Efficient management for a student success support network

Universidad de la Costa has long invested a great deal of effort in supporting student success and promoting on-time graduation. The challenge was never whether it had support strategies, but how efficiently it applied them.

The core problem was that the university could not manually identify the critical variables for its different student profiles, which led to inefficient interventions.

Resources were wasted on strategies for students who actually needed other kinds of support, and at the same time, the support the university could offer was limited by the time of the student wellness department's staff.

One earlier measure was a 20-person call center to monitor student satisfaction, which was not enough to make a real difference in retention.

The university decided to change its approach to student success and well-being, transforming its processes with technology and applying new strategies such as turning full-time faculty into mentors as part of the support for first- and second-semester students. The mentors complemented the Student Wellness Department and formed a strong support network around each student.

As part of the strategy, it also decided to implement Stella, our AI tool for understanding and profiling students, to make support strategies easier to manage. Every instructor was connected directly with their students through Stella: the tool not only generated automatic alerts when it detected a risky behavior pattern, but also gave instructors a real-time, 360° view of their students (grades, attendance, scholarships, history of support sessions, team comments, and more).

Each instructor was assigned 8 to 10 first- and second-semester students, to guide them as they started university and get to know the strengths and weaknesses they might have inside and outside the classroom.

The pillars of the support methodology

1. A support network around the student

The wellness team was made up of experts in carrying out interventions tailored to each student and supporting them through whatever came up during their studies. However, there were not enough people to give initial support to every student during their first year. So the university decided to bring in the people closest to students on campus: their instructors.

The idea, then, was not simply to expand the Wellness team, but to build a network of people around each student, bringing instructors into the support process to improve student well-being and success.

All of this was powered by Stella's technology, which made it possible to build a methodology to better target the highest-risk students and raise everyone's well-being

2. Building a retention culture

The new strategies introduced a culture of retention, in which everyone was responsible for ensuring a good service experience for students and supporting them through every process until they reached their goal: successfully completing their university studies.

The Wellness Department and faculty together held 33,873 support sessions with 8,812 students.

3. Logging interventions: individual and group

The results of every intervention were logged and centralized in Stella:

Instructor follow-up.
Tutoring sessions or workshops.
Specific support actions.

This left a record of and evidence for each strategy, so its impact could be measured. Procedures were also standardized, driving continuous improvement and making the retention process more effective.

Results and metrics

Prediction accuracy: 4 out of 5 students who dropped out had been flagged by Stella as medium or high risk. (78.6% prediction accuracy.)
Effectiveness of actions:- Students who received support have a dropout rate 13 percentage points lower than those who did not.- Actions can reduce dropout from 32% to 12% among the new students they reach. (E.g., action: orientation day.)
Continuous improvement: in 2022-1, actions reduced dropout by 8 percentage points, while in 2022-2 they reduced it by 13 percentage points.
Persistence: during the pandemic, the average dropout rate at universities rose by 7 percentage points, while CUC's fell by 3 percentage points over the same period.

Other universities lost 4 more students out of every 100 than CUC did. (Figures from the MEN, Colombia's Ministry of National Education.)