Intention to use versus actual adoption of technology by university English language learners: what perceptions and factors matter?

References

• Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckman (Eds.), Action-control: From cognition to behavior (pp. 3–15). Hilladale, NJ: Erlbaum.
   Google Scholar
• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. doi:10.1016/0749-5978(91)90020-T
   Web of Science ®Google Scholar
• Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918. doi:10.1037/0033-2909.84.5.888
   Web of Science ®Google Scholar
• Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood-Cliffs, NJ: Prentice-Hall.
   Google Scholar
• Benson, P. (2011). Teaching and researching autonomy. Harlow, New York: Longman Pearson.
   Google Scholar
• Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. doi:10.1037/0033-2909.107.2.238
   PubMed Web of Science ®Google Scholar
• Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage.
   Google Scholar
• Celik, V., & Yesilyurt, E. (2013). Attitudes to technology, perceived computer self-efficacy and computer anxiety as predictors of computer supported education. Computers & Education, 60(1), 148–158. doi:10.1016/j.compedu.2012.06.008
   Web of Science ®Google Scholar
• Chan, W. S. C. (2010). Students’ understanding of generic skills development in a university in Hong Kong. Procedia - Social and Behavioral Sciences, 2(2), 4815–4819. doi:10.1016/j.sbspro.2010.03.776
   Google Scholar
• Cheng, A., & Lee, C. (2018). Factors affecting tertiary English learners’ persistence in the self-directed language learning journey. System, 76, 170–182. doi:10.1016/j.system.2018.06.001
   Web of Science ®Google Scholar
• Cheng, C.-H., & Chen, C.-H. (2019). Investigating the impacts of using a mobile interactive English learning system on the learning achievements and learning perceptions of student with different backgrounds. Computer Assisted Language Learning. doi:10.1080/09588221.2019.1671460
   Web of Science ®Google Scholar
• Cheung, R., & Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Computers & Education, 63, 160–175. doi:10.1016/j.compedu.2012.12.003
   Web of Science ®Google Scholar
• Chu, S. K. W., Capio, C. M., van Aalst, J., & Cheng, E. W. L. (2017). Evaluating the use of a social media tool for collaborative group writing of secondary school students in Hong Kong. Computers and Education, 110, 17–180.
   Web of Science ®Google Scholar
• Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. doi:10.1007/BF02310555
   Web of Science ®Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. doi:10.2307/249008
   Web of Science ®Google Scholar
• Falloon, G. (2015). What’s the difference? Learning collaboratively using iPads in conventional classrooms. Computers & Education, 84, 62–77. doi:10.1016/j.compedu.2015.01.010
   Web of Science ®Google Scholar
• Golonka, E. M., Bowles, A. R., Frank, V. M., Richardson, D. L., & Freynik, S. (2014). Technologies for foreign language learning: A review of technology types and their effectiveness. Computer Assisted Language Learning, 27(1), 70–105. doi:10.1080/09588221.2012.700315
   Web of Science ®Google Scholar
• Hong Kong Census and Statistics Department (2016). Thematic Household Survey Report 59. Hong Kong: Hong Kong Special Administrative Region.
   Google Scholar
• Heijden, H. (2003). Factors influencing the usage of website: The case of a generic portal in The Netherlands. Information & Management, 40, 541–549.
   Web of Science ®Google Scholar
• Hsu, S.-Y. (2005). Building language-learning environments to help technological university students develop English independent learning. The JALT CALL Journal, 1(2), 51–66. doi:10.29140/jaltcall.v1n2.r10
   Google Scholar
• Huang, F., Teo, T., & Zhou, M. (2020). Chinese students’ intentions to use the Internet-based technology for learning. Educational Technology Research and Development, 68(1), 575–591. doi:10.1007/s11423-019-09695-y
   Web of Science ®Google Scholar
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. [Database] doi:10.1080/10705519909540118
   Web of Science ®Google Scholar
• Ifinedo, P. (2017). Examining students’ intention to continue using blogs for learning: Perspectives from technology acceptance, motivational, and social-cognitive frameworks. Computers in Human Behavior, 72, 189–199. doi:10.1016/j.chb.2016.12.049
   Web of Science ®Google Scholar
• Joo, Y. J., Lim, K. Y., & Lim, E. (2014). Investigating the structural relationship among perceived innovation attributes, intention to use and actual use of mobile learning in an online university in South Korea. Australasian Journal of Educational Technology, 30(4), 427–439. doi:10.14742/ajet.681
   Web of Science ®Google Scholar
• Joo, Y. J., Park, S., & Lim, E. (2018). Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self-efficacy, and technology acceptance model. Educational Technology & Society, 21(3), 48–59.
   Web of Science ®Google Scholar
• Kasemsap, K. (2017). Flipped classroom: Advanced issues and applications. In T. Kidd & L.R. Morris Jr. (Eds.), Handbook of research on instructional systems and educational technology (pp. 141–152). Hershey PA: Information Science Reference.
   Google Scholar
• Kirkwood, A., & Price, L. (2005). Learners and learning in the twenty-first century: What do we know about students’ attitudes towards and experiences of information and communication technologies that will us design courses? Studies in Higher Education, 30(3), 257–274. doi:10.1080/03075070500095689
   Web of Science ®Google Scholar
• Lai, C. (2015). Modelling teachers’ influence on learners’ self-directed use of technology for language learning outside the classroom. Computers & Education, 82, 74–83. doi:10.1016/j.compedu.2014.11.005
   Web of Science ®Google Scholar
• Lai, C., Li, X.-S., & Wang, Q. (2017). Students’ perceptions of teacher impact on their self-directed language learning with technology beyond the classroom: Cases of Hong Kong and Educational Technology Research and Development, 65(4), 1105–1133. doi:10.1007/s11423-017-9523-4
   Web of Science ®Google Scholar
• Lai, C., Wang, Q., & Lei, J. (2012). What factors predict undergraduate students’ use of technology for learning? A case from Hong Kong. Computers & Education, 59(2), 569–579. doi:10.1016/j.compedu.2012.03.006
   Web of Science ®Google Scholar
• Lee, L. (2016). Autonomous learning through task-based instruction in fully online language courses. Language Learning & Technology, 20(2), 81–97.
