Predicting the acceptance of MOOCs in a developing country: Application of task-technology fit model, social motivation, and self-determination theory

Online learning courses have expanded the educational landscape to distant and disadvantaged areas. Although such courses have generated extensive interest, there is as yet sparse literature evaluating the determinants of online course acceptance, especially in developing countries. Seeking to close this gap, this study examines the factors influencing students' adoption of Massive Open Online Courses (MOOCs) in a developing country by applying an integrated framework incorporating the task-technology fit model, social motivation, and self-determination theory. In addition, the study investigates the moderating effect of perceived reputation on students' adoption behavior. A self-administered survey was employed for data collection and valid responses from 414 participants were used for testing the proposed model. The data was analyzed using structural equation modeling through Smart-PLS. The results establish the significant contribution of task characteristics and technology characteristics in facilitating task-technology fit, and that the fit positively influences behavioral intentions. Moreover, social recognition, perceived competence, and perceived relatedness have positive and significant effects on the behavioral intentions of the students. This research also reveals that perceived reputation has an important moderating effect on the students' usage behavior. The study results provide both practical and theoretical insights to enrich the understanding of the paradigm shift due to MOOCs and online education.