Browse > Article
http://dx.doi.org/10.5392/IJoC.2016.12.3.047

Korean Students' Intentions to Use Mobile-Assisted Language Learning: Applying the Technology Acceptance Model  

Kim, Gyoo-mi (Liberal Education Semyung University)
Lee, Sang-jun (Information & Communication System Semyung University)
Publication Information
International Journal of Contents / v.12, no.3, 2016 , pp. 47-53 More about this Journal
Abstract
The purpose of this study was to examine how Korean students accept and use mobile-assisted language learning (MALL) and investigate related factors that potentially affect MALL usage. The participants were 244 undergraduate students who were surveyed with a questionnaire. The research model, which included students' self-efficacy, content reliability, interactivity, perceived enjoyment, perceived usefulness, perceived ease of use, attitude, and behavioral intention to use MALL, was developed based on the technology acceptance model (TAM). The structural equation modeling (SEM) technique was employed in order to analyze the overall results of modified TAM and the research model. The results indicated that TAM was a good theoretical tool to understand students' acceptance of MALL. In addition, all constructs, with the exception of self-efficacy and interactivity, had significant effects on students' acceptance possibilities of MALL. Limitations and suggestions for the further study are also presented.
Keywords
Mobile-Assisted Language Learning; English Education; Technology Acceptance Model; Structural Equation Modeling;
Citations & Related Records
연도 인용수 순위
  • Reference
1 J. Wang, "Perceptions of Mobile-Assisted E-Cooperative Learning Quality," Asian Journal of Social Sciences & Humanities, vol. 2, no. 3, 2013, pp. 1-10.
2 B. K. Jung, Investigating the Structural Relationship among Factors Affecting Cyber University Students' Mobile Learning Continuance Intention, MA thesis, Ewha Womans University, 2014.
3 S. Y. Park, "An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use E-learning," Educational Technology & Society, vol. 12, no. 3, 2009, pp. 150-162.
4 A. Kukulska-Hulme, "Will Mobile Learning Change Language Learning?," ReCALL, vol. 21, no. 2, 2009, pp. 157-195.   DOI
5 H. Beetham and R. Sharpe (eds), Rethinking Pedagogy for a Digital Age: Designing for 21st Century Leanring (2nd Ed), Routledge, New York, 2013.
6 F. D. Davis, "Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology," MIS Quarterly, vol. 13, no. 3, 1989, pp. 319-340.   DOI
7 D. Kim, D. Rueckert, D. J. Kim, and D. Seo, "Students' Perceptions and Experiences of Mobile Learning," LLT Journal, vol. 17, no. 3, 2013, pp. 52-73.
8 L. Naismith and D. Corlett, "Reflection on Success: A Retrospective of the mLearn Conference Series 2002-2005," Proc. mLearn 2006 Conference, 2006, p. hal-00197366.
9 H. Beetham and R. Sharpe (eds.), Rethinking Pedagogy for a Digital Age: Designing and Delivering E-learning, Routledge, New York, 2013.
10 M K. O, C. M. Lee, K. Cheung, and Z. Chen, "Acceptance of Internet-based Learning Medium: The Role of Extrinsic and Intrinsic Motivation," Information & Management, vol. 42, 2005, pp. 1095-1104.   DOI
11 S. Liu, H. Lia, and C, Peng, "Applying the Technology Acceptance Model and Flow Theory to Online e-Learning Users' Acceptance Behavior," Issues in Information Systems, vol. 6, no. 2, 2005, pp. 175-181.
12 S. Y. Park and M. W. Nam, "An Analysis of Structural Equation Model in Understanding University Students' Behavioral Intention to Use Mobile Learning based on Technology Acceptance Model," The Journal of Educational Information and Media, vol. 18, no. 1, 2012, pp. 51-75.
13 J. Kang, "A Study on Elementary School Students Acceptance of English Digital Textbooks Using Technology Acceptance Model," Multimedia-Assisted Language Learning, vol. 16, no. 1, 2013, pp. 11-36.
14 R. P. Bagozzi and Y. Yi, "On the Evaluation of Structural Equation Models," Journal of the Academy of Marketing Science, vol. 16, no. 1, 1988, pp. 74-94.   DOI
15 J. F. Hair, R. E. Anderson, R. L. Tatham, and W. C. Black, Multivariate Data Analysis, Prentice Hall International, New York, 1998.
16 H. S. Lee and J. H. Lim, Structural Equation Modeling with AMOS 16.0, Bobmunsa, Seoul, 2009.
17 J. C. Anderson and D. W. Gerbing, "Structural Equation Modeling in Practice: A Review and Recommended Two-step Approach," Psychological Bulletin, vol. 103, no. 3, 1988, pp. 411-423.   DOI
18 C. Fornell and D. F. Larcker, "Evaluating Structural Equation Models with Unobservable Variables and Measurement Error," Journal of Marketing Research, vol. 18, no. 1, 1981, pp. 39-50.   DOI
19 A. Kukulska-Hulme and L. Shield, "An Overview of Mobile-Assisted Language Learning: Can Mobile Devices Support Collaborative Practice in Speaking and Listening?," ReCALL Journal, vol. 20, no. 3, 2008, pp. 271-289.   DOI
20 J. Burston, "Mobile-Assisted Language Learning: A Selected Annotated Bibliography of Implementation Studies 1994-2012," LLT Journal, vol. 17, no. 3, 2013, pp. 157-225.
21 K. M. O, "The effectiveness of Mobile-Assisted Language Learning on L2 Listening Comprehension," Multimedia-Assisted Language Learning, vol. 18, no. 2, 2015, pp. 135-158.
22 T. Lee, "Pleasurable Cities: A Discussion Paper," Proc. Future Lab, 2006. Accessed Jul. 10 2016 from http://nfer.kohaptfs.eu/documents/open/Pleasurable%20Cities%20discussi on%20paper.pdf
23 S. A. Petersen and M. Divitini, "Language Learning: From Individual Learner to Communities," Proc. IEEE International Workshop, 2005, pp. 169-173.
24 P. Thornton and C. Houser, "Using Mobile Phones in English Education in Japan," Journal of Computer Assisted Learning, vol. 21, no. 3, 2005, pp. 217-228.   DOI
25 G. Kismihók and R. V. Corvinus, "Empirical research on Learners' thought about the impact of Mobile Technology on Learning," International Journal of Mobile and Blended Learning, vol. 3, no. 1, 2011, pp. 73-88.   DOI