THE EFFECT OF EDUCATIONAL SUPPORT ON VOCATIONAL COLLEGE TEACHERS’ ACCEPTANCE OF ONLINE TEACHING PLATFORM IN GUANGXI ZHUANG AUTONOMOUS REGION, PEOPLE’S REPUBLIC OF CHINA
Keywords:
Educational support, Teacher acceptance, Online learning platformAbstract
The aim of this study is to predict the effect of educational support, which includes facility support (FS), technical support (TS), management support (MS), and teaching environment support (TES), on acceptance of OTPs by vocational teachers. The technology acceptance model (TAM) created the conceptual framework. A sample of 395 vocational teachers from 49 colleges in the Guangxi Zhuang Autonomous Region of China was tasked with answering questions on an online questionnaire to assess its validity and reliability using a quantitative research approach. The effect of educational support on teachers’ acceptance of OTPs is examined using multiple regression and correlation analysis. The study found that college support was significantly and positively correlated with teachers' perceptions of OTPs, whereas management support had no significant effect. The regression equation is as follows. Y = 0 + 0.24(FS) ** + 0.17(TS) ** + 0.05(MS) + 0.23(TES) **. Analyzing the overall fit of the model, the coefficient of determination R2 = 0.65, the adjust R2 = 0.42, and the F-value is 97.22, with a significant level of 0.00. In addition, the study provided suggestions to improve the functionality and effectiveness of OTPs, such as providing training related to OTPs in colleges, which can help teachers to better integrate into OTPs, and increased investment in basic equipment can also help teachers improve their acceptance of OTPs.
References
Atyang, F., Gathumbi, A., & Babusa, H. (2018). School management and technical support to teachers and students in the integration of ICT in Teaching/Learning English Language. Advances in Social Sciences Research Journal. 5(7): 249 - 258. doi.org/10.14738/assrj.57.4863
Aziz, N., Memon, S. A., & Anjum, S. (2023). Perception of students and teachers regarding online teaching of English language: a case of secondary school Hyderabad - Pakistan. Academy of Education and Social Sciences Review. 3(2): 163 - 171. doi.org/10.48112/aessr.v3i2.495
Basilotta-Gómez-Pablos, V., Matarranz, M., Casado-Aranda, L., & Otto, A. (2022). Teachers’ digital competencies in higher education: a systematic literature review. International Journal of Educational Technology in Higher Education. 19(1): 1 - 16. doi.org/10.1186/s41239-021-00312-8
Bontogon, E. B. (2023). Perception and challenges encountered by teachers in teaching mathematics online. AIDE Interdisciplinary Research Journal. 3(2022): 323 - 337. doi.org/10.56648/aide-irj.v3i1.72
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika. 16(3): 297 - 334. doi.org/10.1007/bf02310555
Crispel, O., & Kasperski, R. (2019). The impact of teacher training in special education on the implementation of inclusion in mainstream classrooms. International Journal of Inclusive Education. 25(9): 1079 - 1090. doi.org/10.1080/13603116.2019.1600590
Davis, F. (1989). Technology acceptance model: TAM. AS: Information Seeking Behavior and Technology Adoption. 35(8): 982 - 1003.
Education Department of Guangxi Zhuang Autonomous Region. (2022, January 4). Guangxi higher education revitalization and development ‘14th Five-Year’ plan. [Online], Available: http://jyt.gxzf.gov.cn/zfxxgk/fdzdgknr/tzgg_58179/t11143482.shtml
Fahrman, B., Norström, P., Gumaelius, L., & Skogh, I. (2019). Experienced technology teachers’ teaching practices. International Journal of Technology and Design Education. 30(1): 163–186. doi.org/10.1007/s10798-019-09494-9
Farkhani, Z. A., Badiei, G., & Rostami, F. (2022). Investigating the teacher’s perceptions of classroom management and teaching self-efficacy during COVID-19 pandemic in the online EFL courses. Asian-Pacific Journal of Second and Foreign Language Education. 7(1): 25. doi.org/10.1186/s40862-022-00152-7.
Fidelis, F., & Onyango, D. O. (2021). Availability of ICT Facilities and Teachers’ Competence in the Use of ICT among Public Secondary Schools in Ngara District, Tanzania. East African Journal of Education and Social Science. 2, 34-40. doi.org/10.46606/eajess2021v02i02.0073
Hick, P., Arshad, R., & Watt, D. (2011). Promoting cohesion, challenging expectations: educating the teachers of tomorrow for race quality and diversity in 21st century schools. [Online], Available: https://www.research.ed.ac.uk/en/publications/promoting-cohesion-challenging-expectations-educating-the-teacher.
