KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Exploring the Determinants of MOOCs continuance intention

  • Jo, Donghyuk (School of Business Administration, Soongsil University)
  • Received : 2018.02.27
  • Accepted : 2018.07.02
  • Published : 2018.08.31
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Abstract

In our current information-based society in which knowledge is a fundamental asset to production, the capability to utilize information and produce knowledge with the use of information technology (IT) has become essential to learning. Massive Open Online Courses (MOOCs) have recently been introduced in light of such changes and are recognized as an alternative to open education. MOOCs' capabilities are being acknowledged in lifelong education in terms of reeducation and knowledge sharing, and also in terms of improving teaching quality, and improving university students' levels of creativity and integrated thinking by supporting high-level content and teaching. Therefore, this study presents an extended research model that combines information system (IS) continuance and task-technology fit models. Our study researches previous literature, revealing factors of continuous use after accepting MOOCs from the learner's perspective, and analyzes the model empirically. The ideal environment for MOOCs learners is evaluated, and a strategic approach to the successful settlement and diffusion of MOOCs is presented based on this study's findings.

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References

  1. M. J. Rosenberg, "Beyond e-learning. Approaches and Technologies to enhance Organizational Knowledge," Learning, and Performance. John Wiley & Sons, 2005.
  2. L. Yuan and S. Powell, "MOOCs and open education: Implications for higher education," 2013.
  3. J. Reich, "Rebooting MOOC research" Science, Vol 347, No. 6217, pp. 34-35, 2015. https://doi.org/10.1126/science.1261627
  4. C. Alario-Hoyos, M. Perez-Sanagustín, C. Delgado-Kloos, M. Munoz-Organero and A. Rodriguez-de-las-Heras, "Analysing the impact of built-in and external social tools in a MOOC on educational technologies," in Proc. of European Conference on Technology Enhanced Learning, pp. 5-18, 2013.
  5. A. Bhattacherjee, J. Perols and C. Sanford, "Information technology continuance: A theoretic extension and empirical test," Journal of Computer Information Systems, Vol 49, No. 1, pp. 17-26, 2008. https://doi.org/10.1080/08874417.2008.11645302
  6. A. Bhattacherjee, "Understanding information systems continuance: an expectation-confirmation model," MIS quarterly, Vol 25, No. 3, pp. 351-370, 2001. https://doi.org/10.2307/3250921
  7. A. Bhattacherjee and A. Barfar, "Information technology continuance research: current state and future directions," Asia Pacific Journal of Information Systems, Vol 21, No. 2, pp. 1-18, 2011. https://doi.org/10.1111/j.1365-2575.2010.00367.x
  8. D. L. Goodhue and R. L. Thompson, "Task-technology fit and individual performance," MIS quarterly, Vol 19, No. 2, pp. 213-236, 1995. https://doi.org/10.2307/249689
  9. I. M. Klopping and E. McKinney, "Extending the technology acceptance model and the task-technology fit model to consumer e-commerce," Information Technology, Learning, and Performance Journal, Vol 22, No. 1, pp. 35-48, 2004.
  10. T. J. McGill and J. E. Klobas, "A task-technology fit view of learning management system impact," Computers & Education, Vol 52, No. 2, pp. 496-508, 2009. https://doi.org/10.1016/j.compedu.2008.10.002
  11. T. Zhou, Y. Lu and B. Wang, "Integrating TTF and UTAUT to explain mobile banking user adoption," Computers in human behavior, Vol 26, No. 4, pp. 760-767, 2010. https://doi.org/10.1016/j.chb.2010.01.013
  12. H. H. Chang, "Task-technology fit and user acceptance of online auction," International Journal of Human-Computer Studies, Vol 68, No. 1, pp. 69-89, 2010. https://doi.org/10.1016/j.ijhcs.2009.09.010
  13. W. S. Lin and C. H. Wang, "Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit," Computers & Education, Vol 58, No.1, pp. 88-99, 2012. https://doi.org/10.1016/j.compedu.2011.07.008
  14. T. Oliveira, M. Faria, M. A. Thomas and A. Popovic, "Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM," International Journal of Information Management, Vol 34, No. 5, pp. 689-703, 2014. https://doi.org/10.1016/j.ijinfomgt.2014.06.004
  15. K. S. Hone and G. R. El Said, "Exploring the factors affecting MOOC retention: A survey study," Computers & Education, 98, 157-168, 2016. https://doi.org/10.1016/j.compedu.2016.03.016
  16. L. Huang, J. Zhang and Y. Liu, "Antecedents of student MOOC revisit intention: Moderation effect of course difficulty," International Journal of Information Management, 37(2), 84-91, 2017. https://doi.org/10.1016/j.ijinfomgt.2016.12.002
  17. J. Reich, "MOOC completion and retention in the context of student intent," EDUCAUSE Review Online, 2014.
  18. F. M. Hollands and D. Tirthali, "MOOCs: Expectations and Reality," Full report. Online Submission, 2014.
  19. A. Chiappe-Laverde, N. Hine and J. A. Martínez-Silva, "Literatura y práctica: una revisión crítica acerca de los MOOC," Comunicar, Vol 22, No. 44, pp.9-18 , 2015.
  20. R. Saadatdoost, A. T. H. Sim, H. Jafarkarimi and J. Mei Hee, "Exploring MOOC from education and Information Systems perspectives: a short literature review," Educational Review, Vol 67, No. 4, pp. 505-518, 2015. https://doi.org/10.1080/00131911.2015.1058748
