Data Science at Watermark Insights
The Predict functionality for the Student Success & Engagement (SS&E) platform is carried out by the Data Science team at Watermark Insights. This team sits in the center of the Watermark Suite, utilizing data from multiple sources to align and inform the SS&E Predict functionality. As the team works to more deeply understand the rela...
Overview
We are excited to announce the following updates to the Predict Analytics Success and Risk factor reasons included with the Student Success & Engagement platform.
'New' Success/Risk Factor Reasons apply and display on a Student Risk display (eg. Top 3 Success and Top 3 Risk Factors) for ALL student enrollments (students/courses) starting with students registe...
This article provides an overview of the Course Completion and Student Persistence predictive models and a recommendation for how to best utilize the risk indicators positioned throughout Student Success & Engagement or SS&E for evaluating the risk associated with students completing a course and the risk associated with students persisting to a future term.
All deplo...
Displaying Risk
Throughout Student Success & Engagement or SS&E, Risk Indicators and Risk Scores are present to allow for seamless interpretation of student risk associated with both course completion and student persistence.
A Student Success & Engagement predictive model is created by applying statistical methods to historical data at an Institution to derive a mathe...
Overview
This article provides an overview of the Student Retention, Student Persistence, and Course Completion Dashboard widgets.
These dashboard widgets reflect actual (as opposed to predicted) student performance at your institution, allowing you to track overall performance or performance for specific student populations.
These widgets update every night, however ...