Huang, M., Xiangming, L., & Zhang, J. (2021). Examining individual demographic and school support factors regarding teachers’ intention to use technology: a hierarchical regression analysis. International Journal of Emerging Technologies in Learning. 16(12): 289-304. doi.org/10.3991/ijet.v16i12.22625
Irfan, T., & Raheem, M. A. (2023). Perception of students and teachers regarding online teaching-learning during Covid-19 at university level. Middle East Journal of Applied Science & Technology. 6(2): 9 - 19. doi.org/10.46431/mejast.2023.6202
Jin, X., & Li, C. (2023). Improvement path of teachers’ informatization teaching ability in colleges and universities in the age of smart education. China Management Informatization. 26(9): 1673-0194. doi.org/10.3969/j.issn.1673-0194.2023.09.055
Kou, L. (2023). A study of university teachers’ willingness to adopt the use of online teaching platforms: based on TAM3. Journal of Nanjing Open University. 2097-0633, 1 - 7.
Likert, R. (1967). The method of constructing and attitude scale, in Attitude Theory and Measurement. New York: Wiley & Son.
Lucas, M., Bem-Haja, P., Siddiq, F., Moreira, A., & Redecker, C. (2021). The relation between in-service teachers’ digital competence and personal and contextual factors: What matters most? Computers & Education. 160, 104052. doi.org/10.1016/j.compedu.2020.104052
Mahdum, M., Hadriana, H., & Safriyanti, M. (2019). Exploring teacher perceptions and motivations to ICT use in learning activities in Indonesia. Journal of Information Technology Education Research. 18, 293 - 317. doi.org/10.28945/4366
Ministry of Education of the People’s Republic of China. (2018, April 18). Education Informatization Action Plan 2.0. [Online], Available: http://www.moe.gov.cn/srcsite/A16/s3342/201804/t20180425_334188.html
Nishio, A. L., Corrêa, C. C. M., Nascimento, J. C., & De Souza, M. P. B. (2023). Digital technologies and the teaching process. In Seven Editora eBooks. doi.org/10.56238/tfisdwv1-052
Protopsaltis, S., & Baum, S. (2019). Does online education live up to its promise? A look at the evidence and implications for federal policy. Center for Educational Policy Evaluation. 1 - 50.
Raut, B. N. (2021). Impact of Technology on Traditional Teaching—Learning Measures in the Era of COVID-19 Pandemic. Samriddhi - a Journal of Physical Sciences, Engineering and Technology. 13(1): 92 - 96. doi.org/10.18090/samriddhi.v13is1.21
Ren, Y. (2018). China’s Education Informatization in the New Era - One of the Interpretations of the Action Plan for Education Informatization 2.0. Informatization of Education. doi.org/10.13811/j.cnki.eer.2018.06.004
Scherer, R., Siddiq, F., & Tondeur, J. (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers and Education. 128, 13 – 35. doi.org/10.1016/j.compedu.2018.09.009
State Council of the People’s Republic of China. (2019, February 23). China Education Modernization 2035. Central People’s Government of the People’s Republic of China. [Online], Available: https://www.gov.cn/zhengce/2019-02/23/content_5367987.htm
Shen, W., Lin, X. F., Chiu, T. K., Chen, X., Xie, S., Chen, R., & Jiang, N. (2024). How school support and teacher perception affect teachers’ technology integration: A multilevel mediation model analysis. Education and Information Technologies. 1-23. doi.org/10.1007/s10639-024-12802-z
Svihus, C. L. (2023). Online teaching in higher education during the COVID-19 pandemic. Education and Information Technologies. 29, 3175-3193. doi.org/10.1007/s10639-023-11971-7
Timotheou, S., Miliou, O., Dimitriadis, Y., Sobrino, S. V., Giannoutsou, N., Cachia, R., Monés, A. M., & Ioannou, A. (2022). Impacts of digital technologies on education and factors influencing schools’ digital capacity and transformation: A literature review. Education and Information Technologies. 28(6): 6695 - 6726. doi.org/10.1007/s10639-022-11431-8
Turner, R. C., & Carlson, L. (2003). Indexes of item-objective congruence for multidimensional items. International Journal of Testing. 3(2): 163 - 71. doi.org/10.1207/s15327574ijt0302_5
Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a research agenda on interventions. Decision Sciences. 39(2): 273 - 315. doi.org/10.1111/j.1540-5915.2008.00192.x
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science. 46(2): 186 - 204. doi.org/10.1287/mnsc.46.2.186.11926
Yamane, T. (1973). Statistics: An Introductory Analysis. (2rd ed.). New York: Harper. and Row.
Zeyab, A., & Alayyar, G. M. (2023). Perspective Chapter: Education Technology (EDTech) and the Online Course Revolution. In Intech Open eBooks. doi.org/10.5772/intechopen.109227
Zhen, Y., Li, H., & Li, C. (2023). How school support affects rural teachers’ retention - a study of multiple mediating effects based on teachers’ sense of efficacy and school culture. Education and Human Resources. 1003-0166.
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