Abstract
With the rapid growth of the Internet, it is much easier to access the web-based technology. The web-based technology has also dramatically influenced our life. Moreover, many institutions, including the government of Taiwan, required that their employees are capable of using technological tools to fulfill their job requirements. Public organizations in Taiwan are now widely utilizing web-based learning techniques to improve the quality of human capital and boost the productivities of public employees; the situation is the same in education field. Many previous studies showed that using the web-based technology efficiently enhances learners’ performances, attitudes and motivation toward on-line learning. Therefore, with the trend of using web-based technology on learning and teaching, numerous education/training institutes and companies have dedicated great efforts and large amount of money to advance on-line learning programs for users. However, while many studies mentioned about the learners’, teachers’ and employees’ acceptance toward on-line learning, few studies have reported the point of view from educational administrators, the crucial group of people who make the educational decisions. Therefore, the purposes of this study are using the theory of planned behavior and theory of reasoned action as background models to investigate the effect of the participants’ subjective norms on their use intention toward on-line learning. The participants in this study were 176 educational administrators in Department of Education, Taipei City Government. A survey questionnaire was administered to understand their subjective norms, including “superior influence,” “peer influence,” and “regulations.” The results demonstrate that peer influence has the most significant effects on participants’ use intention, followed by superior influence. However, regulations have no significant effect on their use intention. Specifically, from the results of correlation analysis, there is a positive relationship between peer influence and their use intention toward on-line learning, however, a negative relationship has shown between superior influence and use intention toward on-line learning. In other words, it seems that the participants are influenced by their peers on using on-line learning, thus expressing higher use intention. Contrary to the peer influence, the participants are less influenced or get discouraged by their superiors on using on-line learning.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ajzen, I.: From intentions to action: A theory of planned behavior. In: Kuhl, J., Beckman (eds.) Action-Control: From Congnition to Behavior, pp. 11–39. Springer, Heidelberg (1985)
Ajzen, I.: The theory of planned behavior. Organizational Behavior and Human Decision Processes 50, 179–211 (1991)
Bansal, H.S., Taylor, S.F.: Investigating interactive effects in the theory of planned behavior in a service-provider switching context. Psychology & Marketing 19(5), 407–425 (2002)
Cheung, W., Huang, W.: Proposing a framework to assess Internet usage in university education: An empirical investigation from a student’s perspective. British Journal of Educational Technology 36(2), 237–253 (2005)
Davis, F.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13(3), 319–340 (1989)
Fishein, M., Ajzen, I.: Belief, attitude, intension and behavior: An introduction to theory and research. Addison-Wesley, Reading (1975)
Gondin, G., Valois, P., Lepage, L., Desharnais, R.: Predictors of smoking behavior: an application of Ajzen’s theory of planned behavior. British Journal of Addiction 87(9), 1335–1343 (1992)
Lee, M.-C.: Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation-confirmation model. Computers & Education 54, 506–516 (2009)
Lee, J., Cerreto, F.A., Lee, J.: Theory of Planned Behavior and Teachers’ Decisions Regarding Use of Educational Technology. Educational Technology & Society 13(1), 152–164 (2010)
Liker, J.K., Sindi, A.A.: User acceptance of expert systems: a test of the theory of reasoned action. Journal of Engineering and Technology Management 14(2), 147–173 (1997)
Liu, I.-F., Chen, M.C., Sun, Y.S., Kuo, C.-H.: Extending the TAM model to explore the factors that affect Intention to Use an Online Learning Community. Computers & Education 54, 600–610 (2009)
Pelgurm, W.J.: Obstacles to the Integration of ICT in Education: Results from a Worldwide Educational Assessment. Computers & Education 37, 163–178 (2001)
Schifter, D.E., Ajzen, I.: Intention, perceived control, and weight loss: An application of the theory of planned behavior. Journal of Personality and Social Psychology 49(3), 843–851 (1985)
Sivo, S.A., Pan, C., Hahs-Vaughn, D.L.: Combined longitudinal effects of attitude and subjective norms on student outcomes in a web-enhanced course: A structural equation modeling approach. British Journal of Educational Technology 38(5), 861–875 (2007)
Teo, T.: The impact of subjective norm and facilitating conditions on pre-service teachers’ attitude toward computer use: a structural equation modeling of an extended technology acceptance model. Journal Educational Computing Research 40(1), 89–109 (2009)
Venkatesh, V., Morris, M.G.: Why don’t men ever stop to ask for directions? Gender, social influences, and their role in the technology acceptance and usage behavior. MIS Quarterly 24(1), 115–139 (2000)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chang, TK., Huang, Hf., Chang, SM. (2013). Understanding Educational Administrators’ Subjective Norms on Their Use Intention toward On-Line Learning. In: Uden, L., Herrera, F., Bajo Pérez, J., Corchado Rodríguez, J. (eds) 7th International Conference on Knowledge Management in Organizations: Service and Cloud Computing. Advances in Intelligent Systems and Computing, vol 172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30867-3_24
Download citation
DOI: https://doi.org/10.1007/978-3-642-30867-3_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-30866-6
Online ISBN: 978-3-642-30867-3
eBook Packages: EngineeringEngineering (R0)