Factors Affecting University Instructors’ Continuance Intention to Use Learning Management Systems: The Blackboard System Case

Samar Mouakket, Anissa M. Bettayeb

Abstract

Although academic institutions have invested heavily in Learning Management Systems (LMS) to support e-learning platform, few studies have examined the factors affecting their usage, particularly by university instructors. To fill this research gap, this study proposes a framework based on the expectation-confirmation model (ECM) to examine the influence of several critical independent factors related to organizational, technological and individual characteristics on university instructors’ perceived usefulness of Blackboard system as one well-known LMS, which in turn will affect their continuance intention to use this technology. Data was gathered from 158 university instructors at a university in the United Arab Emirates (UAE). Structural equation modeling technique was used to validate the causal relationships between the different variables.

References

  1. Agarwal, R., Sambamurthy, V., Stair, R. M., 2000. Research report: The evolving relationship between general and specific computer self-efficacy-An empirical assessment, Information Systems Research, Vol. 11, No. 4, pp. 418-430.
  2. Al-Busaidi, K. L., Al-Shihi, H., 2012. Key factors to instructors' satisfaction of learning management systems in blended learning, Journal of Computing in Higher Education, Vol. 24, No. 1, pp. 18-39.
  3. Amoroso, D. L., Cheney, P. H., 1991. Testing a causal model of end-user application effectiveness, Journal of Management Information Systems, Vol. 8, No. 1, pp. 63-90.
  4. Anderson, J. C., Gerbing, D. W., 1988. Structural equation modeling in practice: A review and recommended two-step approach, Psychological Bulletin, Vol. 103, No. 3, pp. 411-423.
  5. Ball, D. M., Levy, Y., 2008. Emerging Educational Technology: Assessing the Factors that Influence Instructors' Acceptance in Information Systems and Other Classroom, Journal of Information Systems Education, Vol. 9, No. 4, pp. 431-444.
  6. Bentler, P. M., Bonett, D. G., 1980. Significance tests and goodness of fit in the analysis of covariance structure, Psychological Bulletin, Vol. 88, No. 3, pp. 588-606.
  7. Bhattacherjee, A., 2001. Understanding information systems continuance: An expectation-confirmation model, MIS Quarterly, Vol. 25, No. 3, pp. 351-370.
  8. Bhattacherjee, A., Hikmet, N., 2008. Reconceptualizing organizational support and its effect on information technology usage: evidence from the health care sector, Journal of Computer Information Systems, Vol. 48, 4, pp. 69-76.
  9. Bradford, M., Florin, J., 2003. Examining the role of innovation diffusion factors on the implementation success of enterprise resource planning systems, International Journal of Accounting Information Systems, Vol. 4, No. 3, pp. 205-225.
  10. Caputi, V., Garrido, A., 2015. Student-oriented planning of e-learning contents for Moodle, Journal of Network and Computer Applications, Vol. 53, pp. 115-127.
  11. Chang, C-C., 2013. Exploring the determinants of elearning systems continuance intention in academic libraries, Library Management, Vol. 34, No. 1/2, pp. 40-55.
  12. Chatzoglou, P. D., Sarigiannidis, L., Vraimaki, E., Diamantidis, A., 2009. Investigating Greek employees' intention to use web-based training, Computers & Education, Vol. 53, No. 3, pp. 877-889.
  13. Chen, Y-C, 2014. An empirical examination of factors affecting college students' proactive stickiness with a web-based English learning environment, Computers in Human Behavior, Vol. 31, pp. 159-171.
  14. Cheng, Y-M, 2014. Roles of interactivity and usage experience in e-learning acceptance: a longitudinal study, International Journal of Web Information Systems, Vol. 10, No. 1 pp. 2 - 23.
