The influence of online educational platform management on participator’s self-efficacy in China
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Abstract
This present research aims to analyze the influence of online educational platform management towards the participator’s self-efficacy in the context of online teaching and learning in China. A theoretical model was developed based on the theories of social exchange behavior, technology acceptance model and expectation confirmation model to determine whether such factors as educational content’s quality, educational platform system quality and online interaction directly affect Chinese students’ information cognition requirements such as perceived usefulness, expectation confirmation and self-efficacy, which was tested using preliminary statistical analysis through online data collection from a sample of 339 responders in China. Furthermore, Structural Equation Modeling analysis was used to test the hypotheses of this present study, and the results showed that all factors of online educational platform management directly, indirectly and totally effects on Chinese students’ self-efficacy in the online learning environment, which were used to develop the final research model. Practical implications regarding the improvement of online education management system are discussed as well as how the online learning could help students achieve greater self-efficacy. Importantly, this research also addresses the recommendations and limitations conducted with Chinese online educational participators in different educational institutions are presented at the end of the paper.
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References
Abbatt, F. and McMahon, R. (1993). Teaching Health Care Workers. Basingstoke: MacMillan.
Ally, M. (2008). Foundations of educational theory for online learning. In The Theory and Practice of Online Learning. 2nd ed. edited by T. Anderson, pp. 15-44. Athabasca, Alberta: Athabasca University Press. [Online URL: https://www.aupress.ca/app/uploads/120146_99Z_Anderson_2008-Theory_and_Practice_of_Online_Learning.pdf] accessed on February 21, 2020.
Al-Mamary, Y. H., Shamsuddin, A. and Aziati, N. (2014). The relationship between system quality, information quality, and organizational performance. International Journal of Knowledge and Research in Management and E-Commerce 4(3): 7-10.
Anderson, T. D. and Garrison, R. D. (1998). Learning in a networked world: New roles and responsibilities. In Distance Learners in Higher Education: Institutional Responses for Quality Outcomes, edited by C. C. Gibson, pp. 97-112. Madison, Wisconsin: Atwood Publishing.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly 25(3): 351-370.
Blau, P. M. (1964). Exchange and Power in Social Life. New York: Wiley.
Brown, J., Broderick, A. J. and Lee, N. (2007). Word of mouth communication within online communities: Conceptualizing the online social network. Journal of Interactive Marketing 21(3): 2-20.
Chang, H. H. and Wang, I. C. (2008). An investigation of user communication behavior in computer mediated environments. Computers in Human Behavior 24(5): 2336-2356.
Chen, J., Cong, F. and Kang, F. (2009). Influential factor analysis of consumers’ online purchase behavior: A flow approach. Nankai Business Review 12(2):132-140.
Chen, K., and Yen, D. (2004). Improving the quality of online presence through interactivity. Information and Management 42(1): 217-226.
Cronin, J. J., Brady, M. K. and Hult, G. T. M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing 76(2): 193-218.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13(3): 319-340.
Davis, F. D., Bagozzi, R. P. and Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science 35(8): 982-1003.
Debatin, B., Lovejoy, J., Horn, A. and Hughes, B. (2009). Facebook and online privacy: attitudes, behaviors, and unintended consequences. Journal of Computer-Mediated Communication 15(1): 83-108.
DeLone, W. H. and McLean, E. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems 19(4): 9-30.
Downes, S. and Siemens, G. (2008). CCK08 – The Distributed Course. [Online URL: https://sites.google.com/site/themoocguide/3-cck08---the-distributed-course] accessed on June 11, 2020.
Fathema, N. and Sutton, K. L. (2013). Factors influencing faculty members' Learning Management Systems adoption behavior: An analysis using the technology acceptance model. International Journal of Trends in Economics Management & Technology 2(6): 20-28.
Fathema, N., Shannon, D. and Ross, M. (2015). Expanding the Technology Acceptance Model (TAM) to examine faculty use of Learning Management Systems (LMSs) in higher education institutions. Journal of Online Learning and Teaching 11(2): 210-233.
George, D. and Mallery, P. (2003). Using SPSS for Windows Step by Step: A Simple Guide and Reference 4th ed. London: Pearson Education.
Goodhue, D. L. and Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly 19(2): 213-236.
Kankanhalli, A., Tan, B. C. Y. and Wei, K. (2005). Contributing knowledge to electronic repositories: an empirical investigation. MIS Quarterly 29(1): 113-143.
