CEDAR
Reproducible, Ground-Up Analytics for Higher Education
Higher education analytics is more powerful—and more opaque—than ever. Dashboards and predictive models offer insight, but often obscure how results are produced and where interventions actually happen.
CEDAR is built on a different premise:
Analytics should be inspectable, reproducible, and grounded in the contexts where decisions are made.
Why CEDAR Explore the Analyses Perspectives Contribute
Why CEDAR?
Two persistent challenges shape analytic work in higher ed:
1. Distance from Decision-Making Contexts
Students move through programs, departments, and advising—not “the institution.” Most interventions happen locally, but institutional dashboards rarely reach that level. CEDAR supports a ground-up approach, enabling units to analyze and understand the structures that shape student pathways.
2. Lack of Reproducibility
Data teams answer the same questions—about outcomes, equity, or progress—again and again, often:
- constructed ad hoc
- hard to verify
- inconsistently defined
CEDAR treats analytics as a shared, versioned, and documented process, not a series of one-off results.
What CEDAR Does
CEDAR is a code-based framework for:
- defining metrics and transformations explicitly
- analyzing student pathways within local contexts
- ensuring analytic results are reproducible and verifiable
- supporting collaboration across data teams and units
It doesn’t replace dashboards. It ensures what appears in dashboards is consistent, transparent, and institutionally grounded.
Perspectives: Who Uses CEDAR?
CEDAR is designed for multiple audiences. The system is shared, but its value depends on where you sit:
- University Perspective — Provosts, central admin, IR
- College Perspective — Deans, associate deans, college analysts
- Unit Perspective — Department chairs, program directors, local analysts
Each perspective page highlights the core questions, pain points, and CEDAR’s value for that audience.
Transparency in an عصر of Complexity
As analytics systems incorporate more advanced modeling and AI, transparency matters more. Many tools produce results that are hard to interrogate, even when operationally useful.
CEDAR’s approach:
- advanced methods are possible
- analytic processes remain visible
- definitions are explicit
- results are reproducible
The goal: analytic work that is understandable, accountable, and open to revision.
A Complement, Not a Replacement
CEDAR doesn’t replace dashboards or predictive systems. It complements them.
Where dashboards present results, CEDAR ensures those results are:
- consistently defined
- locally meaningful
- reproducible over time
CEDAR is infrastructure: a way of organizing analytic work to support both local decision-making and institutional understanding.
Getting Started
CEDAR is for institutions that:
- value transparency and reproducibility
- need consistent answers to recurring analytic questions
- want to connect institutional patterns with local contexts
If that’s your work, CEDAR is a framework for analytics that are inspectable, shared, and durable.