  15. Chiu, C. M., Hsu, M. H., Sun, S. Y., Lin, T. C., Sun, P. C., 2005. Usability, quality, value and e-learning continuance decisions, Computers & Education, Vol. 45, No. 4, pp. 399-416.
  16. Chiu, C-M., Wang, E. T. G., 2008. Understanding Webbased learning continuance intention: The role of subjective task value, Information & Management, Vol. 45, No. 3, pp. 194-201.
  17. Cho, V., Cheng, T.C. E., Lai, M.W. J., 2009. The role of perceived user-interface design in continued usage intention of self-paced e-learning tool, Computers & Education, Vol. 53, No. 2, pp. 216-227.
  18. Compeau, D. R., Higgins, C. A., 1995. Computer SelfEfficacy: Development of a Measure and Initial Test, MIS Quarterly, Vol. 19, No. 2, pp. 189-211.
  19. Cyr, D., Head, M., Ivanov, A., 2006. Design aesthetics leading to m-loyalty in mobile commerce, Information & Management, Vol. 43, No. 8, pp. 950-963.
  20. Davis, F. D., 1989. Perceived usefulness, perceived ease of use and user acceptance of information technology, MIS Quarterly, Vol. 13, No. 3, pp. 319-340.
  21. Fornell, C., Larcker, D. 1981. Structural equation models with unobservable variables and measurement error, Journal of Marketing Research, Vol. 18, No. 1, pp. 39-50.
  22. Hair, J. F., Anderson, R. E., Tatham, R. L. and Black, W. C. (1998), Multivariate data analysis with readings (5th ed.), New York, NY: Macmillan.
  23. Hair, J., Black, W., Babin, B., Anderson, R., Tatham, R. L., 2006. Multivariate Data Analysis, Pearson Education: Harlow, 6th edition.
  24. Hoehle, H., Sid Huff, S., Goode, S., 2011. The role of continuous trust in information systems continuance, Journal of Computer Information Systems, Vol. 52, No. 4, pp. 1-9.
  25. Hong, J-Ch, Hwang, M-Y, Hsu, H-F, Wong, W-T, Chen, W-Y, 2011. Applying the technology acceptance model in a study of the factors affecting usage of the Taiwan digital archives system, Computers & Education, Vol. 57, No. 3, pp. 2086-2094.
  26. Igbaria, M., Guimaraes, T., Davis, G., Zinatelli, N., Cragg, P., Cavaye, L. M., 1997. Computing acceptance factors in small firms: A structural equation model, MIS Quarterly, Vol. 21, No. 3, pp. 279-305.
  27. Jeong, H., 2011. An investigation of user perceptions and behavioral intention towards the e-library, Library Collections, Acquisitions, & Technical Services, Vol. 35, No. 2, pp. 45-60.
  28. Kim, B., 2010. 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.
  29. Lareki, A., Martínez de Morentin, J. I., Amenabar, N., 2010. Towards an efficient training of university faculty on ICTs”, Computers & Education, Vol. 54, No. 2, pp. 491-497.
  30. Lee, H., Choi, S. Y., Kang, Y. S., 2009. Formation of esatisfaction and repurchase intention: Moderating roles of computer self-efficacy and computer anxiety, Expert Systems with Applications, Vol. 36, No. 4, pp. 7848-7859.
  31. Lee, M-C, 2010. 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.
  32. Liaw, S-S, 2008. Investigating students' perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system, Computers & Education, Vol. 51, pp. 864-873.
  33. Liaw, S-S, Huang, H-M., 2013. Perceived satisfaction, perceived usefulness and interactive learning environments as predictors to self-regulation in elearning environments, Computers & Education, Vol. 60, pp. 14-24.
  34. Limayem, M., Hirt, S.G., Cheung, C.M.K., 2007. How habit limits the predictive power of intention: The case of information systems continuance, MIS Quarterly, Vol. 31, No. 4, pp. 705-737.
  35. Limayem, M., Cheung, C.M.K., 2008. Understanding information systems continuance: The case of Internetbased learning technologies”, Information & Management, Vol. 45, pp. 227-232.
  36. Lin, C.S., Wu, S., Tsai, R.J., 2005. Integrating perceived playfulness into expectation-confirmation model for web portal context, Information & Management, Vol. 42, No. 5, pp. 683-693.
