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Using predictive modeling to forecast financial aid has great potential for insight, but there are often misunderstandings about how to effectively bring the two together. This webinar will focus on both ends of the analytical timeline.
Check out our insight paper to discover four findings from EAB's 2023 survey of higher ed technology leaders.
The Day in the Life series is a practically driven walkthrough of the software. It assumes the context of data analysis for enrollment management, and is narrated in a stream of consciousness so that users can more easily understand the typical usage of the applications in action.
Predictive modeling in higher education offers exciting opportunities to improve decision-making. With thoughtful planning and implementation, modeling can help your institution foster equitable outcomes. Learn 4 characteristics of equitable predictive models to ensure your institution's modeling supports your equity goals.
Predict offers a lot of easy pathways towards answers that are front-of-mind for users and stakeholders alike. In this Deep Dive webinar, look forward to hearing about the ways that Predict can support answers to pressing questions of modeling practice.
If you use data in any capacity at all, you’re already preparing to build a model. Learn the 6 steps to design a predictive model and see which steps you've already completed.
This webinar will help you leverage Construct towards scalable text transformations on your data. We're not assuming any background experience with text manipulations, so come as you are, and find out how you can expertly manipulate strings.
For data and technology to truly deliver value and drive change, you need an intentional technology investment strategy. Learn 5 steps you can take to enact a tech investment strategy that supports your institution's digital transformation.
Dr. Louis Slimak, Associate Provost for Curriculum and Assessment at West Virginia University (WVU), has done extensive work to overhaul the WVU’s program review process—and its culture around data more broadly—since his arrival in 2016. This blog shares Dr. Slimak's advice for implementing a data-informed program review process and his tips for other leaders embarking on large-scale data projects.
In this session, attendees will receive step-by-step guidance in Rapid Insight Predict on how to build a predictive model for GPAs which can apply to students at any point in their academic careers whether it is their first or fourth year. We will also discuss interventions and unexpected discoveries that may surface while using these models. This session is best suited for Rapid Insight users of Predict, student success professionals, individuals that support student success via predictive modeling or data analysis, and individuals interested in learning how to use Predict to support their student success work.