Integration of Learning Analytics Research and Production Systems While Protecting Privacy

Abstract

Learning analytics researchers often face problems when dealing with data that contains personally identifying information, and the protection of stakeholder privacy in analysis systems. As learning management systems become more important within education institutions, these systems are being subject to increasingly stringent standards to protect user privacy. This however has the potential to hinder learning analytics research because data collected in production cannot simply be transferred as is to research systems for real-time analysis. In this paper, we propose a system design that provides an interface between integrated production and research systems to allow user authentication, information, and learning analytics results to be seamlessly transferred between systems. The interface provides a level of anonymity to allow a greater degree of research freedom when analyzing data without exposing private data directly through research systems.