Factors that influence the acceptance of the learning management system in the School of Philosophy and Arts at UANL

Authors

DOI:

https://doi.org/10.29105/rinn15.30-1

Keywords:

e-learning, learning management system (LMS), Task Fit Technology (TTF), Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT)

Abstract

It is indisputable that technology advances exponentially, and people try to adapt to change constantly, however, the change is so fast that many times users can get uncomfortable with the new technology and generate resistance to its use. For this reason, the intention of this study is to propose a model of acceptance of educational modifying the TAM (Technology Acceptance Model) to the needs of the educational context, by adding the variable perception of playful. The study was conducted at the Faculty of Philosophy and Letters of the UANL, where 100 surveys were applied to undergraduate students, obtaining a good reliability in the designed instrument. Later, the statistical package, SPSS (Statistical Package for the Social Sciences) was used to analyze the data, using the method of successive steps of the multivariate regression. The results of the study show that there are significant relationships between the variables in he proposed model. In general, the study shows in a clear and parsimonious way the most important factors that influence the acceptance of the Nexus platform, therefore, it is concluded that it can be applied in the acceptance of educational technology.

Downloads

Download data is not yet available.

Author Biographies

Rubén Suárez Escalona, Autonomous University of Nuevo León

Nací en Monterrey Nuevo León, estudié la licenciatura de Ingeniero Administrador de Sistemas en FIME, posteriormente estudié la maestría en ciencias de la información con acentuación en inteligencia artificial. Actualmente curso el septimo semestre del doctorado en filosofía de la administración en FACPYA. Por otro lado estudié 7 niveles de Inglés en el Centro de idiomas de FFYL y actualmente curso el segundo semestre de frances en esta misma facultad.

Armando Tijerina García, Autonomous University of Nuevo León

Profesor investigador de la UANL.

Gloria Nelly Salas Celestino, Autonomous University of Nuevo León

Investigadora de la UANL

María de la Luz Escalona Galindo, Autonomous University of Nuevo León

Investigadora de la UANL

References

Abu-Shanab, E. A. (2017). E-government familiarity influence on Jordanians’ perceptions. Telematics and Informatics, 34(1), 103-113. DOI: https://doi.org/10.1016/j.tele.2016.05.001

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. J. Kuhl, & J. Beckman (Eds.), Action-control: From cognition to behavior (pp. 11-39). Heidelberg: Springer. DOI: https://doi.org/10.1007/978-3-642-69746-3_2

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice.

Asociación nacional de universidades e instituciones de educación superior, Anuario de educación superior 2016-2017. (2017). Recuperado de http://www.anuies.mx/informacion-y-servicios/informacion-estadistica-de-educacion-superior/anuario-estadistico-de-educacion-superior

Belsley, D. A. (1991). Conditioning Diagnostics: Collinearity and Weak Data in Regression. New York: Wiley.

Cheema, U., Rizwan, M., Jalal, R., Durrani, F., & Sohail, N. (2013). The trend of online shopping in 21st century: Impact of enjoyment in TAM model. Asian Journal of Empirical Research, 3(2), 131-141.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. DOI: https://doi.org/10.2307/249008

Fathema, N., & Sutton, K. L. (2013). Factors influencing faculty members’ Learning Management Systems adoption behavior: An analysis using the Technology Acceptance Model. International Journal of Trends in Economics Management & Technology (IJTEMT), 2(6), 20-28.

Horn, A. M., Rothe, H., & Gersch, M. (marzo, 2014). Which factors drive e-learning usage?. Trabajo presentado en INTED 2014 Conference, Valencia, España.

Lin, P. C., Lu, H. K., & Liu, S. C. (2013). Towards an education behavioral intention model for e-learning systems: an extension of UTAUT. Journal of Theoretical & Applied Information Technology, 47(3), 1120-1127.

Marangunić, N., & Granić, A. (2015). Technology acceptance model: a literature review from 1986 to 2013. Universal Access in the Information Society, 14(1), 81-95. DOI: https://doi.org/10.1007/s10209-014-0348-1

Nistor, N., Göğüş, A., & Lerche, T. (2013). Educational technology acceptance across national and professional cultures: a European study. Educational Technology Research and Development, 61(4), 733-749. DOI: https://doi.org/10.1007/s11423-013-9292-7

Ongena, G., van de Wijngaert, L., & Huizer, E. (2013). Acceptance of online audio-visual cultural heritage archive services: a study of the general public. Information research, 18(2), 1-17.

Rejón, F., Liébana, F. J., & Martínez, M. (junio, 2011). Factores motivacionales de la aceptación de redes sociales de microblogging: modelo µbtam. Trabajo presentado en el tercer congreso internacional UNIVEST 2011, Cataluña, España.

Romero, C. L., de Amo, M. D. C. A., & Borja, M. Á. G. (2011). Adopción de redes sociales virtuales: ampliación del modelo de aceptación tecnológica integrando confianza y riesgo percibido. Cuadernos de Economía y Dirección de la Empresa, 14(3), 194-205. DOI: https://doi.org/10.1016/j.cede.2010.12.003

Sánchez, R. A., & Hueros, A. D. (2010). Motivational factors that influence the acceptance of Moodle using TAM. Computers in human behavior, 26(6), 1632-1640. DOI: https://doi.org/10.1016/j.chb.2010.06.011

Tan, P. J. B. (2013). Applying the UTAUT to understand factors affecting the use of English e-learning websites in Taiwan. Sage Open, 3(4), 1-12. DOI: https://doi.org/10.1177/2158244013503837

Tarhini, A., Hone, K., & Liu, X. (2013). User acceptance towards web-based learning systems: Investigating the role of social, organizational and individual factors in European higher education. Procedia Computer Science, 17, 189-197. DOI: https://doi.org/10.1016/j.procs.2013.05.026

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: https://doi.org/10.1287/mnsc.46.2.186.11926

Venkateh, V., Morris, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478. DOI: https://doi.org/10.2307/30036540

Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221-232. DOI: https://doi.org/10.1016/j.chb.2016.10.028

Zhao, Y., & Zhu, Q. (2009). Blog acceptance model: An empirical study on exploring users' acceptance and continual usage of blogs. Journal of Data and Information Science, 2(3), 44-61.

Published

2018-12-07

How to Cite

Suárez Escalona, R., Tijerina García, A., Salas Celestino, G. N., & Escalona Galindo, M. de la L. (2018). Factors that influence the acceptance of the learning management system in the School of Philosophy and Arts at UANL. Innovaciones De Negocios, 15(30), 147–159. https://doi.org/10.29105/rinn15.30-1