APS
29th APS Annual Convention · 2017
Predicting Student Retention Using Data Mining Techniques
- Melanie Lewis
The University of Oklahoma - Yutian Thompson
The University of Oklahoma - Koby Pascual
The University of Oklahoma - Timothy Burt
The University of Oklahoma
Abstract
Administrative efforts to improve retention must identify relevant causes. Here we present the implementation of cluster analysis and random forest classification to predict a student’s probability of retention based on proposed course plan as well as other known risk factors of attrition. The adviser can then modify the course plan.
Quantitative
