Our top 11 reasons why you should be using Student Insight
Combine student and academic data from your SIS with student activity data from your VLE, Library and other data sources
Advanced predictive analytics and machine learning algorithms learn from your historic student data to predict the risk of student non-continuation and poor academic performance
Understand what factors affect outcomes by being able to see how combinations of student, academic and activity factors increase a student's chances of non-continuation or poor academic performance.
Transparent predictive models allow staff to see what factors contributed to a student's predicted outcome
Tag individual students to group them into cohorts to track their performance, progress and predicted outcomes
Create user defined tag rules that automatically group students based on different student factors
Load your institution's curriculum structure to monitor student progress and predicted outcomes at all levels across the institution
Give personal tutors, course directors, teaching and other staff across the institution access to dashboards summarising performance and outcomes for their students.
Record decisions and actions agreed with the student and manage interventions through dynamic integration with SID
Overlay interventions against student progress to see which interventions were effective