ror.org/026w31v75
Résumés
Abstract
University teachers are the main players when it comes to integrating e-learning systems into higher education institutions. Prior studies have identified four main antecedents that explain teachers’ technology acceptance in the educational context: (a) subjective norms (SN), (b) technological complexity (TC), (c) constructivist beliefs (CB), and (d) motivation for instrumental use (MOT). In this study, we proposed and tested the dual roles of MOT, one as a causal variable and the other as a mediating variable, to explain university teachers’ acceptance of e-learning systems. To test the research model, we collected data from 174 teachers at a large public university in Malaysia using a self-administered survey. Our study shows that MOT mediates the direct effects of SN, TC, and CB on perceived ease of use (PEOU), perceived usefulness (PU), and behavioural intention (BI). This study offers important policy insight for university administrators who seek to enhance acceptance of e-learning systems among university teachers.
Keywords:
- E-learning,
- university teachers,
- behavioural intention,
- constructivist beliefs,
- motivation for instrumental use
Parties annexes
Bibliography
- Aypay, A. (2011). The adaptation of the teaching-learning conceptions questionnaire and its relationships with epistemological beliefs. Educational Sciences: Theory and Practice, 11(1), 21-29.
- Chai, C.S. (2010). The relationships among Singaporean preservice teachers' ICT competencies, pedagogical beliefs and their beliefs on the espoused use of ICT. The Asia-Pacific Education Researcher, 19(3), 387-400. Retrieved from http://hdl.handle.net/10497/4791
- Chan, K.-W., & Elliott, R.G. (2004). Relational analysis of personal epistemology and conceptions about teaching and learning. Teaching and Teacher Education, 20(8), 817-831. doi: 10.1016/j.tate.2004.09.002
- Ellemers, N., De Gilder, D., & Haslam, S.A. (2004). Motivating individuals and groups at work: A social identity perspective on leadership and group performance. Academy of Management Review, 29(3), 459-478. doi: 10.5465/amr.2004.13670967
- Friedrich, D. (2014). Belief and motivation. Theoria, 80(3), 255-268. doi: 10.1111/theo.12030
- Gautreau, C. (2011). Motivational factors affecting the integration of a learning management system by faculty. Journal of Educators Online, 8(1), 1-25. Retrieved from https://eric.ed.gov/?id=EJ917870
- Gibson, S.G., Harris, M.L., & Colaric, S.M. (2008). Technology acceptance in an academic context: Faculty Acceptance of online education. Journal of Education for Business, 83(6), 355-359. doi: 10.3200/JOEB.83.6.355-359
- Hair, J.F., Hult, G.T.M., Ringle, C.M., & Sarstedt, M. (2013). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: Sage.
- Haslam, S.A., Powell, C., & Turner, J. (2000). Social identity, self-categorization, and work motivation: Rethinking the contribution of the group to positive and sustainable organisational outcomes. Applied Psychology, 49(3), 319-339. doi: 10.1111/1464-0597.00018
- Henseler, J., Hubona, G., & Ray, P.A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2-20. doi: 10.1108/IMDS-09-2015-0382
- Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. doi: 10.1007/s11747-014-0403-8
- Joo, J., & Sang, Y. (2013). Exploring Koreans' smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory. Computers in Human Behavior, 29(6), 2512-2518. doi: 10.1016/j.chb.2013.06.002
- Judson, E. (2006). How teachers integrate technology and their beliefs about learning: Is there a connection? Journal of Technology and Teacher Education, 14(3), 581-597. Retrieved from https://www.learntechlib.org/primary/p/6046/
- Kao, C.-P., Wu, Y.-T., & Tsai, C.-C. (2011). Elementary school teachers' motivation toward web-based professional development, and the relationship with Internet self-efficacy and belief about web-based learning. Teaching and Teacher Education, 27(2), 406-415. doi: 10.1016/j.tate.2010.09.010
- Keengwe, J., Onchwari, G., & Agamba, J. (2014). Promoting effective e-learning practices through the constructivist pedagogy. Education and Information Technologies, 19(4), 887-898. doi: 10.1007/s10639-013-9260-1
