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Analysis and Design of Large-scale Online Classes

Martin Vetterli, Paolo Prandoni, Tao-Chun Lee
2014
Report or working paper
Abstract

Massive Open Online Courses (MOOCs) have become an emergent paradigm of large-scale knowledge distribution, have generated wide interest in the higher education community and are anticipated by many to bring impact to the future of higher education. In this research project, we study the learning analytics and learner dynamics of a pilot MOOC, the Digital Signal Processing (DSP) MOOC on Coursera. In the first part, we study the learning analytics using scheduling theories and ranking algorithms; in the second part, we study the learner dynamics using Complementary Cumulative Distribution Functions (CCDFs).

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