The Predictive Learning Analytics Revolution: Leveraging Learning Data for Student Success

Published:
Briefs, Case Studies, Papers, Reports
Author(s) and Contributors:
Author(s): Sakinah Alhadad Kim Arnold Josh Baron Ilana Bayer Christopher Brooks Russ Little Rose Rocchio Shady Shehata John Whitmer
Source(s) and Collection(s):
Sources(s): EDUCAUSE Research Collection(s): EDUCAUSE Working Group
ParentTopics:
Administrative Systems Analytics Data Administration and Management Learning Analytics Learning Management Systems (LMS) Student Information Systems Student Learning Support Student Success

Abstract

Everyone from government agencies to mainstream press are looking for improvements in areas that typically fall under the umbrella of “student success.” Universities are seeing the potential that the vast quantities of data produced in their IT systems hold for addressing strategic challenges facing academia today. The combination of embedded administrative and academic technologies, big data, powerful analytical tools, and sophisticated data-mining techniques are poised to spark a revolution in how education is delivered and how the efficacy of that education is measured. It behooves institutional leaders to gain an understanding of this emerging field as means to guide their institutions into a future where learning data play an important role in the process of education. This paper aims to enable institutional leaders and practitioners to educate themselves about the emerging field of predictive learning analytics and understand how it will impact the higher education landscape.

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