DOI QR코드

DOI QR Code

온라인 수업 만족도 및 사용 의도에 미치는 요인들 연구

Factors Affecting Students' Satisfaction with Online Learning and Intention to Use Online Learning

  • 엄남현 (홍익대학교 광고홍보학부)
  • Um, Namhyun (Department of Advertising & Public, HONGIK University)
  • 투고 : 2022.02.11
  • 심사 : 2022.04.20
  • 발행 : 2022.04.28

초록

코로나 19 팬데믹으로 인해 온라인 교육 시장은 전세계적으로 성장했으며, 온라인 교육은 미래 교육을 지배할 것이라는 예상이다. 본 연구는 온라인 수업 만족도 및 온라인 수업 사용 행동 의도에 영향을 줄 수 있는 인간적 요인으로 자기효능감, 시스템 요인들로 인지된 사회적 실재감 및 인지된 교수 실재감의 효과를 살펴보고 있다. 본 연구에는 수업에서 추가 점수를 받은 조건으로 236명의 학생들이 온라인 서베이에 참여했다. 연구결과, 사회적 실재감과 교수 실재감이 높은 사람들은 사회적 실재감과 교수 실재감이 낮은 사람들보다 온라인 수업 만족 및 온라인 수업 행동 의도가 높은 것으로 나타났다. 또한, 본 연구는 자기 효능감이 높은 사람들은 자기 효능감이 낮은 사람들보다 더 높은 온라인 수업 만족 및 온라인 수업 행동 의도를 보인다는 결과를 밝혀냈다. 본 연구는 온라인 수업에서 학생들의 만족도 및 온라인 교육 사용 의도를 높이는데 있어 이론적 그리고 실무적 시사점을 제공한다.)

Due to the Corona-19 pandemic, online education has grown worldwide and it is now being predicted that online education will dominate the future of education. This study examines, as characteristics of the human factor, the effect of self-efficacy; as system factors influencing learners' satisfaction with online learning and behavioral intention to use online learning, this study examines perceived social presence and perceived teaching presence. Participating in this study were 236 students who filled out an online survey in return for course credits. Study findings suggest that individuals with high social presence and teaching presence will have higher satisfaction with online learning and higher behavioral intention to use online learning than those with low social presence and teaching presence. The study also found that individuals with high self-efficacy have higher satisfaction with online learning and higher behavioral intention to use online learning than those with low self-efficacy. This study provides theoretical implications as well as practical implications for e-learning educators when it comes to enhancing students' satisfaction with online learning and behavioral intention to use online learning.

