Abstract
Social-Media-Based Learning (SMBL) is the use of social-media-based platforms, such as Twitter, Google Plus, Facebook, and YouTube, for learning purposes. It facilitates interactive, participative, and cooperative learning among people in real time. This study aimed to determine the factors influencing SMBL in higher education institutions and to assess the mediating effect of trust on the target platform. To this end, we developed a model by combining the theoretical constructs of the unified theory of acceptance and use of technology theory with the concept of “trust.” We used the structural equation modeling method (partial least squares analysis) to analyze data collected using an online survey of 300 participants that included university students and faculties of higher education institutions in Bangladesh. In addition, we used importance-performance map analysis to determine constructs having relatively high importance, but showing relatively low performance. The study revealed that performance expectancy, effort expectancy, social influence, and facility conditions have a significant impact on social media usage intention. Furthermore, trust partially mediates the direct impact of performance expectancy, effort expectancy, and social influence on social media usage intention. The findings imply that trust has higher importance but relatively low performance.
Similar content being viewed by others
References
Abbad, M. M., Morris, D., & De Nahlik, C. (2009). Looking under the bonnet: Factors affecting student adoption of e-learning systems in Jordan. The International Review of Research in Open and Distributed Learning, 10(2), 1–25. https://doi.org/10.19173/irrodl.v10i2.596.
Abdel-Wahab, A. G. (2008). Modeling students’ intention to adopt e-learning: A case from Egypt. The Electronic Journal of Information Systems in Developing Countries, 34(1), 1–13. https://doi.org/10.1002/j.1681-4835.2008.tb00232.x.
Ajzen, I. (1991). The theory of planned behavior. Orgnizational Behavior and Human Decision Processes, 50, 179–211. https://doi.org/10.1016/0749-5978(91)90020-t.
Al-alak, B. A., & Alnawas, I. A. (2011). Measuring the acceptance and adoption of e-learning by academic staff. Knowledge Management and e-Learning: An International Journal, 3(2), 201–221. https://doi.org/10.34105/j.kmel.2011.03.016.
Al-Ammary, J. H., Al-Sherooqi, A. K., & Al-Sherooqi, H. K. (2014). The acceptance of social networking as a learning tools at University of Bahrain. International Journal of Information and Education Technology, 4(2), 208–214. https://doi.org/10.7763/ijiet.2014.v4.400.
Al-Gahtani, S. S. (2016). Empirical investigation of e-learning acceptance and assimilation: A structural equation model. Applied Computing and Informatics, 12(1), 27–50. https://doi.org/10.1016/j.aci.2014.09.001.
Alrawashdeh, T. A., Muhairat, M. I., & Alqatawnah, S. M. (2012). Factors affecting acceptance of web-based training system: Using extended UTAUT and structural equation modeling. International Journal of Computer Science, 2(2), 156–162. https://doi.org/10.5121/ijcseit.2012.2205.
Ameen, A., Almari, H., & Isaac, O. (2018). Determining underlying factors that influence online social network usage among public sector employees in the UAE. Advances in Intelligent Systems and Computing Recent Trends in Data Science and Soft Computing. https://doi.org/10.1007/978-3-319-99007-1_87.
Amin, M., Rezaei, S., & Abolghasemi, M. (2014). User satisfaction with mobile websites: The impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust. Nankai Business Review International, 5(3), 258–274. https://doi.org/10.1108/nbri-01-2014-0005.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modelling in practice: A review and recommended two step approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1037/0033-2909.103.3.411.
Ansari, J. A. N., & Khan, N. A. (2020). Exploring the role of social media in collaborative learning the new domain of learning. Smart Learning Environments. https://doi.org/10.1186/s40561-020-00118-7.
Asur, S., & Huberman, B. A. (2010). Predicting the future with social media. Paper presented at the Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. https://doi.org/10.1109/WI-IAT.2010.63
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/BF02723327.
