CEDAR
Curricular and Enrollment Data Analytics and Reporting
CEDAR is a dashboard and an open analytics platform.
As a dashboard, CEDAR surfaces what’s happening in curriculum and enrollment from the perspective of the people actually running academic programs. Which courses typically srtruggle with low enrollment? How do DFW rates vary across sections of the same course? Where are students running into walls in a required sequence? These questions come up in scheduling meetings and curriculum committees all the time — and they tend not to get answered, not because the data isn’t there, but because no one has time to pull it together when a decision needs to get made. CEDAR is an attempt to change that.
As a platform, CEDAR is how that analytical work persists. Most one-off analyses live in a spreadsheet or a script that made sense when it was written but is hard to find or rerun the next term and impossible two years later. When a question is worth answering, the methodology is worth keeping. CEDAR keeps analysis in open, documented code — inspectable, rerunnable, and not dependent on any one person’s memory or hard drive.
What CEDAR is built around
Access
The dashboard is built for the people running academic programs — chairs, graduate directors, associate deans. The questions it answers are the ones that matter before a scheduling deadline or during a program review: which sections are at risk this term, how this year’s enrollment compares to three years ago, where students are stalling in a sequence. Specific, time-sensitive, and rarely surfaced by standard institutional reporting that take a bird’s eye view.
Transparency
Every CEDAR analysis is produced by source code in a public repository. The methodology isn’t a separate document — it’s the calculation itself. When there’s a question about how a number was derived, the answer is in the code: what was included, what wasn’t, and what choices were made along the way. That kind of traceability is standard in research. It can be standard in institutional analytics too.
Trust
There are a lot of ways to count enrollment, and the choices aren’t always obvious. Is a section’s enrollment counted at census date or at the end of term? If two departments crosslist the same course, does it appear once or twice in a headcount? What grades are considered passing for different courses? When a department and a college office produce different numbers from “the same” data, it’s usually not an error — it’s different definitions, often set independently without realizing they diverged. A shared platform means shared definitions, or at least clearly named differences. When numbers don’t reconcile, the question becomes answerable: here’s the code, here’s what’s different.
Collaboration
The same analytical problems come up at every institution — and higher education produces them from the same underlying data structures. Crosslisted sections that are one course or two depending on the question. Grade records where a withdrawal means different things depending on when it was recorded. Data exports with conventions that every analyst has had to decode from scratch. CEDAR is built around these particulars. Analyses that solve them at one institution are available to adapt elsewhere — not as abstract templates, but as code written against the actual data that higher education produces. Work done well once doesn’t have to be done again.