The Vendor is required to provide to gather information about platforms that leverage artificial intelligence and predictive analytics to support student success.
- This includes—but is not limited to—tools that help academic advisors identify at-risk students, deliver targeted interventions, and improve retention and graduation outcomes through early warning systems and customized student insights.
- interested in models that produce highly interpretable, individual-level predictions based on longitudinal institutional data— without requiring the construction of a centralized data warehouse or reliance on regression-based inference models that produce generalized rather than individualized outputs.
- Platforms that support iterative retraining and collaborative development are of high interest.
- Especially interested in platforms that:
• Offer individualized, practitioner-ready outputs.
• Analyze a broad scope of academic and non-academic data (120+ elements).
• Deliver pre-interpreted insights without requiring centralized data warehouses.
• Are capable of real-time retraining and iterative model refinement.
• Provide open, transparent AI models—versus black-box algorithms.
- To strengthen academic outcomes, we are exploring AI-driven systems that integrate with institutional processes to offer:
• Predictive insights specific to institutional goals (e.g., degree completion probability, term-on-term retention).
• Seamless integration into advisor workflows.
• Ethical and transparent algorithmic models.
• Collaborative implementation and evaluation strategies.
- Our system is committed to equity, accessibility, and student-centered innovation.
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