Kim, B. and Han, I. (2009). The role of trust belief in community-driven knowledge and its antecedents. Journal of the American Society for Information Science & Technology 60(5): 1012-1026.
Klin, R. B. (2016). Principles and Practice of Structural Equation Modeling. 4th ed. New York: The Guilford Press.
Lee, T. (2005). The impact of perceptions of interactivity on customer trust and transaction intentions in mobile commerce. Journal of Electronic Commerce Research 6(3): 165-180.
Liu, Y. and Shao, P. (2005). Research on the quality of enterprise B2C web site for E-Commerce. Value Engineering (1): 64-67. [in Chinese]
Massey, B. L. and Levy, M. (1999). Interactive, online journalism at English-Language web newspapers in Asia. Gazette (Leiden, Netherlands) 61(6): 523-538.
Molm, L. D. (2001). Theories of social exchange and exchange networks. In Handbook of Social Theory, edited by G. Ritzer and B. Smart, pp. 260-272. London: SAGE Publications.
Moore, M. G. and Kearsley, G. (2005). Distance Education: A Systems View. Belmont, CA: Thomson Wadsworth.
Moore, M. G. and Kearsley, G. (2012). Distance Education: A Systems View of Online Learning. 3rd ed. Belmont, CA: Wadsworth Cengage Learning.
Nahl, D. (2005). Affective and cognitive information behavior: Interaction effects in Internet use. Proceedings of the 68th ASIS&T Annual Meeting, ASIST 2005. Charlotte, North Carolina: Wiley. [Online URL: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/meet.1450420196] accessed on January 21, 2019.
Okafor, D. J., Nico, M. and Azman, B. B. (2016). The influence of perceived ease of use and perceived usefulness on the intention to use a suggested online advertising workflow. Canadian International Journal of Science and Technology 6(14): 162-174.
Pettigrew, K. E. (1999). Waiting for chiropody: contextual results from an ethnographic study of the information behavior among attendees at community clinics. Information Processing & Management 35(6): 801-817.
Pianta, R. C. (1999). Enhancing Relationships Between Children and Teachers. Washington, DC: American Psychological Association.
Popoola, B. A., Chinomona, R. and Chinomona, E. (2014). The influence of information quality, system quality and service quality on student’s self-efficacy at institutions of higher learning in South Africa. Mediterranean Journal of Social Sciences 5(27): 974-984.
Roaimah, O., Ramayah, T., May-Chuin, L., Tan, Y. S. and Rusinah, S. (2010). Information sharing, information quality and usage of information technology (IT) tools in Malaysian organizations. African Journal of Business Management. 4(12): 2486-2499.
Shaari, R., Rahman, S. A. A. and Rajab, A. (2014). Self-Efficacy as a determined factor for knowledge sharing awareness. International Journal of Trade, Economics and Finance 5(1): 39-42.
Skadberg, Y. and Kimmel, J. (2004). Visitors’ flow experience while browsing a Web site: its measurement, contributing factors and consequences. Computers in Human Behavior 20(3): 403-422.
Song, J. H. and Zinkhan, G. M. (2008). Determinants of perceived web site interactivity. Journal of Marketing 72(2): 99-113.
Stephanie, L. S. (2013). The Effect of Teacher-Student Relationships on the Academic Achievement of Fifth Grade Students. Master’s thesis. Goucher College, USA.
Stones, E. (1966). An Introduction to Educational Psychology. London: Methuen.
Straub, D., Boudreau, M. and Gefen, D. (2004). Validation guidelines for IS positivist research. Communications of the Association for Information Systems 13: Article 24.
Tang, L. and Deng, S., (2012). The factors influence on social networking services user’s loyalty behavior. Document, Information and Knowledge 1: 102-108. [in Chinese]
Torres, J. A. S., Arroyo-Cañada, F.-J., Solé-Moro, M.-L. and Argila-Irurita, A. (2018). Impact of gender on the acceptance of electronic word-of-mouth (eWOM) information in Spain. Contaduría Y Administración 63(4): 1-19.
Wiener, D. N. (1948). Subtle and obvious keys for the Minnesota multiphasic personality inventory. Journal of Consulting Psychology 12(3): 164-170.
Wu, J. and Chang, Y. (2005). Towards understanding members' interactivity, trust, and flow in online travel community. Industrial Management & Data Systems 105(7): 937-954.
Yang, Z. (2011). The analysis of SNS website quality evaluation’s basic indicators set. Science and Technology Information 14(10): 390. [in Chinese]