Page 52 - Campus Technology, October/November 2018
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Data Analytics and Student Advising:
Creating a Culture Shift
Understanding campus culture is key to Syracuse University’s “Orange SUccess” initiative, an effort to overhaul the use of data analytics for student advising and improve outcomes across the institution. By Mary Grush
Throughout higher education, data analytics is playing an increasingly important and game-changing role in student advising. Campus leaders are looking for successful models as they work to make the most of data analytics in their student advising programs.
Syracuse University (NY) provides such a model. In alignment with
its 2015 academic strategic plan, Syracuse conducted a university-wide overhaul of its advising practices.
Its “Orange SUccess” initiative would implement a new, centralized student advising system, provide intrusive advising, improve student persistence, and enable the sharing of data seamlessly across all schools and colleges.
By nature, an initiative of this type is built on the latest technology. But for Syracuse, technology is always looked upon as a path to a solution, not a driver of change in itself.
Here, Campus Technology asked Kalpana Srinivas, the university’s director of retention for Academic Affairs, how Syracuse streamlined the process of advising across all schools and colleges, and why understanding campus culture was central to her team’s change management strategy as the initiative analyzed all the underlying business processes across the entire university.
Campus Technology: Where are we now, in higher education’s adoption of data analytics in student advising?
Srinivas: Student advising has always been considered the linchpin of retention, a critical area for higher education institutions. And our retention gurus have held for years that it’s important that a student’s adviser is one of the key people they build a relationship with.
Data analytics may seem to be a more recent phenomenon, but it’s now over 10 years since Educause began publishing articles suggesting that if colleges and universities can place more and better information into the hands of a greater number of people, this enables better decision-making.
These two factors together became the crux of our understanding of how important it is to get critical information into the hands of advisers, so that they can do the holistic
student advising we are asking them to do.
CT: So is there more of a focus now on data analytics in higher education, since it’s finding a niche in student advising?
Srinivas: The overall picture of data analytics in higher education has taken shape mostly in the past five years, and the scholarship on this topic has really exploded recently. Linking data analytics with student advising and the science
of that is a relatively new phenomenon: Even though higher education has been collecting data on students for decades, especially via student information systems, most of that data has not been used to its full potential.4
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