Determinants of Teachers’ Attitude toward Microlecture: Evidence from Elementary and Secondary Schools

Xu Fang; Rui Liu

doi:10.12973/eurasia.2017.01013a

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Xu Fang ¹ ^* , Rui Liu ²

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¹ Institute of higher education, Lanzhou University, Lanzhou, Gansu 730000, China² Department of Economics, San Jose State University, San Jose, CA 95192, USA^* Corresponding Author

Abstract

We study the factors that determine teachers’ behavioral intention to adopt microlecture. We collect 500 survey responses across elementary and secondary schools in China and propose a model based on three previous works: Technology Acceptance Model 3 (TAM 3), Innovation Diffusion Theory and Model of Personal Computer Utilization (MPCU). Our results show that perceived usefulness is a significant determinant for teachers’ attitude toward microlecture. Perceived ease of use and output quality significantly influence perceived usefulness, with the latter being more significant. Additionally, external control and computer self-efficacy are found to be factors that influence perceived usefulness. External control is a more significant contributor to perceived usefulness. Overall, our model accounts for 57.1% of variability in teachers’ intention to use microlecture. Out of 11 formulated hypotheses, 6 are supported by the data. The results provide valuable implications for ways to increase teachers’ acceptance of microlecture.

Keywords

Behavioral Intention
microlecture
Technology Acceptance Model
teachers in elementary and secondary schools

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, Volume 13, Issue 8, August 2017, 5597-5606

https://doi.org/10.12973/eurasia.2017.01013a

Publication date: 22 Aug 2017

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Article Downloads: 1250

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References

Cai, J., & Duan, C. (2016). Influencing factors and upgrade strategy of the network teaching of college teachers. E-education Research, (2), 46-53. doi:10.13811/j.cnki.eer.2016.02.007.
Dai, X., & Ceng, L. (2014). Research of the condition and the optimizing strategy of Micro development of primary and secondary school of our country, China Educational Technology, (9), 78-83. doi:10.13266/j.cnki.kfjyyj.20.02.01.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly, 13(3), 319-340. doi:10.2307/249008.
Dogru, M. (2014). Development of a Self-Efficacy Scale of Technology Usage in Education, Eurasia Journal of mathematics science and technology education, 13(6), 1785-1798. doi:10.12973/eurasia.2014.1204a.
Fang, X. (2015). Research of influencing factor of MOOC study behavior. Open Education Research, (3), 46-54. doi:10.13966/j.cnki.kfjyyj.2015.03.006.
Fang, X. (2016). Research of influencing factors of MOOC teaching behavior intention of college teachers. Open Education Research, 22(2), 267-76. doi:10.13966/j.cnki.kfjyyj.2016.02.009.
He, Q. (2015). Reflection of Micro teaching application from the teacher cognition view----taking Jiang xi province as a case. Jiangxi Normal University Master degree dissertation.
Hsu, M. W. (2016). An Analysis of Intention to Use in Innovative Product Development Model through TAM Model. Eurasia Journal of mathematics science and technology education, 12(3), 487-501, doi:10.13973/eurasia.2016.00495a.
Indu Nair, V., & Mukunda, D. (2012). Using Technology Acceptance Model to assess teachers’ attitude towards use of technology as teaching tool: A SEM Approach. International Journal of Computer Applications, 42(2), 1-6. doi:10.5120/5661-7691.
Kung-Teck, W., Osman, R., & Rahmat, M. K. (2013).Understanding Student Teachers’ Behavioural Intention to Use Technology: Technology Acceptance Model (TAM) Validation and Testing. International Journal of Instruction, 6(1), 89-104. doi:10.207/3036540.
Li, Y. (2011). Empirical research of influencing factor of customer purchasing of network shopping. Westsouth Traffic University doctoral.
Li, Y. (2016). Quantitative model building of the use behavior of information technology of the teachers of middle & primary school. E-education Research, (8), 97-105. doi:10.13811/j.cnki.eer.2016.06.014.
Martocchio, J. J., & Webster, J. (2004). Microcomputer Playfulness: Development of a Measure with Workplace Implications. MIS Quarterly, Group Rearch, 35(2), 195-229. doi:10.2307/249576.
Moon, Y. K. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230. doi:10.1016/S0378-7206(00)00061-6.
Moses, P., Wong, S., Bakar, K., & Mahmud, R. (2013). Perceived Usefulness and Perceived Ease of Use: Antecedents of Attitude towards Laptop Use Among Science and Mathematics Teachers in Malaysia. Asia-Pacific Education Researcher (Springer Science & Business Media B.V.), 22(3), 293-9. doi:10.1007/s40299-012-0054-9.
Peng, H., Wang, Y., Huang, R., & Chen, G. (2006). Research of structure and influencing distance study self-efficacy. Open Education Research, 12(2), 41-45. doi:10.13966/j.cnki.kfjyyj.2006.02.011.
Rogers, E. (1995). Diffusion of Innovations, Free Press, New York.
Rong, T. (2009). AMOS and research way, Chong qing university press.
Safar, A., & Alkhezzi, F. (2016). Students’ perspectives of the impact of online streaming media on teaching and learning at the college of education at Kuwait University. Eurasia Journal of mathematics science and technology education, 12(12), 2975-2989. doi:10.12973/eurasia.2016.02317a.
Shi, R. (2001). Modern psychology, Shang hai: east china normal university press, 22-23.
Shu, H. (2015). Research of Condition of microlecture skill leval and training strategy of Elementary and Secondary Schools. Master degree theses of master of shan xi normal university.
Song, C. (2008). Organizational behavior, Gansu People Press, 152-155.
Tan, G., Xu, F., & Qu, W. (2012). The influencing factor and model of behavior intention of network teaching of college students. E-education Research, (1), 47-58. doi:10.13811/j.cnki.eer.2012.01.005.
Thompson S. H. T. (2001). Demographic and motivation variables associated with Internet usage activities. Internet Research: Electronic Networking Applications and Policy, 11(2), 125-137. doi:10.1108/10662240110695089.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal Computing: Toward a Conceptual Model of Utilization, MIS Quarterly, 15(1), 125-143. doi:10.2307/249443.
Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating perceived behavioral control, computer anxiety and enjoyment into the technology acceptance model. Information Systems Research, 11(4), 342–365. doi:10.1287/isre.11.4.342.11872.
Venkatesh. V. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 426-478. doi:10.2307/30036540.
Venkatesh. V. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273-315. doi:10.1111/j.1540-5915.2008.00192.x.
Webster, J., & Martocchio, J. J. (1992). Effects of Feedback and Cognitive Playfulness on Performance in Microcomputer Software Training. Personnel Psychology, 45(3), 553-578. doi:10.1111/j.1744-6570.1992.tb00860.x.
Wu, J. (2014). Research of effective influencing factor of learning community of network course. Shan dong normal university.
Zhang, S., & Li, Y. (2014). Research of influencing factors of using Model network teaching platform of college teachers. E-education Research, (8), 49-56. doi:10.13811/j.cnki.eer.2014.08.008.
Zhang, W., & Mou, J. (2013). Empirical research of influencing factor network study motivation of college students of higher normal school. E-education Research, (12), 50-59. doi:10.13811/j.cnki.eer.2013.12.001.
Zheng, Q. J., Chen, T., & Kong, D. Y. (2017). An Empirical Study on Context Awareness Integrated Mobile Assisted Instruction and the Factors. Eurasia Journal of mathematics science and technology education, 13(6), 1737-1747. doi:10.12973/eurasia.2017.00695a.
Zhong, J. (2016). Research of obstruction and countermeasure of Micro application primary and secondary school teachers based on innovation theory-taking part of primary and secondary school of jiang xi province, Jiangxi Normal University Master degree dissertation.

