Abstract
Massive Open Online Course (MOOC) has been playing an important role in the latest e-learning initiative and has obtained a widespread popularity in many universities. However, the low course completion rates of students have become an outstanding issue that should not be neglected. Based on the Expectation-Confirmation Model (ECM), this study examines the effects of students’ perceived usefulness, confirmation and satisfaction on MOOC continuance intention. Structural Equation Modeling (SEM) was used to validate the proposed model and hypotheses. Participants were 368 undergraduate students enrolled in a MOOC platform. The study’s result revealed that confirmation has significant effects on students’ perceived usefulness and satisfaction. Perceived usefulness and satisfaction have significant effects on students’ continuance intention while perceived usefulness has no significant effects on students’ satisfaction. This study will help to outspread our understanding of what influence students to continue using MOOC.
Highlights
Massive Open Online Courses (MOOCs) are lessons delivered in an online environment whereby, there is an unlimited participation (Marques, 2013; Alraimi, Zo, & Ciganek, 2015)
The results revealed that confirmation has a positive influence on perceived usefulness ( =0.792, p=
A research model based on the expectation-confirmation model (ECM) was proposed and tested with data collected from 368 putraMOOC students
Summary
Massive Open Online Courses (MOOCs) are lessons delivered in an online environment whereby, there is an unlimited participation (Marques, 2013; Alraimi, Zo, & Ciganek, 2015). MOOC are free and open to any individual who wants to learn online irrespective of his/her place or education level (Bederson, Russell, & Klemmer, 2015) This may be the reason why MOOCs have been undergoing a rapid development in recent years (Jordan, 2014; Konstan et al, 2015). MOOC have become very popular and used all over the world, the main issue that cannot be overlooked is the low course completion rate of students (Siemens, 2013; Ouyang et al, 2017).
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