- Kennedy, M.M. (2016). How does professional development improve teaching? Review of Educational Research, 86(4), 945-980. doi: 10.3102/0034654315626800
- Kim, C., Kim, M.K., Lee, C., Spector, J.M., & DeMeester, K. (2013). Teacher beliefs and technology integration. Teaching and Teacher Education, 29, 76-85. doi: 10.1016/j.tate.2012.08.005
- Kim, Y., & Nah, S. (2017). Internet researchers' data sharing behaviors: An integration of data reuse experience, attitudinal beliefs, social norms, and resource factors. Online Information Review, 42(1), 124-142. doi: 10.1108/OIR-10-2016-0313
- Kreijns, K., Vermeulen, M., van Buuren, H., & Van Acker, F. (2017). Does Successful Use of Digital Learning Materials Predict Teachers' Intention to Use Them Again in the Future? The International Review of Research in Open and Distributed Learning, 18(7), 158-174. doi: 10.19173/irrodl.v18i7.2895
- Kuo, Y.-C., Belland, B.R., Schroder, K.E.E., & Walker, A.E. (2014). K-12 teachers' perceptions of and their satisfaction with interaction type in blended learning environments. Distance Education, 35(3), 360-381. doi: 10.1080/01587919.2015.955265
- Lladós-Masllorens, J., Aibar, E., Meseguer-Artola, A., Minguillón, J. & Lerga, M. (2017). Explaining teaching uses of Wikipedia through faculty personal and contextual features. Online Information Review, 41(5), 728-743. doi: 10.1108/OIR-10-2016-0298
- Ma, W.W.-k., Andersson, R., & Streith, K.-O. (2005). Examining user acceptance of computer technology: an empirical study of student teachers. Journal of Computer Assisted Learning, 21(6), 387-395. doi: 10.1111/j.1365-2729.2005.00145.x
- Marra, R. (2005). Teacher beliefs: The impact of the design of constructivist learning environments on instructor epistemologies. Learning Environments Research, 8(2), 135-155. doi: 10.1007/s10984-005-7249-4
- Naaj, M.A., Nachouki, M., & Ankit, A. (2012). Evaluating student satisfaction with blended learning in a gender-segregated environment. Journal of Information Technology Education: Research, 11(1), 185-200. Retrieved from https://www.learntechlib.org/p/111500/
- Nawaz, A., & Kundi, G.M. (2011). Users of e-learning in higher education institutions (HEIs): perceptions, styles and attitudes. International Journal of Teaching and Case Studies, 3(2-4), 161-174. doi: 10.1504/ijtcs.2011.039555
- Nitzl, C., Roldán, J.L., & Cepeda Carrión, G. (2016). Mediation Analysis in Partial Least Squares Path Modeling: Helping Researchers Discuss More Sophisticated Models. Industrial Management & Data Systems, 116(9), 1849-1864. doi: 10.1108/IMDS-07-2015-0302
- Overbay, A., Patterson, A.S., Vasu, E.S., & Grable, L.L. (2010). Constructivism and technology use: findings from the IMPACTing Leadership project. Educational Media International, 47(2), 103-120. doi: 10.1080/09523987.2010.492675
- Park, N. (2010). Adoption and Use of Computer-Based Voice Over Internet Protocol Phone Service: Toward an Integrated Model. Journal of Communication, 60(1), 40-72. doi: 10.1111/j.1460-2466.2009.01440.x
- Park, N., Lee, K.M., & Cheong, P.H. (2007). University instructors' acceptance of electronic courseware: An application of the technology acceptance model. Journal of Computer‐Mediated Communication, 13(1), 163-186. doi: 10.1111/j.1083-6101.2007.00391.x
- Qin, L., Li, N., Zha, S., & He, W. (2017). Research on factors influencing perceived usefulness of a virtual teacher community: A case study of rural teachers in Inner Mongolia, China. Telematics and Informatics, 34(5), 463-471. doi: 10.1016/j.tele.2016.09.008
- Samuelowicz, K., & Bain, J.D. (2001). Revisiting academics' beliefs about teaching and learning. Higher Education, 41(3), 299-325. doi: 10.1023/A:1004130031247
- Sánchez-Prieto, J.C., Olmos-Migueláñez, S., & García-Peñalvo, F.J. (2016). Informal tools in formal contexts: Development of a model to assess the acceptance of mobile technologies among teachers. Computers in Human Behavior, 55, Part A, 519-528. doi: 10.1016/j.chb.2015.07.002
- Sang, G., Valcke, M., van Braak, J., & Tondeur, J. (2010). Student teachers' thinking processes and ICT integration: Predictors of prospective teaching behaviors with educational technology. Computers & Education, 54(1), 103-112. Retrieved from http://hdl.handle.net/1854/LU-850547
