Evidence of the month: September 2015
In these two videos
Tim Renick talks to a committee of the US Senate about the successful large-scale application of predictive analytics at Georgia State University. The university aims to ensure – using reliable data – that students are doing what they need to do within the context of their ability and their resources and that they are making significant progress towards their degrees.
Renick, who is Vice Provost of the university, explains that they are using data proactively, picking up on problems that are associated with low grades or student dropout. He states that this has resulted in
- Reduction of the average time it takes students to gain a degree
- 1700 more students graduating annually than did so five years ago
- Elimination of achievement gaps based on race, ethnicity and economics.
The university is currently tracking 30,000 students, using predictive modeling based on ten years of data and 800 risk factors.
Students each have individual pathways, made up of a set of courses they should be taking each semester. Those who are making mistakes will find this out almost immediately, as the analytics will trigger a one-to-one meeting with an adviser. These meetings are personalized, engaging students, who get to know their support team better than was the case in the past. Early weaknesses in performance are addressed by immediate interventions, so they are removed rather than compounded.
These short videos do not set out detailed data and analysis, but they do provide evidence of analytics being rolled out at scale, and of engagement with these analytics at a national level.