20 August 2019
The Singapore University of Social Sciences has turned to big data to tackle the high attrition rate of its adult learners.
Using predictive analytics, SUSS can assess if a student is at risk of dropping out, even before the student begins schooling.
Its algorithm analyses as many as 85 data points, such as past grades in secondary school or polytechnic, work experience, and students’ behaviour in submitting university assignments.
Some of the five schools at SUSS have used the data churned out by the university’s Business Intelligence and Analytics Unit to provide earlier and more targeted support for some students.
For instance, the School of Science and Technology set up a peer-mentoring network last year to help freshmen in its part-time programmes who need more help to adjust to university.
Associate Professor Sylvia Chong, project lead of the Business Intelligence and Analytics Unit, said the next phase is to measure how useful the analytics tool is for the different schools.