The Effect of Students' Perceived Social Presence in Distance Learning on Their Willingness to Attend Online Guidance with Improved Social Presence: The Mediating Role of Usefulness, Utility, Chance, and Behavioral Intention
Abstract
Four independent variables, social Presence, ease of use, usability, and risk, significantly affect students' intentions to interact in online tutoring on the Website. Social Presence is the dominant variable influencing students' intentions to interact virtually. These findings bring some implications for the distance learning management team that adopts the Website as their media. Social presence factors affect online guidance and counseling. It is analyzed from the potential of technological development, which is the purpose of this study to see the effect of social presence on the implementation of online guidance-the method used is multiple linear regression analysis, where this study identifies independent variables that affect the dependent variable through multiple regression hypotheses with 80 respondents. This study found that perceived social presence, utility, usefulness, and opportunity significantly influenced behavioral intention on online guidance by increasing social presence. In addition, behavioral intention was observed as the most dominant variable affecting students' intention to interact in distance learning.
Downloads
References
Acuña, M. H., Ogilvie, K. W., Baker, D. N., Curtis, S. A., Fairfield, D. H., & Mish, W. H. (1995). The Global Geospace Science Program and its investigations. In Space Science Reviews (Vol. 71, Issues 1–4, pp. 5–21). https://doi.org/10.1007/BF00751323
Al-Maroof, R. S., Alhumaid, K., & Salloum, S. (2021). The continuous intention to use e-learning, from two different perspectives. Education Sciences, 11(1), 1–20. https://doi.org/10.3390/educsci11010006
Allen, I. E., & Seaman, J. (2017). Digital Compass Learning: Distance Education Enrollment Report 2017. Babson survey research group. Google Scholar
Baber, H. (2021). Modelling the acceptance of e-learning during the pandemic of COVID-19-A study of South Korea. International Journal of Management Education, 19(2), 100503. https://doi.org/10.1016/j.ijme.2021.100503
Blau, I., & Caspi, A. (2009). What Type of Collaboration Helps ? Psychological Ownership , Perceived Learning and Outcome Quality of Collaboration Using Google Docs. Quality, January, 48–55. Google Scholar
Chickering, A. W., & Gamson, Z. F. (1987). Washington Center News Seven Principles For Good Practice in Undergraduate Education A Focus for Improvement. American Association for Higher Education Bulletin, 39(7), 2–6. Google Scholar
Çubukçu, C., & Aktürk, C. (2020). The Rise of Distance Education during Covid-19 Pandemic and the Related Data Threats: A Study about Zoom. Igd Univ Jour Soc Sci, Ek2(Ek2), 127–143. Google Scholar
Cui, G., Lockee, B., & Meng, C. (2013). Building modern online social presence: A review of social presence theory and its instructional design implications for future trends. Education and Information Technologies, 18(4), 661–685. https://doi.org/10.1007/s10639-012-9192-1
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008
Duffett, R. G. (2017). Influence of social media marketing communications on young consumers’ attitudes. Young Consumers, 18(1), 19–39. https://doi.org/10.1108/YC-07-2016-00622
Edison, S. W., & Geissler, G. L. (2003). Measuring attitudes towards general technology: Antecedents, hypotheses and scale development. Journal of Targeting, Measurement and Analysis for Marketing, 12(2), 137–156. https://doi.org/10.1057/palgrave.jt.5740104
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
Enu-Kwesi, F., & Opoku, M. O. (2020). Relevance of the technology acceptance model (TAM) in information management research: a review of selected empirical evidence. Pressacademia, 7(1), 34–44. https://doi.org/10.17261/pressacademia.2020.1186
Fidalgo, P., Thormann, J., Kulyk, O., & Lencastre, J. A. (2020). Students’ perceptions on distance education: A multinational study. International Journal of Educational Technology in Higher Education, 17(1). https://doi.org/10.1186/s41239-020-00194-2
