Causal Factors Influencing the Adoption of Social Media Platform as a Tool for Collaborative Learning among Higher Education Students: The New Normal Post-COVID-19 Outlook
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Abstract
This article aimed to study 1) causal factors influencing the adoption of social media platforms as a tool for collaborative learning among higher education students; and 2) causal relationships between factors influencing the adoption of social media platforms as a tool for collaborative learning among higher education students. This research was a quantitative approach. The sample size was calculated from the sample-size ratio of Hair et al. (2010). The sample consisted of 371 higher education students who had experience using a social media platform for collaborative learning. They were selected by purposive sampling. The instrument for collecting data was a questionnaire. Analysis of data by analyzing the structural equations with PLS-SEM procedures. The results found that the most influential causal factors affecting the adoption of social media platforms as a tool for collaborative learning among higher education students are the capacity to support collaborative teamwork and perceived enjoyment, respectively. The implications of this study reveal the importance of understanding the causal factors that affect social media platforms as a tool for collaborative learning among higher education students. The study recommends that educational institutions and stakeholders enhance the level of social media platforms as a tool for collaborative learning among higher education students related to the current situation and transforming to the new normal of learning patterns.
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References
Adedoyin, O.B., & Soykan, E. (2020). Covid-19 pandemic and online learning: the challenges and opportunities. Interactive Learning Environments, Ahead-of-Print, 1-13. https://doi.org/10.1080/10494820.2020.1813180
Ainin, S., Naqshbandi, M.M., Mogavvemi, S., & Jaafar, N.I. (2015). Facebook usage, socialization and academic performance.Computers & Education, 83, 64-73. https://doi.org/10.1016/j.compedu.2014.12.018
Almaiah, M.A., Al-Khasawneh, A., & Althunibat, A. (2020). Exploring the critical challenges and factors influencing the e-Learning system usage during COVID-19 pandemic. Education and Information Technologies, 25, 5261-5280. https://doi.org/10.1007/s10639-020-10219-y
Anuradha, A.G. (1995). Collaborative Learning Enhances Critical Thinking. Journal of Technology Education, 7(1), 22-30. https://doi.org/10.21061/jte.v7i1.a.2
Baborska-Narozny, M., Stirling, E., & Stevenson, F. (2017). Exploring the Efficacy of Facebook Groups for Collective Occupant Learning About Using Their Homes. American Behavioral Scientist, 61(7), 757–773. https://doi.org/10.1177/0002764217717566
Chin, W.W. (2010). How to write up and report PLS analyses, in Esposito Vinzi, V., Chin, W.W., Henseler, J. and Wang, H. (Eds), Handbook of Partial Least Squares: Concepts, Methods and Applications, Vol. 2, Springer Handbooks of Computational Statistics Series. Springer, Heidelberg: 655-690. https://doi.org/10.1007/978-3-540-32827-8
Čičević, S., Samčović, A., & Nešić, M. (2016). Exploring college students’ generational differences in Facebook usage. Computers in Human Behavior, 56, 83-92. https://doi.org/10.1016/j.chb.2015.11.034
Curtis, L., Edwards, C., Fraser, K.L., Gudelsky, S., Holmquist, J., Thornton, K., & Sweetser, K.D. (2010). Adoption of social media for public relations by nonprofit organizations. Public Relations Review, 36(1), 90-92. https://doi.org/10.1016/j.pubrev.2009.10.003
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Demir, M. (2018). Using online peer assessment in an instructional technology and material design course through social media. Higher Education, 75, 399-414. https://doi.org/10.1007/s10734-020-00505-6
Diamantopoulos, A., & Siguaw, J.A. (2006). Formative vs reflective indicators in measure development: does the choice of indicators matter?. British Journal of Management. 13(4), 263-282. https://doi.org/10.1111/j.1467-8551.2006.00500.x
Elkaseh, A.M., Wong, K.W., & Fung, C.C. (2016). Perceived ease of use and perceived usefulness of social media for e-learning in Libyan higher education: a structural equation modeling analysis. International Journal of Information and Education Technology, 6(3), 192-199. https://doi.org/10.7763/IJIET.2016.V6.683
Elnaj, S. (2021). Council post: the ‘new normal’ and the future of technology after the covid-19 pandemic. Retrieved March 16, 2022 from https://www.forbes.com/sites/forbestechcouncil/2021/01/25/the-new-normal-and-the-future-of-technology-after-the-covid-19-pandemic/
Fishbein, M., & Ajzen, A. (1975). Beliefs, attitudes, intentions, and behavior: An introduction to theory and research. Addison-Wesley.