Balakrishnan, V., Teoh, K. K., Pourshafie, T., & Liew, T. K. (2017). Social media and their use in learning: A comparative analysis between Australia and Malaysia from the learners’ perspectives. Australasian Journal of Educational Technology, 33(1), 81–97. https://doi.org/10.14742/ajet.2469.
Balakrishnan, V. (2016). Key determinants for intention to use social media for learning in higher education institutions. Universal Access in the Information Society, 16(2), 289–301. https://doi.org/10.1007/s10209-016-0457-0.
Belanche, D., Casaló, L. V., & Flavián, C. (2012). Integrating trust and personal values into the technology acceptance model: The case of e-government services adoption. Cuadernos de Economía y Dirección de la Empresa, 15(4), 192–204. https://doi.org/10.1016/j.cede.2012.04.004.
Bornstein, M. H., Jager, J., & Putnick, D. L. (2013). Sampling in developmental science: Situations, shortcomings, solutions, and standards. Developmental Review, 33(4), 357–370. https://doi.org/10.1016/j.dr.2013.08.003.
Boyd, D., & Ellison, N. (2010). Social network sites: Definition, history, and scholarship. IEEE Engineering Management Review, 3(38), 16–31. https://doi.org/10.1109/emr.2010,55(59),pp.139.
Burmaster, A. (2009). Global faces and networked places. Retrieved from http://blog.nielsen.com/nielsenwire/wpcontent/uploads/2009/03/nielsen_globalfaces_mar09.pdf
Chandra, S., Srivastava, S. C., & Theng, Y. (2012). Cognitive absorption and trust for workplace collaboration in virtual worlds: An information processing decision making perspective. Journal of the Association for Information Systems, 13(10), 797–835. https://doi.org/10.17705/1jais.00310.
Chang, S. E., Liu, A. Y., & Shen, W. C. (2017). User trust in social networking services: A comparison of Facebook and LinkedIn. Computers in Human Behavior, 69, 207–217. https://doi.org/10.1016/j.chb.2016.12.013.
Chaouali, W., Yahia, I. B., & Souiden, N. (2016). The interplay of counter-conformity motivation, social influence, and trust in customers’ intention to adopt Internet banking services: The case of an emerging country. Journal of Retailing and Consumer Services, 28, 209–218. https://doi.org/10.1016/j.jretconser.2015.10.007.
Chen, B., & Bryer, T. (2012). Investigating instructional strategies for using social media in formal and informal learning. The International Review of Research in Open and Distributed Learning, 13(1), 87–104. https://doi.org/10.19173/irrodl.v13i1.1027.
Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Routledge.
Compeau, D., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly. https://doi.org/10.2307/249749.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly. https://doi.org/10.2307/249688.
Coursaris, C. K., Van Osch, W., & Albini, A. C. P. (2018). Antecedents and consequents of information usefulness in user-generated online reviews: A multi-group moderation analysis of review valence. AIS Transactions on Human-Computer Interaction. https://doi.org/10.17705/1thci.00102.
Darker, C. D., & French, D. P. (2009). What sense do people make of a theory of planned behaviour questionnaire? A think-aloud study. Journal of Health Psychology, 14(7), 861–871. https://doi.org/10.1177/1359105309340983.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. https://doi.org/10.2307/249008.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivationto use com-puters in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x.
Davis, C. H., III., Deil-Amen, R., Rios-Aguilar, C., & González Canché, M. S. (2015). Social media, higher education, and community colleges: A research synthesis and implications for the study of two-year institutions. Community College Journal of Research and Practice, 39(5), 409–422. https://doi.org/10.1080/10668926.2013.828665.
Ejdys, J. (2018). Building technology trust in ICT application at a University. International Journal of Emerging Markets, 13(5), 980–997. https://doi.org/10.1108/ijoem-07-2017-0234.
El-Masri, M., & Tarhini, A. (2017). Factors affecting the adoption of e-learning systems in Qatar and USA: Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Education Technology Research and Development, 65(3), 743–763. https://doi.org/10.1007/s11423-016-9508-8.
