Summary
Faculty and advisors are increasingly held accountable and responsible for student retention. The main problem is that faculty members have little to no actionable information enabling them to identify which students in their courses may be at-risk until it is typically too late to successfully intervene. Further, even if a student is known to be at-risk, in the absence of knowledge as to the nature of the student’s situation, faculty has difficulty determining the most effective intervention strategy.
Summary of the DSS Proposed
The OAAI Early Alert System is an open source predictive model-driven DSS. It extracts and integrates pre-defined factors that research shows influences attrition from the school’s existing systems. Using pre-defined algorithms, the model can identify which students are at-risk of dropping out with a high degree of accuracy.
Summary of the Benefits of the Proposed DSS
The OAAI Early Alert System will provide stakeholders with the actionable intelligence they need to make effective intervention decisions regarding at-risk students. As reported on the Marist College OAAI (2014) website, results of the pilots revealed that the chosen interventions had a positive and statistically significant impact on course grades (p = .013) and on content mastery (p = .001). While more needs to be learned about what intervention strategy works best in a given situation, a predictive early alert system enables that learning process and will help stakeholders figure out how to achieve the school’s goal of retaining students through course completion and graduation.