Characterizing Learner’s Comments and Rating Behavior in Online Course Platforms at Scale

Abstract

Opinions expressed by learners on courses they attend play a primary role in arranging learning and teaching processes and designing data-driven educational services. The ongoing proliferation of massive open online initiatives and the increasing amount of opinions provided online are turning the exploration and exploitation of this collective intelligence into a challenging, while crucial, task. In this paper, we characterize learner’s opinions conveyed by means of ratings and textual comments released after attending online courses, aiming at getting insights from multiple perspectives. Dynamics of opinion delivering are extracted from data collected along 10 years on a large-scale online learning platform. Our findings show that this domain has main distinguished peculiarities with respect to other educational domains and to other online domains wherein individuals express opinions. We expect that our findings will support the community to better understand opinion patterns in course platforms and, in turn, to devise tailored educational services.

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