Applying the Technology Acceptance Model (TAM) to explore the effects of a Course Management System (CMS)-Assisted EFL writing instruction
Issue: Vol 32 No. 1 (2015)
Journal: CALICO Journal
Subject Areas:
DOI: 10.1558/calico.v32i1.25961
Abstract:
This study illustrates a teaching model that utilizes a Blackboard (Bb) course management system (CMS) to support English writing instruction. It was implemented in a blended English research paper (RP) writing course, with specific learning resources and activities offered inside and outside the Bb CMS. A quasi-experimental study in which the results of two academic years were analyzed is presented. The results showed that the experimental group significantly outperformed the control group in their final drafts. The research methodology includes the technology acceptance model (TAM) to evaluate the course. The results of the survey showed that most students displayed positive learning outcomes, indicating that the instruction model could contribute to the effectiveness of learning English writing. Major factors influencing the improvement of writing performance included technical support, perceived usefulness, perceived ease of use, and attitude; however, the influence of writing activities on the Bb was limited in comparison to the other variables.
Author: Yea-Ru Tsai
References :
Arbaugh, J. B. (2002). Managing the online classroom: A study of technological and behavioral characteristics of web-based MBA courses. Journal of High Technology Management Research, 13 (2): 203–223. http://dx.doi.org/10.1016/S1047-8310(02)00049-4
Cappel, J. J. and Hayen, R. L. (2004). Evaluating e-learning: A case study. Journal of Computer Information Systems, 44: 49–56.
Chan, A. Y., Chow, K.-O. and Jia, W.-J. (2005). A framework for evaluation of learning effectiveness in online courses. In R. W. Lau, Q. Li, R. Cheung, and W. Liu (Eds), Advances in Web-based Learning-ICWL 2005, 383–395. Hong Kong, China: Springer.
Cheng, H. J. (2007). The perceptions of Taiwanese college students toward the English courses using an online course management system. PhD dissertation, Ohio University.
Chou, C., Peng, H. Y., and Chang, C. Y. (2010). The technical framework of interactive functions for course-management systems: Students’ perceptions, uses, and evaluations. Computers & Education, 55 (3): 1004–1017. http://dx.doi.org/10.1016/j.compedu.2010.04.011
Coates, H., James, R., and Baldwin, G. (2005). A critical examination of the effects of learning management systems on university teaching and learning. Tertiary Education and Management, 11 (1): 19–36. http://dx.doi.org/10.1080/13583883.2005.9967137
Davis, F. D. (1986). Technology acceptance model for empirically testing new end-user information systems: Theory and results. MA, USA: Massachusetts Institute of Technology.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3): 319–339. http://dx.doi.org/10.2307/249008
Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man–Machine Studies, 38 (3): 475–487. http://dx.doi.org/10.1006/imms.1993.1022
Elliott, A. C. and Woodward, W. A. (2007). Statistical Analysis Quick Reference Guidebook: With SPSS Examples. London: Sage Publication Inc.
Ferriman, N. (2013). The impact of blended e-learning on undergraduate academic essay writing in English (L2). Computers & Education, 60 (1): 243–253. http://dx.doi.org/10.1016/j.compedu.2012.07.008
Gao, Y. (2005). Applying the technology acceptance model to educational hypermedia: A field study. Journal of Educational Multimedia and Hypermedia, 14 (3): 237–247.
Hölbl, M. and Welzer, T. D. (2010). Students’ feedback and communication habits using Moodle. Electronics and Electrical Engineering, 6 (102): 63–66.
Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: An overview. Theory into Practice, 41 (4): 212–260. http://dx.doi.org/10.1207/s15430421tip4104_2
Landry, B. J. L., Griffeth, R., and Hartman, S. (2006). Measuring student perceptions of blackboard using the technology acceptance model. Decision Sciences Journal of Innovative Education, 4 (1): 87–99. http://dx.doi.org/10.1111/j.1540-4609.2006.00103.x
Leahy, C. (2004). Researching language learning processes in open CALL settings for advanced learners. Computer Assisted Language Learning, 17 (3–4): 289–313. http://dx.doi.org/10.1080/0958822042000319593
Lee, Y. H., Hsieh, Y. C., and Hsu, C. N. (2011). Adding innovation diffusion theory to the Technology Acceptance Model: Supporting employee’s intentions to use e-learning systems. Educational Technology & Society, 14 (2): 124–137.
Liao, C. W. and Lin, S. Y. (2011). An analysis of the interactive behaviors of self-learning management in a web-based Moodle e-learning platform. African Journal of Business Management, 5 (22): 9191–9199.
