In today's digital world, higher education institutions collect and use more data than ever. However, institutional silos create barriers for stakeholders who need data for daily operations and strategy. This article presents a vision of a unified, collaborative future for data governance and actionable steps stakeholders can take.

Background: Deep versus surface knowledge is widely discussed by educational practitioners. A corresponding construct, levels of processing, has received extensive theoretical and empirical attention in learning science and psychology. In both arenas, lower levels of information and shallower levels of processing are predicted and generally…

Education, Big Data, and student privacy are a combustible mix. The improvement of education and the protection of student privacy are key societal values. Big Data and Learning Analytics offer the promise of unlocking insights to improving education through large-scale empirical analysis of data generated from student information and student…

The research urgency is caused by necessity to develop the informational support for management of development of higher education in conditions of high turbulence of external and internal environment. The purpose of the paper is the development of methodology for structuring and analyzing datasets of educational activities in order to reduce…

This chapter describes the background and process for collecting postgraduation outcomes data at a 4-year not-for-profit private college. The strategies, analyses, and reporting of this data-collection effort are highlighted with the use of a case study.