CÁC YẾU TỐ ẢNH HƯỞNG ĐẾN SỰ HÀI LÒNG CỦA SINH VIÊN ĐỐI VỚI HỌC TẬP KẾT HỢP: NGHIÊN CỨU TRƯỜNG HỢP TRƯỜNG DU LỊCH – ĐẠI HỌC HUẾ
Vol. 130 No. 6E (2021), Tạp chí Khoa học Đại học Huế: Khoa học Xã hội và Nhân văn
Vol. 130 No. 6E (2021)

CÁC YẾU TỐ ẢNH HƯỞNG ĐẾN SỰ HÀI LÒNG CỦA SINH VIÊN ĐỐI VỚI HỌC TẬP KẾT HỢP: NGHIÊN CỨU TRƯỜNG HỢP TRƯỜNG DU LỊCH – ĐẠI HỌC HUẾ

Tạp chí Khoa học Đại học Huế: Khoa học Xã hội và Nhân văn
https://doi.org/10.26459/hueunijssh.v130i6E.6222
Published 2021-07-30
  • Nghia Nguyen
  • Tuấn Trần
Nghia Nguyen
Tuấn Trần

Abstract

Blended learning is a flexible teaching organization, a "thorough" combination between online and traditional learning. The effective implementation of a blended learning framework needs to be considered from the learners' side. Consequently, this study examines the opinions of 122 students who have taken blended learning courses to identify the factors that positively affect student satisfaction including (1) Face-to-face learning, (2) Playfulness and usefulness of online learning, (3) Perceived ease of use of an online learning system. The management implications to enhance student satisfaction with blended learning at the School of Hospitality and Tourism are proposed.

https://doi.org/10.26459/hueunijssh.v130i6E.6222
PDF (Vietnamese)

