Influencing Factors of Behavioral Intention Toward Online Teaching in Vocational Colleges in Nanchang, China
Main Article Content
Abstract
Purpose: This study aims to understand the factors that influence vocational college teachers in Nanchang, China, to choose online teaching. The conceptual framework is derived from previous theories, suggesting connections between Attitude (AT), Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), and Behavioral Intention (BI). Research design, data, and methodology: The study analyzed responses from 502 teachers at JiangXi College of Science and Technology. For reliability, a Cronbach's Alpha was employed in a pilot test with 30 participants. The Multiple Linear Regression (MLR) involved questionnaires that contributed to the development of the finalized action research plan. During the strategic plan arrangement, 30 teachers were selected through purposive sampling from the Ideological and Political Department and the School of Nursing at JVC to participate in the study. Results: This research revealed that attitude, performance expectancy, effort expectancy, social influence, and facilitating conditions impacted behavioral intention in the context of JiangXi, China. Conclusions: This study reveals that the primary need is for stability, followed by development factors and respect needs. Recently, China's online teaching environment has become more harmonious, despite the ongoing rise of epidemics. These external changes influence college teachers' online teaching practices.
Downloads
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data, or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution License (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
References
Abeeku, B. B., Felicity, A.-A., & Enya, A.-X. (2023). Developing a framework for entrepreneurship ecosystem for developing countries: The application of institutional theory, Cogent Business & Management, Taylor & Francis Journals, 10(2), 2195967-219.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
https://doi.org/10.1016/0749-5978(91)90020-T
Breckler, S. J., & Wiggins, E. C. (1989). Affect versus evaluation in the structure of attitudes. Journal of Experimental Social Psychology, 25(3), 253-271. https://doi.org/10.1016/0022-1031(89)90022-X
Chopdar, P., Korfiatis, N., Sivakumar, V. J., & Lytras, M. (2018). Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology. Computers in Human Behavior. Forthcoming, 86, 109-128. https://doi.org/10.1016/j.chb.2018.04.017
David-West, O., Iheanachor, N., & Kelikume, I. (2018). A resource-based view of digital financial services (DFS): An exploratory study of Nigerian providers. Journal of Business Research, 88(2), 1-10.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340.
Dawes, J. (2008). Do Data Characteristics Change According to the Number of Scale Points Used? An Experiment Using 5-Point, 7-Point and 10-Point Scales. Ehrenberg- Bass Institute for Marketing Science, University of South Australia.
https://doi.org/10.1177/147078530805000106
Deniswara, K., Prabowo, H., & Bandur, A. (2023). An Empirical Study on the Effects of Financial Management Spirituality and Technology Adoption on Church Performance. Journal of System and Management Sciences, 13(6), 111-126.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed.). Pearson.
Handoko, B. L., Ignatius, E. R., & Gani, E. (2020). Impotence and benefit of application of governance risk and compliance principle.
Jebril, M. (2021). Between construction and destruction: the experience of educationalists at Gaza’s universities. A Journal of Comparative and International Education, 53(6), 986-1004.
Joshi, A., Kale, S., Chandel, S., & Pal, D. (2015). Likert Scale: Explored and Explained. British Journal of Applied Science & Technology, 7, 396-403. https://doi.org/10.9734/BJAST/2015/14975
Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 22, 55.
McKeown, N., Anderson, T., Balakrishnan, H., Parulkar, G., Peterson, L., Rexford, J., Shenker, S., & Turner, J. (2008). OpenFlow: Enabling Innovation in Campus Networks. ACM SIGCOMM Computer Communication Review, 38, 69-74.
http://dx.doi.org/10.1145/1355734.1355746
Ngai, E. W. T., Heung, V. C. S., Wong, Y. H., & Chan, F. K. Y. (2007). Consumer complaint behavior of Asians and non-Asians about hotel services. European Journal of Marketing, 41(11), 1375-1391.
Prada-Villamizar, S., & Sánchez-Peinado, E. (2021). Entrepreneurship, innovation, and internationalization: The moderating role of the institutions. Estudios Gerenciales, 37(160), 506-517.
Raygan, A., & Moradkhani, S. (2020). Factors influencing technology integration in an EFL context: investigating EFL teachers’ attitudes, TPACK level, and educational climate. Computer Assisted Language Learning, 35(2), 1-22.
Rovinelli, R. J., & Hambleton, R. K. (1977). On the Use of Content Specialists in the Assessment of Criterion-Referenced Test Item Validity. Tijdschrift Voor Onderwijs Research, 2, 49-60.
Tan, C. (2017). Teaching critical thinking: Cultural challenges and strategies in Singapore. British Educational Research Journal, 43(5), 988-1002.
Ul-Ain, N., Kiran, K., & Mehwish, W. (2015). The influence of learning value on learning management system use: an extension of UTAUT2. Inf Develop.
van Bussel, M. J. P., Odekerken-Schröder, G. J., Ou, C., Swart, R. R., & Jabobs, M. J. G. (2022). Analyzing the determinants to accept a virtual assistant and use cases among cancer patients: A mixed methods study. BMC Health Services Research, 22, 890. https://doi.org/10.1186/s12913-022-08189-7
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Towards a Unified View. MIS Quarterly, 27, 425-478.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36, 157-178. https://doi.org/10.2307/41410412