The convergence of external accountability pressures, academic systems collecting increasing amounts of data about student effort and learning, and the adoption of data warehousing and business intelligence technologies is providing higher education with unprecedented options for decisions based on analytics. At the same time, institutions, industry associations, and regulators are presenting college performance information in new venues on a near-daily basis.

While current analytics efforts have been able to tell higher education relatively little about what factors lead most reliably to student success, experimentation is under way across academia to identify those factors. A recent example includes efforts at Purdue University by Associate Vice President John Campbell to predict student success based on student aptitudes and levels of effort within courses [see http://educause.edu/apps/er/erm07/erm0742.asp for details about the project]. However, even such limited experimentation is hampered due to concerns about student privacy. These concerns limit faculty and researchers' access to data or place projects on hold until proper mechanisms are developed for storing and sharing analytical results.

This past summer, IMS formed an "Information Analytics" Learning Technology Advisory Council (LTAC) working group to consider the issue and whether there may be a unique role for IMS in establishing and promoting more effective practices. After some debate, this working group believes that IMS has a unique and ongoing role to play in creating policy and technology standards to facilitate the search and use of student success predictors - focused initially on standards to guide the legal, ethical, and practical use of student learning data. In addition to creating an "architecture of privacy" for student learning data, the work of the Information Analytics working group will inform use cases and create prototypes and demonstrations to show the results in practice, with strong potential for applying existing IMS technical standards (e.g., Enterprise Services, Question and Test Interoperability [QTI], Reusable Definition of Competency or Educational Objective [RDCEO], and ePortfolio) for the gathering, compiling, and analysis of student learning data. Therefore, we are issuing this Call for Participation to the broader IMS GLC membership.

We invite interested members to join us in defining a higher education-specific "architecture of privacy" to develop functional requirements for technologies (e.g., identity management software) to help mediate and regulate uses of student learning data from the student-privacy point of view. Our intent is that the group's work product will enable higher education IT professionals and academics (and third parties that support them) to leverage a discrete set of methods and technologies to facilitate the use of learning data to promote student success - while allowing those institutions to accommodate their unique legislative, normative, and student-driven standards of privacy.

Please join representatives of Georgia Tech, the University of Limerick, Purdue University, EDUCAUSE, Oracle, and SunGard Higher Education in tackling this important issue. To indicate your interest, please send an email to InformationArchitecture@imsglobal.org by 31 October 2007.