Exploring the "distance" between MOOC forums: A comparative study on discussion topics

Abstract

In this paper we attempt to measure the semantic distance between forum dialogues in five MOOCs of different subject matters (humanities, mathematics and computing). We examine if such distance can provide evidence of transferable linguistic features, suggesting transferability of forum classification models. For this purpose, we employed Latent Dirichlet Allocation in order to extract the main discussion topics for each MOOC and proceeded to a pairwise semantic comparison between them. We focused on three categories of forum topics, i.e., Content-Related, Logistics-Related and Social Building. In the Content-Related discussions, the study confirmed semantic distance between the humanities course and the other four, while the distances among the mathematics and computing courses were shorter than expected. On the other hand, Logistics-Related and Social Building topics contained a more transferable set of features. The approach that we followed provides insights that could help MOOC researchers interpret the transferable features of their available data to employ in their classification tasks.