Predicting Online Classroom Engagement by Causality Orientation, Goal Contents, and Organismic Integration Theories
Subject Areas :Elham Hajibabaei 1 , Mehrdad Sepehri 2 , Fariba Rahimi 3
1 -
2 -
3 -
Keywords: Engagement, Motivation, Organismic Integration Theories, Self-Determination Theory,
Abstract :
This research endeavor aimed to investigate the extent to which cognitive evaluation and organ-ismic integration theories contribute to accounting for the motivational factors influencing Irani-an EFL learners' engagement in online classrooms. To achieve this objective, a survey study was conducted wherein the participants completed four distinct questionnaires pertaining to their classroom engagement, academic motivation, goal contents, and learning self-regulation. The questionnaires utilized in the study were developed by Fredricks et al. (2005), Vallerand et al. (1992), and Black & Deci (2000); Williams & Deci (1996). The sample comprised 200 Iranian intermediate EFL learners, aged between 19 and 25, who were selected based on the conven-ience sampling technique from Isfahan and Chaharmahal and Bakhtiari Provinces. These partic-ipants were both male and female students pursuing their Bachelor's degrees in English at Islam-ic Azad University. To ensure the homogeneity of their language proficiency, an Oxford Quick Placement Test (OQPT) was administered. The data collection phase involved the distribution of the four questionnaires to the participants electronically via the Google Doc Web application. The collected data underwent a Structural Equation Modeling (SEM) statistical analysis, which revealed that the motivational variables examined in the study exerted a significant influence on online classroom engagement. Consequently, it can be inferred that English language educators who possess knowledge of the potential relationships between online classroom engagement and learners' motivation within the framework of Self-Determination Theory (SDT) can en-hance their effectiveness as educational facilitators, supporters, and counselors.
Akar, E. (2016). Using Facebook as an ad-vertising tool: A study on Turkish consumers. International Review on Public and Nonprofit Marketing, 13(3), 265–283. https://doi.org/10.1007/s12208-016-0156-4
Al-Debei, M. M., Akroush, M. N., & Ash-ouri, M. I. (2015). Consumer attitudes towards online shopping: The effects of trust, perceived benefits, and per-ceived web quality. Internet Research, 25(5), 707–733. https://doi.org/10.1108/IntR-05-2014-0146
Arora, N. (2019). Factors influencing con-sumer behavior and online purchase decision—a literature review. Interna-tional Journal of Management Stud-ies, 6(1), 1–10. https://doi.org/10.18843/ijms/v6i1(1)/01
Bansal, G., Zahedi, F. M., & Gefen, D. (2010). The impact of personal dispo-sitions on information sensitivity, pri-vacy concern and trust in disclosing health information online. Decision Support Systems, 49(2), 138–150. https://doi.org/10.1016/j.dss.2010.01.010
Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., & Lytras, M. D. (2018). Mobile shopping apps adoption and per-ceived risks: A cross-country perspec-tive utilizing the unified theory of ac-ceptance and use of technology. Computers in Human Behavior, 86, 109–128. https://doi.org/10.1016/j.chb.2018.04.017
Chung, N., Han, H., & Joun, Y. (2015). Tourists’ intention to visit a destina-tion: The role of augmented reality (AR) application for a heritage site. Computers in Human Behavior, 50, 588–599. https://doi.org/10.1016/j.chb.2015.02.068
Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: Moderating effects of consumer traits and situational fac-tors. Journal of the Academy of Mar-keting Science, 30(3), 184–201. https://doi.org/10.1177/0092070302303001
Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80. https://doi.org/10.1287/isre.1060.0080
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
Hajli, N. (2015). Social commerce con-structs and consumer’s intention to buy. International Journal of Infor-mation Management, 35(2), 183–191. https://doi.org/10.1016/j.ijinfomgt .2014.12.005
Hansen, J. M., Saridakis, G., & Benson, V. (2018). Risk, trust, and the interaction of perceived ease of use and behav-ioral control in predicting consumers’ use of social media for transactions. Computers in Human Behavior, 80, 197–206. https://doi.org/10.1016/j.chb.2017.11.010
Kim, D. J., Ferrin, D. L., & Rao, H. R. (2009). Trust and satisfaction, two stepping stones for successful e-commerce relationships: A longitudi-nal exploration. Information Systems Research, 20(2), 237–257. https://doi.org/10.1287/isre.1080.0188
Lim, Y. J., Osman, A., Salahuddin, S. N., Romle, A. R., & Abdullah, S. (2016). Factors influencing online shopping behavior: The mediating role of pur-chase intention. Procedia Economics and Finance, 35, 401–410. https://doi.org/10.1016/S2212-5671(16)00050-2
Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology ac-ceptance model. International Journal of Electronic Commerce, 7(3), 101–134. https://doi.org/10.1080/10864415.2003.11044275
Wang, Y. D., & Emurian, H. H. (2005). An overview of online trust: Concepts, elements, and implications. Comput-ers in Human Behavior, 21(1), 105–125. https://doi.org/10.1016/j.chb.2003.11.008