Fornell, C., & Larcker, D.F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(10), 39-50. https://doi.org/10.1177/002224378101800104
Gao, F., Luo, T., & Zhang, K. (2012). Tweeting for learning: a critical analysis of research on microblogging in education published in 2008-2011. British Journal of Educational Technology, 43(5), 783-801. https://doi.org/10.1111/j.1467-8535.2012.01357.x
Habibi, M.R., Laroche, M., & Richard, M.O. (2016). Testing an extended model of consumer behavior in the context of social media-based brand communities. Computers in Human Behavior, 62, 292-302. https://doi.org/10.1016/j.chb.2016.03.079
Hair, J. F, Hult, G.T.M., Ringle, C.M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)(2nd ed.). Sage.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Prentice Hall.
Hamid, S., Waycott, J., Kurnia, S., & Chang, S. (2015). Understanding students’ perceptions of the benefits of online social networking use for teaching and learning. The Internet and Higher Education, 26, 1-9. https://doi.org/10.1016/j.iheduc.2015.02.004
Henseler, J., & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics, 28(2), 565-580. https://doi.org/10.1007/s00180-012-0317-1
Hew, K.F. (2011). Students’ and teachers’ use of Facebook. Computers in Human Behavior, 27(2), 662-676. https://doi.org/10.1016/j.chb.2010.11.020
Ibrahim, N.F., Wang, X., & Bourne, H. (2017). Exploring the effect of user engagement in online brand communities: evidence from Twitter. Computers in Human Behavior, 72, 321-338. https://doi.org/10.1016/j.chb.2017.03.005
Ifinedo, P. (2016). Applying uses and gratifications theory and social influence processes to understand students’ pervasive adoption of social networking sites: perspectives from the Americas. International Journal of Information Management, 36(2), 192-206. https://doi.org/10.1016/j.ijinfomgt.2015.11.007
Lambić, D. (2016). Correlation between Facebook use for educational purposes and academic performance of students. Computers in Human Behavior, 61, 313-320. https://doi.org/10.1016/j.chb.2016.03.052
Lee, C.E.C., & Chong, A.Y.W. (2017). Students’ adoption of Facebook in higher education: a gender-based comparison. Proceedings of the International Conference on Communication and Media: An International Communication Association Regional Conference (i-COME’16), 02 February 2017, pp. 1-6. https://doi.org/10.1051/shsconf/20173300010
Li, C., & Lalani, F. (2020). The COVID-19 pandemic has changed education forever. This is how. https://www.weforum.org/agenda/2020/04/coronavirus-education-global-covid19-online-digital-learning/
Lin, C.P., & Anol, B. (2008). Learning online social support: An investigation of network information technology based on UTAUT. Cyber psychology and Behavior, 11(3), 268-272. http://doi.org/ 10.1089/cpb.2007.0057
Lin J.-W., & Lin K.H.-C. (2019). User acceptance in a computer-supported collaborative learning (CSCL) environment with social network awareness (SNA) support. Australasian Journal of Educational Technology, 35(1), 100-115. https://doi.org/10.14742/ajet.3395
Manca, S., & Ranieri, M. (2017). Networked scholarship and motivations for social media use in scholarly communication. The International Review of Research in Open and Distributed Learning, 18(2), 123-138. https://doi.org/10.19173/irrodl.v18i2.2859
Martínez-Torres, M.R., Toral Marín, S.L., Garcia, F.B., Vazquez, S.G., Oliva, M.A., & Torres, T. (2008). A technological acceptance of e-Learning tools used in practical and laboratory teaching, according to the european higher education area. Behaviour and Information Technology, 27(6), 495-505. https://doi.org/10.1080/01449290600958965
Milosevic, I., Zivkovic, D., Arsic, S., & Manasijevic, D. (2015). Facebook as virtual classroom: eSocial networking in learning and teaching among Serbian students. Telematics and Informatics, 32(4), 576-585. https://doi.org/10.1016/j.tele.2015.02.003
Moghavvemi, S., Paramanathan, T., Rahin, N.M., & Sharabati, M. (2017). Student’s perceptions towards using e-learning via Facebook. Behaviour & Information Technology, 36(10), 1081-1100. https://doi.org/10.1080/0144929X.2017.1347201
Murire, O.T., & Cilliers, L. (2017). Social media adoption among lecturers at a traditional university in Eastern Cape Province of South Africa. South African Journal of Information Management, 19(1), 1-6. https://doi.org/10.4102/sajim.v19i1.834
Nawi, N.C., Al Mamun, A., Nasir, N.A.M., & Muniady, R. (2019). Factors Affecting the Adoption of Social Media as a Business Platform: A Study among Student Entrepreneurs in Malaysia. Vision, 23(1), 1–11. https://doi.org/10.1177/0972262918821200
Nuq, P.A., & Aubert, B. (2013). Towards a better understanding of the intention to use eHealth services by medical professionals: The case of developing countries. International Journal of Healthcare Management, 6(4), 217-236.
