Features Identification and Classification of Discussion Threads in Coursera MOOC Forums
In this chapter, the discussion threads of six MOOCs courses offered from August 2013 to April 2014 via the Coursera forums were analysed. The purpose of this study is to identify important features that may have an impact on supervised classification analysis in predicting discussion threads that require instructors' intervention. This study worked on data from the anonymised Coursera MOOC forums with 45,303 threads to gain an insight into the forums. The important features related to thread structures, social network, and popularity are identified using Univariate Feature Selection. Classification analyses using neural networks, decision trees, and naive Bayes algorithms were applied to generate the predictive models. The results show that the developed predictive model is performing well, and the decision trees algorithm outperformed other algorithms with excellent performance measures based on the level of accuracy, precision, recall, and f measure.