Abstract
An incredible volume of research was conducted to examine the students’ acceptance of e-learning systems through the platforms of higher education institutions (HEIs). However, little debate was made concerning the exploration of the factors influencing the acceptance of e-learning systems via social media applications. Accordingly, this study extends the technology acceptance model (TAM) with social media practices, including knowledge sharing, motivation and uses, and social media features to understand the impact of these determinants on students’ acceptance of e-learning systems. The partial least squares-structural equation modeling (PLS-SEM) along with the importance-performance map analysis (IPMA) are employed to analyze the theoretical model using survey data collected from 410 students. The findings indicated that knowledge sharing, motivation and uses, and social media features have significant positive effects on both perceived ease of use (PEOU) and perceived usefulness (PU). It is also essential to report that the e-learning system acceptance is positively affected by PEOU and PU together. Further, the IPMA results showed that PEOU was the most important influential factor of e-learning systems acceptance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alsabawy, A.Y., Cater-Steel, A., Soar, J.: Determinants of perceived usefulness of e-learning systems. Comput. Human Behav. 64, 843–858 (2016)
Al-Emran, M., Teo, T.: Do knowledge acquisition and knowledge sharing really affect e-learning adoption? An empirical study. Educ. Inf. Technol. 25, 1983–1998 (2020). https://doi.org/10.1007/s10639-019-10062-w
R. A. Al-Maroof and M. Al-Emran, “Research Trends in Flipped Classroom: A Systematic Review,” in Recent Advances in Intelligent Systems and Smart Applications, Springer, 2021, pp. 253–275.
Althunibat, A.: Determining the factors influencing students’ intention to use m-learning in Jordan higher education. Comput. Human Behav. 52, 65–71 (2015). https://doi.org/10.1016/j.chb.2015.05.046
P. J. H. Hu and W. Hui, “Examining the role of learning engagement in technology-mediated learning and its effects on learning effectiveness and satisfaction,” 2012, https://doi.org/10.1016/j.dss.2012.05.014.
Crawford, C., Persaud, C.: Community Colleges Online. J. Coll. Teach. Learn. 10(1), 75–82 (2013). https://doi.org/10.19030/tlc.v10i1.7534
Salloum, S.A., Alhamad, A.Q.M., Al-Emran, M., Monem, A.A., Shaalan, K.: Exploring Students’ Acceptance of E-Learning Through the Development of a Comprehensive Technology Acceptance Model. IEEE Access 7, 128445–128462 (2019). https://doi.org/10.1109/access.2019.2939467
C. Mhamdi, M. Al-Emran, and S. A. Salloum, Text mining and analytics: A case study from news channels posts on Facebook, vol. 740. 2018.
N. Al-Qaysi, N. Mohamad-Nordin, and M. Al-Emran, “Developing an Educational Framework for Using WhatsApp Based on Social Constructivism Theory,” in Recent Advances in Intelligent Systems and Smart Applications, Springer, 2021, pp. 243–252.
Habes, M., Salloum, S.A., Alghizzawi, M., Alshibly, M.S.: The role of modern media technology in improving collaborative learning of students in Jordanian universities. Int. J. Inf. Technol. Lang. Stud. 2(3), 71–82 (2018)
N. Al-Qaysi, N. Mohamad-Nordin, and M. Al-Emran, “Factors Affecting the Adoption of Social Media in Higher Education: A Systematic Review of the Technology Acceptance Model,” in Recent Advances in Intelligent Systems and Smart Applications, Springer, 2021, pp. 571–584.
Costa, C., Alvelos, H., Teixeira, L.: The use of Moodle e-learning platform: a study in a Portuguese University. Procedia Technol. 5, 334–343 (2012)
N. Al-Qaysi, N. Mohamad-Nordin, and M. Al-Emran, “Employing the technology acceptance model in social media: A systematic review,” Educ. Inf. Technol., pp. 1–42, 2020, https://doi.org/10.1007/s10639-020-10197-1.
S. A. Salloum, M. Al-Emran, and K. Shaalan, “The Impact of Knowledge Sharing on Information Systems: A Review,” in International Conference on Knowledge Management in Organizations, 2018, pp. 94–106.
Boyd, D.M., Ellison, N.B.: Social network sites: Definition, history, and scholarship. J. Comput. Commun. 13(1), 210–230 (2007). https://doi.org/10.1111/j.1083-6101.2007.00393.x
Lee, C., Lee, G., Lin, H.: The role of organizational capabilities in successful e-business implementation. Bus. Process Manag. J. 13(5), 677–693 (2007). https://doi.org/10.1108/14637150710823156
Salloum, S.A., Al-Emran, M., Shaalan, K., Tarhini, A.: Factors affecting the E-learning acceptance: A case study from UAE. Educ. Inf. Technol. 24(1), 509–530 (2019). https://doi.org/10.1007/s10639-018-9786-3
Arpaci, I., Al-Emran, M., Al-Sharafi, M.A.: The impact of knowledge management practices on the acceptance of Massive Open Online Courses (MOOCs) by engineering students: A cross-cultural comparison. Telemat, Informatics (2020)
M. Al-Emran and V. Mezhuyev, “Examining the Effect of Knowledge Management Factors on Mobile Learning Adoption Through the Use of Importance-Performance Map Analysis (IPMA),” in International Conference on Advanced Intelligent Systems and Informatics, 2019, pp. 449–458.
