Big Data, Meet Big Achievement: Bringing Predictive Analytics Into the Classroom


Collecting data on students is nothing new- LMS systems across schools almost uniformly record information on student achievement. But only recently have schools started applying this data to help their students get ahead. Colorado State University found that they substantially increased graduation rates when they began to use their data to help find students who needed academic assistance. However, degree-auditing systems often are finicky and hard to use, and give information that can sometimes be incorrect. An example can be found in UW’s own DARS (Degree Audit Reporting System), which often incorrectly categorizes or misrepresents student progress or achievement. This makes academic planning difficult for both students and academic advisers. On top of that, these data-driven tools rarely properly augment the other tools that academic advisers use to help students stay on track.

That may be about to change. A series of acquisitions and mergers in the education data analysis space may suggest that the multiple systems may also be integrated in the near future- and as new standards for software and new ways of applying data are put into effect, educators must make sure to stay ahead of the curve.

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