Research
The Clema research team publishes original analysis and practical guides for institutional research and institutional effectiveness professionals.
In a study of 20 IR and IE offices, one term routinely carried several valid definitions at once. Here is why that happens, the eight layers it happens at, and why it breaks reporting even when the data is clean.
A diagnostic for institutional research teams: the Institutional Intelligence Gap, the three tiers (55% Large, 40% Moderate, 5% Small), a five-factor self-assessment, and an illustrative cost model for key-person dependency in higher ed.
Creating data definitions is achievable. Maintenance is where most efforts collapse. Here is a six-step framework, an AI-readiness argument, and tier-by-tier next steps for IR/IE teams.
A directory of 25 ways to learn institutional research: graduate certificates, AIR professional development, free IPEDS and PDP training, executive programs, and self-paced courses, with formats, costs, and links.
IR teams already sit on years of attendance, GPA, LMS, and aid data. A practical guide to turning that record into forward-looking predictions that change what advisors, deans, and provosts can do this term.
A plain-English guide for IR leadership on why classical ML (specifically XGBoost) outperforms LLMs on student-level retention and graduation prediction, what the benchmark literature actually shows, and how to read a per-student risk score.
A straight comparison between the open-source predictive-analytics stack ($40 to $95 per month) and the major incumbent platforms ($30K to $200K per year). Covers infrastructure cost, licensing, where incumbents are strong and where they leave gaps, and a build-vs-buy framework.
A practical look at the features, engineering choices, and timing decisions that drive a real term-to-term retention model. Written for IR leadership who want to understand what the model sees before they hand its output to advisors.
The graduation use case in detail. Features, course-combination effects, plain-English metric reading, the small-group floor that prevents false certainty, and the drift management every long-horizon prediction needs.
A practical guide to the predictive questions Provosts and CFOs own. Enrollment forecasting (ARIMA, Prophet, LSTM), yield prediction, program margin and viability, IPEDS-based screening, and the honest limits of each.
PPD:2026 looks like a single dataset. On disk it's six Excel files joined on opeid6 + credlev + cip4, with mixed-vintage dollars, statistical-noise privacy suppression, and a CIP-4 key that doesn't match the CIP-6 the STATS test will use. Here's where the analyst hours actually go, and how to skip them.
35% of universities have no formal intake process, and 77% of IR offices require extensive clarification before analysis begins. Analysis of 18 university data request forms reveals what the best systems do differently.
IPEDS 2023–2024 data reveals four-year institutions growing 3x faster in dual enrollment than community colleges, while community colleges carry 32.4% structural reliance. A full side-by-side benchmark.
Discover what IR teams actually benchmark most often, from student outcomes and faculty metrics to aspirational peer lists, based on evidence from 50 institutional research interviews.
Research shows 80% of IR data requests arrive missing critical elements. Learn how Request Intelligence (the quality of requests at intake) determines whether your team spends time analyzing or clarifying.
Discover proven strategies from IR leaders to streamline data requests, implement self-service dashboards effectively, and reclaim up to 60% of your team's capacity for strategic work.