Analysis and Design of Large-scale Online Classes
نویسندگان
چکیده
Massive Open Online Courses (MOOCs) have become an emergent paradigm of large-scale knowledge distribution. One of the dilemma faced by MOOC teachers is the trade-off between introducing new material and reviewing taught material. We model the recap activities as units of monotonically decreasing lengths and study the their schedule. We validate our model with the data of a Digital Signal Processing (DSP) MOOC. Our results include algorithms to construct schedules adhering to some spacing constraints, bounds on the rate at which new material can be introduced, and algorithms for MOOC data processing. We give insights to the design of the DSP MOOC using the Monotonically Decreasing Recap (MDR) schedule.
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