Exploring Teacher Intentions in Rural Faku County Middle School, Shenyang City, Liaoning Province, China
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Abstract
Purpose: This study aims to investigate the influence of six independent variables—constructivist teaching beliefs, perceived ease of use, self-efficacy, social influence, subjective norm, and value beliefs—on one dependent variable: behavioral intention to use technology. Research design, data, and methodology: The research employed the Index of Objective Consistency (IOC) to assess effectiveness and used Cronbach's Alpha to evaluate the reliability of the pilot scale (n=30). A multiple linear regression analysis was conducted to examine the effective responses of 100 teachers from three junior high schools in Faku County, confirming the significant relationships between the variables. Following this, a cohort of 30 teachers participated in a 14-week strategic plan (SP). The quantitative results from the post-strategic plan and pre-strategic plan were then compared using paired sample t-tests. Results: The multiple linear regression analysis revealed that constructivist teaching beliefs, perceived ease of use, value beliefs, and social influence significantly affect teachers' behavior regarding the use of educational technology. Conversely, subjective norm and self-efficacy did not show a significant impact. Finally, the paired sample t-test comparisons demonstrated significant differences in teachers' behavioral intentions to use technology between the post-strategic planning and pre-strategic planning phases. Conclusions: The findings promote deeper understanding and application of knowledge, highlighting the importance of intuitive and accessible digital tools in the learning process.
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References
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckmann (Eds.), Action control: From cognition to behavior (pp. 11-39). Springer.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior (1st ed.). Prentice-Hall.
Armitage, C. J., & Conner, M. (2001). Efficacy of the theory of planned behavior: A meta-analytic review. British Journal of Social Psychology, 40(4), 471-499.
https://doi.org/10.1348/014466601164939
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Advances in Be haviour Research and Therapy, 84(2), 191-215.
https://doi.org/10.1037/0033-295x.84.2.191
Cooper, D. R., & Schindler, P. S. (2014). Business research methods (12th ed.). McGraw-Hill Education.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 19-340. https://doi.org/10.2307/249008
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: an introduction to theory and research (1st ed.). Addison-Wesley.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1995). Multivariate data analysis (4th ed.). Prentice Hall.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2013). Multivariate data analysis (7th ed.). Pearson.
Huang, F., Teo, T., Sánchez-Prieto, J. C., & García-Peñalvo, F. J. (2021). A cross cultural study on the influence of cultural values and teacher beliefs on university teachers’ information and communications technology acceptance. Education Tech Research Dev, 69,1271-1297.
Kagan, D. M. (1992). Implications of research on teacher belief. Educational Psychologist, 27(1), 65-90.
doi:10.1207/s15326985ep2701_6 .
Miller, E. R. (2017). Predicting the use of instructional technology among community college instructors: An extension of the technology acceptance model (TAM) [Doctoral dissertation]. ProQuest LLC.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
Ou, Y. (2022). A study on the influential factors of middle school teachers' smart classroom teaching behavior based on the technology acceptance model: Taking P District of Shenzhen City as an example [Master’s thesis]. East China Normal University.
Pajares, F. (1992). Teacher beliefs and educational research: Clearing up a messy construct. Review of Educational Research, 62(3), 307-332. https://doi.org/10.3102/00346543062003307
Piaget, J. (1972). The principles of genetic epistemology (1st ed.). Routledge & Kegan Paul.
Richey, R. C., & Klein, J. D. (2007). Design and development research: Methods, strategies, and issues (1st ed.). Routledge. https://doi.org/10.4324/9780203826034
Sharma, L., & Srivastava, M. (2020). Teachers’ motivation to adopt technology in higher education. Journal of Applied Research in Higher Education, 21(4), 673-692.
Sharma, S., & Srivastava, A. (2019). Understanding the factors influencing the acceptance of technology in education: A study of Indian higher education. Journal of Educational Technology & Society, 22(1), 1-14.
Teo, T. (2013). Influences of contextual variables on the intention to use technology in education: A latent variable modeling approach. Campus-Wide Information Systems, 30(2), 95-105. https://doi.org/10.1108/10650741311306282
Teo, T., & Lee, C. (2010). Explaining the intention to use technology among student teachers: An application of the Theory of Planned Behavior. Campus-Wide Information Systems, 27(2), 60-67. https://doi.org/10.1108/10650741011033035.
Timothy, J. W. S., Klas, N., Sanghani, H. R., & Al-Mansouri, T. (2018). Circadian Disruptions in the Myshkin Mouse Model of Mania Are Independent of Deficits in Suprachiasmatic Molecular Clock Function. National Library of Medicine, 84(11), 827-837.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478.
Zhong, Y., & Wang, W. (2008). An Empirical Study on Non major Students' self-efficacy in English Learning under Multimedia Environment. Journal of Sichuan University of Foreign Languages, 24(6), 142-144.