Why do students persist? Although there are some commonalities, the answer is different at every institution. Predictive modeling seeks to answer the question of why students persist by discovering hidden relationships in data. By leveraging a clear picture of past and present behavior, predictive modeling uses statistical analysis to generate a confident simulation of future behavior. Higher education institutions can then use that insight to positively impact student trajectories and influence outcomes.
View this web seminar to learn how to drive student success with predictive analytics from an administrator at Crown College in Minnesota, who will share the predictive model they have developed to identify at-risk students, as well as describe the communication flow and intervention process that leverage the information discovered from the model. A student success expert from Jenzabar highlights real-world examples, best practices developed over many years of analyzing data, and some of the most popular risk factors and programs that have been developed to help students succeed.
Director of Academic Programs
Crown College (Minn.)
Product Manager, Student Success Solutions