Predictive Analytics: articles for IR teams
Forecasting enrollment, predicting retention, and applying predictive models in higher education IR.
From reactive reporting to proactive prediction: a playbook for IR teams
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.
Clema Research Team · 10 mins readWhy gradient boosting beats LLMs for student retention prediction
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.
Clema Research Team · 11 mins readPredictive analytics in higher ed: the $40-a-month stack vs the $200K platform
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.
Clema Research Team · 10 mins readPredicting term-to-term retention: what a working model actually looks at
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.
Clema Research Team · 11 mins readPredicting graduation within 150% time: course combinations, confidence, and committee-ready explanations
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.
Clema Research Team · 11 mins readForecasting enrollment and program viability: where prediction meets cabinet-level decisions
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.
Clema Research Team · 10 mins read