Towards Cross-domain MOOC Forum Post Classification

Abstract

Preliminary research is presented on the generalisability of confusion, urgency and sentiment classifiers for MOOC forum posts. The Stanford MOOCPosts data set is used to train classifiers with forum posts from individual courses and validate these classifiers on MOOC forum posts from other domain areas. While low cross-domain classification accuracy is achieved, the experiment highlights the need for transfer learning and domain adaptation algorithms; and provides insight into the types of algorithms required within an educational context.