ABSTRACT
Higher education institutions (HEIs) around the world tend to incorporate various online learning platforms, such as Moodle, Google Classroom, Blackboard, Canvas, Virtual University Expert System (VUES), with the aim of shaping academic activities, which are knowledge sharing and knowledge creating. Despite its numerous benefits and usefulness highlighted in literature, majority are hesitant and reluctant to use online learning platforms available in Bangladesh. Alternatively, scholars from diverse disciplines have identified the construct 'social influence' as a prevailing predictor of the variable 'behavioral intention' to adopt numerous online platforms: blogs, e-services, online game and the predictor, social influence, plays a substantial role in embracing online learning as well as communicating the usefulness of various e-learning platforms. The study, therefore, is spearheaded to ascertain the role of social influence in facilitating learners' behavioral intention to accept online learning and communicating the usefulness of the e-learning in Bangladesh. To manifest the effect that one variable has on another, the study analyzed data of one hundred respondents surveyed randomly and confirmed the existence of the significant relationships: social influence (SI) and behavioral intention (BI), social influence (SI) and perceived usefulness (PU) in facilitating online learning acceptance, which provides an outline to the educators to comprehend behavior of the learners. The result of the study may also assist the educators and administrators to devise useful initiatives to intensify penetration rate of using online learning within the institution in Bangladesh. The research further adds to the existing literature that explains adoption and acceptance behavior of online education.
- A. Al-Azawei, P. Parslow, and K. Lundqvist, "Barriers and opportunities of e-learning implementation in Iraq: A case of public universities," The International Review of Research in Open and Distributed Learning, vol. 17, 2016.Google ScholarCross Ref
- F. D. Davis, "Perceived usefulness, perceived ease of use, and user acceptance of information technology," MIS quarterly, pp. 319--340, 1989.Google ScholarDigital Library
- S.-S. Liaw and H.-M. Huang, "Perceived satisfaction, perceived usefulness and interactive learning environments as predictors to self-regulation in e-learning environments," Computers & Education, vol. 60, pp. 14--24, 2013.Google ScholarCross Ref
- C.-S. Ong, J.-Y. Lai, and Y.-S. Wang, "Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies," Information & management, vol. 41, pp. 795--804, 2004.Google ScholarDigital Library
- M. Aparicio, F. Bacao, and T. Oliveira, "Cultural impacts on e-learning systems' success," The Internet and Higher Education, vol. 31, pp. 58--70, 2016.Google ScholarCross Ref
- M.-H. Ryu, S. Kim, and E. Lee, "Understanding the factors affecting online elderly user's participation in video UCC services," Computers in Human Behavior, vol. 25, pp. 619--632, 2009.Google ScholarDigital Library
- S. Y. Park, "An analysis of the technology acceptance model in understanding university students' behavioral intention to use e-learning," Educational technology & society, vol. 12, pp. 150--162, 2009.Google Scholar
- M. S. H. Khan, M. Hasan, and C. K. Clement, "Barriers to the introduction of ICT into education in developing countries: The example of Bangladesh," International Journal of instruction, vol. 5, 2012.Google Scholar
- A. Al-Adwan, A. Al-Adwan, and J. Smedley, "Exploring students acceptance of e-learning using Technology Acceptance Model in Jordanian universities," International Journal of Education and Development using ICT, vol. 9, 2013.Google Scholar
- V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, "User acceptance of information technology: Toward a unified view," MIS quarterly, pp. 425--478, 2003.Google ScholarDigital Library
- C.-L. Hsu and J. C.-C. Lin, "Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation," Information & management, vol. 45, pp. 65--74, 2008.Google ScholarDigital Library
- G. Kirkup and A. Kirkwood, "Information and communications technologies (ICT) in higher education teaching---a tale of gradualism rather than revolution," Learning, Media and Technology, vol. 30, pp. 185--199, 2005.Google ScholarCross Ref
- R. Oliver, "The role of ICT in higher education for the 21st century: ICT as a change agent for education," Retrieved April, vol. 14, p. 2007, 2002.Google Scholar
- K. Yasemin, xe, U. ak, A. Petek, x15f, kar, et al., "A Structural Equation Model for ICT Usage in Higher Education," Journal of Educational Technology & Society, vol. 11, pp. 262--273, 2008.Google Scholar
- H. Ardi, "INTERNET-BASED ACTIVITIES IN DEVELOPING STUDENTS'ENGLISH SKILLS," Lingua Didaktika: Jurnal Bahasa dan Pembelajaran Bahasa, vol. 6, pp. 26--36, 2012.Google ScholarCross Ref
- L. Rashotte, "Social influence," The Blackwell encyclopedia of sociology, 2007.Google Scholar
- Y. Malhotra and D. F. Galletta, "Extending the technology acceptance model to account for social influence: Theoretical bases and empirical validation," in Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers, 1999, p. 14 pp.Google Scholar
- D. Urumsah, "Factors Influencing Consumers to Use e-services in Indonesian Airline Companies," in E-services Adoption: Processes by Firms in Developing Nations, ed: Emerald Group Publishing Limited, 2015, pp. 5--254.Google Scholar
- D. L. Goodhue, W. Lewis, and R. Thompson, "Does PLS have advantages for small sample size or non-normal data?," Mis Quarterly, pp. 981--1001, 2012.Google ScholarCross Ref
- S. J. Barnes and M. Böhringer, "Modeling use continuance behavior in microblogging services: the case of Twitter," Journal of Computer Information Systems, vol. 51, pp. 1--10, 2011.Google Scholar
- M. A. Cohen, "Some new evidence on the seriousness of crime," Criminology, vol. 26, pp. 343--353, 1988.Google ScholarCross Ref
- P.-C. Sun, R. J. Tsai, G. Finger, Y.-Y. Chen, and D. Yeh, "What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction," Computers & education, vol. 50, pp. 1183--1202, 2008.Google ScholarDigital Library
Index Terms
- Roles of Social Influence in Expediting Online Learning Acceptance: A Preliminary Study on Bangladeshi Learners
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