  37. Liu, I-F, Chen, M. C., Sun, Y. S., Wible, D., Kuo, C-H, 2010. Extending the TAM model to explore the factors that affect Intention to use an online learning community, Computers & Education, Vol. 54, pp. 600-610.
  38. Ngai, E.W.T., Poon, J.K.L., Chan, Y.H.C., 2007. Empirical examination of the adoption of WebCT using TAM, Computers & Education, Vol. 48, No. 2, pp. 250-267.
  39. Nelson, R. R., Cheney, P., 1987. Training End Users: An Exploratory Study, MIS Quarterly, Vol. 11, No. 4, pp. 547-559.
  40. Nunnally, J. C., Bernstein, I. H., 1994. Psychometric theory, McGraw-Hill, New York, 3rd edition.
  41. Paechter, M., Maier, B., Macher, D., 2010. Students' expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction, Computers & Education, Vol. 54, No. 1, pp. 222-229.
  42. Randeree, K., Narwani, A., 2009. Managing Change in Higher Education: An Exploration of the Role of Training in ICT Enabled Institutions in the United Arab Emirates, The International Journal of Learning, Vol. 16, No. 4, pp. 447-456.
  43. Sørebø, A. M., Sørebø, Ø., 2009. Understanding elearning satisfaction in the context of university teachers”, International Journal of Humanities and Social Sciences, Vol. 3, No. 4, pp. 309-312.
  44. Sumner, M., Hostetler, D., 1999. Factors influence the adoption of technology in teaching, Journal of Computer Information Systems, Vol. 40, No. 1, pp. 81-87.
  45. Sun, P-C, Tsai, R. J., Finger, G., Chen, Y-Y, Yeh, D., 2008. What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction, Computers & Education, Vol. 50, No. 4, pp. 1183-1202.
  46. Sawang, S., Newton, C., Jamieson, K. 2013. Increasing learners' satisfaction/intention to adopt more elearning, Education + Training, Vol. 55, No. 1, pp. 83 - 105.
  47. Tarhini, A., Honea, K., Liua, X., 2013. User acceptance towards web-based learning systems: investigating the role of social, organizational and individual factors in European higher education, Procedia Computer Science, Vol. 17, pp. 189 - 197.
  48. Tong, K.P., Triniada, S.G., 2005. Conditions and constraints of sustainable innovative pedagogical practices using technology, Journal of International Electronic for leadership in learning, Vol. 9, No. 3, pp. 1-27.
  49. Williams, P., 2002. The learning Web: the development, implementation and evaluation of Internet-based undergraduate materials for the teaching of key skills, Active Learning in Higher Education, Vol. 3, No. 1, pp. 40-53.
  50. Yi, M. Y., Hwang, Y, 2003. Predicting the use of webbased information systems: self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model, International Journal of HumanComputer Studies, Vol. 59, No. 4, pp. 431-449.
  51. Yoon, C., Kim, S., 2007. Convenience and TAM in a ubiquitous computing environment: The case of wireless LAN, Electronic Commerce Research and Applications, Vol. 6, No. 1, pp. 102-112.
Download


Paper Citation


in Harvard Style

Mouakket S. and Bettayeb A. (2016). Factors Affecting University Instructors’ Continuance Intention to Use Learning Management Systems: The Blackboard System Case . In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-187-8, pages 215-222. DOI: 10.5220/0005748102150222


in Bibtex Style

@conference{iceis16,
author={Samar Mouakket and Anissa M. Bettayeb},
title={Factors Affecting University Instructors’ Continuance Intention to Use Learning Management Systems: The Blackboard System Case},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2016},
pages={215-222},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005748102150222},
isbn={978-989-758-187-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Factors Affecting University Instructors’ Continuance Intention to Use Learning Management Systems: The Blackboard System Case
SN - 978-989-758-187-8
AU - Mouakket S.
AU - Bettayeb A.
PY - 2016
SP - 215
EP - 222
DO - 10.5220/0005748102150222