Résumés
Abstract
Although online learning has become ubiquitous worldwide, earlier research has neglected the relationship between its actual use and security concerns. Learners’ lack of security awareness while using learning technologies remains rarely studied. This paper integrates Delone and McLean’s information system success (D&M-ISS) model with the security triangle framework. Data from 2,451 higher education students at different universities and a wide variety of disciplines in Iraq were collected. In addition to the effectiveness of the D&M-ISS factors, the research findings based on the structural equation model suggest that the three constructs of the security triangle framework—namely, confidentiality, integrity, and availability—were significant predictors of students’ use of online learning. This research can thus help academic organizations understand factors that can lead to the successful implementation of online learning and learners’ security awareness.
Keywords:
- online learning,
- Delone and McLean's information system success model,
- security triangle framework,
- higher education
Parties annexes
Bibliography
- Ab Hamid, M. R., Sami, W., & Mohmad Sidek, M. H. (2017). Discriminant validity assessment: Use of Fornell & Larcker criterion versus HTMT criterion. Journal of Physics: Conference Series, 890(1), Article 012163. https://doi.org/10.1088/1742-6596/890/1/012163
- Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Prentice Hall.
- Al-Adwan, A. S., Albelbisi, N. A., Hujran, O., Al-Rahmi, W. M., & Alkhalifah, A. (2021). Developing a holistic success model for sustainable e-learning: A structural equation modeling approach. Sustainability, 13(16), Article 9453. https://doi.org/10.3390/su13169453
- Al-Adwan, A. S., Nofal, M., Akram, H., Albelbisi, N. A., & Al-Okaily, M. (2022). Towards a sustainable adoption of e-learning systems: The role of self-directed learning. Journal of Information Technology Education: Research, 21, 245–267. https://doi.org/10.28945/4980
- Al-Azawei, A. (2019). What drives successful social media in education and e-learning? A comparative study on Facebook and Moodle. Journal of Information Technology Education: Research, 18, 253–274. https://doi.org/10.28945/4360
- Al-Azawei, A., & Al-Azawi, R. (2021). Evaluating Facebook success in Iraq: An extension of the DeLone and McLean’s model of information systems success (ISS). Journal of Physics: Conference Series, 1804, Article 012114. https://doi.org/10.1088/1742-6596/1804/1/012114
- Al-Azawei, A., & Lundqvist, K. (2015). Learner differences in perceived satisfaction of an online learning: An extension to the technology acceptance model in an Arabic sample. Electronic Journal of E-Learning, 13(5), 408–426. https://academic-publishing.org/index.php/ejel/article/view/1942
- Al-Azawei, A., Parslow, P., & Lundqvist, K. (2016). Barriers and opportunities of e-learning implementation in Iraq: A case of public universities. The International Review of Research in Open and Distance Learning, 17(5), 126–146. https://doi.org/10.19173/irrodl.v17i5.2501
- Al-shargabi, B., Sabri, O., & Aljawarneh, S. (2021). The adoption of an e-learning system using information systems success model: A case study of Jazan University. PeerJ Computer Science, 7, Article e723. https://doi.org/10.7717/peerj-cs.723
- Alowayr, A., & Al-Azawei, A. (2021). Predicting mobile learning acceptance: An integrated model and empirical study based on the perceptions of higher education students. Australasian Journal of Educational Technology, 37(3), 38–55. https://doi.org/10.14742/ajet.6154
- Alshurideh, M., Al Kurdi, B., & Salloum, S. A. (2020). Examining the main mobile learning system drivers’ effects: A mix empirical examination of both the expectation-confirmation model (ECM) and the technology acceptance model (TAM). Advances in Intelligent Systems and Computing, 1058, 406–417.https://doi.org/10.1007/978-3-030-31129-2_37
- Ameen, N., Tarhini, A., Shah, M. H., & Madichie, N. (2020). Employees’ behavioural intention to smartphone security: A gender-based, cross-national study. Computers in Human Behavior, 104, Article 106184. https://doi.org/10.1016/j.chb.2019.106184
- Awad, R., Aljaafreh, A., & Salameh, A. (2022). Factors affecting students’ continued usage intention of e-learning during COVID-19 pandemic: Extending Delone & Mclean IS success model. International Journal of Emerging Technologies in Learning, 17(10), 120–144. https://doi.org/10.3991/ijet.v17i10.30545
- Çelik, K., & Ayaz, A. (2022). Validation of the Delone and McLean information systems success model: A study on student information system. Education and Information Technologies, 27(4), 4709–4727. https://doi.org/10.1007/s10639-021-10798-4
- Chaeikar, S., Jafari, M., Taherdoost, H., & Chaei Kar, N. S. (2012). Definitions and criteria of CIA security triangle in electronic voting system. International Journal of Advanced Computer Science and Information Technology, 1(1), 14–23. https://ssrn.com/abstract=2372782
- Cidral, W., Aparicio, M., & Oliveira, T. (2020). Students’ long-term orientation role in e-learning success: A Brazilian study. Heliyon, 6, Article e05735. https://doi.org/10.1016/j.heliyon.2020.e05735
- Davis, F. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and results [PhD Dissertation, Massachusetts Institute of Technology]. http://hdl.handle.net/1721.1/15192
- Delone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95. https://doi.org/10.1287/isre.3.1.60
- Delone, W. H., & McLean, E. R. (2003). The Delone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748
- Dong, T. P., Cheng, N. C., & Wu, Y. C. J. (2014). A study of the social networking Website service in digital content industries: The Facebook case in Taiwan. Computers in Human Behavior, 30, 708–714. https://doi.org/10.1016/j.chb.2013.07.037
- El-Khatib, K., Korba, L., Xu, Y., & Yee, G. (2003). Privacy and security in e-learning. International Journal of Distance Education Technologies (IJDET), 1(4), Article 1. https://doi.org/10.4018/jdet.2003100101
- Farooq, A., Ahmad, F., Khadam, N., Lorenz, B., & Isoaho, J. (2020). The impact of perceived security on intention to use e-learning among students. In Proceedings—2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT) (pp. 360–364). IEEE Computer Society/Conference Publishing Services. https://doi.org/10.1109/ICALT49669.2020.00115
- Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
- Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Pearson Prentice Hall.
