English
15 (1) 2020
Phân tích các yếu tố ảnh hưởng đến ý định tham gia E-Learning từ quan điểm của giảng viên: Một nghiên cứu điển hình về Việt Nam
Tác giả liên hệ, Email:Tóm tắt
Tài liệu tham khảo
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Ajzen, I., & Fishbein, M. M. (1980). Understanding attitudes and predicting social behavior. Eaglewood Cliffs, NJ: Prentice-Hall.
Allen, I. E., & Seaman, J. (2012). Conflicted: Faculty and online education, 2012. Retrieved November 17, 2019, from https://files.eric.ed.gov/fulltext/ED535214.pdf
Allen, I. E., & Seaman, J. (2014). Grade change: Tracking online education in the United States. Retrieved November 18, 2019, from https://www.onlinelearningsurvey.com/reports/gradechange.pdf
Allen, I. E., & Seaman, J. (2015). Grade level: Tracking online education in the United States. Retrieved November 19, 2019, from http://files.eric.ed.gov/fulltext/ED572778.pdf
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.
Baris, M. F. (2015). Future of E-Learning: Perspective of European teachers. Eurasia Journal of Mathematics, Science & Technology Education, 11(2), 421-429.
Bhattacherjee, A. (2001). Understanding information systems continuance. An expectation- confirmation model. MIS Quarterly, 25(3), 351-370.
Davis, D. F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Journal, 13(3), 319-340.
Dijkstra, T. K. (2010). Latent variables and indices: Herman Wold’s basic design and partial least squares. In Handbook of partial least squares (pp. 23-46). Berlin, Germany: Springer.
Fishbein, M. (1967). Readings in attitude theory and measurement. Oxford, UK: Wiley.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of email: An extension to the technology acceptance model. MIS Quarterly, 21(4), 389-400.
Götz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS) approach. In Handbook of partial least squares (pp. 691-711). Berlin, Germany: Springer.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall.
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). New York, NY: Sage Publications.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433.
Jaschik, S., & Lederman, D. (2014). Faculty attitudes on technology. Retrived November 20, 2019, from https://mediasite.com/wp-content/uploads/2018/11/2018-Faculty-Survey-Mediasite.pdf
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29-39.
Moore (2014). Thị trường giáo dục trực tuyến - Digital activities report 2014. Retrieved November 21, 2019, from http://moore.vn/tin-tuc/digital-report
Nunnally, J. C. (1994). Psychometric theory 3E. New York, NY: McGraw-Hill Education.
Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012). Editor’s comments: A critical look at the use of PLS-SEM. MIS Quarterly, 36(1), iii-xiv.
Sulčič, V., & Lesjak, D. (2009). E-Learning and study effectiveness. Journal of Computer Information Systems, 49(3), 40-47.
Tarhini, A., Hone, K., & Liu, X. (2015). A cross-cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between British and Lebanese university students. British Journal of Educational Technology, 46(4), 739-755.
Teo, T., & Noyes, J. (2014). Explaining the intention to use technology among pre-service teachers: A multi-group analysis of the unified theory of acceptance and use of technology. Interactive Learning Environments, 22(1), 51-66.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
Wong, K.-T., Teo, T., & Goh, P. S. C. (2015). Understanding the intention to use interactive whiteboards: Model development and testing. Interactive Learning Environments, 23(6), 731-747.
Wu, I. L., & Chen, J. L. (2005). An extension of Trust and TAM model with TPB in the initial adoption of online tax: An empirical study. International Journal of Human-Computer Studies, 62(6), 784-808.
Zhao, Y., Lei, J., Yan, B., Lai, C., & Tan, H. S. (2005). What makes the difference? A practical analysis of research on the effectiveness of distance education. Teachers College Record, 107(8), 1836-1884.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.