Predictive Analytics in Higher Education
Helping universities use their data to enhance education quality and access.
Context
Higher education is an increasingly crowded field, with more colleges offering even more programs for an ever-growing pool of applicants. In such a landscape, it becomes harder to stand out and pull in the right students. Predictive analytics and big data can help answer the tough questions, improve application numbers, and improve education quality and efficiency.
Forecasting how many admissions offers will convert into acceptances has always been tricky. A good estimate will help universities better budget and allocate resources for the coming academic year, making this one of the most vital processes within the school administration. To that end, we have developed a top-performing predictive model that will utilize historical data to generate reliable and accurate estimates for the school’s budgeting process.
Outcome
In addition, we have worked on several POCs to highlight opportunities where predictive analytics can shine. For example, we have applied advanced text analysis (topic modelling) to help colleges better understand their unstructured text data, be it admissions essays or course feedback. We have also started working on predicting classroom utilization to help universities better allocate scarce resources in the most efficient way possible.