  21. Y. Wang and R. Baker, "Content or platform: Why do students complete MOOCs?," Journal of Online Learning and Teaching, Vol 11, No. 1, 17-30, 2015.
  22. R. F. Kizilcec, M. Perez-Sanagustín and J. J. Maldonado, "Recommending self-regulated learning strategies does not improve performance in a MOOC," in Proc. of Proceedings of the Third (2016) ACM Conference on Learning@ Scale, ACM, pp. 101-104, 2016.
  23. K. Jordan, "Massive open online course completion rates revisited: Assessment, length and attrition," The International Review of Research in Open and Distributed Learning, Vol 16, No. 3, pp. 341-358, 2015.
  24. R. Meyer, "What it's like to teach a MOOC (and what the heck'sa MOOC?)," The Atlantic, 2012.
  25. M. T. Dishaw and D. M. Strong, "Supporting software maintenance with software engineering tools: A computed task-technology fit analysis," Journal of Systems and Software,Vol 44, No. 2, pp. 107-120, 1998. https://doi.org/10.1016/S0164-1212(98)10048-1
  26. R. M. Fuller and A. R. Dennis, "Does fit matter? The impact of task-technology fit and appropriation on team performance in repeated tasks," Information Systems Research,Vol 20, No. 1, pp. 2-17, 2009. https://doi.org/10.1287/isre.1070.0167
  27. K. Mathieson and M. Keil, "Beyond the interface: Ease of use and task/technology fit," Information & Management, Vol 34, No. 4, pp. 221-230, 1998. https://doi.org/10.1016/S0378-7206(98)00058-5
  28. P. C. Pendharkar, M. Khosrowpour and J. A. Rodger, "Development and testing of an instrument for measuring the user evaluations of information technology in health care," Journal of Computer Information Systems, Vol 41, No. 4, pp. 84-89, 2001.
  29. S. Jarupathirun and F. M. Zahedi, "Exploring the influence of perceptual factors in the success of web-based spatial DSS," Decision Support Systems, Vol 43, No. 3, pp. 933-951, 2007. https://doi.org/10.1016/j.dss.2005.05.024
  30. T. C. Lin and C. C. Huang, "Understanding knowledge management system usage antecedents: An integration of social cognitive theory and task technology fit," Information & Management, Vol 45, No. 6, pp. 410-417, 2008. https://doi.org/10.1016/j.im.2008.06.004
  31. T. J. Larsen, A. M. Sorebo and O. Sorebo, "The role of task-technology fit as users' motivation to continue information system use," Computers in Human Behavior, Vol 25, No. 3, pp. 778-784, 2009. https://doi.org/10.1016/j.chb.2009.02.006
  32. F. D. Davis, R. P. Bagozzi and P. R. Warshaw, "User acceptance of computer technology: a comparison of two theoretical models," Management science, Vol 35, No. 8, pp. 982-1003, 1989. https://doi.org/10.1287/mnsc.35.8.982
  33. R. L. Oliver, "A cognitive model of the antecedents and consequences of satisfaction decisions," Journal of marketing research, Vol 17, No. 4, pp. 460-469, 1980. https://doi.org/10.2307/3150499
  34. M. H. Hsu, C. M. Chiu and T. L. Ju, "Determinants of continued use of the WWW: an integration of two theoretical models," Industrial management & data systems, Vol 104, No. 9, pp. 766-775, 2004. https://doi.org/10.1108/02635570410567757
  35. C. S. Lin, S. Wu and R. J. Tsai, "Integrating perceived playfulness into expectation-confirmation model for web portal context," Information & management, Vol 42, No. 5, pp. 683-693, 2005. https://doi.org/10.1016/j.im.2004.04.003
  36. J. C. Roca, C. M. Chiu and F. J. Martinez, "Understanding e-learning continuance intention: An extension of the Technology Acceptance Model," International Journal of human-computer studies, Vol 64, No. 8, pp. 683-696, 2006. https://doi.org/10.1016/j.ijhcs.2006.01.003
  37. J. Y. Thong, S. J. Hong and K. Y. Tam, "The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance," International Journal of Human-Computer Studies, Vol 64, No. 9, pp. 799-810, 2006. https://doi.org/10.1016/j.ijhcs.2006.05.001
  38. M. Limayem and C. M. Cheung, "Understanding information systems continuance: The case of Internet-based learning technologies," Information & management, Vol 45, No. 4, pp. 227-232, 2008. https://doi.org/10.1016/j.im.2008.02.005
  39. B. Kim, "An empirical investigation of mobile data service continuance: Incorporating the theory of planned behavior into the expectation-confirmation model," Expert systems with applications, Vol 37, No. 10, pp. 7033-7039, 2010. https://doi.org/10.1016/j.eswa.2010.03.015
  40. C. H. Ho, "Continuance intention of e-learning platform: Toward an integrated model," International Journal of Electronic Business Management, Vol 8, No. 3, pp. 206-215, 2010.
  41. W. S. Lin, "Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives," International Journal of Human-Computer Studies, Vol 70, No. 7, pp. 498-507, 2012. https://doi.org/10.1016/j.ijhcs.2012.01.006
  42. M. C. Lee, "Explaining and predicting users' continuance intention toward e-learning: An extension of the expectation-confirmation model," Computers & Education, Vol. 54, No. 2, pp. 506-516, 2010. https://doi.org/10.1016/j.compedu.2009.09.002
  43. S. Petter, W. DeLone and E. R. McLean, "Information systems success: The quest for the independent variables," Journal of Management Information Systems, Vol. 29, No. 4, pp.7-62, 2013. https://doi.org/10.2753/MIS0742-1222290401

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