- Steel, J., & Hudson, A. (2001). Educational Technology in Learning and Teaching: The Perceptions and Experiences of Teaching Staff. Innovations in Education and Teaching International, 38(2), 103-111. doi: 10.1080/13558000010030158
- Sun, J., Sheng, D., Gu, D., Du, J. & Min, C. (2017). Understanding link sharing tools continuance behavior in social media. Online Information Review, 41(1), 119-133. doi: 10.1108/OIR-08-2015-0261
- Teo, T. (2009). Modelling technology acceptance in education: A study of pre-service teachers. Computers & Education, 52(2), 302-312. doi: 10.1016/j.compedu.2008.08.006
- Teo, T. (2010). A path analysis of pre-service teachers' attitudes to computer use: applying and extending the technology acceptance model in an educational context. Interactive Learning Environments, 18(1), 65-79. doi: 10.1080/10494820802231327
- Teo, T. (2011a). Factors influencing teachers' intention to use technology: Model development and test. Computers & Education, 57(4), 2432-2440. doi: 10.1016/j.compedu.2011.06.008
- Teo, T. (2011b). Technology acceptance research in education. AW Rotterdam: Sense Publisher.
- Teo, T. (2012). Examining the intention to use technology among pre-service teachers: an integration of the technology acceptance model and theory of planned behavior. Interactive Learning Environments, 20(1), 3-18. doi: 10.1080/10494821003714632
- Teo, T. (2014). Unpacking teachers' acceptance of technology: Tests of measurement invariance and latent mean differences. Computers & Education, 75, 127-135. doi: 10.1016/j.compedu.2014.01.014
- Teo, T., Chai, C.S., Hung, D., & Lee, C.B. (2008). Beliefs about teaching and uses of technology among pre‐service teachers. Asia-Pacific Journal of Teacher Education, 36(2), 163-174. doi: 10.1080/13598660801971641
- Teo, T., Lee, C.B., & Chai, C.S. (2008). Understanding pre‐service teachers' computer attitudes: applying and extending the technology acceptance model. Journal of Computer Assisted Learning, 24(2), 128-143. doi: 10.1111/j.1365-2729.2007.00247.x
- Teo, T., Milutinović, V., & Zhou, M. (2016). Modelling Serbian pre-service teachers' attitudes towards computer use: A SEM and MIMIC approach. Computers & Education, 94, 77-88. doi: 10.1016/j.compedu.2015.10.022
- Teo, T., & Zhou, M. (2016). The influence of teachers' conceptions of teaching and learning on their technology acceptance. Interactive Learning Environments, 1-15. doi: 10.1080/10494820.2016.1143844
- Tondeur, J., Hermans, R., van Braak, J., & Valcke, M. (2008). Exploring the link between teachers' educational belief profiles and different types of computer use in the classroom. Computers in Human Behavior, 24(6), 2541-2553. doi: 10.1016/j.chb.2008.02.020
- van Schaik, P., & Teo, T. (2013). Understanding technology acceptance in pre-service teachers: a structural-equation modeling approach. The Asia-Pacific Education Researcher, 18(1), 47-66.
- Venkatesh, V., & Bala, H. (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
- 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: 10.1287/mnsc.46.2.186.11926
- Wang, Q., Quek, C.L., & Hu, X. (2017). Designing and Improving a Blended Synchronous Learning Environment: An Educational Design Research. The International Review of Research in Open and Distributed Learning, 18(3), 99-118. doi: 10.19173/irrodl.v18i3.3034
- West, R.E., Waddoups, G., & Graham, C.R. (2007). Understanding the experiences of instructors as they adopt a course management system. Educational Technology Research and Development, 55(1), 1-26. doi: 10.1007/s11423-006-9018-1
- Wright, N. (2015). A case for adapting and applying continuance theory to education: understanding the role of student feedback in motivating teachers to persist with including digital technologies in learning. Teachers and Teaching, 21(4), 459-471. doi: 10.1080/13540602.2014.969105
- Yuen, A.H., & Ma, W.W. (2008). Exploring teacher acceptance of e‐learning technology. Asia‐Pacific Journal of Teacher Education, 36(3), 229-243. doi: 10.1080/13598660802232779