A Study of Chinese College Students' Plans to Use Blended Learning: a Dual Moderation Model of Student Satisfaction and Social Pressure
DOI:
https://doi.org/10.14456/jsasr.2023.30Keywords:
Blended Learning; , Motivation;, Satisfaction;, Social influenceAbstract
Background and Aim: After 2022, Chinese universities will start to build their courses in a way that includes blended learning. To make blended course design and education planning better, it is important to understand why and how learners want to use blended learning, as well as the factors that affect them.
Materials and Methods: This study used quantitative analysis and a questionnaire. A five-point Likert scale was used to collect five hundred university students' intentions and motivation to engage in blended learning, their perceptions of self-efficacy, satisfaction, and the perceived social impact of participation, and to collect demographic information about them.
Results: This study found that student motivation is a relatively stable predictor of behavioral intention. It is moderated by student satisfaction and social influence and influences student self-efficacy. The role of satisfaction also implies that the current blended learning instructional design needs to be improved to induce greater continuity in their satisfaction with the course in the present and in the acquisition of self-efficacy in their learning to support subsequent learning experiences.
Conclusion: Both motivation and self-efficacy are important predictors of whether or not a student will want to do blended learning. There is also a gap between male and female students in terms of motivation and social influence. When designing blended learning, it's important to think about not only how well the course helps students learn after it, but also how the students are and where they are in their learning.
References
Bandura, A. (2002). Social Cognitive Theory in Cultural Context. Applied Psychology, 51(2), 269–290. https://doi.org/10.1111/1464-0597.00092
Billari, F.C., Philipov, D., & Testa, M. R. (2009). Attitudes, Norms, and Perceived Behavioural Control: Explaining Fertility Intentions in Bulgaria. European Journal of Population / Revue Européenne De Démographie, 25(4), 439–465. https://doi.org/10.1007/s10680-009-9187-9
Braden, A.P. (2000), “McClelland’s theory of needs”, WordPress, Retrieved 24 July 2021 from: https://www.changecom.files.wordpress.com
Chang, C.C. (2013). Exploring the determinants of E‐Learning Systems Continuance intention in academic libraries. Library Management, 34(1/2), 40-55. https://doi.org/10.1108/01435121311298261
Chiu, C.-M., Hsu, M.-H., Sun, S.-Y., Lin, T.-C., & Sun, P.-C. (2005). Usability, quality, value and e-learning continuance decisions. Computers & Education, 45(4), 399–416. https://doi.org/10.1016/j.compedu.2004.06.001
Chua, P. Y., Rezaei, S., Gu, M.-L., Oh, Y. M., & Jambulingam, M. (2018). Elucidating social networking apps decisions. Nankai Business Review International, 9(2), 118–142. https://doi.org/10.1108/nbri-01-2017-0003
Dickfos, J., Cameron, C., & Hodgson, C. (2014). Blended learning: Making an impact on assessment and self-reflection in accounting education. Education + Training, 56(2/3), 190–207. https://doi.org/10.1108/et-09-2012-0087
Dutil, I., Prakash, V., Nogami, J., & Ramsay, S. (2015). Introduction of reusable learning objects in a first-year materials science and engineering course. Proceedings of the 2015 ASEE Annual Conference and Exposition, Article 26. https://doi.org/10.18260/ p.24370
Eagly, A. H., & Wood, W. (2016). Social Role Theory of sex differences. The Wiley Blackwell Encyclopedia of Gender and Sexuality Studies, 1-3. https://doi.org/10.1002/9781118663219.wbegss183
Foroughi, B., Iranmanesh, M., & Hyun, S. S. (2019). Understanding the determinants of mobile banking continuance usage intention. Journal of Enterprise Information Management, 32(6), 1015–1033. https://doi.org/10.1108/jeim-10-2018-0237
Guterres, A. (2022). Education transformation needed for 'inclusive, just and peaceful world' – un chief | | 1UN news. United Nations. Retrieved October 11, 2022, from https://news.un.org/en/story/2022/09/1127011
Joo, Y. J., So, H.-J., & Kim, N. H. (2018). Examination of relationships among students' self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers & Education, 122, 260–272. https://doi.org/10.1016/j.compedu.2018.01.003
McMahon, R. (2017). A comparison amongst face-to-face, blended, and mostly online course options. Proceedings of the 18th Annual Conference on Information Technology Education. https://doi.org/10.1145/3125659.3125663
McShane, S. L., & Von Glinow, M. A. (2005). Organizational Behavior. 3rd edition. McGraw-Hill/ Irwin.