El Ouirdi, M., El Ouirdi, A., Segers, J., & Pais, I. (2016). Technology adoption in employee recruitment: The case of social media in Central and Eastern Europe. Computers in Human Behavior, 57, 240–249. https://doi.org/10.1016/j.chb.2015.12.043.
Escobar-Rodrguez, T., Carvajal-Trujillo, E., & Monge-Lozano, P. (2014). Factors that influence the perceived advantages and relevance of Facebook as a learning tool: An extension of the UTAUT. Australasian Journal of Educational Technology, 30(2), 136–151. https://doi.org/10.14742/ajet.585.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–50. https://doi.org/10.2307/3151312.
Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101–107. https://doi.org/10.1093/biomet/61.1.101.
Ganim, M. A. M., & Kamruzzaman, M. (2014). E-governance using social network: A model for strong democratic environment in Bangladesh. Paper presented at the 16th International Conference of Computer and Information Technology, Khulna, Bangladesh, pp. 218–223.
Gao, S., & Yang, Y. (2014). The role of trust towards the adoption of mobile services in China: An empirical study. In H. Li, M. Mäntymäki, & X. Zhang (Eds.), Digital services and information intelligence. I3E 2014. IFIP advances in information and communication technology. (Vol. 445). Springer.
Gao, T., & Deng, Y. (2012). A study on users' acceptance behavior to mobile e-books application based on UTAUT model. Paper presented at the 2012 IEEE International Conference on Computer Science and Automation Engineering, Beijing, China, pp. 376–379
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519.
Gefen, D., Straub, D., & Boudreau, M.-C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(1), 7. https://doi.org/10.17705/1CAIS.00407.
Gefen, D., & Straub, D. J. (2003). Managing user trust in B2C e-services. e-Service Journal, 2(2), 7–24. https://doi.org/10.1353/esj.2003.0011.
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly. https://doi.org/10.2307/249689.
Hair, J. F., Jr., Anderson, R. E., Tatham, R. L., & Black, W. C. (1995). Multivariate data analysis: Englewood cliffs. . Prentice Hall.
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). . Sage Publications.
Hair, J., Jr., Black, W., Babin, B., & Anderson, R. (2010). Multivariate data analysis: A global perspective. . Pearson Education Inc.
Hair, J. F., Jr., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). (2nd ed.). Sage Publications.
Hanson, C., West, J., Neiger, B., Thackeray, R., Barnes, M., & McIntyre, E. (2011). Use and acceptance of social media among health educators. American Journal of Health Education, 42(4), 197–204. https://doi.org/10.1080/19325037.2011.10599188.
Hock, C., Ringle, C. M., & Sarstedt, M. (2010). Management of multi-purpose stadiums: Importance and performance measurement of service interfaces. International Journal of Services Technology and Management, 14(2–3), 188–207. https://doi.org/10.1504/ijstm.2010.034327.
Honebein, P. C., & Honebein, C. H. (2015). Effectiveness, efficiency, and appeal: pick any two? The influence of learning domains and learning outcomes on designer judgments of useful instructional methods. Educational Technology Research and Development, 63(6), 937–955. https://doi.org/10.1007/s11423-015-9396-3.
Hoque, R., & Sorwar, G. (2017). Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. International Journal of Medical Informatics, 101, 75–84. https://doi.org/10.1016/j.ijmedinf.2017.02.002.
Hossain, M. A., Salam, M. A., & Shilpi, F. (2016). Readiness and challenges of using information and communications technology (ICT) in higher education of Bangladesh. The Online Journal of New Horizons in Education, 6(1), 123–132.
Hughes, D. J., Rowe, M., Batey, M., & Lee, A. (2012). A tale of two sites: Twitter vs. Facebook and the personality predictors of social media usage. Computers in Human Behavior, 28(2), 561–569. https://doi.org/10.1016/j.chb.2011.11.001.
Hull, C. H., & Nie, N. H. (1981). SPSS update. McGraw Hill.
Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195–204. https://doi.org/10.1002/(SICI)1097-0266(199902)20:2%3c195::AID-SMJ13%3e3.0.CO;2-7.
Jager, J., Putnick, D. L., & Bornstein, M. H. (2017). II. More than just convenient: The scientific merits of homogeneous convenience samples. Monographs of the Society for Research in Child Development, 82(2), 13–30. https://doi.org/10.1111/mono.12296.
Jong, D., & Wang, T. (2009). Student acceptance of web-based learning system. In Proceedings. The 2009 International Symposium on Web Information Systems and Applications (WISA 2009), Vol. 8. Academy Publisher, pp. 533–536
Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53(1), 59–68. https://doi.org/10.1016/j.bushor.2009.09.003.
Kemp, S. (Nov 19, 2018). Digital in 2018: World’s internet users pass the 4 billion mark. https://wearesocial.com/blog/2018/01/global-digital-report-2018
Kietzmann, J. H., Hermkens, K., McCarthy, I. P., & Silvestre, B. S. (2011). Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons, 54(3), 241–251. https://doi.org/10.1016/j.bushor.2011.01.005.
Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44, 544–564. https://doi.org/10.1016/j.dss.2007.07.001.
Kline, R. B. (2015). Principles and practice of structural equation modeling. (4th ed.). Guilford Publications.
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration (IJeC), 11(4), 1–10. https://doi.org/10.4018/ijec.2015100101.
Kumar, A., Bezawada, R., Rishika, R., Janakiraman, R., & Kannan, P. (2016). From social to sale: The effects of firm-generated content in social media on customer behavior. Journal of Marketing, 80(1), 7–25. https://doi.org/10.1509/jm.14.0249.
Lee, Y.-H., Hsieh, Y.-C., & Chen, Y.-H. (2013). An investigation of employees’ use of e-learning systems: Applying the technology acceptance model. Behaviour and Information Technology, 32(2), 173–189. https://doi.org/10.1080/0144929x.2011.577190.
Leonard-Barton, D., & Deschamps, I. (1988). Managerial influence in the implementation of new technology. Management Science, 34(10), 1252–1265. https://doi.org/10.1287/mnsc.34.10.1252.
Lolic, T., Dionisio, R., Ciric, D., Ristic, S., & Stefanovic, D. (2020). Factors influencing students usage of an e-learning system: Evidence from IT students. In Z. Anisic, B. Lalic, & D. Gracanin (Eds.), Proceedings on 25th International Joint Conference on Industrial Engineering and Operations Management – IJCIEOM. Springer.
Lu, Y., Yang, S., Chau, P. Y., & Cao, Y. (2011). Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. Information and Management, 48(8), 393–403. https://doi.org/10.1016/j.im.2011.09.006.
Meyliana, Widjaja, H. A. E., Santoso, S. W., Petrus, S., Jovian, & Jessica. (2019). The enhancement of learning management system in teaching learning process with the UTAUT2 and trust model. International Conference on Information Management and Technology (ICIMTech). https://doi.org/10.1109/icimtech.2019.8843828.
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192.
Mtebe, J. S., & Raisamo, R. (2014). Challenges and instructors’ intention to adopt and use open educational resources in higher education in Tanzania. The International Review of Research in Open and Distributed Learning, 15(1), 249–271. https://doi.org/10.19173/irrodl.v15i1.1687.
North-Samardzic, A., & Jiang, B. (2015). Acceptance and use of Moodle by students and academics. Paper presented at the Twenty-first Americas Conference on Information Systems (AMCIS). http://hdl.handle.net/10536/DRO/DU:30083128
Nunnally, J. C., & Bernstein, I. (1978). Psychometric theory. (2nd ed.). MacGraw-Hill.
O’brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality and Quantity, 41(5), 673–690. https://doi.org/10.1007/s11135-006-9018-6.
Ofori, K. S., Boakye, K. G., Addae, J. A., Ampong, G. O. A., & Adu, A. S. Y. (2017). An empirical study on the adoption of consumer-to-consumer e-commerce: Integrating the UTAUT model and the initial trust model. Paper Presented at the International Conference on e-Infrastructure and e-Services for Developing Countries. https://doi.org/10.1007/978-3-319-98827-6_27.
