Ferpa|Sherpa

In 2013, the AISP team conducted in-depth interviews with staff at eight Network sites. The resulting case studies carefully examine the diverse IDS models that exist across the Network, analyze how each site uses their IDS to produce actionable intelligence for social policy and practice, and document core components of robust IDS sites.  

Too often, debates about students’ privacy are conducted within an isolated context of digital privacy law, instead of where they really belong––within discussions about improving teaching and learning. Parents are becoming more worried about students’ privacy because they hear a lot about risks and not enough about how students’ information can advance teaching and learning. […]

This policy aims to set out how the University will use student data in an ethical way in order to shape the student support provided.  The policy is based around eight key principles, each of which is linked to particular aspects of learning analytics.

This document tells the reader about important developments in the use of information The Open University holds about its students.

While a great deal of attention has been paid recently to protecting the privacy of students’ personal information and education records, this resource argues that families and educators also need to be aware of the use and disclosure of students‘ personal information in research conducted by universities and other entities. This resource explores some potential […]

This report focuses on the applications strand which sought to yield further insight into: the main areas of focus and most promising types of applications for the postsecondary community over the next few years ; a shared understanding of issues (for example, data types or methodologies) that may warrant additional ethical consideration; the potential for guiding principles […]

Student success has come into sharp focus for higher education. New models have emerged in response to outcome-based funding at the state level and a completion agenda at the national level. Integrated planning and advising services (IPAS) systems show promise for improving student success and college completion rates, but IPAS use of student and institutional […]

This paper explores issues around consent and the seemingly simple choice to allow students to opt-in or opt-out of having their data tracked. We consider how 3 providers of massive open online courses (MOOCs) inform users of how their data is used, and discuss how higher education institutions can work toward an approach which engages […]

In ‘The Promise and Peril of Predictive Analytics in Higher Education: A Landscape Analysis,’ authors Manuela Ekowo and Iris Palmer describe how predictive analytics are used in higher education to identify students who need extra support, steer students in courses they will do well in, and provide digital tools that can customize the learning process […]

This report discusses the use of data in higher education, which are primarily used in the following ways: • Early-Alert Systems. In an early-alert system, flags are triggered based on academic and nonacademic data from students that signal when they may need additional support. Academic interventions may include tutoring, meetings with an adviser, or assigning a […]