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Massive Open Online Courses are educational programs that are open andaccessible to a large number of people through the internet. To facilitatelearning, MOOC discussion forums exist where students and instructorscommunicate questions, answers, and thoughts related to the course.  The primary objective of this paper is to investigate tracing discussionforum posts back to course lecture videos and readings using topic analysis. Weutilize both unsupervised and supervised variants of Latent DirichletAllocation (LDA) to extract topics from course material and classify forumposts. We validate our approach on posts bootstrapped from five Courseracourses and determine that topic models can be used to map student discussionposts back to the underlying course lecture or reading. Labeled LDA outperformsunsupervised Hierarchical Dirichlet Process LDA and base LDA for ourtraceability task. This research is useful as it provides an automated approachfor clustering student discussions by course material, enabling instructors toquickly evaluate student misunderstanding of content and clarify materialsaccordingly.

Tracing Forum Posts to MOOC Content using Topic Analysis