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We present a shared data model for enabling data science in Massive OpenOnline Courses (MOOCs). The model captures students interactions with theonline platform. The data model is platform agnostic and is based on some basiccore actions that students take on an online learning platform. Studentsusually interact with the platform in four different modes: Observing,Submitting, Collaborating and giving feedback. In observing mode students aresimply browsing the online platform, watching videos, reading material, readingbook or watching forums. In submitting mode, students submit information to theplatform. This includes submissions towards quizzes, homeworks, or anyassessment modules. In collaborating mode students interact with other studentsor instructors on forums, collaboratively editing wiki or chatting on googlehangout or other hangout venues. With this basic definitions of activities, anda data model to store events pertaining to these activities, we then create acommon terminology to map Coursera and edX data into this shared data model.This shared data model called MOOCdb becomes the foundation for a number ofcollaborative frameworks that enable progress in data science without the needto share the data.

MOOCdb: Developing Standards and Systems to Support MOOC Data Science