Towards real-time analytics in MOOCs

Daniel T. Seaton, Yoav Bergner, Isaac Chuang, Pitor Mitros, David E. Pritchard

Research output: Contribution to journalConference article

Abstract

Massive open online courses (MOOCs) collect essentially complete records of all student interactions in a self-contained learning environment, with the benefit of large sample sizes. Building on our data mining of the first course in MITx (now edX) we demonstrate ways to analyze data to illustrate important issues in the course: how to distinguish browsers from certificate-earners, which resources were accessed the most and how much time was allocated by certificate-earners. Each topic is addressed via appropriate displays that, in future courses, can be updated in real time. Furthermore, we stress that analytics can provide useful information to teachers, to resource creators (authors), and to members of organizations trying to improve their MOOCs.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
Volume985
StatePublished - Jan 1 2013
Event2nd International Workshop on Teaching Analytics, IWTA 2013 - Leuven, Belgium
Duration: Apr 8 2013Apr 8 2013

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ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Seaton, D. T., Bergner, Y., Chuang, I., Mitros, P., & Pritchard, D. E. (2013). Towards real-time analytics in MOOCs. CEUR Workshop Proceedings, 985.