institutional research

How AI Analytics Is Helping Colleges Improve Student Performance

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AI analytics improves student performance by turning activity and assessment data into early alerts, engagement scores, and targeted interventions—so advisors and faculty act before small issues become dropouts.​ What works in practice Measurable impact Advisor and faculty dashboards Models and methods Governance and equity 30‑day rollout plan Bottom line: by combining early‑alert models, engagement scoring, … Read more

The Role of Machine Learning in Predicting Student Dropout Rates

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Core idea Machine learning identifies at‑risk students earlier and more accurately by analyzing patterns across academic, engagement, and socio‑demographic data, enabling timely, targeted interventions that improve retention—especially when models are explainable, fair, and embedded in student support workflows. Why ML works for dropout prediction Evidence and 2024–2025 signals High‑value features to engineer Model choices and … Read more