How to cite this article

APA

Fang, X., & Liu, R. (2017). Determinants of Teachers’ Attitude toward Microlecture: Evidence from Elementary and Secondary Schools. Eurasia Journal of Mathematics, Science and Technology Education, 13(8), 5597-5606. https://doi.org/10.12973/eurasia.2017.01013a

Vancouver

Fang X, Liu R. Determinants of Teachers’ Attitude toward Microlecture: Evidence from Elementary and Secondary Schools. EURASIA J Math Sci Tech Ed. 2017;13(8):5597-606. https://doi.org/10.12973/eurasia.2017.01013a

AMA

Fang X, Liu R. Determinants of Teachers’ Attitude toward Microlecture: Evidence from Elementary and Secondary Schools. EURASIA J Math Sci Tech Ed. 2017;13(8), 5597-5606. https://doi.org/10.12973/eurasia.2017.01013a

Chicago

Fang, Xu, and Rui Liu. "Determinants of Teachers’ Attitude toward Microlecture: Evidence from Elementary and Secondary Schools". Eurasia Journal of Mathematics, Science and Technology Education 2017 13 no. 8 (2017): 5597-5606. https://doi.org/10.12973/eurasia.2017.01013a

Harvard

Fang, X., and Liu, R. (2017). Determinants of Teachers’ Attitude toward Microlecture: Evidence from Elementary and Secondary Schools. Eurasia Journal of Mathematics, Science and Technology Education, 13(8), pp. 5597-5606. https://doi.org/10.12973/eurasia.2017.01013a

MLA

Fang, Xu et al. "Determinants of Teachers’ Attitude toward Microlecture: Evidence from Elementary and Secondary Schools". Eurasia Journal of Mathematics, Science and Technology Education, vol. 13, no. 8, 2017, pp. 5597-5606. https://doi.org/10.12973/eurasia.2017.01013a