Academic Factors in IT Student Graduation Rates

In this paper, we investigate the relationship between academic features and attrition rates. Using registrar information from a set of IT students, we investigate how student performance in specific classes impacts their likelihood of graduating and length of time to graduation. Our results show that significant relationships exist between courses that are classified as required, difficult, or more advanced. This work-in-progress is building towards a model using student academic features and demographic information to predict students at risk for attrition.