https://doi.org/10.1179/2047971913Y.0000000 033
Owusu, G.M.Y., Bekoe, R.A., Otoo, D.S., & Koli, A.P.E. (2019). Adoption of social networking sites for educational use. Journal of Applied Research in Higher Education, 11(1), 2-19. https://doi.org/10.1108/JARHE-04-2018-0069
Pinho, J.C.M.R., & Soares, A.M. (2011). Examining the technology acceptance model in the adoption of social networks. Journal of Research in Interactive Marketing, 5(2/3), 116-129. https://doi.org/10.1108/17505931111187767
Phumkeaw, P. (2019). Development of a Model of Organizing for Learning For Enhancement of Reflective Thinking Ability of Student Teachers. 25(1), The Journal of Educational Measurement Mahasarakham University, 25(1), 188-205.
Rahman, N.S.A, Handayani, L., Othman, M.S., Al-Rahmi, W.M., Kasim, S., & Sutikno, T. (2020). Social media for collaborative learning. International Journal of Electrical and Computer Engineering (IJECE), 10(1), 1070-1078. https://doi.org/10.11591/ijece.v10i1.pp1070-1078
Rimor, R., & Arie, P. (2016). Visit to a small planet’: achievements and attitudes of high school students towards learning on Facebook – a case study. Handbook of Research on Technology Tools for Real-World Skill Development, IGI Global: 528-557. https://doi.org/10.4018/978-1-4666-9441-5.ch020
Ringle, C.M., Götz, O., Wetzels, M., & Wilson, B. (2009). On the use of formative measurement specifications in structural equation modeling: A Monte Carlo simulation study to compare covariance-based and partial least squares model estimation methodologies. In METEOR Research Memoranda (RM/09/014): Maastricht University. https://doi.org/10.26481/ umamet.2009014
Rodríguez-Hoyos, C., Haya, I., & Fernández-Díaz, E. (2015). Research on SNS and education: the state of the art and its challenges. Australasian Journal of Educational Technology, 31(1), 100-111. https://doi.org/10.14742/ajet.995
Rovinelli, R.J., & Hambleton, R.K. (1977). On the Use of Content Specialists in the Assessment of Criterion-Referenced Test Item Validity. Tijdschrift Voor Onderwijs Research, 2, 49-60.
Setiawan, R.A., Setyohadi, D.B., & Pranowo, P. (2018). Understanding customers’ intention to use social network sites as complaint channel: an analysis of young customers’ perspectives. E3S Web of Conferences, 31, 1-17. https://doi.org/10.1051/e3sconf/20183111014
Setkhumbong, T. (2012). Effect of e-Learning Using Collaborative Learning via Social Media on Competency of Using Information and Communication Technology of Undergraduate Educational Students. Veridian E-Journal, SU, 5(2), 569-584.
Sharma, S.K., Joshi, A., & Sharma, H. (2016). A multi-analytical approach to predict the Facebook usage in higher education. Computers in Human Behavior, 55, 340-353. https://doi.org/ 10.1016/j.chb.2015.09.020
Supakit, P. (2016). Collaborative Learning and Constructivist Learning for Learners in the Digital Age. Journal of Education, Silpakorn University, 14(1), 6-14.
Tess, P.A. (2013). The role of social media in higher education classes (real and virtual) – a literature review. Computers in Human Behavior, 9(5), 60-68. http://dx.doi.org/10.1016/j.chb.2012.12.032
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
Wong, K.K.K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32. http://marketing-bulletin. masseyac.nz/V24/ MB_V24_T1_Wong.pdf