As higher education continues to leverage student data and make predictions as to whether students will enroll, be retained, and graduate, the inevitable question that comes up is … why do students behave the way they do?

It is not enough just to apply black-box algorithms to the data and rely purely on output. Interpreting output and looking at cause and effect relationships is very important when determining why students behave the way they do and what university leadership can do to support them throughout their college career and even into alumni relations long after they have graduated.

To read the full article and learn how to differentiate between causation and correlation in analytics, click here.