Predictive Analytics
SEAtS Predictive Analytics analyses and scores data from physical and digital touch-points throughout the campus to identify emerging trends.
What we do
The volume, velocity and variety of data Higher Education Institutions generate is rapidly increasing. SEAtS harnesses and analyses this data to provide powerful insights. Physical data like class attendance and library visits are interwoven with digital data from timetables, socio-demographic profiles and historic attainment to understand how a student learns. The result is a personalised view of engagement, retention and achievement for every student. Historic retention and attainment outcomes are used to train our machine learning models to identify patterns applicable to the student population as a whole. While student attendance data can provide a broad indication of progress, predictive analytics can provide a specific indication relative to thousands of current and historical data.
SEAtS Data Repository supports both structured and unstructured data from your campus and beyond. By combining and analysing student data, institutions can monitor emerging trends for greater efficiency in managing resources.
What it means for your campus
SEAtS delivers integrated predictive analytics using the SEAtS data repository. These powerful tools will help your team drive student success by identifying critical early interventions that will increase engagement, student retention and achievement ratios on your campus.