Student network analysis: A novel way to predict delayed graduation in higher education

Abstract

We present a prediction model to detect delayed graduation cases based on student network analysis. In the U.S. only 60% of undergraduate students finish their bachelors’ degrees in 6 years [1]. We present many features based on student networks and activity records. To our knowledge, our feature design, which includes conventional academic performance features, student network features, and fix-point features, is one of the most comprehensive ones. We achieved the F-1 score of 0.85 and AUCROC of 0.86.