- Harefa, E. B. (2020). Usability measurement of Google Classroom applications as elearning for students of department of building engineering education IKIP Gunungsitoli. Indonesian Science Education Research, 2(1), 11–14. https://jurnal.unimed.ac.id/2012/index.php/iser/article/view/20170/14273
- Hartono, E., Kim, K.-Y., Na, K.-S., Simpson, J. T., & Berkowitz, D. (2013). Perceived site security as a second order construct and its relationship to e-commerce site usage. In Á. Rocha, A. Correia, T. Wilson, & K. Stroetmann (Eds.), Advances in information systems and technologies (pp. 1075–1085). Springer. https://doi.org/10.1007/978-3-642-36981-0_102
- Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135. https://doi.org/10.1007/s11747-014-0403-8
- Isaac, O., Aldholay, A., Abdullah, Z., & Ramayah, T. (2019). Online learning usage within Yemeni higher education: The role of compatibility and task-technology fit as mediating variables in the IS success model. Computers and Education, 136, 113–129. https://doi.org/10.1016/j.compedu.2019.02.012
- Lowry, P. B., & Gaskin, J. (2014). Partial least squares (PLS) structural equation modeling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE Transactions on Professional Communication, 57(2), 123–146. https://doi.org/10.1109/TPC.2014.2312452
- Maqableh, M., Hmoud, H. Y., & Jaradat, M. (2021). Integrating an information systems success model with perceived privacy, perceived security, and trust: The moderating role of Facebook addiction. Heliyon, 7(9), Article E07899. https://doi.org/10.1016/j.heliyon.2021.e07899
- Meharia, P. (2012). Assurance on the reliability of mobile payment system and its effects on its use: An empirical examination. Accounting and Management Information Systems, 11(1), 97–111. https://ideas.repec.org/a/ami/journl/v11y2012i1p97-111.html
- Mshali, H., & Al-Azawei, A. (2022). Predicting online learning adoption: The role of compatibility, self-efficacy, knowledge sharing, and knowledge acquisition. Journal of Information Science Theory and Practice, 10(3), 24–39. https://doi.org/10.1633/JISTaP.2022.10.3.3
- Pallant, J. (2013). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (5th ed.). McGraw Hill.
- Peat, J. K., & Barton, B. (2005). Medical statistics: A guide to data analysis and critical appraisal (1st ed.). Blackwell Publishing.
- Petter, S., & McLean, E. R. (2009). A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level. Information and Management, 46(3), 159–166. https://doi.org/10.1016/j.im.2008.12.006
- Pitt, L. F., Watson, R. T., & Kavan, C. B. (1995). Service quality: A measure of information systems effectiveness. MIS Quarterly: Management Information Systems, 19(2), 173–185. https://doi.org/10.2307/249687
- Ramirez-Correa, P. E., Javier Rondan-Cataluña, F., Arenas-Gaitán, J., & Alfaro-Perez, J. L. (2017). Moderating effect of learning styles on a learning management system’s success. Telematics and Informatics, 34, 272–286. https://doi.org/10.1016/j.tele.2016.04.006
- Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. http://www.smartpls.com
- Roemer, E., Schuberth, F., & Henseler, J. (2021). HTMT2—An improved criterion for assessing discriminant validity in structural equation modeling. Industrial Management and Data Systems, 121(12), 2637–2650. https://doi.org/10.1108/IMDS-02-2021-0082
- Rönkkö, M., & Cho, E. (2022). An updated guideline for assessing discriminant validity. Organizational Research Methods, 25(1), 6–47. https://doi.org/10.1177/1094428120968614
- Salam, N. R. A., & Ali, S. (2020). Determining factors of cloud computing adoption: A study of Indonesian local government employees. Journal of Accounting and Investment, 21(2), 312–333. https://doi.org/10.18196/jai.2102151
- Saunders, M., Lewis, P., & Thornhill, A. (2012). Research methods for business students (6th ed.). Pearson.
- Shim, M., & Sug Jo, H. (2020). What quality factors matter in enhancing the perceived benefits of online health information sites? Application of the updated DeLone and McLean information systems success model. International Journal of Medical Informatics, 137, Article 104093. https://doi.org/10.1016/j.ijmedinf.2020.104093
- Solimeno, A., Mebane, M. E., Tomai, M., & Francescato, D. (2008). The influence of students and teachers characteristics on the efficacy of face-to-face and computer supported collaborative learning. Computers & Education, 51(1), 109–128. https://doi.org/10.1016/j.compedu.2007.04.003
- Stallings, W. (2003). Network security essentials: Applications and standards (2nd ed.). Prentice Hall.
- Tsiakis, T., & Sthephanides, G. (2005). The concept of security and trust in electronic payments. Computers and Security, 24(1), 10–15. https://doi.org/10.1016/j.cose.2004.11.001
- Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
- Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
- Zhang, Z., Cao, T., Shu, J., & Liu, H. (2020). Identifying key factors affecting college students’ adoption of the e-learning system in mandatory blended learning environments. Interactive Learning Environments, 30(8), 1388–1401. https://doi.org/10.1080/10494820.2020.1723113