Perceptions and use of an early warning system during a higher education transition program

Abstract

This paper reports findings from the implementation of a learning analytics-powered Early Warning System (EWS) by academic advisors who were novice users of data-driven learning analytics tools. The information collected from these users sheds new light on how student analytic data might be incorporated into the work practices of advisors working with university students. Our results indicate that advisors predominantly used the EWS during their meetings with students---despite it being designed as a tool to provide information to prepare for meetings and identify students who are struggling academically. This introduction of an unintended audience brings significant design implications to bear that are relevant for learning analytics innovations.