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Original Articles

South Korean university students’ mobile learning acceptance and experience based on the perceived attributes, system quality and resistance

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References

  • Adkins, S. (2011). The worldwide market for mobile learning products and services: 2010–2015 forecast and analysis. Retrieved from http://www.ambientinsight.com/Resources/Documents/Ambient-Insight-2010-2015-Worldwide-Mobile-Learning-Market-Forecast-Executive-Overview.pdf
  • Al-Hajraf, H., & Al-Sharhan, S. (2012). Total quality management (TQM) of blended e-learning systems: A new integrated model and framework. Literacy Information and Computer Education Journal, 3, 591–598.10.20533/licej.2040.2589.
  • Brown, T. H. (2005). Towards a model for m-learning in Africa. International Journal on E-Learning, 4, 299–315.
  • Celik, I., Sahin, I., & Aydin, M. (2014). Reliability and validity study of the mobile learning adoption scale developed based on the diffusion of innovations theory. International Journal of Education in Mathematics, Science and Technology, 2, 300–316.10.18404/ijemst.65217
  • Chen, H. (2010). Linking employees’ e-learning system use to their overall job outcomes: An empirical study based on the IS success model. Computers & Education, 55, 1628–1639.10.1016/j.compedu.2010.07.005
  • Cheng, F., Lin, I., & Wang, K. (2013, May). Measuring the adoption and resistance of e-learning by students. The International Conference on E-Technologies and Business on the Web, University of the Thai Chamber of Commerce, Bangkok, Thailand.
  • Cheung, W. S., & Hew, K. F. (2009). A review of research methodologies used in studies on mobile handheld devices in K-12 and higher education settings. Australasian Journal of Educational Technology, 25, 153–183.
  • Cornescu, V., & Adam, C. (2013). The consumer resistance behaviour towards innovation. Procedia Economics and Finance, 6, 457–465.10.1016/S2212-5671(13)00163-9
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319–339.10.2307/249008
  • El-Hussein, M. O. M., & Cronje, J. C. (2010). Defining mobile learning in the higher education landscape. Educational Technology & Society, 13, 12–21.
  • Ellen, P. S., Bearden, W. O., & Sharma, S. (1991). Resistance to technological innovations: An examination of the role of self-efficacy and performance satisfaction. Journal of the Academy of Marketing Science, 19, 297–307.10.1007/BF02726504
  • Gafni, R. (2009). Quality metrics for PDA-based m-learning information systems. Interdisciplinary Journal of E-Learning and Learning Objects, 5, 359–378.
  • Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. London: Prentice-Hall International.
  • Hora, S. C., & Wilcox, J. B. (1982). Estimation of error rates in several-population discriminant analysis. Journal of Marketing Research, 19, 57–61.10.2307/3151530
  • Hsu, L. C., Lu, H. P., & Hsu, H. H. (2007). Adoption of the mobile internet: An empirical study of multimedia message service (MMS). Omega, 35, 715–726.10.1016/j.omega.2006.03.005
  • Huang, R., Jang, S., Machtmes, K., & Deggs, D. (2012). Investigating the roles of perceived playfulness, resistance to change and self-management of learning in mobile English learning outcome. British Journal of Educational Technology, 43, 1004–1015.10.1111/bjet.2012.43.issue-6
  • Huang, Y. (2014). Empirical analysis on factors impacting mobile learning acceptance in higher engineering education ( Unpublished doctoral dissertation). Knoxville: University of Tennessee.
  • Iqbal, S., & Qureshi, I. (2012). M-learning adoption: A perspective from a developing country. The International Review of Research in Open and Distance Learning, 13, 147–164.
  • Jabbour, K. K. (2013). An analysis of the effect of mobile learning on Lebanese higher education. Bulgarian Journal of Science and Education Policy, 7, 280–381.
  • Kamran, K., & Kim, H. (2009). Factors affecting consumer resistance to innovation: A study of smartphones ( Unpublished master’s thesis). Sweden: Jönköping University.
  • Kang, M., Liew, B. Y. T., Lim, H., Jang, J., & Lee, S. (2015). Investigating the determinants of mobile learning acceptance in Korea using UTAUT2. In G. Chen, et al. (Eds.), Emerging issues in smart learning (pp. 209–216). New York, NY: Springer.
  • Kearney, M., Schuck, S., Burden, K., & Aubusson, P. (2012). Viewing mobile learning from a pedagogical perspective. Research in Learning Technology, 20(1063519), 1–17. doi:10.3402/rlt.v20i0/14406
  • Klopfer, E., & Squire, K. (2008). Environmental detectives: The development of an augmented reality platform for environmental simulations. Educational Technology Research & Development, 56, 203–228.10.1007/s11423-007-9037-6
  • Konkuk University Center for Teaching and Learning. (2013). 2013 Annual report of the Center for Teaching and Learning. Seoul: Konkuk University.
  • Korucu, A. T., & Alkan, A. (2011). Differences between m-learning (mobile learning) and e-learning, basic terminology and usage of m-learning in education. Procedia Social and Behavioural Sciences, 15, 1925–1930.10.1016/j.sbspro.2011.04.029
  • Lewin, K. (1997). Resolving social conflicts and field theory in social science. Washington, DC: American Psychological Association.10.1037/10269-000
  • Liu, T., Lin, Y., Tsai, M., & Paas, M. (2012). Split-attention redundancy effects on mobile learning in physical environments. Computers & Education, 58, 172–180.10.1016/j.compedu.2011.08.007
  • Mac Callum, K. (2014). Adoption theory and the integration of mobile technology in education. Retrieved from http://deanz.org.nz/dnzwp/wp-content/uploads/2009/08/MacCallum.pdf
  • Park, S. Y. (2009). An analysis of technology acceptance model in understanding university students’ behavioural intention to use e-learning. Educational Technology & Society, 12, 150–162.
  • Park, S. Y. (2010). SAS and educational statistics data processing and analysis. Seoul: Changjsa.
  • Park, S. Y., Nam, M., & Cha, S. (2012). University students’ behavioral intention to use mobile learning: Evaluating the technology acceptance model. British Journal of Educational Technology, 43, 592–605.10.1111/j.1467-8535.2011.01229.x
  • Park, Y. (2011). A pedagogical framework for mobile learning: Categorizing educational applications of mobile technologies into four types. The International Review of Research in Open and Distributed Learning, 12, 78–102.
  • Ram, S. (1987). A model of innovation resistance. Advances in Consumer Research, 14, 208–212.
  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.
  • Sarathy, P., Tadisetty, S., Saini, H. S., & Fukuda, A. (2012, July). Mobile learning system for improving efficiency of conventional education. 2012 International Conference on Education and e-Learning Innovations (ICEELI), Sousse, Tunisia.
  • Wang, M., Shen, M., Novak, D., & Pan, D. (2009). The impact of mobile learning on students’ learning behaviours and performance: Report from a large blended classroom. British Journal of Educational Technology, 40, 673–695.10.1111/bjet.2009.40.issue-4

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