Harness the power of your campus data
SEAtS Optional Student Success Scoring Analytics uses machine learning algorithms and statistical modeling techniques to quickly and accurately predict and identify at-risk students and to help improve outcomes and attainment for all students. Student attendance data provides current insights. Predictive Analytics uses historical and current data to anticipate student interventions even sooner.
STUDENT SUCCESS
SCORING ANALYTICS
Evaluate each student using a single score calculated from hundreds of touch-points, both real-time and historical.
IDENTIFY AT-RISK
STUDENTS
Initiate engagement as early as the third week and make critical corrections for better student outcomes.
MACHINE LEARNING
AND STATISTICAL MODELLING
Statistical analysis on expected goals, pre-defined objectives and preferred outcomes allows faculty staff to engage with students so everyone is on the same page.
Product Features
Student Engagement Analytics Dashboard
Student Engagement is a fundamental indicator of student success. SEAtS works with leading institutions to deliver real-time data to specific stakeholders for a wide range of use cases. With custom fields available, use our pre-built dashboards or create your own.
AI ENGAGEMENT SCORE
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.
AI DATA VISUALISATION
Historic retention and attainment outcomes are used to train our machine learning models to identify patterns applicable to the student population as a whole. Statistical modelling generates comparative charts for future outcomes in attendance, grades and overall performance.
SEAtS Predictive Analytics
Every time a student interacts with their university – be that going to the library, logging into their virtual learning environment or submitting assessments online – they leave behind a digital footprint. Learning analytics is the process of using this data to improve learning and teaching.
Better Student Retention and Outcomes
SEAtS have developed a process driven approach to Retention and Engagement based on the simple principle that you cannot manage what you cannot measure. The answer to the Retention Conundrum lies in the data locked away in systems all over you campus, on paper attendance registers, in administrative and academic, pastoral and welfare notes and emails.
SEAtS offer our customers a single unified secure shared platform that bring all this data together. SEAtS processes it and identify causes for concern in patterns of engagement and attendance. It then prompts academics and administrators to take critical early interventions.
Featured Resources
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