Linguistic Reflections of Student Engagement in Massive Open Online Courses

摘要: While data from Massive Open Online Courses (MOOCs) offers the potential to gain new insights into ways in which online communities can contribute student learning, much of richness trace is still yet be mined. In particular, very little work has attempted fine-grained content analyses interactions MOOCs. Survey research indicates importance goals and intentions keeping them involved a MOOC over time.  Automated offer detect monitor evidence engagement how it relates other aspects their behavior. Ultimately these indicators reflect commitment remaining course.  As methodological contribution, this paper we investigate using computational linguistic models measure learner motivation cognitive text forum posts.  We validate our techniques survival that evaluate predictive validity variables connection with attrition time. conduct evaluation three MOOCs focusing on different types learning materials. Prior demonstrates participation discussion forums at all strong indicator commitment. Our methodology allows us differentiate better among students, identify danger signs struggling need support within population whose interaction course opportunity for effective administered.  Theoretical practical implications will discussed.