Wheeler, B. C., & Valacich, J. S. (1995). Using IT to Reengineer Business Education: An Exploratory Investigation of Collaborative Telelearning. MIS Quarterly, 19(3), 293-312. https://doi.org/10.2307/249597

Chin, W., & Marcoulides, G. (1998). The Partial Least Squares Approach to Structural Equation Modeling. Modern Methods for Business Research, 8.

Cohen, J. (1988). Set Correlation and Contingency Tables. Applied Psychological Measurement, 12(4), 425-434. https://doi.org/10.1177/014662168801200410

Colley, A. M., Gale, M. T., & Harris, T. A. (1994). Effects of Gender Role Identity and Experience on Computer Attitude Components. Journal of Educational Computing Research, 10(2), 129-137. https://doi.org/10.2190/8NA7-DAEY-GM8P-EUN5

Collis, B. (1991). Anticipating the impact of multimedia in education: lessons from literature. International Journal of Computers in Adult Education and Training, 2(2), 136-149.

Daft, R. L., & Lengel, R. H. (1986). Organizational Information Requirements, Media Richness and Structural Design. Management Science, 32(5), 554-571. https://doi.org/10.1287/mnsc.32.5.554

Eom, S., Wen, J., & Ashill, N. (2006). The Determinants of Students’ Perceived Learning Outcomes and Satisfaction in University Online Education: An Empirical Investigation. Decision Sciences Journal of Innovative Education, 4, 215-235. https://doi.org/10.1111/j.1540-4609.2006.00114.x

Falk, R., & Miller, N. (1992). A Primer for Soft Modeling. The University of Akron Press: Akron, OH.

Graham, M., & Scarborough, H. (2001). Enhancing the learning environment for distance education students. Distance Education, 22(2), 232-244. https://doi.org/10.1080/0158791010220204

Hillman, D. C. A., Willis, D. J., & Gunawardena, C. N. (1994). Learner‐interface interaction in distance education: An extension of contemporary models and strategies for practitioners. American Journal of Distance Education, 8(2), 30-42. https://doi.org/10.1080/08923649409526853

Keramati, A., Afshari-Mofrad, M., Amir-Ashayeri, D., & Nili, A. (2011). The Intervening Role of Infrastructures in E-Learning Performance. Digital Enterprise and Information Systems, Berlin, Heidelberg.

Leidner, D., & Jarvenpaa, S. (1995). The Use of Information Technology to Enhance Management School Education: A Theoretical View. MIS Quarterly, 19(3), 265-291. https://doi.org/10.2307/249596

Martin, F., Parker, M., & Deale, D. (2012). Examining Interactivity in Synchronous Virtual Classrooms. International Review of Research in Open and Distance Learning, 13, 227-260. https://doi.org/10.19173/irrodl.v13i3.1174

Moore, M. (1989). Three Types of Interaction. American Journal of Distance Education, 3, 1-7. https://doi.org/10.1080/08923648909526659

Nunnally, J. C. B. I. H. (1994). Psychometric theory. McGraw-Hill.

Peltier, J., Drago, W., & Schibrowsky, J. (2003). Virtual Communities and the Assessment of Online Marketing Education. Journal of Marketing Education, 25, 260-276. https://doi.org/10.1177/0273475303257762

Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-Based Virtual Learning Environments: A Research Framework and a Preliminary Assessment of Effectiveness in Basic IT Skills Training. MIS Quarterly, 25, 401-426. https://doi.org/10.2307/3250989

Quispe-Prieto, S., Cavalcanti-Bandos, M. F., Caipa-Ramos, M., Paucar-Caceres, A., & Rojas-Jiménez, H. H. (2021). A Systemic Framework to Evaluate Student Satisfaction in Latin American Universities under the COVID-19 Pandemic. Systems, 9(1), 15. https://doi.org/10.3390/systems9010015

Reeves, T., & Harmon, S. (1993). Systematic evaluation procedures for instructional hypermedia/multimedia. Annual Meeting of the American Educational Research Association, Atlanta.

Sanders Lopez, E., & Nagelhout, E. (1995). Building a Model for Distance Collaboration in the Computer-Assisted Business Communication Classroom. Business Communication Quarterly, 58(2), 15-20. https://doi.org/10.1177/108056999505800203

Schunk, D. H., & Zimmerman, B. J. (1994). Self-regulation of learning and performance: Issues and educational applications. Lawrence Erlbaum Associates, Inc.

Smith, P. (2001). Understanding Self-Regulated Learning and Its Implications for Accounting Educators and Researchers. Issues in Accounting Education, 16, 663-700. https://doi.org/10.2308/iace.2001.16.4.663

Soong, M. B., Chan, H. C., Chua, B. C., & Loh, K. F. (2001). Critical success factors for on-line course resources. Computers & Education, 36(2), 101-120. https://doi.org/10.1016/S0360-1315(00)00044-0

Swan, K. (2001). Virtual interaction: Design factors affecting student satisfaction and perceived learning in asynchronous online courses. Distance Education, 22(2), 306-331. https://doi.org/10.1080/0158791010220208

Trevitt, C. (1995). Interactive Multimedia in University Teaching and Learning: Some Pointers to Help Promote Discussion of Design Criteria. Paper presented at the Computers in University biological Education Virtual Conference, CITI Liverpool.

Volery, T., & Lord, D. (2000). Critical success factors in online education. International Journal of Educational Management, 14, 216-223. https://doi.org/10.1108/09513540010344731

Webster, J., & Hackley, P. (1997). Teaching Effectiveness in Technology-Mediated Distance Learning. The Academy of Management Journal, 40(6), 1282-1309. https://doi.org/10.2307/257034

Downloads

Published

2022-06-12

How to Cite

Cao, X. T., & Truong, T. D. (2022). Factors Affecting Students’ Perceived Outcomes and Satisfaction in Virtual Classrooms. Vietnam Journal of Education, 6(2), 161–171. https://doi.org/10.52296/vje.2022.167

Issue

Section

Articles