Exploring the factors affecting learners' continuance intention of moocs for online collaborative learning: An extended ecm perspective

Abstract

The purpose of this paper was to investigate what factors influence learners' continuance intention in massive open online courses (MOOCs) for online collaborative learning. An extended expectation confirmation model (ECM) was adopted as the theoretical foundation. A total of 435 valid samples were collected in mainland China and structural equation model (SEM) approach was adopted. The descriptive statistics show that platforms from abroad, such as Coursera and Khan, are more popular than native ones in mainland China. The empirical results show that the effects of three ECM factors (satisfaction with prior learning experience, confirmation with prior learning experience, and perceived usefulness) are significant. Different factors have different predicting power. Knowledge outcome is the first powerful indicator of learners' continuance intention of MOOCs, followed by social influence, learners' satisfaction with prior learning experience, and performance proficiency. The effects of knowledge outcome, performance proficiency, and social influence are significant, showing the success of extended ECM.