Exploring the drivers of technology acceptance: a study of Nepali school students
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The question of what drives learners to adopt and use certain technologies over others, generally referred to as technology acceptance in the literature, is of interest to educational technology researchers, to policymakers, and developers in educational institutions. Technology acceptance models can inform adoption and implementation decisions. Despite the growing literature on technology acceptance, there is less evidence from countries with the lowest economic development indicators such as Nepal. The present study investigates the factors motivating technology use in the Nepali context. The study is grounded in an extended technology acceptance model (TAM) applied to using the internet for learning (not limited to online learning environments). The data were collected from 126 school students in Nepal (Mage = 15.19). We found empirical support for our proposed research model. There were strong relationships between computer self-efficacy and perceived enjoyment, and perceived enjoyment and behavioral intention. We found no influence of perceived usefulness or attitude on behavioral intention, contrary to theorized relationships and the empirical literature. Our findings show that the extended TAM translates to understudied populations such as Nepali secondary school students and suggests that it is sensitive to local situational differences that influence technology acceptance behaviors.
KeywordsTechnology acceptance Antecedents to use Nepal Underdeveloped perspective
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.Google Scholar
- Baller, S., Battista, A., Dutta, S., & Lanvin, B. (2016). The networked readiness index 2016 (pp. 1–36). Retrieved from http://www3.weforum.org/docs/GITR2016/WEF_GITR_Chapter1.1_2016.pdf.
- Bhuasiri, W., Xaymoungkhoun, O., Zo, H., Rho, J. J., & Ciganek, A. P. (2012). Critical success factors for e-learning in developing countries: A comparative analysis between ICT experts and faculty. Computers & Education, 58(2), 843–855.Google Scholar
- Center for Education Innovations. (2015). Integration of Technology in Schools. Retrieved 22 July, 2017 from http://www.educationinnovations.org/program/integration-technology-schools.
- Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.Google Scholar
- Davis, F. D., Bagozzi, R., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.Google Scholar
- Dawadi, B. R., & Shakya, S. (2016). ICT implementation and infrastructure deployment approach for rural Nepal. In Proceedings of the International Conference on Computing and Information Technology (pp. 319–331). Switzerland: Springer.Google Scholar
- Doleck, T., Bazelais, P., & Lemay, D. J. (2017c). Examining the antecedents of Facebook acceptance via structural equation modeling: A case of CEGEP students. Knowledge Management & E-Learning, 9(1), 69–89.Google Scholar
- Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.Google Scholar
- Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.Google Scholar
- Hamner, M., & Qasi, R. (2009). Expanding the technology acceptance model to examine personal computing technology utilization in government agencies in developing countries. Government Information Quarterly, 26(1), 128–136.Google Scholar
- Jahan, S. (2016). Human development report 2016 (pp. 1–286). New York, NY. Retrieved 22 July, 2017 from http://hdr.undp.org/sites/default/files/2016_human_development_report.pdf.
- Kock, N. (2015a). WarpPLS. Retrieved from http://www.warppls.com.
- Kock, N. (2015b). WarpPLS 5.0 user manual. ScripWarp Systems. Retrieved from http://cits.tamiu.edu/WarpPLS/UserManual_v_5_0.pdf.
- Lee, Y.-H., Hsieh, Y.-C., & Hsu, C.-N. (2011). Adding innovation diffusion theory to the technology acceptance model: Supporting employees’ intentions to use E-learning systems. Educational Technology & Society, 14(4), 124–137.Google Scholar
- Ministry of Education. (2016). Eduation in figures 2016 (pp. 1–26). Kathmandu: Ministry of Education. Retrieved from http://www.moe.gov.np/assets/uploads/files/Nepal_Education_in_Figures_2016.pdf.
- Musa, P. F. (2006). Making a case for modifying the technology acceptance model to account for limited accessibility in developing countries. Information Technology for Development, 12(3), 213–224.Google Scholar
- Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use E-learning. Educational Technology & Society, 12(3), 150–162.Google Scholar
- Park, N., Roman, R., Lee, S., & Chung, J. E. (2009). User acceptance of a digital library system in developing countries: An application of the technology acceptance model. International Journal of Information Management, 29(3), 196–209.Google Scholar
- Rogers, E. (1983). Diffusion of innovations. New York: Free Press.Google Scholar
- Sang, G., Valcke, M., van Braak, J., Tondeur, J., & Zhu, C. (2010). Predicting ICT integration into classroom teaching in Chinese primary schools: Exploring the complex interplay of teacher-related variables. Journal of Computer Assisted Learning, 27(2), 160–172. https://doi.org/10.1111/j.1365-2729.2010.00383.x.Google Scholar
- Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information and Management, 44(1), 90–103.Google Scholar
- Tarhini, A., Hone, K., & Liu, X. (2013). Factors affecting students’ acceptance of E-learning environments in developing countries: A structural equation modeling approach. International Journal of Information and Education Technology, 3(1), 54.Google Scholar
- Tarhini, A., Hone, K., Liu, X., & Tarhini, T. (2017). Examining the moderating effect of individual-level cultural values on users’ acceptance of E-learning in developing countries: A structural equation modeling of an extended technology acceptance model. Interactive Learning Environments, 25(3), 306–328.Google Scholar
- Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.Google Scholar
- Teo, T., & Fan, X. (2013). Coefficient alpha and beyond: Issues and alternatives for educational research. Asia-Pacific Education Researcher, 22(2), 209–213.Google Scholar
- Teo, T., & Noyes, J. (2011). An assessment of the influence of perceived enjoyment and attitude on the intention to use technology among pre-service teachers: A structural equation modeling approach. Computers & Education, 57(2), 1645–1653. https://doi.org/10.1016/j.compedu.2011.03.002.Google Scholar
- The World Bank. (2017). Data Nepal. Retrieved 22 July 2017, from http://data.worldbank.org/country/nepal.
- UNESCO. (2015). Education for all: National Review report (pp. 1–125). Kathmandu, Nepal: UNESCO. Retrieved from http://unesdoc.unesco.org/images/0023/002327/232769E.pdf.
- Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27, 451–481.Google Scholar
- 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.Google Scholar
- Wodon, Q. (2015). Technology in the classroom: Learning from OLE Nepal|global partnership for education. Globalpartnership.org. Retrieved 23 July 2017, from http://www.globalpartnership.org/blog/technology-classroom-learning-ole-nepal.