In massive open online courses (MOOCs), misjudgments by teachers and managers are caused by the disconfirmation effect of online reviews, i.e., the inconsistency between the degree of attention paid to course factors and the importance of that factor to learner satisfaction. Based on the two-factor theory of emotion, this paper uses 4,070 courses from Chinese University MOOC as research data, and identifies the effect of sentiment factors on the disconfirmation effect through text mining techniques and econometric models. The empirical results show that negative reviews have the significant disconfirmation effect. Relative to fear sentiment reviews, sadness sentiment reviews and anger sentiment reviews have the stronger disconfirmation effect. Relative to knowledge-based and practice-based courses, instrument-based course reviews have the stronger disconfirmation effect. In addition, negative course word-of-mouth and learner reputation play a moderating role between the effect of sentiment on the disconfirmation effect.


Paper Number 1620; Track e-Learning; Complete Paper


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