   Web of Science ®Google Scholar
• Lee, C., Yeung, A. S., & Cheung, K. W. (2019). Learner perceptions versus technology usage: A study of adolescent English learners in Hong Kong secondary schools. Computers & Education, 133, 13–26.
   Web of Science ®Google Scholar
• Lee, D. Y., & Lehto, M. R. (2013). User acceptance of Youtube for procedural learning. An extension of the TAM. Computers & Education, 61, 193–208. doi:10.1016/j.compedu.2012.10.001
   Web of Science ®Google Scholar
• Mac Callum, K., & Kinshuk, L. J. (2014). Factors impacting teachers’ adoption of mobile learning. Journal of Information Technology Education: Research, 13, 141–162. doi:10.28945/1970
   Google Scholar
• Martin, F., & Ertzberger, J. (2013). Here and now mobile learning: An experimental study on the use of mobile technology. Computers & Education, 68, 76– 85.
   Web of Science ®Google Scholar
• Muthén, L., & Muthén, B. (2015). Mplus. The comprehensive modelling program for applied researchers: User’s guide, 5.
   Google Scholar
• Park, S. Y., Nam, M.-W., & Cha, S.-B. (2012). University students’ behavioural intention to use mobile learning: Evaluating the technology acceptance model. British Journal of Educational Technology, 43(4), 592–605. doi:10.1111/j.1467-8535.2011.01229.x
   Web of Science ®Google Scholar
• Pena, M. I., & Yeung, A. S. (2009). University students’ satisfaction with online and face-to-face Spanish learning. International Journal of Learning, 16, 637–648.
   Google Scholar
• Peng, T.-Q., Zhu, J. J. H., Tong, J.-J., & Jiang, S.-J. (2012). Predicting Internet non-users’ adoption intention and adoption behavior. Information, Communication & Society, 15(8), 1236–1257.
   Web of Science ®Google Scholar
• Rahimi, M., & Yadollahi, S. (2011). Computer anxiety and ICT integration in English classes among EFL teachers. Procedia Computer Science, 3, 203–209. doi:10.1016/j.procs.2010.12.034
   Google Scholar
• Schumacker, R. E., & Lomax, R. G. (1996). A beginner's guide to structural equation modeling. Mahwah, NJ: L. L. Erlbaum Associates.
   Google Scholar
• Staddon, R. V. (2020). Bring technology to the mature classroom: Age differences in age and attitudes. International Journal of Educational Technology in Higher Education, 17(1), 1–20. doi:10.1186/s41239-020-00184-4
   Web of Science ®Google Scholar
• Taguchi, N., & Skyes, J. M. (2013). Technology in interlanguage pragmatics research and teaching. Amsterdam, Philadelphia: John Benjamins Publishing Company.
   Google Scholar
• Teo, T., & Zhou, M-m. (2014). Explaining the intention to use technology among university students: A structural equation modelling approach. Journal of Computing in Higher Education, 26(2), 124–142. doi:10.1007/s12528-014-9080-3
   Web of Science ®Google Scholar
• Teo, T., Zhou, M., Chun, A. W. F., & Huang, F. (2019). Factors that influence university students’ intention to use Moodle: A study in Macau. Educational Technology Research and Development, 67(3), 749–766. doi:10.1007/s11423-019-09650-x
   Web of Science ®Google Scholar
• Thang, S. M., Lee, Y. S., & Zulkifli, N. F. (2012). The role of the electronic portfolio in enhancing Information and Communication Technology and English language skills: The voices of six Malaysian undergraduates. Computer Assisted Language Learning, 25(3), 277–293. doi:10.1080/09588221.2012.655299
   Web of Science ®Google Scholar
• Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1–10. doi:10.1007/BF02291170
   Web of Science ®Google Scholar
• Un Jan, A., & Contreras, V. (2011). Technology acceptance model for the use of information technology in universities. Computers in Human Behavior, 27(2), 845–851. doi:10.1016/j.chb.2010.11.009
   Web of Science ®Google Scholar
• Valentin, A., Mateos, P. M., Gonzalez-Tablas, M. M., Perez, L., Lopez, E., & Garcia, I. (2013). Motivation and learning strategies in the use of ICTs among university students. Computers and Education, 61, 52–58.
   Google Scholar
• Venkatesh, V., & Davis, F. (2000). 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
   Web of Science ®Google Scholar
• Verhoeven, J.C., Heerwegh, D., & De Wit, K. D. (2010). Information and communication technologies in the life of university freshmen: An analysis of change. Computers & Education, 55, 53–66.
   Web of Science ®Google Scholar
• Webb, M., & Doman, E. (2020). Impacts of flipped classrooms on learner attitudes towards technology-enhanced language learning. Computer Assisted Language Learning, 33(3), 240–274. doi:10.1080/09588221.2018.1557692
   Web of Science ®Google Scholar
• Yang, F.-Y., & Tsai, C.-C. (2008). Investigating university student preferences and beliefs about learning in the web-based context. Computers & Education, 50, 1284–1303.
   Web of Science ®Google Scholar
• Zou, B., Smith, S., & Hoey, M. (Eds.). (2015). Corpus linguistics in Chinese contexts. Houndsmill, Basingstoke, Hampshire, New York: Palgrave Macmillan.
   Google Scholar