Predicting Instructor Intervention in MOOC forums

Snigdha Chaturvedi     Dan Goldwasser     Hal Daumé III.    
Association for Computational Linguistics (ACL), 2014


Instructor intervention in student discussion forums is a vital component in Massive Open Online Courses (MOOCs), where personalized interaction is limited. This paper introduces the problem of predicting instructor interventions in MOOC forums. We propose several prediction models designed to capture unique aspects of MOOCs, combining course information, forum structure and posts content. Our models abstract contents of individual posts of threads using latent categories, learned jointly with the binary intervention prediction problem. Experiments over data from two Coursera MOOCs demonstrate that incorporating the structure of threads into the learning problem leads to better predictive performance

Bib Entry

    author = "Snigdha Chaturvedi and Dan Goldwasser and Hal Daumé III.",
    title = "Predicting Instructor Intervention in MOOC forums",
    booktitle = "Association for Computational Linguistics (ACL)",
    year = "2014"