키워드

참고문헌

  1. Y. C. Kuo, A. E. Walker, K. E. Schroder & B. R. Belland. (2014). Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. The internet and higher education, 20, 35-50. https://doi.org/10.1016/j.iheduc.2013.10.001
  2. M. Weigold. (2020). Succeeding in Online Advertising Education. Journal of Advertising Education, 24(1), 69-73. https://doi.org/10.1177/1098048220917129
  3. R. M. Bernard, P. C. Abrami, Y. Lou, E. Borokhovski, A. Wade, L. Wozney & B. Huang, (2004). How does distance education compare with classroom instruction? A meta-analysis of the empirical literature. Review of Educational Research, 74(3), 379-439. https://doi.org/10.3102/00346543074003379
  4. B. Means, Y. Toyama, R. Murphy, M. Bakia & K. Jones. (2009). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. US Department of Education.
  5. I. E. Allen & J. Seaman. (2010). Class differences: Online education in the United States, 2010. Sloan Consortium (NJ1).
  6. National Center for Education Statistics. (2008). Distance education at degree-granting postsecondary institutions: 2006-07. US Department of Education. NCES 2009-044.
  7. D. Klein & M. Ware. (2003). E-learning: New opportunities in continuing professional development. Learned publishing, 16(1), 34-46. https://doi.org/10.1087/095315103320995078
  8. A. F. Algahtani. (2011). Evaluating the Effectiveness of the E-learning Experience in Some Universities in Saudi Arabia from Male Students' Perceptions, Durham theses, Durham University.
  9. J. R. Marc. (2002). Book review: e-learning strategies for delivering knowledge in the digital age. Internet and Higher Education, 5, 185-188. https://doi.org/10.1016/S1096-7516(02)00082-9
  10. S. Hameed, A. Badii & A. J. Cullen. (2008, May). Effective e-learning integration with traditional learning in a blended learning environment. In European and Mediterranean Conference on Information Systems (pp. 25-26).
  11. J. Smedley. (2010). Modelling the impact of knowledge management using technology. OR insight, 23(4), 233-250. https://doi.org/10.1057/ori.2010.11
  12. N. Wagner, K. Hassanein & M. Head. (2008). Who is responsible for e-learning success in higher education? A stakeholders' analysis. Journal of Educational Technology & Society, 11(3), 26-36.
  13. L. M. Angelino, F. K. Williams & D. Natvig. (2007). Strategies to engage online students and reduce attrition rates. Journal of Educators Online, 4(2), n2.
  14. S. Carr. (2000). As distance education comes of age, the challenge is keeping the students. The Chronicle of Higher Education, 46(23), A39-A41.
  15. L. V. Morris, C. Finnegan & S. S. Wu. (2005). Tracking student behavior, persistence, and achievement in online courses. The Internet and Higher Education, 8(3), 221-231. https://doi.org/10.1016/j.iheduc.2005.06.009
  16. K. Frankola. (2001). Why online learners drop out. WORKFORCE-COSTA MESA-, 80(10), 52-61.
  17. J. Short, E. Williams & B. Christie. (1976). The social psychology of telecommunications. John Wiley & Sons.
  18. C. H. Tu. (2002). The measurement of social presence in an online learning environment. International Journal on E-learning, 1(2), 34-45.
  19. C. H. Tu & M. McIsaac. (2002). The relationship of social presence and interaction in online classes. The American journal of distance education, 16(3), 131-150. https://doi.org/10.1207/S15389286AJDE1603_2
  20. C. N. Gunawardena & F. J. Zittle. (1997). Social presence as a predictor of satisfaction within a computer mediated conferencing environment. American Journal of Distance Education, 11(3), 8-26. https://doi.org/10.1080/08923649709526970
  21. A. G. Picciano. (2002). Beyond student perceptions: Issues of interaction, presence, and performance in an online course. Journal of Asynchronous learning networks, 6(1), 21-40.
  22. K. Swan & L. F. Shih. (2005). On the nature and development of social presence in online course discussions. Journal of Asynchronous Learning Networks, 9(3), 115-136.
  23. R. D. Johnson, H. Gueutal & C. M. Falbe. (2009). Technology, trainees, metacognitive activity and e learning effectiveness. Journal of Managerial Psychology, 24(6), 545-566. https://doi.org/10.1108/02683940910974125
  24. C. Hostetter & M. Busch. (2006). Measuring up online: The relationship between social presence and student learning satisfaction. Journal of the Scholarship of Teaching and Learning, 1-12.
  25. J. C. Richardson & K. Swan. (2003). Examining social presence in online courses in relation to students' perceived learning and satisfaction. Journal of Asynchronous Learning Networks, 7(1), 68-88.
  26. T. Anderson, R. Liam, D. R. Garrison & W. Archer. (2001). Assessing teaching presence in a computer conferencing context. Journal of Asynchronous Learning Networks, 5(2), 1-17.
  27. P. J. Shea, A. M. Pickett & W. E. Pelz. (2003). A follow-up investigation of "teaching presence" in the SUNY Learning Network. Journal of asynchronous learning networks, 7(2), 61-80.
  28. Y. J. Joo, K. Y. Lim & E. K. Kim. (2011). Online university students' satisfaction and persistence: Examining perceived level of presence, usefulness and ease of use as predictors in a structural model. Computers & ducation, 57(2), 1654-1664.
  29. A. Bandura. (1997). Self-efficacy: The exercise of control. New York: Freeman.
  30. A. Bandura. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.
  31. S. S. Liaw & H. M. Huang. (2013). Perceived satisfaction, perceived usefulness and interactive learning environments as predictors to self-regulation in e-learning environments. Computers & Education, 60(1), 14-24. https://doi.org/10.1016/j.compedu.2012.07.015
  32. D. Shen, M. H. Cho, C. L. Tsai & R. Marra. (2013). Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction. The Internet and Higher Education, 19, 10-17. https://doi.org/10.1016/j.iheduc.2013.04.001
  33. E. Alqurashi. (2017). Self-efficacy and the interaction model as predictors of student satisfaction and perceived learning in online learning environments. (Doctoral dissertation, Duquesne University).
  34. J. C. Hong, M. Y. Hwang, E. Szeto, C. R. Tsai, Y. C. Kuo & W. Y. Hsu. (2016). Internet cognitive failure relevant to self-efficacy, learning interest, and satisfaction with social media learning. Computers in Human Behavior, 55, 214-222. https://doi.org/10.1016/j.chb.2015.09.010
  35. J. C. Womble. (2007). E-learning: The relationship among learner satisfaction, self-efficacy, and usefulness (pp. 1-132). Alliant International University, San Diego.
  36. Y. M. Lin, G. Y. Lin & J. M. Laffey. (2008). Building a social and motivational framework for understanding satisfaction in online learning. Journal of Educational Computing Research, 38(1), 1-27. https://doi.org/10.2190/EC.38.1.a
  37. S. S. Liaw. (2008). Investigating students' perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers & Education, 51(2), 864-873. https://doi.org/10.1016/j.compedu.2007.09.005
  38. S. B. Eom & N. Ashill. (2016). The determinants of students' perceived learning outcomes and satisfaction in university online education: An update. Decision Sciences Journal of Innovative Education, 14(2), 185-215. https://doi.org/10.1111/dsji.12097
  39. Y. Malhotra & D. F. Galletta. (1999). Extending the technology acceptance model to account for social influence: Theoretical bases and empirical validation. In Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers (pp. 14-pp). IEEE.
  40. H. Gangadharbatla. (2020). What we stand to lose with fully online advertising education. Journal of Advertising Education, 24(1), 74-80. https://doi.org/10.1177/1098048220916919