Ganguly, B., Dash, S. B., Cyr, D., & Head, M. (2010). The effects of website design on purchase intention in online shopping: the mediating role of trust and the moderating role of culture. International Journal of Electronic Business, 8(4/5), 302. https://doi.org/10.1504/ijeb.2010.035289
Ghozali, I. (2018). Aplikasi Analisis Multivariete SPSS 25 Edisi 9 Prof Dr H Imam Ghozali M Com Akt. Semarang: Badan Penerbit Universitas Diponegoro. Google Scholar
Ikhsan, R. B., Saraswati, L. A., Muchardie, B. G., Vional, & Susilo, A. (2019). The determinants of students’ perceived learning outcomes and satisfaction in BINUS online learning. Proceedings of 2019 5th International Conference on New Media Studies, CONMEDIA 2019, 68–73. https://doi.org/10.1109/CONMEDIA46929.2019.8981813
Isriyah, M., Degeng, I. N. S., Lasan, B. B., & Muslihati. (2020). Online guidance study on the enhancement of completeness in completing the final duties of distance students. International Journal of Psychosocial Rehabilitation, 24(8), 12412–12423. https://doi.org/10.37200/IJPR/V24I8/PR281225
Kear, K., Chetwynd, F., & Jefferis, H. (2014). Social presence in online learning communities: The role of personal profiles. Research in Learning Technology, 22(January). https://doi.org/10.3402/rlt.v22.19710
Kim, J., Song, H., & Luo, W. (2016). Broadening the understanding of social presence: Implications and contributions to the mediated communication and online education. Computers in Human Behavior, 65, 672–679. https://doi.org/10.1016/j.chb.2016.07.009
Kim, M., Chen, J.-L., Kools, S., & Weiss, S. (2016). The Impact of Personality Traits and Acculturation on the Mental Health of Korean American Adolescents. Psychology, 07(09), 1256–1265. https://doi.org/10.4236/psych.2016.79128
Law, M., Kwok, R. C. W., & Ng, M. (2016). An extended online purchase intention model for middle-aged online users. Electronic Commerce Research and Applications, 20, 132–146. https://doi.org/10.1016/j.elerap.2016.10.005
Lee, B. C., Yoon, J. O., & Lee, I. (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers and Education, 53(4), 1320–1329. https://doi.org/10.1016/j.compedu.2009.06.014
Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003). The Technology Acceptance Model: Past, Present, and Future. Communications of the Association for Information Systems, 12. https://doi.org/10.17705/1cais.01250
Leeds, E., Campbell, S., Baker, H., Ali, R., Brawley, D., & Crisp, J. (2013). The impact of student retention strategies: An em pirical study. International Journal of Management in Education, 7(1–2), 22–43. https://doi.org/10.1504/IJMIE.2013.050812
Legault, L. (2016). Encyclopedia of Personality and Individual Differences. Encyclopedia of Personality and Individual Differences. https://doi.org/10.1007/978-3-319-28099-8
Li, D. C., & Tsai, C. Y. (2020). An empirical study on the learning outcomes of e-learning measures in taiwanese small and medium-sized enterprises (SMEs) based on the perspective of goal orientation theory. Sustainability (Switzerland), 12(12), 1–23. https://doi.org/10.3390/su12125054
Lowenthal, P. R. (2011). Social Presence. Social Computing, 129–136. https://doi.org/10.4018/978-1-60566-984-7.ch011
Ludwig-Hardman, S., & Dunlap, J. C. (2003). Learner support services for online students: Scaffolding for success. International Review of Research in Open and Distance Learning, 4(1), 45–61. https://doi.org/10.19173/irrodl.v4i1.131
Mailizar, M., Burg, D., & Maulina, S. (2021). Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model. Education and Information Technologies, 26(6), 7057–7077. https://doi.org/10.1007/s10639-021-10557-5
Masoud, E. Y. (2013). The effect of perceived risk on online shopping in Jordan. European Journal of Business and Management, 5(6), 76-87. Google Scholar
Murugan, S., & Nagarajan, P. S. (2017). Influence of social media in vacation travels. ACADEMICIA: An International Multidisciplinary Research Journal, 7(9), 114. https://doi.org/10.5958/2249-7137.2017.00093.3
Nugroho, Y. A. (2016). the Effect of Perceived Ease of Use, Perceive of Usefulness, Perceive Risk and Trust Towards Behavior Intention in Transaction By Internet. Business and Entrepreneurial Review, 9(1), 79–90. https://doi.org/10.25105/ber.v9i1.26