Paton, C., Bamidis, P., Eysenbach, G., Hansen, M., & Cabrer, M. (2011). Experience in the use of social media in medical and health education. Yearbook of Medical Informatics, 20(01), 21–29. https://doi.org/10.1055/s-0038-1638732.
Podsakoff, P., MacKenzie, S., Lee, J., & Podsakoff, N. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879.
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/BRM.40.3.879.
Raman, A., & Don, Y. (2013). Preservice teachers’ acceptance of learning management software: An application of the UTAUT2 model. International Education Studies, 6(7), 157–164. https://doi.org/10.5539/ies.v6n7p157.
Raman, A., Sani, R. M., & Kaur, P. (2014). Facebook as a collaborative and communication tool: A study of secondary school students in Malaysia. Procedia-Social and Behavioral Sciences, 155, 141–146. https://doi.org/10.1016/j.sbspro.2014.10.270.
Rauniar, R., Rawski, G., Yang, J., Johnson, B. J. J., & o. E. I. M. . (2014). Technology acceptance model (TAM) and social media usage: An empirical study on Facebook. Journal of Enterprise Information Management, 27(1), 6–30. https://doi.org/10.1108/jeim-04-2012-0011.
Reigeluth, C. M., & Carr-Chellman, A. (2009). Understanding instructional theory. In C. M. Reigeluth & A. Carr-Chellman (Eds.), Instructional-design theories and models: Building a common knowledge base. (Vol. III, pp. 3–26). Lawrence Erlbaum Associates.
Rodriguez, J. E. (2011). Social media use in higher education: Key areas to consider for educators. MERLOT Journal of Online Learning and Teaching, 7(4), 539–550.
Rogers, E. (2013). Diffusion of innovations. . The Free Press.
Schivinski, B., & Dabrowski, D. (2016). The effect of social media communication on consumer perceptions of brands. Journal of Marketing Communications, 22(2), 189–214. https://doi.org/10.1080/13527266.2013.871323.
Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15(3), 325–343. https://doi.org/10.1086/209170.
Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290–312. https://doi.org/10.2307/270723.
Sumak, B., Polancic, G., & Hericko, M. (2010). An empirical study of virtual learning environment adoption using UTAUT. Paper presented at the 2010 Second International Conference on Mobile, Hybrid, and On-Line Learning, Saint Maarten, Netherlands Antilles, pp. 17–22.
Teo, T., Zhou, M., Fan, A. C. W., & 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. https://doi.org/10.1007/s11423-019-09650-x.
Taylor, S., & Todd, P. (1995a). Assessing IT usage: The role of prior experience. MIS Quarterly. https://doi.org/10.2307/249633.
Taylor, S., & Todd, P. A. (1995b). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176. https://doi.org/10.1287/isre.6.2.144.
Tess, P. A. (2013). The role of social media in higher education classes (real and virtual): A literature review. Computers in Human Behavior, 29(5), A60–A68. https://doi.org/10.1016/j.chb.2012.12.032.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly. https://doi.org/10.2307/249443.
Tung, F.-C., Chang, S.-C., & Chou, C.-M. (2008). An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry. International Journal of Medical Informatics, 77(5), 324–335. https://doi.org/10.1016/j.ijmedinf.2007.06.006.
University Grants Commission of Bangladesh (2018). Annual-Report-2018. Retrieved August 19, 2020 from http://www.ugc.gov.bd/site/annual_reports/ed1ed68d-c017-4e3e-a66c-ba1fb83fc0bc/Annual-Report-2018.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.1192.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly. https://doi.org/10.2307/30036540.
Venkatesh, V., Thong, J., & 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.
Wang, Y., Min, Q., & Han, S. (2016). Understanding the effects of trust and risk on individual behavior toward social media platforms: A meta-analysis of the empirical evidence. Computers in Human Behavior, 56, 34–44. https://doi.org/10.1016/j.chb.2015.11.011.