Liaw, S. S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers & Education, 51 (2): 864–873. http://dx.doi.org/10.1016/j.compedu.2007.09.005
Ling, W. C. and Yang, S. C. (2011). Exploring students’ perceptions of integrating Wiki technology and peer feedback into English writing courses. English Teaching: Practice and Critique, 10 (2): 88–103.
Liu, I-F., Chen, M. C., Sun, Y. L., Wible, D., and Kuo, C.-H. (2010). Extending the TAM model to explore the factors that affect intention to use an online learning community. Computers & Education, 54 (2): 600–610. http://dx.doi.org/10.1016/j.compedu.2009.09.009
Malikowski, S. R. (2008). Factors related to breadth of use in course management systems. The Internet and Higher Education, 11 (2): 81–86. http://dx.doi.org/10.1016/j.iheduc.2008.03.003
Martin-Blas, T. and Serrano-Fernandez, A. (2009). The role of new technologies in the learning process: Moodle as a teaching tool in physics. Computers & Education, 52 (1): 35–44. http://dx.doi.org/10.1016/j.compedu.2008.06.005
Matsumura, S. and Hann, G. (2004). Computer anxiety and students’ preferred feedback methods in EFL writing. The Modern Language Journal, 88 (3): 403–418. http://dx.doi.org/10.1111/j.0026-7902.2004.00237.x
Ngai, E. W. T., Poon, J. K. L. and Chan, Y. H. C. (2007). Empirical examination of the adoption of WebCT using TAM. Computers and Education, 48 (2): 250–267. http://dx.doi.org/10.1016/j.compedu.2004.11.007
Novo-Corti, I., Varela-Candamio, L., and Ramil-Díaz, M. (2003). E-learning and face to face mixed methodology: Evaluating effectiveness of e-learning and perceived satisfaction for a microeconomic course using the Moodle platform. Computers in Human Behavior, 29 (2): 410–415. http://dx.doi.org/10.1016/j.chb.2012.06.006
Park, N. (2005). User acceptance of e-learning in higher education: An application of Technology Acceptance Model. Proceedings of the International Communication Association 2005 Annual Meeting, 1–41. New York.
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.
Roca, J. C., Chiu, C.-M., and Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. Journal of Human-Computer Studies, 64 (8): 683–696. http://dx.doi.org/10.1016/j.ijhcs.2006.01.003
Sánchez, R. A. and Hueros, A. D. (2010). Motivational factors that influence the acceptance of Moodle using TAM. Computers in Human Behavior, 26 (6): 1632–1640. http://dx.doi.org/10.1016/j.chb.2010.06.011
Sanprasert, N. (2010). The application of a course management system to enhance autonomy in learning English as a foreign language. System, 38 (1): 109–123. http://dx.doi.org/10.1016/j.system.2009.12.010
Sarker, S. (2005). Knowledge transfer and collaboration in distributed U.S.–Thai teams. Journal of Computer-Mediated Communication, 10 (4). http://dx.doi.org/10.1111/j.1083-6101.2005.tb00278.x
Tsai, Y. R. and Ernst, C. A. (2009). The model and implementation of a Course-Management-System (CMS)-assisted EFL Reading Strategy Instruction. International Journal of Digital Learning Technology, 1 (3): 206–226.
Tsai, Y. R., & Talley, P. C. (2014). The effect of a course management system (CMS)-supported strategy instruction on EFL reading comprehension and strategy use. Computer Assisted Language Learning, 27 (5): 422–438. http://dx.doi.org/10.1080/09588221.2012.757754
Venkatesh, V. (2001). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11 (4): 342–365. http://dx.doi.org/10.1287/isre.11.4.342.11872
Venkatesh, V. and Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46 (2): 186–204. http://dx.doi.org/10.1287/mnsc.46.2.186.11926
Vovides, Y., Sanchez-Alonso, S., Mitropoulou, V., and Nickmans, G. (2007). The use of e-learning course management systems to support learning strategies and to improve self-regulated learning. Educational Research Review, 2 (1): 64–74. http://dx.doi.org/10.1016/j.edurev.2007.02.004
West, R. E., Waddoups, G., and 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. http://dx.doi.org/10.1007/s11423-006-9018-1
Winkler, A. A. and McCuen, J. R. (2008). Writing the Research Paper. Taipei: The Crane Publisher.
Winne, P. H. and Hadwin, A. F. (1998). Studying as self-regulated learning. In D. J. Hacker, J. Dunlosky, and A. C. Graesser (Eds), Metacognition in Educational Theory and Practice, 277–304. Mahwah, NJ: Lawrence Erlbaum Associates.
Yu, W.-K., Sun, Y.-C., and Chang, Y.-J. (2010). When technology speaks language: An evaluation of course management systems used in a language learning context. ReCALL, 22 (3): 332–355. http://dx.doi.org/10.1017/S0958344010000194