Pan, C. C., Sivo, S., Gunter, G., & Cornell, R. (2005). Students’ perceived ease of use of an eLearning management system: An exogenous or endogenous variable? Journal of Educational Computing Research, 33(3), 285–307. https://doi.org/10.2190/7M4G-R742-W9FT-JX1J
Richardson, J. C., & Swan, K. (2003). Examining social presence in online courses in relation to students’ perceived learning and satisfaction. Journal of Asynchronous Learning Network, 7(1). https://doi.org/10.24059/olj.v7i1.1864
Robbins, J. H. (1964). Tissue culture studies of the human lymphocyte. Science, 146(3652), 1648–1655. https://doi.org/10.1126/science.146.3652.1648
Rovai, A. P. (2002). Building sense of community at a distance. International Review of Research in Open and Distance Learning, 3(1), 74–85. https://doi.org/10.19173/irrodl.v3i1.79
Rovai, A. P. (2002). Sense of community, perceived cognitive learning, and persistence in asynchronous learning networks. Internet and Higher Education, 5(4), 319–332. https://doi.org/10.1016/S1096-7516(02)00130-6
Sayer, A. (2005). Class, moral worth and recognition. Sociology, 39(5), 947–963. https://doi.org/10.1177/0038038505058376
Swan, K., & Shih, L. F. (2019). on the Nature and Development of Social Presence in Online Course Discussions. Online Learning, 9(3), 115–136. https://doi.org/10.24059/olj.v9i3.1788
Thuy, V. T. N., Vi, D. T. T., & Linh, N. H. P. (2015). The Impact of Social Presence in the Web Interface on Customer’s Purchase Intention toward Online Stores: The Case of Vietnam. International Journal of Education and Social Science, 2(4), 70–84. Google Scholar
Tu, C. H. (2002). The impacts of text-based CMC on online social presence. Journal of Interactive Online Learning, 1(2), 1–24. Google Scholar
Umar. (2011). Extending the Technology Acceptance Model to Account for Social Influence, Trust and Integration for Pervasive Computing Environment: A Case Study in University Industry. American Journal of Economics and Business Administration, 3(3), 552–559. https://doi.org/10.3844/ajebasp.2011.552.559
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. https://doi.org/10.2307/30036540
Vesga, J. A. B., Kirilov, S. K., & Jr, A. P. E. (2018). Main Predictors of Attitudes toward the Use of Moodle for Learning Business Administration Courses in an Asian International University Setting. In Researchgate.Net (Issue October 2017). Google Scholar
Wan, Z., Wang, Y., & Haggerty, N. (2008). Why people benefit from e-learning differently: The effects of psychological processes on e-learning outcomes. Information and Management, 45(8), 513–521. https://doi.org/10.1016/j.im.2008.08.003
Woolfolk Hoy, A., Davis, H. A., & Anderman, E. M. (2013). Theories of Learning and Teaching in TIP. Theory into Practice, 52(SUPPL 1), 9–21. https://doi.org/10.1080/00405841.2013.795437
Yasa, N. N. K., Ratnaningrum, L. P. R. A., & Sukaatmadja, P. G. (2014). the Application of Technology Acceptance Model on Internet Banking Users in the City of Denpasar. Jurnal Manajemen Dan Kewirausahaan, 16(2), 93–102. https://doi.org/10.9744/jmk.16.2.93-102
Copyright (c) 2023 Mudafiatun Isriyah, Hariyanto Hariyanto, Nasruliyah Hikmatul Maghfiroh
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1) Authors retain copyright and grant the journal the right to first publication, with the work simultaneously licensed under the Creative Commons Attribution that allows the sharing of articles published with the acknowledgement of authorship and the initial publication in this magazine.
2) The authors are authorized to make additional contracts separately for distribution of the version of the work published in this journal (for example, publication in an institutional repository or as a chapter of the book), as long as there is recognition of authorship and initial publication in this journal.
3) Authors are authorized and encouraged to publish and distribute their work online (for example, in institutional repositories or on their personal pages) at any time before or during the editorial process, as it increases the impact and reference of the published work.
