To do this, Desire2Learn wants to bring predictive analytics into play in education. But why? Well, first and foremost because, today, if students want to figure out whether a course is right for them — or how well they might perform in that course — they’re hard pressed to find a good answer. They can ask fellow students, check websites that rank faculty based on nebulous criteria or try to find surveys, but none of these options are ideal.
With its new analytics engine, Desire2Learn aims to change that by giving students the ability to predict their success in a particular course based on what they’ve studied in the past and how they performed in those classes. The new, so-called “Student Success System,” was built (in part) from the technology it acquired from Degree Compass; however, while Degree Compass used predictive analytics to help students optimize their course selection, the new product aims to help both sides of the learning equation: Students and teachers.
On the teacher side, Desire2Learn’s new analytics engine allows them to view predictive data visualizations that compare student performance against their peers so that they can identify at-risk students, for example, and monitor a student’s progress over time.
The idea is to give teachers access to important insight on stuff like class dynamics and learning trends, which they can then combine with assessment data, to improve their instruction or adapt to the way individual students learn. In theory, this leads not only to higher engagement, but also better outcomes