  Massive Open Online Course (MOOC) platforms incorporate large course catalogs
from which individual students may register multiple courses. We performed a
network-based analysis of student achievement, considering how course-course
interactions may positively or negatively affect student success. Our dataset
included 378,000 users and 1,000,000 unique registration events in France
Universite Numerique (FUN), a national MOOC platform. We adapt reliability
theory to model certificate completion rates with a Weibull survival function,
following the intuition that students "survive" in a course for a certain time
before stochastically dropping out. Course-course interactions are found to be
well described by a single parameter for user engagement that can be estimated
from a user's registration profile. User engagement, in turn, correlates with
certificate rates in all courses regardless of specific content. The
reliability approach is shown to capture several certificate rate patterns that
are overlooked by conventional regression models. User engagement emerges as a
natural metric for tracking student progress across demographics and over time.