M. Al-Emran, V. Mezhuyev, and A. Kamaludin, “Towards a conceptual model for examining the impact of knowledge management factors on mobile learning acceptance,” Technol. Soc., 2020.
Al-Qaysi, N., Al-Emran, M.: Code-switching Usage in Social Media: A Case Study from Oman. Int. J. Inf. Technol. Lang. Stud. 1(1), 25–38 (2017)
Lüders, M., Brandtzæg, P.B.: ‘My children tell me it’s so simple’: A mixed-methods approach to understand older non-users’ perceptions of Social Networking Sites. New media Soc. 19(2), 181–198 (2017)
Chatti, M.A., Jarke, M., Frosch-Wilke, D.: The future of e-learning: a shift to knowledge networking and social software. Int. J. Knowl. Learn. 3(4–5), 404–420 (2007)
F. Rennie and T. Morrison, E-learning and social networking handbook: Resources for higher education. Routledge, 2013.
Keller, J., Suzuki, K.: Learner motivation and e-learning design: A multinationally validated process. J. Educ. Media 29(3), 229–239 (2004)
Lee, Y.-C.: An empirical investigation into factors influencing the adoption of an e-learning system. Online Inf. Rev. 30(5), 517–541 (2006)
Sun, P.-C., Tsai, R.J., Finger, G., Chen, Y.-Y., Yeh, D.: What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Comput. Educ. 50(4), 1183–1202 (2008)
Zacharis, N.Z.: Predicting college students’ acceptance of podcasting as a learning tool. Interact. Technol. Smart Educ. 9(3), 171–183 (2012)
Law, K.M.Y., Lee, V.C.S., Yu, Y.-T.: Learning motivation in e-learning facilitated computer programming courses. Comput. Educ. 55(1), 218–228 (2010)
Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989). https://doi.org/10.2307/249008
Al-Qaysi, N., Mohamad-Nordin, N., Al-Emran, M.: A systematic review of social media acceptance from the perspective of educational and information systems theories and models. J. Educ. Comput. Res. 57(8), 2085–2109 (2020). https://doi.org/10.1177/0735633118817879
Tarhini, A., Hone, K., Liu, X.: The effects of individual differences on e-learning users’ behaviour in developing countries: A structural equation model. Comput. Human Behav. 41, 153–163 (2014). https://doi.org/10.1016/j.chb.2014.09.020
Tarhini, A., Hone, K., Liu, X.: Factors affecting students’ acceptance of e-learning environments in developing countries: A structural equation modeling approach. Int. J. Inf. Educ. Technol. 3(1), 54–59 (2013). https://doi.org/10.7763/IJIET.2013.V3.233
C. M. Ringle, S. Wende, and J. Becker, “SmartPLS 3. Bönningstedt: SmartPLS.” 2015, [Online]. Available: http://www.smartpls.com.
M. Al-Emran, V. Mezhuyev, and A. Kamaludin, “PLS-SEM in Information Systems Research: A Comprehensive Methodological Reference,” in 4th International Conference on Advanced Intelligent Systems and Informatics (AISI 2018), 2018, pp. 644–653.
J. F. Hair Jr, G. T. M. Hult, C. Ringle, and M. Sarstedt, A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications, 2016.
Henseler, J., Ringle, C.M., Sarstedt, M.: A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 43(1), 115–135 (2015). https://doi.org/10.1007/s11747-014-0403-8
Ringle, C.M., Sarstedt, M.: Gain more insight from your PLS-SEM results: The importance-performance map analysis. Ind. Manag. Data Syst. 116(9), 1865–1886 (2016). https://doi.org/10.1108/IMDS-10-2015-0449
Acknowledgment
This is an extended version of a conference paper published by the International Conference on Advanced Intelligent Systems and Informatics 2019.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Salloum, S.A., Al-Emran, M., Habes, M., Alghizzawi, M., Ghani, M.A., Shaalan, K. (2021). What Impacts the Acceptance of E-learning Through Social Media? An Empirical Study. In: Al-Emran, M., Shaalan, K. (eds) Recent Advances in Technology Acceptance Models and Theories. Studies in Systems, Decision and Control, vol 335. Springer, Cham. https://doi.org/10.1007/978-3-030-64987-6_24
Download citation
DOI: https://doi.org/10.1007/978-3-030-64987-6_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-64986-9
Online ISBN: 978-3-030-64987-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)