Wang, Y. S., Wu, M. C., & Wang, H. Y. J. B. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1), 92–118. https://doi.org/10.1111/j.1467-8535.2007.00809.x.
Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): A literature review. Journal of Enterprise Information Management, 28(3), 443–488. https://doi.org/10.1108/jeim-09-2014-0088.
Wu, K., Zhao, Y., Zhu, Q., Tan, X., & Zheng, H. (2011). A meta-analysis of the impact of trust on technology acceptance model: Investigation of moderating influence of subject and context type. International Journal of Information Management, 31(6), 572–581. https://doi.org/10.1016/j.ijinfomgt.2011.03.004.
Yildiz Durak, H. (2018). Examining the acceptance and use of online social networks by preservice teachers within the context of unified theory of acceptance and use of technology model. Journal of Computing in Higher Education, 31(1), 173–209. https://doi.org/10.1007/s12528-018-9200-6.
Yousuf, R., Bakar, S. M. A., Haque, M., Islam, M. N., & Salam, A. (2017). Medical professional and usage of social media. Bangladesh Journal of Medical Science, 16(4), 606–609. https://doi.org/10.3329/bjms.v16i4.33622.
Yueh, H.-P., Huang, J.-Y., & Chang, C. (2015). Exploring factors affecting students’ continued Wiki use for individual and collaborative learning: An extended UTAUT perspective. Australasian Journal of Educational Technology. https://doi.org/10.14742/ajet.170.
Zhao, X., Lynch, J. G., Jr., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis. Journal of Consumer Research, 37(2), 197–206. https://doi.org/10.1086/651257.
Acknowledgements
This research was supported by the Doctoral Candidate Research Grant of Keimyung University in 2019.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
Constructs | Items | Sources |
---|---|---|
Performance expectancy | PE1: I find social media-based learning useful for my study PE2: I can accomplish my tasks more quickly by using social media-based learning PE3: I can increase my learning productivity by using social media-based learning PE4: I will increase my chances of getting more competence by using social media-based learning | Davis (1989), Davis et al. (1989), Moore and Benbasat (1991), Compeau and Higgins (1995), Compeau et al. (1999) and Venkatesh et al. (2003) |
Effort expectancy | EE1: I think my interaction with social media-based learning is clear and understandable EE2: I consider social media-based learning as an easy medium to become a skillful person EE3: I would prefer to use social media compared to other modes (emails, phone calls) as a communication medium with peers and/or academics as it is simple and easy to use EE4: I perceive that operating social media-based learning will be easy for me | Davis (1989), Davis et al. (1989), Moore and Benbasat (1991) and Venkatesh et al. (2003) |
Social influence | SI1: I am influenced by friends and family in the way I use social media in learning SI2: I am influenced by faculty teaching courses in the way I use social media in learning SI3: I learned from friends about how to access learning materials through social media sites | |
Facilitating conditions | FC1: I have the resources necessary to use social media-based learning FC2: I have the knowledge necessary to use social media-based learning FC3: I use other systems compatible with social media-based learning FC4: I get assistance from experts when I face difficulties with social media-based learning | Ajzen (1991), Taylor and Todd (1995a, 1995b), Thompson et al. (1991) and Venkatesh et al. (2003) |
Trust | T1: I trust social media-based learning T2: I am certain about what to expect from social media-based learning T3: Social media-based learning is trustworthy | |
Behavioral intention to use the system | IU1: I intend to continue using social media-based learning in the future IU2: I predict that I will continue using social media-based learning in the future IU3: I have the plan to continue using social media-based learning in the future | Venkatesh et al. (2003) |
Rights and permissions
About this article
Cite this article
Rahman, T., Kim, Y.S., Noh, M. et al. A study on the determinants of social media based learning in higher education. Education Tech Research Dev 69, 1325–1351 (2021). https://doi.org/10.1007/s11423-021-09987-2
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11423-021-09987-2