Onofrei, G., & Ferry, P. (2020). Reusable learning objects: A blended learning tool in teaching computer-aided design to engineering undergraduates. International Journal of Educational Management, 34(10), 1559–1575. https://doi.org/10.1108/ijem-12-2019-0418
Pirmohamed, S., Debowska, A., & Boduszek, D. (2017). Gender differences in the correlates of academic achievement among university students. Journal of Applied Research in Higher Education, 9(2), 313–324. https://doi.org/10.1108/jarhe-03-2016-0015
Richard, L., Dedobbeleer, N., Champagne, F., & Potvin, L. (2009). Predicting Child Restraint Device Use: A Comparison of Two Models1. Journal of Applied Social Psychology, 24(20), 1837–1847. https://doi.org/10.1111/j.1559-1816.1994.tb01578.x
Rothwell, W. J., Maldonado, C., Li, J., Hunt, D., & Butler, M. (2006). The Handbook of Training Technologies: An Introductory Guide to Facilitating Learning with Technology--from planning through evaluation. Pfeiffer.
Saad, I. (2017). The role of cooperative learning method in the teaching of science subject at elementary school level: an experimental study. Bulletin of Education and Research, 39(2), 1–17.
Schunk, D. H., & DiBenedetto, M. K. (2020). Motivation and social cognitive theory. Contemporary Educational Psychology, 60, 101832. https://doi.org/10.1016/j.cedpsych.2019.101832
ShanghaiRanking. (2021). ShanghaiRanking-Universities. Retrieved October 31, 2022, from https://www.shanghairanking.cn/institution
Stone, R. W., & Baker-Eveleth, L. J. (2013). Students’ intentions to purchase electronic textbooks. Journal of Computing in Higher Education, 25(1), 27–47. https://doi.org/10.1007/s12528-013-9065-7
Strong, R., Wynn, T.J. and McCleur, M.M. (2012), “Investigating students satisfaction with eLearning courses: the effect of the learning environment and social presence”. Journal of Agricultural Education, 53 (3), 98-110. doi: 10.5032/jae.2012.03098.
Sullivan, K. R., & Kedrowicz, A. A. (2012). Gendered tensions: Engineering student's resistance to communication instruction. Equality, Diversity, and Inclusion: An International Journal, 31(7), 596–611. https://doi.org/10.1108/02610151211263405
Taylor, D. G., Voelker, T. A., & Pentina, I. (2011). Towards the acceptance of RSS to support learning: an empirical study to validate the technology acceptance model in Lebanon. International Journal of Mobile Marketing, 6(2), 60–70.
Thulstrup, E. W., & Koswara, J. (2001). Participation of East Asian women in Higher Education with particular emphasis on science-based fields. International Journal of Sociology and Social Policy, 21(1/2), 72–83. https://doi.org/10.1108/01443330110789592
Touré-Tillery, M., & Fishbach, A. (2014). How to Measure Motivation: A Guide for the Experimental Social Psychologist. Social and Personality Psychology Compass, 8(7), 328–341. https://doi.org/10.1111/spc3.12110
Upadhyay, N., Upadhyay, S., & Dwivedi, Y. K. (2021). Theorizing Artificial Intelligence Acceptance and Digital Entrepreneurship Model. International Journal of Entrepreneurial Behavior & Research, 28(5), 1138–1166. https://doi.org/10.1108/ijebr-01-2021-0052
Venkatesh, Morris, Davis, & Davis. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540
Wang, Y., Han, X., & Yang, J. (2015). Revisiting the blended learning literature: using a complex adaptive systems framework. Journal of Educational Technology and Society, 18(2), 380–393.
Warren, L., Reilly, D., Herdan, A., & Lin, Y. (2020). Self-efficacy, performance and the role of blended learning. Journal of Applied Research in Higher Education, 13(1), 98–111. https://doi.org/10.1108/jarhe-08-2019-0210
Xinhua News Agency. (2022). Building a new form of higher education through digitalization. Presentation by the Director of Higher Education, Ministry of Education. Retrieved November 10, 2022, from https://baijiahao.baidu.com/s?id=1740009396480767736&wfr=spider&for=pc
Yang, H. C. (2013). Bon Appétit for Apps: Young American Consumers' Acceptance of Mobile Applications. Journal of Computer Information Systems, 53(3), 85–96. https://doi.org/10.1080/08874417.2013.11645635
Zaccone, M. C., & Pedrini, M. (2019). The effects of intrinsic and extrinsic motivation on student's learning effectiveness. exploring the moderating role of gender. International Journal of Educational Management, ahead-of-print(ahead-of-print). https://doi.org/10.1108/ijem-03-2019-0099
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