References

  1. Afacan, Y. (2018). Student experiences of blended learning in interior architecture. Journal of Information Technology Education: Research, 17, 399-422.
  2. Ali, A., & Ahmad, I. (2011). Key factors for determining student satisfaction in distance learning courses: A study of Allama Iqbal Open University. Contemporary Educational Technology, 2(2), 118-134.
  3. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (pp. 11-39). Springer, Berlin, Heidelberg.
  4. Akkoyunlu, B., & Soylu, M. Y. (2006). A study on students’ views on blended learning environment. Turkish Online Journal of Distance Education, 7(3), 43-56.
  5. Allen, I. E., & Seaman, J. (2010). Class differences: Online education in the United States, 2010. Sloan Consortium (NJ1).
  6. Bandura, A. (1986). Fearful expectations and avoidant actions as coeffects of perceived self-inefficacy.
  7. Harvey, B., & Beards, D. (2004). E‐learning in Scottish further and higher education. Education+ Training.
  8. Bhuasiri, W., Xaymoungkhoun, O., Zo, H., Rho, J. J., & Ciganek, A. P. (2012). Critical success factors for e-learning in developing countries: A comparative analysis between ICT experts and faculty. Computers & Education, 58(2), 843-855.
  9. Birbal, R., Ramdass, M., & Harripaul, M. C. (2018). Student teachers’ attitudes towards blended learning. Journal of Education and Human Development, 7(2), 9-26.
  10. Booker, Q. E., & Rebman, C. E. (2005). E-student retention: Factors affecting customer loyalty for online program success. Issues in Information Systems, 6(1), 183-189.
  11. Brew, L. S. (2008). The role of student feedback in evaluating and revising a blended learning course. The Internet and Higher Education, 11(2), 98-105.
  12. Çakır, H., & Bichelmeyer, B. A. (2016). Effects of teacher professional characteristics on student achievement: an investigation in blended learning environment with standards-based curriculum. Interactive Learning Environments, 24(1), 20-32.
  13. Shernoff, D. J., Csikszentmihalyi, M., Schneider, B., & Shernoff, E. S. (2014). Student engagement in high school classrooms from the perspective of flow theory. In Applications of flow in human development and education (pp. 475-494). Springer, Dordrecht.
  14. Chen, H. R., & Tseng, H. F. (2012). Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan. Evaluation and program planning, 35(3), 398-406.
  15. Cheng, B., Wang, M., Moormann, J., Olaniran, B. A., & Chen, N. S. (2012). The effects of organizational learning environment factors on e-learning acceptance. Computers & Education, 58(3), 885-899.
  16. Chow, M., Herold, D. K., Choo, T. M., & Chan, K. (2012). Extending the technology acceptance model to explore the intention to use Second Life for enhancing healthcare education. Computers & education, 59(4), 1136-1144.
  17. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
  18. Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International journal of man-machine studies, 38(3), 475-487.
  19. DeBourgh, G. A. (2003). Predictors of student satisfaction in distance-delivered graduate nursing courses: what matters most?. Journal of Professional Nursing, 19(3), 149-163.
  20. Driscoll, M. (2002). Blended learning: Let’s get beyond the hype. E-learning, 1(4), 1-4.
  21. Elliott, K. M., & Shin, D. (2002). Student satisfaction: An alternative approach to assessing this important concept. Journal of Higher Education policy and management, 24(2), 197-209.
  22. Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological bulletin, 82(2), 261.
  23. Garrison, D. R., & Kanuka, H. (2004). Blended learning: Uncovering its transformative potential in higher education. The internet and higher education, 7(2), 95-105.
  24. Graham, C. R. (2006). Blended learning systems. The handbook of blended learning: Global perspectives, local designs, 1, 3-21.
  25. Graham, C. R. (2009). Blended learning models. In Encyclopedia of Information Science and Technology, Second Edition (pp. 375-382). IGI Global.
  26. Graham, C. R. (2013). Emerging practice and research in blended learning. Handbook of distance education, 3, 333-350.
  27. Hrastinski, S. (2019). What do we mean by blended learning?. TechTrends, 63(5), 564-569.
  28. Joo, Y. J., Lim, K. Y., & Kim, E. K. (2011). Online university students' satisfaction and persistence: Examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & education, 57(2), 1654-1664.
  29. King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & management, 43(6), 740-755.
  30. Lee, B. C., Yoon, J. O., & Lee, I. (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers & education, 53(4), 1320-1329.
  31. Li, Y., Duan, Y., Fu, Z., & Alford, P. (2012). An empirical study on behavioural intention to reuse e‐learning systems in rural China. British Journal of Educational Technology, 43(6), 933-948.
  32. Lin, W. S., & Wang, C. H. (2012). Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit. Computers & Education, 58(1), 88-99
  33. Masrom, M. (2007). Technology acceptance model and e-learning. Technology, 21(24), 81.
  34. Mohammadi, H. (2015). Investigating users’ perspectives on e-learning: An integration of TAM and IS success model. Computers in human behavior, 45, 359-374.
  35. Abou Naaj, M., Nachouki, M., & Ankit, A. (2012). Evaluating student satisfaction with blended learning in a gender-segregated environment. Journal of Information Technology Education: Research, 11(1), 185-200.
  36. Rahman, N. A. A., Hussein, N., & Aluwi, A. H. (2015). Satisfaction on blended learning in a public higher education institution: What factors matter?. Procedia-social and behavioral sciences, 211, 768-775.
  37. Olapiriyakul, K., & Scher, J. M. (2006). A guide to establishing hybrid learning courses: Employing information technology to create a new learning experience, and a case study. The Internet and Higher Education, 9(4), 287-301.
  38. Oliver, M., & Trigwell, K. (2005). Can ‘blended learning’be redeemed?. E-learning and Digital Media, 2(1), 17-26.
  39. Padilla-Meléndez, A., del Aguila-Obra, A. R., & Garrido-Moreno, A. (2013). Perceived playfulness, gender differences and technology acceptance model in a blended learning scenario. Computers & Education, 63, 306-317.
  40. Picciano, A. G. (2002). Beyond student perceptions: Issues of interaction, presence, and performance in an online course. Journal of Asynchronous learning networks, 6(1), 21-40.
  41. Prieto, I. M., & Revilla, E. (2006). Assessing the impact of learning capability on business performance: empirical evidence from Spain. Management Learning, 37(4), 499-522.
  42. Reinhart, J., & Schneider, P. (2001). Student satisfaction, self-efficacy, and the perception of the two-way audio/video distance learning environment: A preliminary examination. Quarterly Review of Distance Education, 2(4), 357-65.
  43. Styron Jr, R. (2010). Student satisfaction and persistence: Factors vital to student retention. Research in Higher Education Journal, 6, 1.
  44. Sahin, I., & Shelley, M. (2008). Considering students' perceptions: The distance education student satisfaction model. Journal of Educational Technology & Society, 11(3), 216-223.
  45. Sher, A. (2009). Assessing the relationship of student-instructor and student-student interaction to student learning and satisfaction in web-based online learning environment. Journal of Interactive Online Learning, 8(2).
  46. Small, F., Dowell, D., & Simmons, P. (2012). Teacher communication preferred over peer interaction: Student satisfaction with different tools in a virtual learning environment. Journal of International Education in Business, 5(2), 114-128.
  47. Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & education, 50(4), 1183-1202.
  48. Sweeney, J. C., & Ingram, D. (2001). A comparison of traditional and web-based tutorials in marketing education: An exploratory study. Journal of Marketing Education, 23(1), 55-62.
  49. Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS quarterly, 561-570.
  50. Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information systems research, 11(4), 342-365.
  51. Walker, S. L., & Fraser, B. J. (2005). Development and validation of an instrument for assessing distance education learning environments in higher education: The Distance Education Learning Environments Survey (DELES). Learning Environments Research, 8(3), 289-308.
  52. Watson, J. (2008). Blended Learning: The Convergence of Online and Face-to-Face Education. Promising Practices in Online Learning. North American Council for Online Learning.
  53. Chen, N. S., Wei, C. W., & Chen, H. J. (2008). Mining e-Learning domain concept map from academic articles. Computers & Education, 50(3), 1009-1021.
  54. Wu, J. H., Tennyson, R. D., & Hsia, T. L. (2010). A study of student satisfaction in a blended e-learning system environment. Computers & Education, 55(1), 155-164.
  55. Wu, J., & Liu, W. (2013). An empirical investigation of the critical factors affecting students' satisfaction in EFL blended learning. Journal of Language Teaching & Research, 4(1).
  56. Zacharis, N. Z. (2015). A multivariate approach to predicting student outcomes in web-enabled blended learning courses. The Internet and Higher Education, 27, 44-53.
  57. Diep, A. N., Zhu, C., Struyven, K., & Blieck, Y. (2017). Who or what contributes to student satisfaction in different blended learning modalities?. British Journal of Educational Technology, 48(2), 473-489.
  58. Shernoff, D. J., Tonks, S., & Anderson, B. (2014). The impact of the learning environment on student engagement in high school classrooms. National society for the study of education, 113(1), 166-177